**Meet the editor**

Dr. Kais Ghedira is an assistant professor of Bioinformatics and a member at the Laboratory of Bioinformatics, Biomathematics and Biostatistics, Institut Pasteur de Tunis (IPT), Tunisia. He graduated in Biological Sciences in 2004 from ISBM, Monastir, Tunisia. He pursued his master degree from the Faculty of Pharmacy, Monastir, Tunisia and defended his master project on

January 2007. He then participated in the "Informatics in Biology" course held at the Institut Pasteur Paris, France and obtained a diploma for this course. This course allowed him to acquire many skills in the field of bioinformatics that were valuable for his PhD degree. He started his PhD degree in Bioinformatics in September 2007 from the Faculty of Sciences, Bizerte, Tunisia, and pursued his PhD project at IPT. During his thesis, he was at BIOBASE GmbH, Germany, for several months working on predicting transcription factor binding sites (TFBSs) using several bioinformatic tools and updating existing BIOBASE databases. He is a bioinformatician with a biological background who has been published in several peer-reviewed journals with high impacts. He is involved in several national and international research projects collaborating with worldwide researchers. He is highly involved in training bioinformatics in Tunisia and Africa. He is mainly interested in gene expression and gene regulation analysis, functional genomics and integrative biology, analysis of high throughput data, comparative genomics and database, and webtool development. He is currently working on several projects related to understanding diseases/phenotypes through the analysis of gene expression, integration of multiple Omics and high throughput data, meta-analyses, and gene regulatory networks. As gene expression regulation is a fundamental process for cell living, the editor believes that researchers and the scientific community would find a variety of new ideas and hints in this book that would be helpful to them to tackle transcriptional and post-transcriptional regulations.

Contents

**Preface VII**

Kais Ghedira

**Hematopoiesis 13** Jianchang Yang

**from Latency 35**

**MicroRNAs 101**

**Section 1 Transcriptional and Post-transcriptional Regulation 1**

Chapter 2 **Function of the Stem Cell Transcription Factor SALL4 in**

Chapter 3 **The Glucocorticoid Receptor and Certain KRÜPPEL-Like**

S.A. Sharawi, Ehab M. El-Nahas and Clinton Jones

Chapter 4 **Roles of Non-Coding RNAs in Transcriptional Regulation 55**

Cheemala Ashok and Sudhakar Baluchamy

**Section 2 The Interplay Between Transcription Factors and**

**for Crop Improvement 103**

Chapter 5 **MicroRNAs in Bone Diseases: Progress and Prospects 77**

Chapter 6 **Transcription Factors and MicroRNA Interplay: A New Strategy**

Sumit Jangra, Vrantika Chaudhary and Neelam R. Yadav

Loudu Srijyothi, Saravanaraman Ponne, Talukdar Prathama,

**Transcription Factors have the Potential to Synergistically Stimulate Bovine Herpesvirus 1 Transcription and Reactivation**

Fouad S. El-mayet, Ayman S. El-Habbaa, Gabr F. El-Bagoury, Saad

Hui-Yi Loh, Yuin-Yee Lau, Kok-Song Lai and Mohd Azuraidi Osman

**Post-transcriptional Regulation 3**

Chapter 1 **Introductory Chapter: A Brief Overview of Transcriptional and**

## Contents

### **Preface XI**



Fouad S. El-mayet, Ayman S. El-Habbaa, Gabr F. El-Bagoury, Saad S.A. Sharawi, Ehab M. El-Nahas and Clinton Jones


Preface

book.

Gene expression is a complex process that is controlled at multiple cellular layers including the chromatin level through chromatin modification and remodeling, the mRNA level (tran‐ scriptional and post-transcriptional regulation) and protein level (translational regulation and post-translational degradation). It constitutes a fundamental process to diverse biologi‐ cal processes that occur within the cell including cell development and differentiation, the response and the adaptation to environmental stresses and others. Transcriptional and posttranscriptional regulations have been extensively studied and are the most investigated lay‐ ers apart from gene regulation. This is explained by the fact that regulations at the transcriptional and post-transcriptional levels are the fundamental and the most important steps for gene regulation because biological techniques allowing for the study of transcrip‐ tion control are well established, accessible, and highly used by the scientific community. Transcriptional regulation involves the interaction and the specific binding of proteins called transcription factors (TFs) to regulatory elements within DNA called transcription factor binding sites (TFBSs) to control the expression of downstream genes, while the posttranscriptional regulation involves the interaction of non-coding RNAs (miRNAs) by hy‐

bridizing to target mRNAs and thereby regulating their translation and/or stability. The book "Transcriptional and Post Transcriptional Regulation" contains six chapters.

bovine herpesvirus 1 transcription and its reactivation from latency.

ulations and their relevance in cancers.

The **first chapter** is an Introductory Chapter, where the editor introduces transcriptional and post-transcriptional regulations and gives a general overview of the contents of the

The **second chapter** "Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis" was written by Jianchang Yang. This chapter summarizes recent advances in the knowledge of SALL4 biology with a focus on its regulatory functions in normal and leukemic hematopoiesis. The **third chapter** entitled "The Glucocorticoid Receptor and Certain Krüppel-Like Tran‐ scription Factors Have the Potential to Synergistically Stimulate Bovine Herpesvirus 1 Tran‐ scription and Reactivation from Latency" by Fouad S. El-mayet et al. emphasizes the effects of Krüppel-like transcription factors and glucocorticoid receptors on the reactivation of the

The **fourth chapter** by Sudhakar Baluchamy, and co-workers entitled "Roles of Non-Coding RNAs in Transcriptional Regulation" provides an interesting depiction of non-coding RNAs (ncRNAs) and focuses mainly on their role(s) in transcriptional and post-transcriptional reg‐

## Preface

Gene expression is a complex process that is controlled at multiple cellular layers including the chromatin level through chromatin modification and remodeling, the mRNA level (tran‐ scriptional and post-transcriptional regulation) and protein level (translational regulation and post-translational degradation). It constitutes a fundamental process to diverse biologi‐ cal processes that occur within the cell including cell development and differentiation, the response and the adaptation to environmental stresses and others. Transcriptional and posttranscriptional regulations have been extensively studied and are the most investigated lay‐ ers apart from gene regulation. This is explained by the fact that regulations at the transcriptional and post-transcriptional levels are the fundamental and the most important steps for gene regulation because biological techniques allowing for the study of transcrip‐ tion control are well established, accessible, and highly used by the scientific community. Transcriptional regulation involves the interaction and the specific binding of proteins called transcription factors (TFs) to regulatory elements within DNA called transcription factor binding sites (TFBSs) to control the expression of downstream genes, while the posttranscriptional regulation involves the interaction of non-coding RNAs (miRNAs) by hy‐ bridizing to target mRNAs and thereby regulating their translation and/or stability.

The book "Transcriptional and Post Transcriptional Regulation" contains six chapters.

The **first chapter** is an Introductory Chapter, where the editor introduces transcriptional and post-transcriptional regulations and gives a general overview of the contents of the book.

The **second chapter** "Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis" was written by Jianchang Yang. This chapter summarizes recent advances in the knowledge of SALL4 biology with a focus on its regulatory functions in normal and leukemic hematopoiesis.

The **third chapter** entitled "The Glucocorticoid Receptor and Certain Krüppel-Like Tran‐ scription Factors Have the Potential to Synergistically Stimulate Bovine Herpesvirus 1 Tran‐ scription and Reactivation from Latency" by Fouad S. El-mayet et al. emphasizes the effects of Krüppel-like transcription factors and glucocorticoid receptors on the reactivation of the bovine herpesvirus 1 transcription and its reactivation from latency.

The **fourth chapter** by Sudhakar Baluchamy, and co-workers entitled "Roles of Non-Coding RNAs in Transcriptional Regulation" provides an interesting depiction of non-coding RNAs (ncRNAs) and focuses mainly on their role(s) in transcriptional and post-transcriptional reg‐ ulations and their relevance in cancers.

The **fifth chapter** by Lai Kok-Song and colleagues entitled "MicroRNAs in Bone Diseases: Progress and Prospects" focuses on the role of miRNAs in normal osteoblast and osteosarco‐ ma cells. It also discusses the great potential of miRNA as a new therapeutic approach to treat human bone diseases.

The book concludes with the **sixth chapter** "Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement", which provides a new tip based on the relation‐ ship and the interplay between transcription factors and miRNA in different plant species.

The editor would like to thank all the authors for their contributions. The editor is also grateful to Intech Open publisher, particularly Ms. Ivana Glavic, for her assistance and pa‐ tience until the publication of this book.

> **Dr. Kais Ghedira** Laboratory of Bioinformatics, Biomathematics and Biostatistics Institut Pasteur de Tunis Tunisia

**Section 1**

**Transcriptional and Post-transcriptional**

**Regulation**

**Transcriptional and Post-transcriptional Regulation**

The **fifth chapter** by Lai Kok-Song and colleagues entitled "MicroRNAs in Bone Diseases: Progress and Prospects" focuses on the role of miRNAs in normal osteoblast and osteosarco‐ ma cells. It also discusses the great potential of miRNA as a new therapeutic approach to

The book concludes with the **sixth chapter** "Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement", which provides a new tip based on the relation‐ ship and the interplay between transcription factors and miRNA in different plant species. The editor would like to thank all the authors for their contributions. The editor is also grateful to Intech Open publisher, particularly Ms. Ivana Glavic, for her assistance and pa‐

Laboratory of Bioinformatics, Biomathematics and Biostatistics

**Dr. Kais Ghedira**

Tunisia

Institut Pasteur de Tunis

treat human bone diseases.

VIII Preface

tience until the publication of this book.

**Chapter 1**

Provisional chapter

**Introductory Chapter: A Brief Overview of**

Introductory Chapter: A Brief Overview of

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.79753

Kais Ghedira

Kais Ghedira

1. Prologue

mRNA.

degradation).

miRNA gene targets.

**Transcriptional and Post-transcriptional Regulation**

DOI: 10.5772/intechopen.79753

The regulation of gene expression is the process by which expression of genes is controlled (induced or repressed) at the cell level in a particular time under a particular condition. It is a fundamental process to diverse other biological processes that occur within the cell including cell development and differentiation, the response and the adaptation to environmental stresses. Gene regulation has classically been viewed as the interaction between proteins to regulatory elements located at the vicinity of the transcription start site within promoters. However, gene regulation is a more complex process that involves additional layers of control including chromatin remodeling, nucleosome positioning, histone modifications, DNAbinding regulatory proteins such as transcription factors and noncoding RNA [1–3]. Such process requires structural and chemical changes to the genetic material, binding of proteins to specific DNA elements to regulate transcription, or mechanisms that modulate translation of

Indeed, gene expression is controlled at multiple cellular levels consisting in the chromatin level through chromatin modification and remodeling, the mRNA level (transcriptional and posttranscriptional regulation) and protein level (translation regulation and posttranslational

This introductory chapter will give a brief overview on the transcriptional and posttranscriptional regulation, list the main database resources that can be used for transcriptional and/or posttranscriptional regulation data and finally list the main tools allowing to predict TF and

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

Transcriptional and Post-transcriptional Regulation

#### **Introductory Chapter: A Brief Overview of Transcriptional and Post-transcriptional Regulation** Introductory Chapter: A Brief Overview of Transcriptional and Post-transcriptional Regulation

DOI: 10.5772/intechopen.79753

#### Kais Ghedira Kais Ghedira

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.79753

## 1. Prologue

The regulation of gene expression is the process by which expression of genes is controlled (induced or repressed) at the cell level in a particular time under a particular condition. It is a fundamental process to diverse other biological processes that occur within the cell including cell development and differentiation, the response and the adaptation to environmental stresses. Gene regulation has classically been viewed as the interaction between proteins to regulatory elements located at the vicinity of the transcription start site within promoters. However, gene regulation is a more complex process that involves additional layers of control including chromatin remodeling, nucleosome positioning, histone modifications, DNAbinding regulatory proteins such as transcription factors and noncoding RNA [1–3]. Such process requires structural and chemical changes to the genetic material, binding of proteins to specific DNA elements to regulate transcription, or mechanisms that modulate translation of mRNA.

Indeed, gene expression is controlled at multiple cellular levels consisting in the chromatin level through chromatin modification and remodeling, the mRNA level (transcriptional and posttranscriptional regulation) and protein level (translation regulation and posttranslational degradation).

This introductory chapter will give a brief overview on the transcriptional and posttranscriptional regulation, list the main database resources that can be used for transcriptional and/or posttranscriptional regulation data and finally list the main tools allowing to predict TF and miRNA gene targets.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

## 2. Transcriptional regulation

Regulation at the transcriptional level involves proteins called transcription factors (TFs) that recognize and bind specifically to regulatory elements within the promoter regions to control the expression of a downstream gene. These TFs regulate target genes—by turning them on and off—in order to make sure that they are transcribed into mRNA within the cell at the right time and in the right amount. TFs are classified into three large families of DNA-binding domains that include:


High-throughput techniques including ChIP-on-chip/ChIP-seq and enhanced yeast onehybrid have been widely employed to uncover protein-DNA interactions [9, 10] and represent convenient methods to identify and characterize the repertoire of regulatory elements that can be targeted by a protein of interest or transcription factors that can bind a DNA sequence of interest [11], respectively. Thanks to the ENCODE (Encyclopedia of DNA Elements) project aiming to build a comprehensive parts list of functional elements in the human genome including regulatory elements that control cells, such regulatory data were made available for the scientific community (https://www.encodeproject.org/; http://genome.ucsc.edu/encode/ downloads.html) [12] and led to largely improve our understanding of gene regulation.

In addition to the ENCODE project, several regulatory databases have been developed for including multiple animals/plants/microorganisms regulation data. Table 1 lists the most widely used transcriptional regulation database with a brief description, reference to original publication and current accessible website URL.


3. Post-transcriptional regulation

Acronyms in bold letters denote curated databases.

Table 1. Eukaryotic and prokaryotic regulation databases.

PRODORIC PRODORIC2 http://www.

Regulatory Network Repository of Transcription Factor and microRNA Mediated Gene Regulations

Transcriptional Regulatory Element Database

Transcriptional Regulatory Relationships Unraveled by Sentence Based Text mining

Open Regulatory Annotation

Gene Transcription Regulation

Transcription factor prediction

database

Database

database

A very large part of the human genome constitutes noncoding elements classified as small noncoding RNAs (sncRNAs) and long noncoding RNAs (lncRNAs). These noncoding components are receiving increased attention from researchers due to their predicted important role in posttranscriptional regulation. Small ncRNAs class includes small interfering RNAs (siRNAs), microRNAs (miRNAs), PIWI-interacting RNAs (piRNAs), endogenous small interfering RNAs (endo-siRNAs or esiRNAs), promoter associate RNAs (pRNAs), small nucleolar RNAs (snoRNAs), and sno-derived RNAs, while lncRNAs includes linc RNA, NAT, eRNA,

Database Acronym Website link Description References genome/funcgen/ index.html

> regnetworkweb. org/source.jsp

RegNetwork http://www.

TRED http://rulai.cshl. edu/TRED/

TRRUST http://www.

ORegAnno http://www.

grnpedia.org/ trrust/

oreganno.org/

prodoric2.de

transcriptionfactor. org/index.cgi? Home

GTRD http://gtrd.biouml. org/

DBD http://www.

expression and its regulation in human and mouse, with a focus on

http://dx.doi.org/10.5772/intechopen.79753

RegNetwork is developed based on 25 databases that provide the regulatory relationship information, annotation, and other necessary information in order to derive the regulatory relationships.

TRED provides good training datasets for further genome-wide cisregulatory element prediction, assist detailed functional studies, and facilitate to decipher the gene regulatory networks.

TRRUST database provides information of mode of regulation (activation or repression).

The Open Regulatory Annotation database (ORegAnno) is a resource for curated regulatory annotation.

The PRODORIC2 database hosts one of the largest collections of DNAbinding sites for prokaryotic transcription factors.

The most complete collection of uniformly processed ChIP-seq data to identify transcription factor binding sites for human and mouse.

DBD is a database of predicted transcription factors in completely

sequenced genomes.

[16]

5

[17]

[18]

[19]

[20]

[21]

[22]

the transcriptional and posttranscriptional mechanisms.

Introductory Chapter: A Brief Overview of Transcriptional and Post-transcriptional Regulation

Introductory Chapter: A Brief Overview of Transcriptional and Post-transcriptional Regulation http://dx.doi.org/10.5772/intechopen.79753 5


Table 1. Eukaryotic and prokaryotic regulation databases.

## 3. Post-transcriptional regulation

2. Transcriptional regulation

4 Transcriptional and Post-transcriptional Regulation

2. The TFs with basic leucine zipper domains [6].

tion and current accessible website URL.

Transcription Regulatory Regions database

Ensembl Regulation Ensembl

TRANSFAC TRANSFAC http://genexplain.

Regulation

Regulation at the transcriptional level involves proteins called transcription factors (TFs) that recognize and bind specifically to regulatory elements within the promoter regions to control the expression of a downstream gene. These TFs regulate target genes—by turning them on and off—in order to make sure that they are transcribed into mRNA within the cell at the right time and in the right amount. TFs are classified into three large families of DNA-binding domains that include:

1. Basic helix-loop-helix (bHLH) proteins found in organisms from yeast to humans and function in critical developmental processes controlling embryonic development, particu-

3. TFs with the helix-turn-helix (HTH) domains that are involved in a wide range of functions beyond transcription regulation, including DNA repair and replication, RNA metabolism, and protein-protein interactions in diverse signaling contexts [7, 8]. This group also includes homeobox (zinc finger, HOX-like, TALE, POU, etc.) and homeodomain protein products. High-throughput techniques including ChIP-on-chip/ChIP-seq and enhanced yeast onehybrid have been widely employed to uncover protein-DNA interactions [9, 10] and represent convenient methods to identify and characterize the repertoire of regulatory elements that can be targeted by a protein of interest or transcription factors that can bind a DNA sequence of interest [11], respectively. Thanks to the ENCODE (Encyclopedia of DNA Elements) project aiming to build a comprehensive parts list of functional elements in the human genome including regulatory elements that control cells, such regulatory data were made available for the scientific community (https://www.encodeproject.org/; http://genome.ucsc.edu/encode/ downloads.html) [12] and led to largely improve our understanding of gene regulation.

In addition to the ENCODE project, several regulatory databases have been developed for including multiple animals/plants/microorganisms regulation data. Table 1 lists the most widely used transcriptional regulation database with a brief description, reference to original publica-

Database Acronym Website link Description References

TRANSFAC® is a maintained and curated database of eukaryotic transcription factors, their genomic binding sites, and DNA-binding

TRRD is a unique information resource, accumulating information on the structural and functional organization of transcription regulatory regions of eukaryotic

Ensembl Regulation provides resources used for studying gene [13]

[14]

[15]

profiles.

genes.

com/transfac/

bionet.nsc.ru/mgs/ gnw/trrd/

https://www. ensembl.org/info/

TRRD http://wwwmgs.

larly in neurogenesis, myogenesis, heart development, and hematopoiesis [4, 5].

A very large part of the human genome constitutes noncoding elements classified as small noncoding RNAs (sncRNAs) and long noncoding RNAs (lncRNAs). These noncoding components are receiving increased attention from researchers due to their predicted important role in posttranscriptional regulation. Small ncRNAs class includes small interfering RNAs (siRNAs), microRNAs (miRNAs), PIWI-interacting RNAs (piRNAs), endogenous small interfering RNAs (endo-siRNAs or esiRNAs), promoter associate RNAs (pRNAs), small nucleolar RNAs (snoRNAs), and sno-derived RNAs, while lncRNAs includes linc RNA, NAT, eRNA, circ RNA, ceRNAs, PROMPTS. Both lncRNAs and sncRNAs have been identified at regulatory elements [23, 24]. Among these noncoding elements, microRNAs have been the most widely investigated since their discovery in the early 1990s, underscoring their importance in posttranscriptional gene regulation [25]. These later act as posttranscriptional regulators of their messenger RNA (mRNA) targets via mRNA degradation and/or translational repression [26]. It has been widely evidenced that miRNA-mediated downregulation is a one-way process leading to the repression of translation and/or target mRNA degradation [27–30]; however, recent studies have shown that miRNAs are able to upregulate gene expression in specific cell types and conditions with distinct transcripts and proteins [31].

4. The interplay between TFs and miRNAs

system.

TF-target prediction

BART: Binding analysis for regulation of transcription

MiRNA-target prediction

MATCH http://gene-regulation.

TargetScan http://www.targetscan.

miRWalk http://zmf.umm.uni-

Table 3. TF and miRNA target prediction tools.

RNAhybrid https://bibiserv.

Transcription factors (TFs) and microRNAs (miRNAs) are key regulators of gene expression. Several studies have shown that abnormal miRNA and/or TF expression can be critical for cell survival and development through targeting critical genes in the cellular system. In the last decade, several bioinformatic studies have been performed to elucidate transcriptional and posttranscriptional (mostly miRNA-mediated) regulatory interactions. Besides experimental techniques (ChIP-Seq, ChIP-ChIP, yeast two-hybrid, miRISCs), computational tools have been developed to predict the TF-gene target and/or miRNA-target interactions. Table 3 lists some bioinformatic tools used to predict transcriptional and posttranscriptional regulation. Using such tools and/or through the integration of data collected from public databases (Tables 1 and 2), researchers were able to generate regulatory networks aiming to understand mechanisms involved in some phenotypes and/or diseases. Recent studies focused on the study of mixed miRNA/TF feed-forward regulatory loops (FFLs) through genome-wide transcriptional and posttranscriptional regulatory network integration to decipher the complex and interlinked cascade of events related to several diseases [46–48]. Such approaches provide the scientific community with the ability to investigate the interplay between TFs and miRNAs in a given

Introductory Chapter: A Brief Overview of Transcriptional and Post-transcriptional Regulation

http://dx.doi.org/10.5772/intechopen.79753

7

Tool/Web tool Website link Description References

selected genes.

mouse.

miRNA.

DNA sequences.

show a similar expression pattern to a group of user-

A novel computational method and software package for predicting functional transcription factors that regulate a query gene set or associate with a query genomic profile, based on more than 6000 existing ChIP-seq datasets for over 400 factors in human or

Match is a weight matrix-based program for predicting transcription factor binding sites (TFBS) in

RNAhybrid is a tool for finding the minimum free energy hybridization of a long and a short RNA.

TargetScan predicts biological targets of miRNAs by searching for the presence of conserved 8mer, 7mer, and 6mer sites that match the seed region of each

Supplying the biggest available collection of predicted

and experimentally verified miRNA-target interactions with various novel and unique features. [40]

[41]

[42]

[43]

[44]

[45]

TargetFinder http://targetfinder.org/ Provides a web-based resource for finding genes that

http://faculty.virginia. edu/zanglab/bart/

com/pub/programs. html#match

cebitec.uni-bielefeld.de/

heidelberg.de/apps/zmf/

rnahybrid/

org/vert\_72/

mirwalk2/

Pulling down microRNA-induced silencing complexes (miRISCs) immunoprecipitation method allows researchers to collect information on microRNAs and their mRNA targets in vivo. Such information has been collected and stored in several public databases. Table 2 contains the most widely used posttranscriptional regulation database with a brief description, reference to original publication and current functional website URL.


Acronyms in bold letters denote curated databases.

Table 2. Eukaryotic and prokaryotic posttranscriptional regulation databases.

## 4. The interplay between TFs and miRNAs

circ RNA, ceRNAs, PROMPTS. Both lncRNAs and sncRNAs have been identified at regulatory elements [23, 24]. Among these noncoding elements, microRNAs have been the most widely investigated since their discovery in the early 1990s, underscoring their importance in posttranscriptional gene regulation [25]. These later act as posttranscriptional regulators of their messenger RNA (mRNA) targets via mRNA degradation and/or translational repression [26]. It has been widely evidenced that miRNA-mediated downregulation is a one-way process leading to the repression of translation and/or target mRNA degradation [27–30]; however, recent studies have shown that miRNAs are able to upregulate gene expression in specific cell

Pulling down microRNA-induced silencing complexes (miRISCs) immunoprecipitation method allows researchers to collect information on microRNAs and their mRNA targets in vivo. Such information has been collected and stored in several public databases. Table 2 contains the most widely used posttranscriptional regulation database with a brief description, reference to origi-

Database Acronym Website link Description References

The miRBase database is a searchable database of published miRNA sequences

miRTarBase has accumulated miRNAtarget interactions (MTIs), which are collected by manually surveying pertinent

miRDB is an online database for miRNA target prediction and functional

An online resource that stores information related to the known miRNAs in metazoan.

Contains predicted viral miRNA candidate

ViTa collects virus data from miRBase and ICTV, VirGne, VBRC, etc. and provide effective annotations, including human miRNA expression, virus-infected tissues, annotation of virus, and comparisons.

miRecords is a resource for animal miRNA-

Provides several million human microRNA-target predictions, which were collected across 30 different resources.

[32]

[33]

[34]

[35]

[36]

[37]

[38]

[39]

and annotation.

literature.

annotations

hairpins

target interactions.

mirbase.org/

mbc.nctu.edu.tw/ php/index.php

mbc.nctu.edu.tw/

sinica.edu.tw/cgibin/miRNA/ miRNA.cgi

accurascience.com/ miRecords/

utoronto.ca/mirDIP/

miRTarBase http://mirtarbase.

miRDB/

edu.tw/

mirDIP http://ophid.

Table 2. Eukaryotic and prokaryotic posttranscriptional regulation databases.

types and conditions with distinct transcripts and proteins [31].

nal publication and current functional website URL.

The microRNA database miRBase http://www.

6 Transcriptional and Post-transcriptional Regulation

miRDB miRDB http://mirdb.org/

miRNAMap miRNAMap http://mirnamap.

Vir-Mir Vir-Mir http://alk.ibms.

Virus miRNA Target ViTA http://vita.mbc.nctu.

miRecords miRecords http://c1.

Acronyms in bold letters denote curated databases.

The experimentally validated microRNAtarget interactions database

microRNA Data Integration Portal Transcription factors (TFs) and microRNAs (miRNAs) are key regulators of gene expression. Several studies have shown that abnormal miRNA and/or TF expression can be critical for cell survival and development through targeting critical genes in the cellular system. In the last decade, several bioinformatic studies have been performed to elucidate transcriptional and posttranscriptional (mostly miRNA-mediated) regulatory interactions. Besides experimental techniques (ChIP-Seq, ChIP-ChIP, yeast two-hybrid, miRISCs), computational tools have been developed to predict the TF-gene target and/or miRNA-target interactions. Table 3 lists some bioinformatic tools used to predict transcriptional and posttranscriptional regulation. Using such tools and/or through the integration of data collected from public databases (Tables 1 and 2), researchers were able to generate regulatory networks aiming to understand mechanisms involved in some phenotypes and/or diseases. Recent studies focused on the study of mixed miRNA/TF feed-forward regulatory loops (FFLs) through genome-wide transcriptional and posttranscriptional regulatory network integration to decipher the complex and interlinked cascade of events related to several diseases [46–48]. Such approaches provide the scientific community with the ability to investigate the interplay between TFs and miRNAs in a given system.


Table 3. TF and miRNA target prediction tools.

## 5. Conclusion

During these last years, transcriptional and posttranscriptional regulation constituted the most important layers of gene regulation. However, a recent study by Barna group [49] has upset our understanding of gene regulation. Indeed, while researchers have believed for decades that ribosomes are identical showing no preference for translating RNA molecules into proteins, it appears that these later exhibit a preference for translating certain types of genes. One type of ribosome, for example, prefers to translate genes involved in cellular differentiation, while another specializes in genes that carry out essential metabolic duties. This study is uncovering a new layer of gene expression regulation that will have broad implications for basic science and human disease.

[7] Wintjens R, Rooman M. Structural classification of HTH DNA-binding domains and protein-DNA interaction modes. Journal of Molecular Biology. 1996;262(2):294-313. DOI:

Introductory Chapter: A Brief Overview of Transcriptional and Post-transcriptional Regulation

http://dx.doi.org/10.5772/intechopen.79753

9

[8] Aravind L, Anantharaman V, Balaji S, Babu MM, Iyer LM. The many faces of the helixturn-helix domain: Transcription regulation and beyond. FEMS Microbiology Reviews.

[9] Johnson DS, Mortazavi A, Myers RM, Wold B. Genome-wide mapping of in vivo protein-

[10] Reece-Hoyes JS, Barutcu AR, McCord RP, Jeong JS, Jiang L, MacWilliams A, Yang X, Salehi-Ashtiani K, Hill DE, Blackshaw S, Zhu H, Dekker J, Walhout AJM. Yeast onehybrid assays for gene-centered human gene regulatory network mapping. Nature

[11] Reece-Hoyes JS, Diallo A, Lajoie B, Kent A, Shrestha S, Kadreppa S, Pesyna C, Dekker J, Myers CL, Walhout AJ. Enhanced yeast one-hybrid assays for high-throughput genecentered regulatory network mapping. Nature Methods. 2011;8(12):1059-1064. DOI: 10.1038/nmeth.1748. PubMed PMID: 22037705; PubMed Central PMCID: PMC3235803

[12] ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature. 2012;489(7414):57-74. DOI: 10.1038/nature11247. PubMed PMID:

[13] Wingender E. The TRANSFAC project as an example of framework technology that supports the analysis of genomic regulation. Brief Bioinform. 2008 Jul;9(4):326-332. DOI:

[14] Kolchanov NA, Ignatieva EV, Ananko EA, Podkolodnaya OA, Stepanenko IL, Merkulova TI, Pozdnyakov MA, Podkolodny NL, Naumochkin AN, Romashchenko AG. Transcription regulatory regions database (TRRD): Its status in 2002. Nucleic Acids Research. 2002;

[15] Zerbino DR, Johnson N, Juetteman T, Sheppard D, Wilder SP, Lavidas I, Nuhn M, Perry E, Raffaillac-Desfosses Q, Sobral D, Keefe D, Gräf S, Ahmed I, Kinsella R, Pritchard B, Brent S, Amode R, Parker A, Trevanion S, Birney E, Dunham I, Flicek P. Ensembl regulation resources. Database (Oxford). 2016 Feb 17;2016. pii: bav119. DOI: 10.1093/database/bav119.

[16] Liu ZP, Wu C, Miao H, Wu H. RegNetwork: An integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse. Database (Oxford). 2015 Sep 30;2015. pii: bav095. DOI: 10.1093/database/bav095. Print 2015. PubMed PMID:

[17] Jiang C, Xuan Z, Zhao F, Zhang MQ. TRED: A transcriptional regulatory element database, new entries and other development. Nucleic Acids Research. 2007;35(Database issue):D137-D140. PubMed PMID: 17202159; PubMed Central PMCID: PMC1899102

Print 2016. PubMed PMID: 26888907; PubMed Central PMCID: PMC4756621

10.1006/jmbi.1996.0514. PMID 8831795

2005;29(2):231-262. Review. PubMed PMID: 15808743

DNA interactions. Science. 2007;316:1497-1502

22955616; PubMed Central PMCID: PMC3439153

26424082; PubMed Central PMCID: PMC4589691

10.1093/bib/bbn016. Epub 2008 Apr 24. PubMed PMID: 18436575

Methods. 2011;8:1050-1052

30(1):312-317

## Author details

### Kais Ghedira

Address all correspondence to: kais.ghedira@pasteur.rns.tn

Laboratory of Bioinformatics, Biomathematics and Biostatistics, Institut Pasteur de Tunis, University of Tunis El-Manar, Tunis, Tunisia

## References


[7] Wintjens R, Rooman M. Structural classification of HTH DNA-binding domains and protein-DNA interaction modes. Journal of Molecular Biology. 1996;262(2):294-313. DOI: 10.1006/jmbi.1996.0514. PMID 8831795

5. Conclusion

Author details

Kais Ghedira

References

basic science and human disease.

8 Transcriptional and Post-transcriptional Regulation

Address all correspondence to: kais.ghedira@pasteur.rns.tn

istry and Molecular Biology. 2009;44:117-141

Nature Reviews. Genetics. 2009;10:155-159

2(6):621-702. PMID 7553065

PMC463060

12192032

Nature Reviews. Molecular Cell Biology. 2006;7:612-616

University of Tunis El-Manar, Tunis, Tunisia

During these last years, transcriptional and posttranscriptional regulation constituted the most important layers of gene regulation. However, a recent study by Barna group [49] has upset our understanding of gene regulation. Indeed, while researchers have believed for decades that ribosomes are identical showing no preference for translating RNA molecules into proteins, it appears that these later exhibit a preference for translating certain types of genes. One type of ribosome, for example, prefers to translate genes involved in cellular differentiation, while another specializes in genes that carry out essential metabolic duties. This study is uncovering a new layer of gene expression regulation that will have broad implications for

Laboratory of Bioinformatics, Biomathematics and Biostatistics, Institut Pasteur de Tunis,

[1] Venters BJ, Pugh BF. How eukaryotic genes are transcribed. Critical Reviews in Biochem-

[2] Mercer TR, Dinger ME, Mattick JS. Long non-coding RNAs: Insights into functions.

[3] Goodrich JA, Kugel JF. Non-coding-RNA regulators of RNA polymerase II transcription.

[4] Littlewood TD, Evan GI. Transcription factors 2: Helix-loop-helix. Protein Profile. 1995;

[5] Jones S. An overview of the basic helix-loop-helix proteins. Genome Biology. 2004;5(6): 226. Epub 2004 May 28. Review. PubMed PMID: 15186484; PubMed Central PMCID:

[6] Vinson C, Myakishev M, Acharya A, Mir AA, Moll JR, Bonovich M. Classification of human B-ZIP proteins based on dimerization properties. Molecular and Cellular Biology. 2002;22(18):6321-6335. DOI: 10.1128/MCB.22.18.6321-6335.2002. PMC 135624. PMID


[18] TRRUST v2: An expanded reference database of human and mouse transcriptional regulatory interactions. Nucleic Acids Research; 26 Oct, 2017

[31] Place RF, Li LC, Pookot D, Noonan EJ, Dahiya R. MicroRNA-373 induces expression of genes with complementary promoter sequences. Proceedings of the National Academy of Sciences of the United States of America. 2008;105(5):1608-1613. DOI: 10.1073/pnas.0707594 105. Epub 2008 Jan 28. Erratum in: Proc Natl Acad Sci U S A. 2018 Mar 19;:. PubMed PMID:

Introductory Chapter: A Brief Overview of Transcriptional and Post-transcriptional Regulation

http://dx.doi.org/10.5772/intechopen.79753

11

[32] Kozomara A, Griffiths-Jones S. miRBase: Annotating high confidence microRNAs using

[33] Chou C-H, Shrestha S, Yang C-D, Chang N-W, Lin Y-L, Liao K-W, Huang W-C, Sun T-H, Tu S-J, Lee W-H, Chiew M-Y, Tai C-S, Wei T-Y, Tsai T-R, Huang H-T, Wang C-Y, Wu H-Y, Ho S-Y, Chen P-R, Chuang C-H, Hsieh P-J, Wu Y-S, Chen W-L, Li M-J, Wu Y-C, Huang X-Y, Ng FL, Buddhakosai W, Huang P-C, Lan K-C, Huang C-Y, Weng S-L, Cheng Y-N, Liang C, Hsu W-L, Huang H-D. miRTarBase update 2018: A resource for experimentally validated microRNA-target interactions. Nucleic Acids Research. 2018;46(D1):D296-D302.

[34] Wong N, Wang X. miRDB: An online resource for microRNA target prediction and func-

[35] Hsu SD, Chu CH, Tsou AP, Chen SJ, Chen HC, Hsu PW, Wong YH, Chen YH, Chen GH, Huang HD. miRNAMap 2.0: Genomic maps of microRNAs in metazoan genomes.

[36] Li SC, Shiau CK, Lin WC. Vir-Mir db: Prediction of viral microRNA candidate hairpins. Nucleic Acids Res. 2008 Jan;36(Database issue):D184-D189. Epub 2007 Aug 15. PubMed

[37] Hsu PW, Lin LZ, Hsu SD, Hsu JB, Huang HD. ViTa: Prediction of host microRNAs targets

[38] Xiao F, Zuo Z, Cai G, Kang S, Gao X, Li T. miRecords: An integrated resource for

[39] Tokar T, Pastrello C, Rossos AEM, Abovsky M, Hauschild AC, Tsay M, Lu R, Jurisica I. mirDIP 4.1-integrative database of human microRNA target predictions. Nucleic Acids Research. 2018;46(D1):D360-D370. DOI: 10.1093/nar/gkx1144. PubMed PMID: 29194489;

[40] Szymon M. Kiełbasa, Nils Blüthgen, Michael Fähling, Ralf Mrowka; Targetfinder.org: A resource for systematic discovery of transcription factor target genes, Nucleic Acids

[41] Wang Z, Civelek M, Miller CL, Sheffield NC, Guertin MJ, Zang C. BART: A transcription factor prediction tool with query gene sets or epigenomic profiles. Bioinformatics. 2018 Mar 28. DOI: 10.1093/bioinformatics/bty194. [Epub ahead of print] PubMed PMID:

on viruses. Nucleic Acids Research. 2007;35(Database issue):D381-D385

microRNA-target interactions. Nucleic Acids Research. 2009;37:D105-D110

tional annotations. Nucleic Acids Research. 2015;43(D1):D146-D152

Nucleic Acids Research. 2008;36(Database issue):D165-D169

PMID: 17702763; PubMed Central PMCID: PMC2238904

Research, 38, suppl 2, 2010, W233–W238, 10.1093/nar/gkq374

PubMed Central PMCID: PMC5753284

29608647

18227514; PubMed Central PMCID: PMC2234192

deep sequencing data. Narrative. 2014;42:D68-D73

DOI: 10.1093/nar/gkx1067


[31] Place RF, Li LC, Pookot D, Noonan EJ, Dahiya R. MicroRNA-373 induces expression of genes with complementary promoter sequences. Proceedings of the National Academy of Sciences of the United States of America. 2008;105(5):1608-1613. DOI: 10.1073/pnas.0707594 105. Epub 2008 Jan 28. Erratum in: Proc Natl Acad Sci U S A. 2018 Mar 19;:. PubMed PMID: 18227514; PubMed Central PMCID: PMC2234192

[18] TRRUST v2: An expanded reference database of human and mouse transcriptional regu-

[19] Lesurf R, Cotto KC, Wang G, Griffith M, Kasaian K, Jones SJM, Montgomery SB, Griffith OL, The Open Regulatory Annotation Consortium. ORegAnno 3.0: A community-driven resource for curated regulatory annotation. Nucleic Acids Research. 2016;44(D1):D126-

[20] Münch R, Hiller K, Barg H, Heldt D, Linz S, Wingender E, Jahn D. PRODORIC: Prokary-

[21] Yevshin IS, Sharipov RN, Valeev TF, Kel AE, Kolpakov FA. GTRD: A database of transcription factor binding sites identified by ChIP-seq experiments. Nucleic Acids Research.

[22] Wilson D, Charoensawan V, Kummerfeld SK, Teichmann SA. DBD––Taxonomically broad transcription factor predictions: New content and functionality. Nucleic Acids Research.

[23] Lewis BP, Shih I-H, Jones-Rhoades MW, Bartel DP, Burge CB. Prediction of mammalian

[24] Brennecke J, Stark A, Russell RB, Cohen SM. Principles of microRNA-target recognition.

[25] Valinezhad Orang A, Safaralizadeh R, Kazemzadeh-Bavili M. Mechanisms of miRNAmediated gene regulation from common downregulation to mRNA-specific upregulation. International Journal of Genomics. 2014;2014:970607. DOI: 10.1155/2014/970607. Epub 2014 Aug 10. Review. PubMed PMID: 25180174; PubMed Central PMCID: PMC4142390

[26] Catalanotto C, Cogoni C, Zardo G. MicroRNA in control of gene expression: An overview of nuclear functions. International Journal of Molecular Sciences. 2016;17(10):pii: E1712.

[27] Zeng Y, Yi R, Cullen BR. MicroRNAs and small interfering RNAs can inhibit mRNA expression by similar mechanisms. Proceedings of the National Academy of Sciences of the United States of America. 2003;100(17):9779-9784. Epub 2003 Aug 5. PubMed PMID:

[28] Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, Bettinger JC, Rougvie AE, Horvitz HR, Ruvkun G. The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis

[29] Llave C, Xie Z, Kasschau KD, Carrington JC. Cleavage of scarecrow-like mRNA targets directed by a class of Arabidopsis miRNA. Science. 2002;297(5589):2053-2056. PubMed

[30] Lee RC, Feinbaum RL, Ambros V. The C. Elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell. 1993;75(5):843-854. PubMed PMID:

Review. PubMed PMID: 27754357; PubMed Central PMCID: PMC5085744

elegans. Nature. 2000;403(6772):901-906. PubMed PMID: 10706289

otic database of gene regulation. Nucleic Acids Research. 2003;31:266-269

latory interactions. Nucleic Acids Research; 26 Oct, 2017

2008;36(suppl\_1):D88-D92. DOI: 10.1093/nar/gkm964

microRNA targets. Cell. 2003;115(7):787-798

12902540; PubMed Central PMCID: PMC187842

D132. DOI: 10.1093/nar/gkv1203

10 Transcriptional and Post-transcriptional Regulation

2017;45(D1):D61-D67

PLoS Biology. 2005;3(3):e85

PMID: 12242443

8252621


[42] Kel AE, Goessling E, Reuter I, Cheremushkin E, Kel-Margoulis OV, Wingender E. Match (TM): A tool for searching transcription factor binding sites in DNA sequences. Nucleic Acids Research. 2003;31:3576-3579

**Chapter 2**

**Provisional chapter**

**Function of the Stem Cell Transcription Factor SALL4 in**

**Function of the Stem Cell Transcription Factor SALL4 in** 

SALL4 is a zinc finger DNA-binding protein that has been well characterized in development and in embryonic stem cell (ESC) maintenance. Notably, SALL4 may be one of the few genes that are also involved in tissue stem cells in adults, and SALL4 protein expression has been correlated with the presence of stem and progenitor cell populations in various organ systems and also in human cancers. In normal hematopoiesis, SALL4 expression is restricted to the rare hematopoietic stem/progenitor cell (HSC/ HPC) fractions but is rapidly silenced following lineage differentiation. In hematopoietic malignancies, however, SALL4 is persistently expressed and its expression levels are linked with deteriorated disease status. Furthermore, SALL4 activation participates in the pathogenesis of tumor initiation and disease progression. This chapter summarizes recent advances in our knowledge of SALL4 biology with a focus on its regulatory functions in normal and leukemic hematopoiesis. A better understanding of SALL4's biologic functions and mechanisms is needed to facilitate the development of advanced therapies

**Keywords:** pluripotency, leukemogenesis, hematopoietic stem/progenitor cell,

MLL-rearrangement, epigenetic, histone methylation, DNA methylation, differentiation,

SALL4 is one of four human homologs (*SALL-1, -2, -3, -4*) of the Drosophila region-specific gene *Spalt* (*sal*). In Drosophila, *sal* is a homeotic gene essential for development of posterior head and anterior tail segments. As a DNA-binding transcription factor, the SALL4 protein is characterized by multiple Cys2His2 zinc finger (C2H2-ZF) domain distributed over the entire

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

DOI: 10.5772/intechopen.76454

**Hematopoiesis**

**Hematopoiesis**

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.76454

Jianchang Yang

**Abstract**

in future.

**1. Introduction**

zinc finger domain

Jianchang Yang


#### **Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis**

DOI: 10.5772/intechopen.76454

#### Jianchang Yang Jianchang Yang

[42] Kel AE, Goessling E, Reuter I, Cheremushkin E, Kel-Margoulis OV, Wingender E. Match (TM): A tool for searching transcription factor binding sites in DNA sequences. Nucleic

[43] Marc R, Steffen P, Hoechsmann M, Giegerich R. Fast and effective prediction of microRNA/

[44] Agarwal V, Bell GW, Nam JW, Bartel DP. Predicting effective microRNA target sites in mammalian mRNAs. Elife. 2015 Aug 12;4. DOI: 10.7554/eLife.05005. PubMed PMID:

[45] Dweep H et al. miRWalk—Database: Prediction of possible miRNA binding sites by 'walking' the genes of 3 genomes. Journal of Biomedical Informatics. 2011;44:839-837 [46] Friard O, Re A, Taverna D, De Bortoli M, Corá D. CircuitsDB: A database of mixed micro-RNA/transcription factor feed-forward regulatory circuits in human and mouse. BMC Bioinformatics. 2010;11:435. DOI: 10.1186/1471-2105-11-435. PubMed PMID: 20731828; PubMed

[47] Wang H, Luo J, Liu C, Niu H, Wang J, Liu Q, Zhao Z, Xu H, Ding Y, Sun J, Zhang Q. Investigating microRNA and transcription factor co-regulatory networks in colorectal cancer. BMC Bioinformatics. 2017;18(1):388. DOI: 10.1186/s12859-017-1796-4. PubMed

[48] Nampoothiri SS, Fayaz SM, Rajanikant GK. A novel five-node feed-forward loop unravels miRNA-gene-TF regulatory relationships in ischemic stroke. Molecular Neurobiology. 2018. DOI: 10.1007/s12035-018-0963-6. [Epub ahead of print] PubMed PMID: 29524052 [49] Simsek D, Tiu GC, Flynn RA, Byeon GW, Leppek K, Xu AF, Chang HY, Barna M. The mammalian ribo-interactome reveals ribosome functional diversity and heterogeneity. Cell. 2017;169(6):1051-1065.e18. DOI: 10.1016/j.cell.2017.05.022. PubMed PMID: 28575669; PubM-

Acids Research. 2003;31:3576-3579

12 Transcriptional and Post-transcriptional Regulation

target duplexes RNA. RNA. 2004

Central PMCID: PMC2936401

ed Central PMCID: PMC5548193

26267216; PubMed Central PMCID: PMC4532895

PMID: 28865443; PubMed Central PMCID: PMC5581471

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.76454

#### **Abstract**

SALL4 is a zinc finger DNA-binding protein that has been well characterized in development and in embryonic stem cell (ESC) maintenance. Notably, SALL4 may be one of the few genes that are also involved in tissue stem cells in adults, and SALL4 protein expression has been correlated with the presence of stem and progenitor cell populations in various organ systems and also in human cancers. In normal hematopoiesis, SALL4 expression is restricted to the rare hematopoietic stem/progenitor cell (HSC/ HPC) fractions but is rapidly silenced following lineage differentiation. In hematopoietic malignancies, however, SALL4 is persistently expressed and its expression levels are linked with deteriorated disease status. Furthermore, SALL4 activation participates in the pathogenesis of tumor initiation and disease progression. This chapter summarizes recent advances in our knowledge of SALL4 biology with a focus on its regulatory functions in normal and leukemic hematopoiesis. A better understanding of SALL4's biologic functions and mechanisms is needed to facilitate the development of advanced therapies in future.

**Keywords:** pluripotency, leukemogenesis, hematopoietic stem/progenitor cell, MLL-rearrangement, epigenetic, histone methylation, DNA methylation, differentiation, zinc finger domain

## **1. Introduction**

SALL4 is one of four human homologs (*SALL-1, -2, -3, -4*) of the Drosophila region-specific gene *Spalt* (*sal*). In Drosophila, *sal* is a homeotic gene essential for development of posterior head and anterior tail segments. As a DNA-binding transcription factor, the SALL4 protein is characterized by multiple Cys2His2 zinc finger (C2H2-ZF) domain distributed over the entire

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

protein [1–3]. In mammals, the expression of SALL4 has been primarily detected in ESCs and in adult tissue "stem-like" cells, where it mainly activates pluripotency and/or multipotency genes and suppresses differentiation-related genes, thereby modulating the cell "stemness" in development and in tissue generation [4–8]. In humans, heterozygous SALL4 mutation has been linked to Okihiro syndrome, Holt-Oram syndrome, acro-renal-ocular syndrome, and IVIC syndrome, all characterized by multiple organ malformations [9–11]. While normally downregulated or no longer expressed in fully differentiated somatic cells, abnormal reactivation of SALL4 in adult cells may lead to malignancy. To date, aberrant SALL4 expression has been detected in over 10 types of human solid tumors and in several common types of leukemias, and SALL4 has been considered a useful biomarker for these diseases [7, 8, 12, 13]. In addition, studies suggest that SALL4 may be a therapeutic target in treating human leukemias [12, 13]. For these reasons, it will be important to understand how SALL4, a critical pluripotency factor, exerts its effects in different cell contexts, and how we can effectively translate our knowledge gains into treatment breakthroughs in future.

## **2. SALL4 roles in stem cells and development**

#### **2.1. The roles of SALL4 in ESC property maintenance and embryonic development**

SALL4 has been one of the most studied transcriptional regulators in ESC self-renewal and pluripotency maintenance. It has been reported that in human ESCs, a well-controlled SALL4/ OCT4 transcription regulatory loop balances proper expression dosage of SALL4 and OCT4; and reduction of SALL4, like OCT4, results in re-specification of ESCs to the trophoblast lineage [14–17]. In mouse ESC studies, chromatin immunoprecipitation coupled to microarray hybridization (ChIP-on-chip) revealed that SALL4 binds to about twice as many gene promoters as NANOG and binds about four times more genes than OCT4; and the three factors were found to form heteromeric protein complex in regulating stem cell pluripotency. Further, SALL4 binds many genes that are regulated by chromatin-based epigenetic events mediated by cohesin complex, polycomb-repressive complexes 1 and 2 (PRC1 and PRC2), and bivalent domains [18, 19]. Thus, SALL4 plays a diverse role in regulating stem cell pluripotency (see **Figure 1**).

In early embryonic development, SALL4 expression in mouse is detected at as early as the two cell stage. At the blastocyst stage, SALL4 expression becomes enriched in the inner cell mass (ICM) and the trophectoderm [17, 20–22]. Reduction of SALL4 in oocytes and ESCs results in early embryo defects, and disruption of both *Sall4* alleles causes embryonic lethality during peri-implantation [23–25]. SALL4 is also expressed in extraembryonic endoderm (XEN) cells, where it participates in cell fate decision by simultaneously activating pluripotency-maintaining factors and silencing endoderm lineage-associated factors such as GATA6, GATA4, and SOX17 [26, 27]. During subsequent stages, heterozygous disruption of *Sall4* allele leads to multi-organ malformations including limb and heart defects, which model human disease [25]. It has been reported that TBX5, a gene encoding a T-box transcription factor, regulates SALL4 expression in the developing forelimb and heart, and interacts with SALL4 to synergistically regulate downstream gene expression [24, 25, 28].

**2.2. SALL4 is a potent regulator in reprogramming somatic cells to pluripotency**

PRC: polycomb-repressive complexes.

Decreased SALL4 expression in ESCs has been shown to downregulate the expression levels of Oct4, Sox2, Klf4, and c-Myc (OSKM), the four proteins capable of reprogramming murine somatic cells to an induced pluripotent state [18, 29]. Consistently, knockdown of SALL4 in fibroblasts decreased the efficiency of induced pluripotent stem cell (iPSC) generation, while overexpression of SALL4 significantly increased iPSC generation [30, 31]. In a recent study by Shu et al., the GATA family members GATA4 and GATA6 have been found to substitute for OCT4 in mouse somatic reprogramming, and SALL4 is identified as a major target gene of the GATA members [32]. In another study by Buganim et al., ectopic expression of SALL4, NANOG, ESRRB, and LIN28 in mouse fibroblasts generated high-quality iPSCs more

**Figure 1.** SALL4 plays a variety of regulatory functions in maintaining and/or reprogramming cells to pluripotency.

Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis

http://dx.doi.org/10.5772/intechopen.76454

15

protein [1–3]. In mammals, the expression of SALL4 has been primarily detected in ESCs and in adult tissue "stem-like" cells, where it mainly activates pluripotency and/or multipotency genes and suppresses differentiation-related genes, thereby modulating the cell "stemness" in development and in tissue generation [4–8]. In humans, heterozygous SALL4 mutation has been linked to Okihiro syndrome, Holt-Oram syndrome, acro-renal-ocular syndrome, and IVIC syndrome, all characterized by multiple organ malformations [9–11]. While normally downregulated or no longer expressed in fully differentiated somatic cells, abnormal reactivation of SALL4 in adult cells may lead to malignancy. To date, aberrant SALL4 expression has been detected in over 10 types of human solid tumors and in several common types of leukemias, and SALL4 has been considered a useful biomarker for these diseases [7, 8, 12, 13]. In addition, studies suggest that SALL4 may be a therapeutic target in treating human leukemias [12, 13]. For these reasons, it will be important to understand how SALL4, a critical pluripotency factor, exerts its effects in different cell contexts, and how we can effectively

translate our knowledge gains into treatment breakthroughs in future.

**2.1. The roles of SALL4 in ESC property maintenance and embryonic development**

SALL4 has been one of the most studied transcriptional regulators in ESC self-renewal and pluripotency maintenance. It has been reported that in human ESCs, a well-controlled SALL4/ OCT4 transcription regulatory loop balances proper expression dosage of SALL4 and OCT4; and reduction of SALL4, like OCT4, results in re-specification of ESCs to the trophoblast lineage [14–17]. In mouse ESC studies, chromatin immunoprecipitation coupled to microarray hybridization (ChIP-on-chip) revealed that SALL4 binds to about twice as many gene promoters as NANOG and binds about four times more genes than OCT4; and the three factors were found to form heteromeric protein complex in regulating stem cell pluripotency. Further, SALL4 binds many genes that are regulated by chromatin-based epigenetic events mediated by cohesin complex, polycomb-repressive complexes 1 and 2 (PRC1 and PRC2), and bivalent domains [18, 19]. Thus, SALL4 plays a diverse role in regulating stem cell pluripotency (see **Figure 1**).

In early embryonic development, SALL4 expression in mouse is detected at as early as the two cell stage. At the blastocyst stage, SALL4 expression becomes enriched in the inner cell mass (ICM) and the trophectoderm [17, 20–22]. Reduction of SALL4 in oocytes and ESCs results in early embryo defects, and disruption of both *Sall4* alleles causes embryonic lethality during peri-implantation [23–25]. SALL4 is also expressed in extraembryonic endoderm (XEN) cells, where it participates in cell fate decision by simultaneously activating pluripotency-maintaining factors and silencing endoderm lineage-associated factors such as GATA6, GATA4, and SOX17 [26, 27]. During subsequent stages, heterozygous disruption of *Sall4* allele leads to multi-organ malformations including limb and heart defects, which model human disease [25]. It has been reported that TBX5, a gene encoding a T-box transcription factor, regulates SALL4 expression in the developing forelimb and heart, and interacts with SALL4

to synergistically regulate downstream gene expression [24, 25, 28].

**2. SALL4 roles in stem cells and development**

14 Transcriptional and Post-transcriptional Regulation

**Figure 1.** SALL4 plays a variety of regulatory functions in maintaining and/or reprogramming cells to pluripotency. PRC: polycomb-repressive complexes.

#### **2.2. SALL4 is a potent regulator in reprogramming somatic cells to pluripotency**

Decreased SALL4 expression in ESCs has been shown to downregulate the expression levels of Oct4, Sox2, Klf4, and c-Myc (OSKM), the four proteins capable of reprogramming murine somatic cells to an induced pluripotent state [18, 29]. Consistently, knockdown of SALL4 in fibroblasts decreased the efficiency of induced pluripotent stem cell (iPSC) generation, while overexpression of SALL4 significantly increased iPSC generation [30, 31]. In a recent study by Shu et al., the GATA family members GATA4 and GATA6 have been found to substitute for OCT4 in mouse somatic reprogramming, and SALL4 is identified as a major target gene of the GATA members [32]. In another study by Buganim et al., ectopic expression of SALL4, NANOG, ESRRB, and LIN28 in mouse fibroblasts generated high-quality iPSCs more efficiently than the combination of OSKM [33]. Similarly, Mansour et al., showed that the combined overexpression of SALL4 with stem cell factors SALL1, UTF1, NANOG and MYC also replaced exogenous OSK expression and generated chimaera formation- competent iPSC clones [34]. Together, these studies suggest that SALL4 not only plays a role in ESC property maintenance, but its overexpression also drives reprogramming of somatic cells toward a stem cell-like fate (see **Figure 1**).

the expression of more than half of its binding genes in ESCs, but downregulation of SALL4 did not result in similar expression changes in the majority of these genes in XEN cells [26].

Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis

http://dx.doi.org/10.5772/intechopen.76454

17

In humans and mice, the SALL4 proteins exist in at least three isoforms termed A, B and C, with SALL4A (full length) and SALL4B (lacks a portion of exon2 sequence) being the most studied [38–40]. To date, the function of SALL4C isoform (exon2 sequence spliced out) has not been well characterized. In the human blood system, the cellular expressions of SALL4 isoforms have been originally investigated by immunofluorescence staining and qRT-PCR assays, which revealed that both A and B isoforms are highly expressed in bone marrow CD34+CD38− HSCs, downregulated in CD34+CD38+ HPCs, and absent in CD34− differentiated lineage cells. Similarly, the SALL4 -A and -B isoforms in mouse bone marrows were found selectively expressed in the nuclei of Lin-Sca1+cKit+ (LSK) HSCs. The functions of SALL4 in the self-renewal of HSCs/HPCs have been explored. We and others reported that the SALL4 isoforms are robust stimulators for CD34+ (or CD133+) HSCs/HPCs *ex vivo* expansion, and the SALL4-mediated cell expansion was associated with enhanced cell engraftment and long-term repopulation capacity in transplanted mice [40–44]. In mouse model studies, forced overexpression of the SALL4 isoforms in bone marrow LSK cells likewise leads to sustained cell proliferation, as well as enhanced marrow-repopulating potential *in vivo* [39]. By transcripts assays, the increased HSC/HPC growth was found associated with upregulation of important HSC regulatory genes including HOXB4, NOTCH1, BMI1, RUNX1, CMYC, MEIS1 and NF-YA [39]. Further, in a myeloid progenitor cell line (32D cell) study, overexpression of the SALL4 isoforms blocked granulocyte-colony stimulating factor (G-CSF)-induced granulocytic differentiation, and permitted expansion of undifferentiated cells in the presence of defined cytokines [39, 40]. Thus, the SALL4 isoforms stimulate HSC/HPC proliferation by activating important self-renewal regulators and simultaneously inhibiting cellular differentiation. These studies provide a new avenue for investigating mechanisms of SALL4 regulated HSC/HPC self-renewal and potentially achieving clinically significant expansion of

**3.2. ChIP-on-chip and gene expression assays identified important target genes that** 

In their study of SALL4 regulated networks in normal hematopoiesis, Gao et al. have sorted human bone marrow and cord blood CD34+ cells, and performed ChIP-on-chip together with gene expression assays . This investigation identified that CD34, RUNX1, HOXA9, and PTEN are SALL4-directed target genes in these cells. In particular, HOXA9 was characterized as a major SALL4 target in normal hematopoiesis . In another study, the polycomb complex protein BMI-1 as a critical SALL4 downstream target has been documented [45]. Chromatin

**3. Functions of SALL4 and its regulated networks in normal** 

**3.1. The SALL4 isoforms are robust simulators for HSC/HPC** *ex vivo* **expansion**

**hematopoiesis**

transplantable human HSCs.

**are regulated by SALL4**

#### **2.3. SALL4 regulates distinct transcriptional networks in ESCs and XEN cells**

SALL4 appears to be unique among the core ESC pluripotency regulators because it is also expressed in non-ESC stem cell fractions where Oct4 and/or Nanog are silenced. These include XEN cells, mesodermal progenitor cells [35], embryonic cardiac progenitor cells [36], fetal liver stem/progenitor cells [27], and adult stem cells such as bone marrow HSCs/HPCs [37]. In these cells, SALL4 regulates downstream networks in a cell type-specific manner. Genomewide promoter binding assays in murine ESCs and XEN cells revealed that SALL4 regulates disparate gene sets in these cells, and down-regulation of SALL4 targets in the respective cell types induced differentiation [26]. Also consistent with the previous report [18], Sall4, Oct4, Sox2, and Nanog in murine ESCs formed a crucial interconnected autoregulatory network. In XEN cells however, SALL4 regulates the key XEN lineage-associated genes Gata4, Gata6, Sox7, and Sox17 (see **Figure 2**). Moreover, transcription assays revealed that SALL4 regulates

**Figure 2.** SALL4 binds and regulates distinct target genes in ESCs and XEN cells. Shown are examples of such genes in each cell types. Figure modified from Ref. [26].

the expression of more than half of its binding genes in ESCs, but downregulation of SALL4 did not result in similar expression changes in the majority of these genes in XEN cells [26].

## **3. Functions of SALL4 and its regulated networks in normal hematopoiesis**

efficiently than the combination of OSKM [33]. Similarly, Mansour et al., showed that the combined overexpression of SALL4 with stem cell factors SALL1, UTF1, NANOG and MYC also replaced exogenous OSK expression and generated chimaera formation- competent iPSC clones [34]. Together, these studies suggest that SALL4 not only plays a role in ESC property maintenance, but its overexpression also drives reprogramming of somatic cells toward a

SALL4 appears to be unique among the core ESC pluripotency regulators because it is also expressed in non-ESC stem cell fractions where Oct4 and/or Nanog are silenced. These include XEN cells, mesodermal progenitor cells [35], embryonic cardiac progenitor cells [36], fetal liver stem/progenitor cells [27], and adult stem cells such as bone marrow HSCs/HPCs [37]. In these cells, SALL4 regulates downstream networks in a cell type-specific manner. Genomewide promoter binding assays in murine ESCs and XEN cells revealed that SALL4 regulates disparate gene sets in these cells, and down-regulation of SALL4 targets in the respective cell types induced differentiation [26]. Also consistent with the previous report [18], Sall4, Oct4, Sox2, and Nanog in murine ESCs formed a crucial interconnected autoregulatory network. In XEN cells however, SALL4 regulates the key XEN lineage-associated genes Gata4, Gata6, Sox7, and Sox17 (see **Figure 2**). Moreover, transcription assays revealed that SALL4 regulates

**Figure 2.** SALL4 binds and regulates distinct target genes in ESCs and XEN cells. Shown are examples of such genes in

**2.3. SALL4 regulates distinct transcriptional networks in ESCs and XEN cells**

stem cell-like fate (see **Figure 1**).

16 Transcriptional and Post-transcriptional Regulation

each cell types. Figure modified from Ref. [26].

#### **3.1. The SALL4 isoforms are robust simulators for HSC/HPC** *ex vivo* **expansion**

In humans and mice, the SALL4 proteins exist in at least three isoforms termed A, B and C, with SALL4A (full length) and SALL4B (lacks a portion of exon2 sequence) being the most studied [38–40]. To date, the function of SALL4C isoform (exon2 sequence spliced out) has not been well characterized. In the human blood system, the cellular expressions of SALL4 isoforms have been originally investigated by immunofluorescence staining and qRT-PCR assays, which revealed that both A and B isoforms are highly expressed in bone marrow CD34+CD38− HSCs, downregulated in CD34+CD38+ HPCs, and absent in CD34− differentiated lineage cells. Similarly, the SALL4 -A and -B isoforms in mouse bone marrows were found selectively expressed in the nuclei of Lin-Sca1+cKit+ (LSK) HSCs. The functions of SALL4 in the self-renewal of HSCs/HPCs have been explored. We and others reported that the SALL4 isoforms are robust stimulators for CD34+ (or CD133+) HSCs/HPCs *ex vivo* expansion, and the SALL4-mediated cell expansion was associated with enhanced cell engraftment and long-term repopulation capacity in transplanted mice [40–44]. In mouse model studies, forced overexpression of the SALL4 isoforms in bone marrow LSK cells likewise leads to sustained cell proliferation, as well as enhanced marrow-repopulating potential *in vivo* [39]. By transcripts assays, the increased HSC/HPC growth was found associated with upregulation of important HSC regulatory genes including HOXB4, NOTCH1, BMI1, RUNX1, CMYC, MEIS1 and NF-YA [39]. Further, in a myeloid progenitor cell line (32D cell) study, overexpression of the SALL4 isoforms blocked granulocyte-colony stimulating factor (G-CSF)-induced granulocytic differentiation, and permitted expansion of undifferentiated cells in the presence of defined cytokines [39, 40]. Thus, the SALL4 isoforms stimulate HSC/HPC proliferation by activating important self-renewal regulators and simultaneously inhibiting cellular differentiation. These studies provide a new avenue for investigating mechanisms of SALL4 regulated HSC/HPC self-renewal and potentially achieving clinically significant expansion of transplantable human HSCs.

#### **3.2. ChIP-on-chip and gene expression assays identified important target genes that are regulated by SALL4**

In their study of SALL4 regulated networks in normal hematopoiesis, Gao et al. have sorted human bone marrow and cord blood CD34+ cells, and performed ChIP-on-chip together with gene expression assays . This investigation identified that CD34, RUNX1, HOXA9, and PTEN are SALL4-directed target genes in these cells. In particular, HOXA9 was characterized as a major SALL4 target in normal hematopoiesis . In another study, the polycomb complex protein BMI-1 as a critical SALL4 downstream target has been documented [45]. Chromatin immunoprecipitation coupled with quantitative PCR (ChIP-qPCR) in the 32D myeloid progenitor cells reveals that SALL4 binds to a specific region of *Bmi-1* gene promoter, and heterozygous disruption of *Sall4* allele significantly reduced BMI-1 expression in bone marrow cells. Further, in transgenic mice that constitutively overexpress human SALL4B, there is upregulated expression of BMI-1, whose levels increase in the progression from normal to preleukemic (myelodysplastic syndrome [MDS]) and leukemic (acute myeloid leukemia [AML]) stages [45].

in partial remission (PR), and then even lower in complete remission (CR) [61, 62]. Further, SALL4 was found to decrease throughout the treatment process in the drug responsive group but increase in drug resistant group [62]. In other leukemia cases, aberrant SALL4 expression

Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis

http://dx.doi.org/10.5772/intechopen.76454

acute lymphocytic leukemia (B-ALL), most prominently in B-ALL patients with TEL-AML1 translocation, which is the most common genetic abnormality in pediatric B-ALL [67, 68]. SALL4 expression is also detected in precursor B-cell (but not T-cell) lymphoblastic leukemia/ lymphomas [61]. In addition, SALL4 expression has been detected in patient samples from blastic stage of chronic myeloid leukemia (CML), as opposed to the chronic phase, and in samples from CML patients who have achieved complete remission or those who have tyro-

Given the detection of aberrant SALL4 expression in leukemia patients, our research group has previously investigated transgenic mice that overexpress either human SALL4A or SALL4B. Interestingly, all the *SALL4B* mice developed MDS-like features at 2 months of age, and nine of them (53%) progressed to AML. In contrast, the SALL4A mice did not exhibit leukemia formation during the test period [59]. These studies suggest that SALL4B, but not SALL4A, has oncogenic activity in inducing leukemogenesis. In mechanism studies, the SALL4 isoforms were found to bind β-catenin protein, and these factors synergistically enhanced the Wnt/β-catenin signaling pathway. As expected, the expression levels of cyclin-D1 and c-Myc, the two known targets of the Wnt/β-catenin pathway, were both increased in the *SALL4B* mice bone marrow cells. Interestingly, in a recent study, transgenic activation of the SALL4 target β-catenin in osteoblasts, the HSC/HPC niche, also induced MDS and AML development. Notably, these β-catenin mutated mice were anemic at as early as 2 weeks and died before 6 weeks of age, indicating a severe driving event in leukemogenesis [71]. Further in-depth studies are therefore needed to elucidate whether SALL4B in transgenic mice poten-

ALCL) [66], B cell

19

has been reported in ALK positive anaplastic large cell lymphoma (ALK+

**4.2. Role of SALL4 in transgenic model and in MLL-rearranged leukemia**

tially induces leukemogenesis via activating β-catenin in the osteoblastic niche.

Recently, our group explored SALL4 functions in leukemia pathogenesis induced by MLL-AF9, one of the most common mixed lineage leukemia (MLL)-rearranged (MLL-r) oncoproteins found in leukemia patients which is associated with very poor prognosis [72–76]. A previous study showed that SALL4 physically interacts with the MLL wild type protein in regulating HOXA9 expression [77]. In this study, our data revealed that loss of SALL4 in MLL-AF9-transformed bone marrow cells largely disrupted their clonogenic ability in methylcellulose-based medium and in liquid culture, induced markable apoptosis and cell cycle arrest at G1. Consistently, conditional disruption of both *Sall4* alleles in transplanted mice completely blocked leukemia initiation and significantly attenuated pre-existing disease progression [46]. Therefore, these studies suggest that SALL4 is an essential transcriptional regulator in MLL-r leukemogenesis.

Our research group has previously conducted ChIP-on-chip assays with a promyelocytic leukemic cell line NB4 [78]. Analysis of the SALL4-bound genes revealed the most prominent pathways involving WNT/β-catenin, apoptosis, NOTCH signaling, the polycomb complex

sine kinase inhibitor resistance [61, 69, 70].

**4.3. SALL4 regulated pathways in leukemia**

### **3.3. SALL4 roles in normal HSC/HPC capacity maintenance**

In human CD34+ cell studies, a shRNA-mediated SALL4 knockdown resulted in decreased *in vitro* myeloid-colony-forming ability and impaired *in vivo* engraftment. Further, loss of either SALL4 or its downstream target HOXA9 expression in CD34+ cells shared a similar phenotype. These findings indicate that the role of SALL4 and HOXA9 in normal hematopoiesis is to maintain the HSPCs in an undifferentiated stage with self-renewal capacity [37]. Very recently, the roles of SALL4 in normal hematopoiesis have been further explored using conditional gene targeting approaches in mice [46]. Unexpectedly, wild type *Sall4f/f*/CreERT2 mice treated with tamoxifen or vav-Cre-mediated (hematopoietic-specific) *Sall4*−/− mice were all healthy and displayed no significant hematopoietic defects, which contrasts to previous findings from human CD34+ cell studies. Reasons for this discrepancy have not been fully addressed. However, it has been speculated that SALL4 may have a redundant role during homeostasis, which can be compensated by other *Sall* gene family members, or *pretreatment* of gene knockdown may not truly reflect the actual performance of gene functions *in vitro* or *in vivo*. On the other hand, some genes may exert aberrant functions only when cells encounter transplantation or replicative stress (see review [47]), and some vav/Cre knockout models may demonstrate hematopoietic defects at late stages [48]. Therefore, it might be necessary to perform serial transplantation and/or stress induction (such as 5-fluorouracil injury) assays with SALL4-deficient cells to fully clarify SALL4 effect and mechanisms in normal HSC capacity maintenance.

## **4. Functions of SALL4 and its regulated networks in leukemia**

#### **4.1. SALL4 is aberrantly expressed in human leukemias**

SALL4 is absent in most adult tissues and SALL4 expression in bone marrow is restricted to the rare CD34+ HSCs/HPCs. However, aberrant expression of SALL4 has been detected in various human solid tumors as well as different types of leukemias [49–57]. In patients with MDS, a group of preleukemic hematologic disorders, a high level of SALL4 expression is detected and correlated with high-risk patients with poor survival [58, 59]. In AML cases, our group and others have reported that SALL4 mRNA or proteins are aberrantly expressed in various AML subtypes (ranging from M1 to M5, the French-American-British [FAB] classification), and SALL4 expression is involved in chromosomal instability and associated with disease status and drug treatments [59–65]. SALL4 expression is found significantly higher in AML patients with complex karyotype (equal to or more than three aberrant karyotypes) than that in MDS patients with normal karyotype [63]. In chemotherapy cases, it has been reported that SALL4 has the highest expression level in de novo AML patients which then decreases in partial remission (PR), and then even lower in complete remission (CR) [61, 62]. Further, SALL4 was found to decrease throughout the treatment process in the drug responsive group but increase in drug resistant group [62]. In other leukemia cases, aberrant SALL4 expression has been reported in ALK positive anaplastic large cell lymphoma (ALK+ ALCL) [66], B cell acute lymphocytic leukemia (B-ALL), most prominently in B-ALL patients with TEL-AML1 translocation, which is the most common genetic abnormality in pediatric B-ALL [67, 68]. SALL4 expression is also detected in precursor B-cell (but not T-cell) lymphoblastic leukemia/ lymphomas [61]. In addition, SALL4 expression has been detected in patient samples from blastic stage of chronic myeloid leukemia (CML), as opposed to the chronic phase, and in samples from CML patients who have achieved complete remission or those who have tyrosine kinase inhibitor resistance [61, 69, 70].

#### **4.2. Role of SALL4 in transgenic model and in MLL-rearranged leukemia**

immunoprecipitation coupled with quantitative PCR (ChIP-qPCR) in the 32D myeloid progenitor cells reveals that SALL4 binds to a specific region of *Bmi-1* gene promoter, and heterozygous disruption of *Sall4* allele significantly reduced BMI-1 expression in bone marrow cells. Further, in transgenic mice that constitutively overexpress human SALL4B, there is upregulated expression of BMI-1, whose levels increase in the progression from normal to preleukemic (myelodysplastic syndrome [MDS]) and leukemic (acute myeloid leukemia [AML]) stages [45].

In human CD34+ cell studies, a shRNA-mediated SALL4 knockdown resulted in decreased *in vitro* myeloid-colony-forming ability and impaired *in vivo* engraftment. Further, loss of either SALL4 or its downstream target HOXA9 expression in CD34+ cells shared a similar phenotype. These findings indicate that the role of SALL4 and HOXA9 in normal hematopoiesis is to maintain the HSPCs in an undifferentiated stage with self-renewal capacity [37]. Very recently, the roles of SALL4 in normal hematopoiesis have been further explored using conditional gene targeting approaches in mice [46]. Unexpectedly, wild type *Sall4f/f*/CreERT2 mice treated with tamoxifen or vav-Cre-mediated (hematopoietic-specific) *Sall4*−/− mice were all healthy and displayed no significant hematopoietic defects, which contrasts to previous findings from human CD34+ cell studies. Reasons for this discrepancy have not been fully addressed. However, it has been speculated that SALL4 may have a redundant role during homeostasis, which can be compensated by other *Sall* gene family members, or *pretreatment* of gene knockdown may not truly reflect the actual performance of gene functions *in vitro* or *in vivo*. On the other hand, some genes may exert aberrant functions only when cells encounter transplantation or replicative stress (see review [47]), and some vav/Cre knockout models may demonstrate hematopoietic defects at late stages [48]. Therefore, it might be necessary to perform serial transplantation and/or stress induction (such as 5-fluorouracil injury) assays with SALL4-deficient cells to fully

**3.3. SALL4 roles in normal HSC/HPC capacity maintenance**

18 Transcriptional and Post-transcriptional Regulation

clarify SALL4 effect and mechanisms in normal HSC capacity maintenance.

**4. Functions of SALL4 and its regulated networks in leukemia**

SALL4 is absent in most adult tissues and SALL4 expression in bone marrow is restricted to the rare CD34+ HSCs/HPCs. However, aberrant expression of SALL4 has been detected in various human solid tumors as well as different types of leukemias [49–57]. In patients with MDS, a group of preleukemic hematologic disorders, a high level of SALL4 expression is detected and correlated with high-risk patients with poor survival [58, 59]. In AML cases, our group and others have reported that SALL4 mRNA or proteins are aberrantly expressed in various AML subtypes (ranging from M1 to M5, the French-American-British [FAB] classification), and SALL4 expression is involved in chromosomal instability and associated with disease status and drug treatments [59–65]. SALL4 expression is found significantly higher in AML patients with complex karyotype (equal to or more than three aberrant karyotypes) than that in MDS patients with normal karyotype [63]. In chemotherapy cases, it has been reported that SALL4 has the highest expression level in de novo AML patients which then decreases

**4.1. SALL4 is aberrantly expressed in human leukemias**

Given the detection of aberrant SALL4 expression in leukemia patients, our research group has previously investigated transgenic mice that overexpress either human SALL4A or SALL4B. Interestingly, all the *SALL4B* mice developed MDS-like features at 2 months of age, and nine of them (53%) progressed to AML. In contrast, the SALL4A mice did not exhibit leukemia formation during the test period [59]. These studies suggest that SALL4B, but not SALL4A, has oncogenic activity in inducing leukemogenesis. In mechanism studies, the SALL4 isoforms were found to bind β-catenin protein, and these factors synergistically enhanced the Wnt/β-catenin signaling pathway. As expected, the expression levels of cyclin-D1 and c-Myc, the two known targets of the Wnt/β-catenin pathway, were both increased in the *SALL4B* mice bone marrow cells. Interestingly, in a recent study, transgenic activation of the SALL4 target β-catenin in osteoblasts, the HSC/HPC niche, also induced MDS and AML development. Notably, these β-catenin mutated mice were anemic at as early as 2 weeks and died before 6 weeks of age, indicating a severe driving event in leukemogenesis [71]. Further in-depth studies are therefore needed to elucidate whether SALL4B in transgenic mice potentially induces leukemogenesis via activating β-catenin in the osteoblastic niche.

Recently, our group explored SALL4 functions in leukemia pathogenesis induced by MLL-AF9, one of the most common mixed lineage leukemia (MLL)-rearranged (MLL-r) oncoproteins found in leukemia patients which is associated with very poor prognosis [72–76]. A previous study showed that SALL4 physically interacts with the MLL wild type protein in regulating HOXA9 expression [77]. In this study, our data revealed that loss of SALL4 in MLL-AF9-transformed bone marrow cells largely disrupted their clonogenic ability in methylcellulose-based medium and in liquid culture, induced markable apoptosis and cell cycle arrest at G1. Consistently, conditional disruption of both *Sall4* alleles in transplanted mice completely blocked leukemia initiation and significantly attenuated pre-existing disease progression [46]. Therefore, these studies suggest that SALL4 is an essential transcriptional regulator in MLL-r leukemogenesis.

#### **4.3. SALL4 regulated pathways in leukemia**

Our research group has previously conducted ChIP-on-chip assays with a promyelocytic leukemic cell line NB4 [78]. Analysis of the SALL4-bound genes revealed the most prominent pathways involving WNT/β-catenin, apoptosis, NOTCH signaling, the polycomb complex protein BMI-1, PTEN, and nuclear factor-kB (see **Figure 3**). When the cells were treated with a SALL4-specific shRNA vector, the expression levels of proapoptotic genes TNF, TP53, PTEN, CARD9, CARD11, ATF3, and LTA were upregulated. In contrast, the expression levels of antiapoptotic genes such as BCL2, BMI-1, DAD1, TEGT, BIRC7, and BIRC4 (XIAP) are downregulated. In line with the expression studies, reduction of SALL4 also diminished tumorigenicity of leukemic cells in immunodeficient mice. Further, the SALL4 knockdown-induced apoptosis was reversed by ectopic expression BMI-1. In a separate study, SALL4 knockdown in combination with a BCL-2 inhibitor also synergistically increased apoptosis in AML cells. Other studies have reported that SALL4 recruits the nucleosome remodeling and histone deacetylation (NuRD/HDAC) repressive complex to the promoter of *PTEN* and decrease its gene expression [79], while conversely, a SALL4-derived peptide blocking this protein-protein interaction resulted in notable leukemic cell death, and this effect was reversed by treatment of a PTEN inhibitor [80]. In AML differentiation studies, SALL4 expression has also been

reported to block all-trans retinoic acid (ATRA)-induced myeloid differentiation in ATRAsensitive and -resistant AML cells. Further, inhibition of SALL4 and its interacting epigenetic factor LSD1 synergistically promoted ATRA-induced cell differentiation and growth arrest. In mechanistic studies, SALL4 and LSD1 have been found to co-occupy on the ATRA targets *RARβ*, *ID2*, and *CYP26* gene promoters, and cooperatively regulate their expression [81–82]. Recently, our research group also conducted ChIP assays with sequencing (ChIP-Seq) assays with MLL-AF9 transformed murine leukemic cells. This study revealed that SALL4 binds to the key MLL-AF9 target genes *Meis1*, *Hoxa9*; MLL-r leukemia related genes *Cebpα*, *Id2*, *Elf1*, *Evl*, *Flt3*, *Nf1*, *Tal1*, *Tcf7l1*, *Nkx2*–*3*; the Hox factors *Hoxa-9*, *−10*, *−11*, *−13*; the Notch ligand *Jag2*, and Wnt/β-catenin regulator *Wnt7b* (see **Figure 3** and [46]). mRNA microarrays assays following early *Sall4* deletion identified multiple upregulated genes including cell cycle inhibitors *Cdkn1a (p21)*, *Trp53inp1*; HSC/HPC colony-forming repressor *Slfn2*; and hematopoietic differentiation markers *Col5a1*, *Fyb*, *Irf8* and *Pira6*. In contrast, the TGFβ family genes, *Tgfβ2*, *Tgfβ3*, *Tgfβr3,* and the genes related to chemo-resistance or leukemia aggressiveness, such as *Thbs1*, *Tgm2*, and Ambp were downregulated [46, 83]. In comparison with the mRNA expression data, not many of the ChIP-Seq-identified SALL4 targets were associated with early expression changes. This limited overlap has been considered to be related to the length of time of SALL4 inactivation, the presence of other co-regulators in play, and/or the relatively lower number of genes identi-

Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis

http://dx.doi.org/10.5772/intechopen.76454

21

fied in relevant assays. More detailed studies would help to address these issues.

**4.4. SALL4 regulates different downstream networks in normal and leukemic cells**

In the SALL4-binding genes identified in NB4 leukemia and those in normal CD34+ cells, less than 20% of the targets were found commonly bound by SALL4. This limited overlap mirrors the findings from ESC and XEN cell promoter binding studies, and further indicates that SALL4 functions in a manner specific to cell type or cell context (see **Figure 4**). Particularly, downregulation of SALL4 expression seems to have an opposite effect on genes involved apoptosis. For example, in leukemic cells, when SALL4 was downregulated along with the apoptotic phenotype, the expression levels of proapoptosis genes TRO

**Figure 4.** SALL4 functions in a manner specific to cell type or cell context. Shown are main effects following SALL4

knockdown in indicated cell types.

**Figure 3.** Key signaling pathways bound by SALL4 in NB4 acute promyelocytic and MLL-AF9 transformed leukemic cells.

reported to block all-trans retinoic acid (ATRA)-induced myeloid differentiation in ATRAsensitive and -resistant AML cells. Further, inhibition of SALL4 and its interacting epigenetic factor LSD1 synergistically promoted ATRA-induced cell differentiation and growth arrest. In mechanistic studies, SALL4 and LSD1 have been found to co-occupy on the ATRA targets *RARβ*, *ID2*, and *CYP26* gene promoters, and cooperatively regulate their expression [81–82].

Recently, our research group also conducted ChIP assays with sequencing (ChIP-Seq) assays with MLL-AF9 transformed murine leukemic cells. This study revealed that SALL4 binds to the key MLL-AF9 target genes *Meis1*, *Hoxa9*; MLL-r leukemia related genes *Cebpα*, *Id2*, *Elf1*, *Evl*, *Flt3*, *Nf1*, *Tal1*, *Tcf7l1*, *Nkx2*–*3*; the Hox factors *Hoxa-9*, *−10*, *−11*, *−13*; the Notch ligand *Jag2*, and Wnt/β-catenin regulator *Wnt7b* (see **Figure 3** and [46]). mRNA microarrays assays following early *Sall4* deletion identified multiple upregulated genes including cell cycle inhibitors *Cdkn1a (p21)*, *Trp53inp1*; HSC/HPC colony-forming repressor *Slfn2*; and hematopoietic differentiation markers *Col5a1*, *Fyb*, *Irf8* and *Pira6*. In contrast, the TGFβ family genes, *Tgfβ2*, *Tgfβ3*, *Tgfβr3,* and the genes related to chemo-resistance or leukemia aggressiveness, such as *Thbs1*, *Tgm2*, and Ambp were downregulated [46, 83]. In comparison with the mRNA expression data, not many of the ChIP-Seq-identified SALL4 targets were associated with early expression changes. This limited overlap has been considered to be related to the length of time of SALL4 inactivation, the presence of other co-regulators in play, and/or the relatively lower number of genes identified in relevant assays. More detailed studies would help to address these issues.

### **4.4. SALL4 regulates different downstream networks in normal and leukemic cells**

In the SALL4-binding genes identified in NB4 leukemia and those in normal CD34+ cells, less than 20% of the targets were found commonly bound by SALL4. This limited overlap mirrors the findings from ESC and XEN cell promoter binding studies, and further indicates that SALL4 functions in a manner specific to cell type or cell context (see **Figure 4**). Particularly, downregulation of SALL4 expression seems to have an opposite effect on genes involved apoptosis. For example, in leukemic cells, when SALL4 was downregulated along with the apoptotic phenotype, the expression levels of proapoptosis genes TRO

**Figure 4.** SALL4 functions in a manner specific to cell type or cell context. Shown are main effects following SALL4 knockdown in indicated cell types.

**Figure 3.** Key signaling pathways bound by SALL4 in NB4 acute promyelocytic and MLL-AF9 transformed leukemic

protein BMI-1, PTEN, and nuclear factor-kB (see **Figure 3**). When the cells were treated with a SALL4-specific shRNA vector, the expression levels of proapoptotic genes TNF, TP53, PTEN, CARD9, CARD11, ATF3, and LTA were upregulated. In contrast, the expression levels of antiapoptotic genes such as BCL2, BMI-1, DAD1, TEGT, BIRC7, and BIRC4 (XIAP) are downregulated. In line with the expression studies, reduction of SALL4 also diminished tumorigenicity of leukemic cells in immunodeficient mice. Further, the SALL4 knockdown-induced apoptosis was reversed by ectopic expression BMI-1. In a separate study, SALL4 knockdown in combination with a BCL-2 inhibitor also synergistically increased apoptosis in AML cells. Other studies have reported that SALL4 recruits the nucleosome remodeling and histone deacetylation (NuRD/HDAC) repressive complex to the promoter of *PTEN* and decrease its gene expression [79], while conversely, a SALL4-derived peptide blocking this protein-protein interaction resulted in notable leukemic cell death, and this effect was reversed by treatment of a PTEN inhibitor [80]. In AML differentiation studies, SALL4 expression has also been

20 Transcriptional and Post-transcriptional Regulation

cells.

and ABL1 increased, and the expression of anti-apoptosis gene BCL2 decreased. While in CD34+ cells, there was no notable apoptosis with SALL4 knockdown, and the expression of BCL2 increased whereas the expression of TRO and ABL1 decreased. This differential regulatory effect by SALL4 should be helpful in developing SALL4-targeted anti-leukemia strategies to spare normal blood cells.

apoptosis, tumor induction or suppression. For example, in NB4 AML cells that were transduced with a lentiviral SALL4 vector, there was an overall increased percentage of DNA methylation at various CpG sites of tumor suppression gene *PTEN*, which co-relates with a downregulated gene transcription [84]. In mouse bone marrow LSK cells, overexpression of SALL4 also induced increased percentage of methylation at the CpG sites of early B-cell factor 1 (*Ebf1*) promoter, as well as the *Sall4* gene promoter itself, which facilitates an undifferentiated cellular status [84]. Similarly, the SALL4 overexpression levels significantly affected LSD1 binding and altered H3K4me2 levels at the promoter regions of tumor necrosis factor (*Tnf*) and differentiation-related genes *EBF1*, *GATA1*, *RARβ*, *ID2*, and *CYP26*, which are associated with relevantly altered gene transcription levels [81, 87]. Also, while SALL4 interacts with the NuRD/HDAC1/2 complex to silence *PTEN* promoter via reduced acetylation of histone H3 at its binding sites, the SALL4 derived peptide blocks this interaction and leads to reactivated PTEN expression. Additionally, in the 32D myeloid progenitor cells following lentiviral SALL4 transduction, the H3K4me3 and H3K79me2/3 levels at *Bmi1* promoter regions were increased [45]. In MLL-AF9 leukemia studies, the expression levels of SALL4 also affected LSD1 and Dot1l binding and relevant H3K4me3 and H3K79me3 amounts at the promoter regions of *Meis1* and multiple HOX family genes in bone

Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis

http://dx.doi.org/10.5772/intechopen.76454

23

**5.2. SALL4 regulated epigenetic modification programs are cell type-dependent**

SALL4-based disease subtype–specific anti-leukemia strategies.

Consistent with the findings from SALL4 genome-wide promoter binding and relevant expression assays, SALL4-regulated epigenetic modification programs are also strictly dependent on the cellular context. As reported, SALL4-bound genomic loci in murine ESCs are largely enriched for the activating marker H3K4me3, which indicates an association of SALL4 with non-repressed genes. In XEN cells, however, SALL4-binding loci displayed significantly less H3K4me3 enrichment. Instead, most of these regions are either accompanied with H3K27me3 or lacking both H3K4me3 and H3K27me3, the "epi-markers" frequently associated with gene repression [26]. In our MLL-AF9 leukemia model studies, SALL4 has been shown to recruit DOT1L and LSD1 to *Meis1* and HOX family gene promoters and modulate their H3K79me2/3 and H3K4me3 levels [46]. The previously demonstrated SALL4-MLL interaction may contribute to the observed HEK4me3 changes. However, in some non-MLL-r human AMLs, the DOT1L-regulated H3K79 methylation may not play a role, and it has been reported that administration of DOT1l inhibitors sensitized chemotherapy in MLL-r but not in non-MLL-r AML cells [97]. Further, the DOT1L recruitment to MLL-AF9 has been associated with the level of leukemic transformation [98–100]. Therefore, one may anticipate that SALL4 differentially interacts with individual epigenetic factors to exerting a disease/subtype–dependent regulatory effect. This concept, if proven true, should further facilitate the development of

Abnormal expression of SALL4 has been frequently detected in different types of human leukemias and associated with disease status and drug treatments. On the other hand, proper manipulation of SALL4 expression might be useful in achieving clinically significant

marrow cells [46, 77, 79].

**6. Conclusions**

## **5. Epigenetic mechanisms involved in SALL4's regulatory functions**

#### **5.1. SALL4 interacts with a variety of epigenetic factors to regulate downstream gene expression**

So far the reported SALL4-interacting epigenetic factors (see **Figure 5**) include: DNA methyltransferases DNMT-1, -3A, -3B, -3 L, methyl-CpG-binding domain 2 protein (MBD2) [84]; NuRD complex that contains histone deacetylases HDAC1/2 [79]; H3K4 methyltransferase MLL1 [77]; H3K79 methyltransferase DOT1L [46]; H3K36 methyltransferase Wolf-Hirschhorn syndrome candidate 1 (WHSC1) [85, 86]; and lysine-specific histone demethylase LSD1/KDM1A [46, 81, 87]. All of these are critical regulators in normal blood development and are frequent targets for dysregulation in hematological malignancies [88–90], and clinical epigenetic remedies inhibiting such epigenetic factors have been shown effective in treating leukemia [91–93]. In fact, in MLL-AF9-mediated mouse AML studies, genetic disruption of either SALL4, DNMT1, LSD1, or DOT1L likewise blocked leukemia initiation and delayed disease progression *in vivo* [94–96].

By interacting with specific epigenetic factors, SALL4 expression can affect DNA methylation and histone methylation/acetylation status at genes that control hematopoietic differentiation,

**Figure 5.** The SALL4-associated epigenetic factors. DNMTs: DNA methyltransferases. HDACs: histone deacetylases. HDMs: histone demethylases. HMTs: histone methyltransferases.

apoptosis, tumor induction or suppression. For example, in NB4 AML cells that were transduced with a lentiviral SALL4 vector, there was an overall increased percentage of DNA methylation at various CpG sites of tumor suppression gene *PTEN*, which co-relates with a downregulated gene transcription [84]. In mouse bone marrow LSK cells, overexpression of SALL4 also induced increased percentage of methylation at the CpG sites of early B-cell factor 1 (*Ebf1*) promoter, as well as the *Sall4* gene promoter itself, which facilitates an undifferentiated cellular status [84]. Similarly, the SALL4 overexpression levels significantly affected LSD1 binding and altered H3K4me2 levels at the promoter regions of tumor necrosis factor (*Tnf*) and differentiation-related genes *EBF1*, *GATA1*, *RARβ*, *ID2*, and *CYP26*, which are associated with relevantly altered gene transcription levels [81, 87]. Also, while SALL4 interacts with the NuRD/HDAC1/2 complex to silence *PTEN* promoter via reduced acetylation of histone H3 at its binding sites, the SALL4 derived peptide blocks this interaction and leads to reactivated PTEN expression. Additionally, in the 32D myeloid progenitor cells following lentiviral SALL4 transduction, the H3K4me3 and H3K79me2/3 levels at *Bmi1* promoter regions were increased [45]. In MLL-AF9 leukemia studies, the expression levels of SALL4 also affected LSD1 and Dot1l binding and relevant H3K4me3 and H3K79me3 amounts at the promoter regions of *Meis1* and multiple HOX family genes in bone marrow cells [46, 77, 79].

#### **5.2. SALL4 regulated epigenetic modification programs are cell type-dependent**

Consistent with the findings from SALL4 genome-wide promoter binding and relevant expression assays, SALL4-regulated epigenetic modification programs are also strictly dependent on the cellular context. As reported, SALL4-bound genomic loci in murine ESCs are largely enriched for the activating marker H3K4me3, which indicates an association of SALL4 with non-repressed genes. In XEN cells, however, SALL4-binding loci displayed significantly less H3K4me3 enrichment. Instead, most of these regions are either accompanied with H3K27me3 or lacking both H3K4me3 and H3K27me3, the "epi-markers" frequently associated with gene repression [26]. In our MLL-AF9 leukemia model studies, SALL4 has been shown to recruit DOT1L and LSD1 to *Meis1* and HOX family gene promoters and modulate their H3K79me2/3 and H3K4me3 levels [46]. The previously demonstrated SALL4-MLL interaction may contribute to the observed HEK4me3 changes. However, in some non-MLL-r human AMLs, the DOT1L-regulated H3K79 methylation may not play a role, and it has been reported that administration of DOT1l inhibitors sensitized chemotherapy in MLL-r but not in non-MLL-r AML cells [97]. Further, the DOT1L recruitment to MLL-AF9 has been associated with the level of leukemic transformation [98–100]. Therefore, one may anticipate that SALL4 differentially interacts with individual epigenetic factors to exerting a disease/subtype–dependent regulatory effect. This concept, if proven true, should further facilitate the development of SALL4-based disease subtype–specific anti-leukemia strategies.

## **6. Conclusions**

**Figure 5.** The SALL4-associated epigenetic factors. DNMTs: DNA methyltransferases. HDACs: histone deacetylases.

and ABL1 increased, and the expression of anti-apoptosis gene BCL2 decreased. While in CD34+ cells, there was no notable apoptosis with SALL4 knockdown, and the expression of BCL2 increased whereas the expression of TRO and ABL1 decreased. This differential regulatory effect by SALL4 should be helpful in developing SALL4-targeted anti-leukemia

**5. Epigenetic mechanisms involved in SALL4's regulatory functions**

So far the reported SALL4-interacting epigenetic factors (see **Figure 5**) include: DNA methyltransferases DNMT-1, -3A, -3B, -3 L, methyl-CpG-binding domain 2 protein (MBD2) [84]; NuRD complex that contains histone deacetylases HDAC1/2 [79]; H3K4 methyltransferase MLL1 [77]; H3K79 methyltransferase DOT1L [46]; H3K36 methyltransferase Wolf-Hirschhorn syndrome candidate 1 (WHSC1) [85, 86]; and lysine-specific histone demethylase LSD1/KDM1A [46, 81, 87]. All of these are critical regulators in normal blood development and are frequent targets for dysregulation in hematological malignancies [88–90], and clinical epigenetic remedies inhibiting such epigenetic factors have been shown effective in treating leukemia [91–93]. In fact, in MLL-AF9-mediated mouse AML studies, genetic disruption of either SALL4, DNMT1, LSD1, or DOT1L likewise blocked leukemia initiation and delayed disease progression *in vivo* [94–96]. By interacting with specific epigenetic factors, SALL4 expression can affect DNA methylation and histone methylation/acetylation status at genes that control hematopoietic differentiation,

**5.1. SALL4 interacts with a variety of epigenetic factors to regulate downstream** 

strategies to spare normal blood cells.

22 Transcriptional and Post-transcriptional Regulation

**gene expression**

HDMs: histone demethylases. HMTs: histone methyltransferases.

Abnormal expression of SALL4 has been frequently detected in different types of human leukemias and associated with disease status and drug treatments. On the other hand, proper manipulation of SALL4 expression might be useful in achieving clinically significant expansion of transplantable human HSCs. Therefore, understanding how SALL4 mechanisms maintain normal HSCs/HPCs vs. leukemic cells will facilitate development of newer, more efficient therapies in clinic.

**NuRD/HDAC** nucleosome remodeling and histone deacetylation

Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis

http://dx.doi.org/10.5772/intechopen.76454

25

Department of Surgery and Medicine, Baylor College of Medicine, Houston, TX, USA

to the drosophila gene Spalt. Genomics. 1996;**38**(3):291-298

Organs. 2012;**196**(3):206-220. PubMed PMID: 22572102

[1] Kohlhase J, Schuh R, Dowe G, Kuhnlein RP, Jackle H, Schroeder B, et al. Isolation, characterization, and organ-specific expression of two novel human zinc finger genes related

[2] Eildermann K, Aeckerle N, Debowski K, Godmann M, Christiansen H, Heistermann M, et al. Developmental expression of the pluripotency factor Sal-like protein 4 in the monkey, human and mouse testis: Restriction to premeiotic germ cells. Cells, Tissues,

[3] Sweetman D, Munsterberg A. The vertebrate Spalt genes in development and disease.

[4] Yang J, Liao W, Ma Y. Role of SALL4 in hematopoiesis. Current Opinion in Hematology.

[5] Kohlhase J, Heinrich M, Schubert L, Liebers M, Kispert A, Laccone F, et al. Okihiro syndrome is caused by SALL4 mutations. Human Molecular Genetics. 2002;**11**(23):2979-2987.

[6] Kohlhase J. SALL4-related disorders. In: Adam MP, Ardinger HH, Pagon RA, Wallace SE, Bean LJH, Mefford HC, et al., editors. Gene Reviews. Seattle, WA; 1993. GeneReviews®

[7] Tatetsu H, Kong NR, Chong G, Amabile G, Tenen DG, Chai L. SALL4, the missing link

[8] Xiong J. SALL4: Engine of cell Stemness. Current Gene Therapy. 2014;**14**(5):400-411.

[Internet]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK1373/

between stem cells, development and cancer. Gene. 2016;**584**(2):111-119

Developmental Biology. 2006;**293**(2):285-293. PubMed PMID: 16545361

**ATRA** all-trans retinoic acid

**Ebf1** early B-cell factor 1

**Author details**

Jianchang Yang

**References**

2012;**19**(4):287-291

PubMed PMID: 12393809

PubMed PMID: 25174577

**ChIP-Seq** ChIP assays with sequencing

Address all correspondence to: jianchay@bcm.edu

**MBD2** methyl-CpG-binding domain 2 protein **WHSC1** Wolf-Hirschhorn syndrome candidate 1

## **Acknowledgements**

This work was partially supported by American Cancer Society Research Scholar Grant RSG-12-216-01-LIB (to J.Y.).

## **Conflict of interest**

The authors declare that they have no conflicts of interest with the contents of this article.

## **Acronyms and abbreviations**



## **Author details**

expansion of transplantable human HSCs. Therefore, understanding how SALL4 mechanisms maintain normal HSCs/HPCs vs. leukemic cells will facilitate development of newer,

This work was partially supported by American Cancer Society Research Scholar Grant RSG-

The authors declare that they have no conflicts of interest with the contents of this article.

**ChIP-on-chip** chromatin immunoprecipitation followed by microarray hybridization

more efficient therapies in clinic.

24 Transcriptional and Post-transcriptional Regulation

**Acknowledgements**

12-216-01-LIB (to J.Y.).

**Conflict of interest**

**Acronyms and abbreviations**

**ESC** embryonic stem cell

**C2H2-ZF** Cys2His2 zinc finger

**ICM** inner cell mass

**HSPs/HPCs** hematopoietic stem/progenitor cells

**PRC** polycomb-repressive complexes

**XEN** extraembryonic endoderm

**MDS** myelodysplastic syndrome

**AML** acute myeloid leukemia

**CML** chronic myeloid leukemia

**LSK** lineage- Sca-1+ c-kit+

**iPSC** induced pluripotent stem cell

**G-CSF** granulocyte-colony stimulating factor

**FAB** the French-American-British classification

**MLL-r** mixed lineage leukemia (MLL)-rearranged

**B-ALL** B cell acute lymphocytic leukemia

**ALK+ ALCL** ALK positive anaplastic large cell lymphoma

Jianchang Yang

Address all correspondence to: jianchay@bcm.edu

Department of Surgery and Medicine, Baylor College of Medicine, Houston, TX, USA

## **References**


[9] Al-Baradie R, Yamada K, St Hilaire C, Chan WM, Andrews C, McIntosh N, et al. Duane radial ray syndrome (Okihiro syndrome) maps to 20q13 and results from mutations in SALL4, a new member of the SAL family. American Journal of Human Genetics. 2002;**71**(5):1195-1199

[20] Xu K, Chen X, Yang H, Xu Y, He Y, Wang C, et al. Maternal Sall4 is indispensable for epigenetic maturation of mouse oocytes. The Journal of Biological Chemistry. 2017;**292**(5): 1798-1807. PubMed PMID: 28031467; PubMed Central PMCID: PMCPMC5290953 [21] Sakaki-Yumoto M, Kobayashi C, Sato A, Fujimura S, Matsumoto Y, Takasato M, et al. The murine homolog of SALL4, a causative gene in Okihiro syndrome, is essential for embryonic stem cell proliferation, and cooperates with Sall1 in anorectal, heart, brain and kidney development. Development. 2006;**133**(15):3005-3013. PubMed PMID: 16790473 [22] Elling U, Klasen C, Eisenberger T, Anlag K, Treier M. Murine inner cell mass-derived lineages depend on Sall4 function. Proceedings of the National Academy of Sciences of the United States of America. 2006;**103**(44):16319-16324. PubMed PMID: 17060609; PubMed

Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis

http://dx.doi.org/10.5772/intechopen.76454

27

[23] Warren M, Wang W, Spiden S, Chen-Murchie D, Tannahill D, Steel KP, et al. A Sall4 mutant mouse model useful for studying the role of Sall4 in early embryonic development and organogenesis. Genesis. 2007;**45**(1):51-58. PubMed PMID: 17216607; PubMed

[24] Harvey SA, Logan MP. Sall4 acts downstream of tbx5 and is required for pectoral fin

[25] Koshiba-Takeuchi K, Takeuchi JK, Arruda EP, Kathiriya IS, Mo R, Hui CC, et al. Cooperative and antagonistic interactions between Sall4 and Tbx5 pattern the mouse

[26] Lim CY, Tam WL, Zhang J, Ang HS, Jia H, Lipovich L, et al. Sall4 regulates distinct transcription circuitries in different blastocyst-derived stem cell lineages. Cell Stem Cell.

[27] Oikawa T, Kamiya A, Kakinuma S, Zeniya M, Nishinakamura R, Tajiri H, et al. Sall4 regulates cell fate decision in fetal hepatic stem/progenitor cells. Gastroenterology.

[28] Bohm J, Heinritz W, Craig A, Vujic M, Ekman-Joelsson BM, Kohlhase J, et al. Functional analysis of the novel TBX5 c.1333delC mutation resulting in an extended TBX5 protein. BMC Medical Genetics. 2008;**9**:88. PubMed PMID: 18828908; PubMed Central PMCID:

[29] Takahashi K, Yamanaka S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell. 2006;**126**(4):663-676. PubMed

[30] Tsubooka N, Ichisaka T, Okita K, Takahashi K, Nakagawa M, Yamanaka S. Roles of Sall4 in the generation of pluripotent stem cells from blastocysts and fibroblasts. Genes

[31] Wong CC, Gaspar-Maia A, Ramalho-Santos M, Reijo Pera RA. High-efficiency stem cell fusion-mediated assay reveals Sall4 as an enhancer of reprogramming. PLoS One. 2008;**3**(4):e1955. PubMed PMID: 18414659; PubMed Central PMCID: PMCPMC2278370

limb and heart. Nature Genetics. 2006;**38**(2):175-183. PubMed PMID: 16380715

outgrowth. Development. 2006;**133**(6):1165-1173. PubMed PMID: 16501170

Central PMCID: PMCPMC1637580

Central PMCID: PMCPMC2593393

2009;**136**(3):1000-1011. PubMed PMID: 19185577

to Cells. 2009;**14**(6):683-694. PubMed PMID: 19476507

2008;**3**(5):543-554

PMCPMC2567295

PMID: 16904174


[20] Xu K, Chen X, Yang H, Xu Y, He Y, Wang C, et al. Maternal Sall4 is indispensable for epigenetic maturation of mouse oocytes. The Journal of Biological Chemistry. 2017;**292**(5): 1798-1807. PubMed PMID: 28031467; PubMed Central PMCID: PMCPMC5290953

[9] Al-Baradie R, Yamada K, St Hilaire C, Chan WM, Andrews C, McIntosh N, et al. Duane radial ray syndrome (Okihiro syndrome) maps to 20q13 and results from mutations in SALL4, a new member of the SAL family. American Journal of Human Genetics.

[10] Kohlhase J, Schubert L, Liebers M, Rauch A, Becker K, Mohammed SN, et al. Mutations at the SALL4 locus on chromosome 20 result in a range of clinically overlapping phenotypes, including Okihiro syndrome, Holt-Oram syndrome, acro-renal-ocular syndrome, and patients previously reported to represent thalidomide embryopathy. Journal of Medical Genetics. 2003;**40**(7):473-478. PubMed PMID: 12843316; PubMed Central

[11] Paradisi I, Arias S. IVIC syndrome is caused by a c.2607delA mutation in the SALL4 locus. American Journal of Medical Genetics Part A. 2007;**143**(4):326-332. PubMed PMID:

[12] Zhang X, Yuan X, Zhu W, Qian H, Xu W. SALL4: An emerging cancer biomarker and

[13] Wang F, Zhao W, Kong N, Cui W, Chai L. The next new target in leukemia: The embryonic stem cell gene SALL4. Mol Cell Oncol. 2014;**1**(4):e969169. PubMed PMID: 25977939;

[14] Zhang J, Tam WL, Tong GQ, Wu Q, Chan HY, Soh BS, et al. Sall4 modulates embryonic stem cell pluripotency and early embryonic development by the transcriptional regula-

[15] Yang J, Gao C, Chai L, Ma Y. A novel SALL4/OCT4 transcriptional feedback network for pluripotency of embryonic stem cells. PLoS One. 2010;**5**(5):e10766. PubMed PMID:

[16] Nosi U, Lanner F, Huang T, Cox B. Overexpression of trophoblast stem cell-enriched microRNAs promotes trophoblast fate in embryonic stem cells. Cell Reports.

[17] Miller A, Gharbi S, Etienne-Dumeau C, Nishinakamura R, Hendrich B. Transcriptional control by Sall4 in blastocysts facilitates lineage commitment of inner cell mass cells.

[18] Yang J, Chai L, Fowles TC, Alipio Z, Xu D, Fink LM, et al. Genome-wide analysis reveals Sall4 to be a major regulator of pluripotency in murine-embryonic stem cells. Proceedings of the National Academy of Sciences of the United States of America. 2008;**105**(50):

19756-19761. PubMed PMID: 19060217; PubMed Central PMCID: PMC2604985

[19] Abboud N, Moore-Morris T, Hiriart E, Yang H, Bezerra H, Gualazzi MG, et al. A cohesin-OCT4 complex mediates Sox enhancers to prime an early embryonic lineage. Nature Communications. 2015;**6**:6749. PubMed PMID: 25851587; PubMed Central PMCID:

target. Cancer Letters. 2015;**357**(1):55-62. PubMed PMID: 25444934

PubMed Central PMCID: PMCPMC4428154

tion of Pou5f1. Nature Cell Biology. 2006;**8**(10):1114-1123

20505821; PubMed Central PMCID: PMC2874005

2017;**19**(6):1101-1109. PubMed PMID: 28494860

2002;**71**(5):1195-1199

26 Transcriptional and Post-transcriptional Regulation

PMCID: PMCPMC1735528

17256792

bioRxiv. 2017

PMCPMC5531045


[32] Shu J, Zhang K, Zhang M, Yao A, Shao S, Du F, et al. GATA family members as inducers for cellular reprogramming to pluripotency. Cell Research. 2015;**25**(2):169-180. PubMed PMID: 25591928; PubMed Central PMCID: PMCPMC4650575

[44] Akhavan Rahnama M, Movassaghpour AA, Soleimani M, Atashi A, Anbarlou A, Shams AK. MicroRNA-15b target Sall4 and diminish in vitro UCB-derived HSCs expansion. EXCLI Journal. 2015;**14**:601-610. PubMed PMID: 26648817; PubMed Central PMCID:

Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis

http://dx.doi.org/10.5772/intechopen.76454

29

[45] Yang J, Chai L, Liu F, Fink LM, Lin P, Silberstein LE, et al. Bmi-1 is a target gene for SALL4 in hematopoietic and leukemic cells. Proceedings of the National Academy of Sciences of the United States of America. 2007;**104**(25):10494-10499. PubMed PMID:

[46] Yang L, Liu L, Gao H, Pinnamaneni JP, Sanagasetti D, Singh VP, et al. The stem cell factor SALL4 is an essential transcriptional regulator in mixed lineage leukemia-rearranged

[47] Rossi L, Lin KK, Boles NC, Yang L, King KY, Jeong M, et al. Less is more: Unveiling the functional core of hematopoietic stem cells through knockout mice. Cell Stem Cell. 2012;**11**(3):302-317. PubMed PMID: 22958929; PubMed Central PMCID: PMCPMC3461270

[48] Damnernsawad A, Kong G, Wen Z, Liu Y, Rajagopalan A, You X, et al. Kras is required for adult hematopoiesis. Stem Cells. 2016;**34**(7):1859-1871. PubMed PMID: 26972179;

[49] Oikawa T, Kamiya A, Zeniya M, Chikada H, Hyuck AD, Yamazaki Y, et al. Sal-like protein 4 (SALL4), a stem cell biomarker in liver cancers. Hepatology. 2013;**57**(4):1469-1483.

[50] Ushiku T, Shinozaki A, Shibahara J, Iwasaki Y, Tateishi Y, Funata N, et al. SALL4 represents fetal gut differentiation of gastric cancer, and is diagnostically useful in distinguishing hepatoid gastric carcinoma from hepatocellular carcinoma. The American

[51] Kobayashi D, Kuribayashi K, Tanaka M, Watanabe N. Overexpression of SALL4 in lung cancer and its importance in cell proliferation. Oncology Reports. 2011;**26**(4):965-970.

[52] Kobayashi D, Kuribayshi K, Tanaka M, Watanabe N. SALL4 is essential for cancer cell proliferation and is overexpressed at early clinical stages in breast cancer. International

[53] Ardalan Khales S, Abbaszadegan MR, Abdollahi A, Raeisossadati R, Tousi MF, Forghanifard MM. SALL4 as a new biomarker for early colorectal cancers. Journal of Cancer Research

[54] Zhang L, Yan Y, Jiang Y, Cui Y, Zou Y, Qian J, et al. The expression of SALL4 in patients with gliomas: High level of SALL4 expression is correlated with poor outcome. Journal

[55] Miettinen M, Wang Z, McCue PA, Sarlomo-Rikala M, Rys J, Biernat W, et al. SALL4 expression in germ cell and non-germ cell Tumors: A systematic Immunohistochemical

Journal of Surgical Pathology. 2010;**34**(4):533-540. PubMed PMID: 20182341

Journal of Oncology. 2011;**38**(4):933-939. PubMed PMID: 21274508

of Neuro-Oncology. 2015;**121**(2):261-268. PubMed PMID: 25359397

and Clinical Oncology. 2014. PubMed PMID: 25156818

leukemogenesis. Journal of Hematology & Oncology. 2017;**10**(1):159

PMCPMC4669904

17557835; PubMed Central PMCID: PMC1965541

PubMed Central PMCID: PMCPMC5358545

PubMed PMID: 23175232

PubMed PMID: 21725617


[44] Akhavan Rahnama M, Movassaghpour AA, Soleimani M, Atashi A, Anbarlou A, Shams AK. MicroRNA-15b target Sall4 and diminish in vitro UCB-derived HSCs expansion. EXCLI Journal. 2015;**14**:601-610. PubMed PMID: 26648817; PubMed Central PMCID: PMCPMC4669904

[32] Shu J, Zhang K, Zhang M, Yao A, Shao S, Du F, et al. GATA family members as inducers for cellular reprogramming to pluripotency. Cell Research. 2015;**25**(2):169-180. PubMed

[33] Buganim Y, Markoulaki S, van Wietmarschen N, Hoke H, Wu T, Ganz K, et al. The developmental potential of iPSCs is greatly influenced by reprogramming factor selection. Cell Stem Cell. 2014;**15**(3):295-309. PubMed PMID: 25192464; PubMed Central

[34] Mansour AA, Gafni O, Weinberger L, Zviran A, Ayyash M, Rais Y, et al. The H3K27 demethylase Utx regulates somatic and germ cell epigenetic reprogramming. Nature.

[35] Pacini S, Carnicelli V, Trombi L, Montali M, Fazzi R, Lazzarini E, et al. Constitutive expression of pluripotency-associated genes in mesodermal progenitor cells (MPCs). PLoS One. 2010;**5**(3):e9861. PubMed PMID: 20360837; PubMed Central PMCID:

[36] Jia G, Preussner J, Guenther S, Yuan X, Yekelchyk M, Kuenne C, et al. Single cell RNAseq and ATAC-seq indicate critical roles of Isl1 and Nkx2-5 for cardiac progenitor cell

[37] Gao C, Kong NR, Li A, Tatetu H, Ueno S, Yang Y, et al. SALL4 is a key transcription regulator in normal human hematopoiesis. Transfusion. 2013;**53**(5):1037-1049. PubMed

[38] Rao S, Zhen S, Roumiantsev S, McDonald LT, Yuan GC, Orkin SH. Differential roles of Sall4 isoforms in embryonic stem cell pluripotency. Molecular and Cellular Biology. 2010;**30**(22):5364-5380. PubMed PMID: 20837710; PubMed Central PMCID: PMCPMC

[39] Yang J, Aguila JR, Alipio Z, Lai R, Fink LM, Ma Y. Enhanced self-renewal of hematopoietic stem/progenitor cells mediated by the stem cell gene Sall4. Journal of Hematology & Oncology. 2011;**4**:38. PubMed PMID: 21943195; PubMed Central PMCID: PMC3184628

[40] Aguila JR, Liao W, Yang J, Avila C, Hagag N, Senzel L, et al. SALL4 is a robust stimulator for the expansion of hematopoietic stem cells. Blood. 2011;**118**(3):576-585. PubMed

[41] Liao W, Aguila JR, Yao Y, Yang J, Zieve G, Jiang Y, et al. Enhancing bone marrow regeneration by SALL4 protein. Journal of Hematology & Oncology. 2013;**6**:84. PubMed

[42] Mossahebi-Mohammadi M, Atashi A, Kaviani S, Soleimani M. Efficient expansion of SALL4-transduced umbilical cord blood derived CD133+hematopoietic stem cells. Acta

[43] Tatetsu H, Wang F, Gao C, Ueno S, Tian X, Armant M, et al. SALL4 is a key factor in HDAC inhibitor mediated ex vivo expansion of human peripheral blood mobilized

PMID: 25591928; PubMed Central PMCID: PMCPMC4650575

2012;**488**(7411):409-413. PubMed PMID: 22801502

transition states and lineage settlement. bioRxiv. 2017

PMID: 22934838; PubMed Central PMCID: PMC3653586

PMID: 21602528; PubMed Central PMCID: PMC3142902

PMID: 24283261; PubMed Central PMCID: PMCPMC3882884

Medica Iranica. 2017;**55**(5):290-296. PubMed PMID: 28724268

stem/progenitor CD34+CD90+ cells. Blood. 2014;**124**(21):1566

PMCID: PMCPMC4170792

28 Transcriptional and Post-transcriptional Regulation

PMCPMC2845604

2976381


study of 3215 cases. The American Journal of Surgical Pathology. 2014;**38**(3):410-420. PubMed PMID: 24525512

therapeutic target. Experimental Hematology. 2014;**42**(4):307-316 e8. PubMed PMID:

Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis

http://dx.doi.org/10.5772/intechopen.76454

31

[68] Cui W, Kong NR, Ma Y, Amin HM, Lai R, Chai L. Differential expression of the novel oncogene, SALL4, in lymphoma, plasma cell myeloma, and acute lymphoblastic leuke-

[69] Lu J, Ma Y, Kong N, Alipio Z, Gao C, Krause DS, et al. Dissecting the role of SALL4, a newly identified stem cell factor, in chronic myelogenous leukemia. Leukemia. 2011;**25**(7):1211-1213. PubMed PMID: 21468036; PubMed Central PMCID: PMC3675449

[70] Hupfeld T, Chapuy B, Schrader V, Beutler M, Veltkamp C, Koch R, et al. Tyrosinekinase inhibition facilitates cooperation of transcription factor SALL4 and ABC transporter A3 towards intrinsic CML cell drug resistance. British Journal of Haematology.

[71] Kode A, Manavalan JS, Mosialou I, Bhagat G, Rathinam CV, Luo N, et al. Leukaemogenesis induced by an activating beta-catenin mutation in osteoblasts. Nature. 2014;**506**(7487):

[72] Prange KHM, Mandoli A, Kuznetsova T, Wang SY, Sotoca AM, Marneth AE, et al. MLL-AF9 and MLL-AF4 on cofusion proteins bind a distinct enhancer repertoire and target the RUNX1 program in 11q23 acute myeloid leukemia. Oncogene. 2017;**36**(23):3346-

[73] Winters AC, Bernt KM. MLL-rearranged leukemias—An update on science and clinical approaches. Frontiers in Pediatrics. 2017;**5**:4. PubMed PMID: 28232907; PubMed Central

[74] Zhu N, Chen M, Eng R, DeJong J, Sinha AU, Rahnamay NF, et al. MLL-AF9- and HOXA9 mediated acute myeloid leukemia stem cell self-renewal requires JMJD1C. The Journal

[75] Marschalek R. MLL leukemia and future treatment strategies. Archiv der Pharmazie

[76] de Boer J, Walf-Vorderwulbecke V, Williams O. In focus: MLL-rearranged leukemia.

[77] Li A, Yang Y, Gao C, Lu J, Jeong HW, Liu BH, et al. A SALL4/MLL/HOXA9 pathway in murine and human myeloid leukemogenesis. The Journal of Clinical Investigation. 2013;**123**(10):4195-4207. PubMed PMID: 24051379; PubMed Central PMCID: PMC3r784519

[78] Yang J, Chai L, Gao C, Fowles TC, Alipio Z, Dang H, et al. SALL4 is a key regulator of

[79] Lu J, Jeong HW, Kong N, Yang Y, Carroll J, Luo HR, et al. Stem cell factor SALL4 represses the transcriptions of PTEN and SALL1 through an epigenetic repressor complex. PLoS One. 2009;**4**(5):e5577. PubMed PMID: 19440552; PubMed Central PMCID: PMC2679146

survival and apoptosis in human leukemic cells. Blood. 2008;**112**(3):805-813

of Clinical Investigation. 2016;**126**(3):997-1011. PubMed PMID: 26878175

(Weinheim). 2015;**348**(4):221-228. PubMed PMID: 25740345

Leukemia. 2013;**27**(6):1224-1228. PubMed PMID: 23515098

240-244. PubMed PMID: 24429522; PubMed Central PMCID: PMCPMC4116754

3356. PubMed PMID: 28114278; PubMed Central PMCID: PMCPMC547456r5

mia. Modern Pathology. 2006;**19**(12):1585-1592. PubMed PMID: 16998462

24463278; PubMed Central PMCID: PMC4135469

2013;**161**(2):204-213. PubMed PMID: 23432194

PMCID: PMCPMCr5299633


therapeutic target. Experimental Hematology. 2014;**42**(4):307-316 e8. PubMed PMID: 24463278; PubMed Central PMCID: PMC4135469

[68] Cui W, Kong NR, Ma Y, Amin HM, Lai R, Chai L. Differential expression of the novel oncogene, SALL4, in lymphoma, plasma cell myeloma, and acute lymphoblastic leukemia. Modern Pathology. 2006;**19**(12):1585-1592. PubMed PMID: 16998462

study of 3215 cases. The American Journal of Surgical Pathology. 2014;**38**(3):410-420.

[56] Mei K, Liu A, Allan RW, Wang P, Lane Z, Abel TW, et al. Diagnostic utility of SALL4 in primary germ cell tumors of the central nervous system: A study of 77 cases. Modern

[57] Cao D, Guo S, Allan RW, Molberg KH, Peng Y. SALL4 is a novel sensitive and specific marker of ovarian primitive germ cell tumors and is particularly useful in distinguishing yolk sac tumor from clear cell carcinoma. The American Journal of Surgical Pathology.

[58] Wang F, Guo Y, Chen Q, Yang Z, Ning N, Zhang Y, et al. Stem cell factor SALL4, a potential prognostic marker for myelodysplastic syndromes. Journal of Hematology & Oncology.

[59] Ma Y, Cui W, Yang J, Qu J, Di C, Amin HM, et al. SALL4, a novel oncogene, is constitutively expressed in human acute myeloid leukemia (AML) and induces AML in trans-

[60] Abo-Elwafa H, Aziz S, Salah M, Sedek O. The SALL4 gene in acute leukemias. The

[61] Shen Q, Liu S, Hu J, Chen S, Yang L, Li B, et al. The differential expression pattern of the BMI-1, SALL4 and ABCA3 genes in myeloid leukemia. Cancer Cell International. 2012;**12**(1):42. PubMed PMID: 23067006; PubMed Central PMCID: PMCPMC3538712 [62] Jeong HW, Cui W, Yang Y, Lu J, He J, Li A, et al. SALL4, a stem cell factor, affects the side population by regulation of the ATP-binding cassette drug transport genes. PLoS One. 2011;**6**(4):e18372. PubMed PMID: 21526180; PubMed Central PMCID: PMC3079717

[63] Wang F, Gao C, Lu J, Tatetsu H, Williams DA, Muller LU, et al. Leukemic survival factor SALL4 contributes to defective DNA damage repair. Oncogene. 2016;**35**(47):6087-6095.

[64] Chen Q, Qian J, Lin J, Yang J, Li Y, Wang CZ, et al. Expression of SALL4 gene in patients with acute and chronic myeloid leukemia. Zhongguo Shi Yan Xue Ye Xue Za Zhi.

[65] Milanovich S, Peterson J, Allred J, Stelloh C, Rajasekaran K, Fisher J, et al. Sall4 overexpression blocks murine hematopoiesis in a dose-dependent manner. Experimental Hematology. 2015;**43**(1):53-64 e1-8. PubMed PMID: 25246269; PubMed Central PMCID:

[66] Wang P, Zhang JD, Wu F, Ye X, Sharon D, Hitt M, et al. The expression and oncogenic effects of the embryonic stem cell marker SALL4 in ALK-positive anaplastic large cell

[67] Ueno S, Lu J, He J, Li A, Zhang X, Ritz J, et al. Aberrant expression of SALL4 in acute B cell lymphoblastic leukemia: Mechanism, function, and implication for a potential novel

lymphoma. Cellular Signalling. 2012;**24**(10):1955-1963. PubMed PMID: 22743134

PubMed PMID: 27132514; PubMed Central PMCID: PMCPMC5093088

2013;**6**(1):73. PubMed PMID: 24283704; PubMed Central PMCID: PMC3856454

Pathology. 2009;**22**(12):1628-1636. PubMed PMID: 19820689

2009;**33**(6):894-904. PubMed PMID: 19295406

genic mice. Blood. 2006;**108**:2726-2735

Egyptian Journal of Haematology. 2015;**40**(3):121-129

2013;**21**(2):315-319. PubMed PMID: 23628023

PMCPMC4268405

PubMed PMID: 24525512

30 Transcriptional and Post-transcriptional Regulation


[80] Gao C, Dimitrov T, Yong KJ, Tatetsu H, Jeong HW, Luo HR, et al. Targeting transcription factor SALL4 in acute myeloid leukemia by interrupting its interaction with an epigenetic complex. Blood. 2013;**121**(8):1413-1421. PubMed PMID: 23287862; PubMed Central PMCID: PMC3578956

[92] Gallipoli P, Giotopoulos G, Huntly BJ. Epigenetic regulators as promising therapeutic targets in acute myeloid leukemia. Therapeutic Advances in Hematology. 2015;**6**(3): 103-119. PubMed PMID: 26137202; PubMed Central PMCID: PMCPMC4480521 [93] Bernt KM, Armstrong SA. Targeting epigenetic programs in MLL-rearranged leuke-

Function of the Stem Cell Transcription Factor SALL4 in Hematopoiesis

http://dx.doi.org/10.5772/intechopen.76454

33

[94] Trowbridge JJ, Sinha AU, Zhu N, Li M, Armstrong SA, Orkin SH. Haploinsufficiency of Dnmt1 impairs leukemia stem cell function through derepression of bivalent chromatin domains. Genes & Development. 2012;**26**(4):344-349. PubMed PMID: 22345515;

[95] Kuntimaddi A, Achille NJ, Thorpe J, Lokken AA, Singh R, Hemenway CS, et al. Degree of recruitment of DOT1L to MLL-AF9 defines level of H3K79 di- and tri-methylation on target genes and transformation potential. Cell Reports. 2015;**11**(5):808-820. PubMed

[96] Harris WJ, Huang X, Lynch JT, Spencer GJ, Hitchin JR, Li Y, et al. The histone demethylase KDM1A sustains the oncogenic potential of MLL-AF9 leukemia stem cells. Cancer

[97] Liu W, Deng L, Song Y, Redell M. DOT1L inhibition sensitizes MLL-rearranged AML to chemotherapy. PLoS One. 2014;**9**(5):e98270. PubMed PMID: 24858818; PubMed Central

[98] Bernt KM, Zhu N, Sinha AU, Vempati S, Faber J, Krivtsov AV, et al. MLL-rearranged leukemia is dependent on aberrant H3K79 methylation by DOT1L. Cancer Cell. 2011;**20**(1):66-78. PubMed PMID: 21741597; PubMed Central PMCID: PMCPMC3329803

[99] Bernt KM, Armstrong SA.A role for DOT1L in MLL-rearranged leukemias. Epigenomics.

[100] Chen CW, Armstrong SA. Targeting DOT1L and HOX gene expression in MLLrearranged leukemia and beyond. Experimental Hematology. 2015;**43**(8):673-684.

PubMed PMID: 26118503; PubMed Central PMCID: PMCPMC4540610

mias. Hematology. 2011;**2011**:354-360. PubMed PMID: 22160057

PMID: 25921540; PubMed Central PMCID: PMCPMC4426023

PubMed Central PMCID: PMCPMC3289882

Cell. 2012;**21**(4):473-487. PubMed PMID: 22464800

2011;**3**(6):667-670. PubMed PMID: 22126283

PMCID: PMCPMC4032273


[92] Gallipoli P, Giotopoulos G, Huntly BJ. Epigenetic regulators as promising therapeutic targets in acute myeloid leukemia. Therapeutic Advances in Hematology. 2015;**6**(3): 103-119. PubMed PMID: 26137202; PubMed Central PMCID: PMCPMC4480521

[80] Gao C, Dimitrov T, Yong KJ, Tatetsu H, Jeong HW, Luo HR, et al. Targeting transcription factor SALL4 in acute myeloid leukemia by interrupting its interaction with an epigenetic complex. Blood. 2013;**121**(8):1413-1421. PubMed PMID: 23287862; PubMed Central

[81] Liu L, Liu L, Leung E, Cooney AJ, Chen C, Rosengart TK, et al. Knockdown of SALL4 enhances all-trans retinoic acid-induced cellular differentiation in acute myeloid leukemia cells. The Journal of Biological Chemistry. 2015;**290**(17):10599-10609. PubMed

[82] Gao C, Kong NR, Chai L. The role of stem cell factor SALL4 in leukemogenesis. Critical Reviews in Oncogenesis. 2011;**16**(1-2):117-127. PubMed PMID: 22150312; PubMed

[83] Zhang W, Xia X, Reisenauer MR, Rieg T, Lang F, Kuhl D, et al. Aldosterone-induced Sgk1 relieves Dot1a-Af9-mediated transcriptional repression of epithelial Na+ channel

[84] Yang J, Corsello TR, Ma Y. Stem cell gene SALL4 suppresses transcription through recruitment of DNA methyltransferases. The Journal of Biological Chemistry. 2012;**287**(3):

[85] Campos-Sanchez E, Deleyto-Seldas N, Dominguez V, Carrillo-de-Santa-Pau E, Ura K, Rocha PP, et al. Wolf-Hirschhorn syndrome candidate 1 is necessary for correct hematopoietic and B cell development. Cell Reports. 2017;**19**(8):1586-1601. PubMed PMID:

[86] Nimura K, Ura K, Shiratori H, Ikawa M, Okabe M, Schwartz RJ, et al. A histone H3 lysine 36 trimethyltransferase links Nkx2-5 to Wolf-Hirschhorn syndrome. Nature.

[87] Liu L, Souto J, Liao W, Jiang Y, Li Y, Nishinakamura R, et al. Histone lysine-specific demethylase 1 (LSD1) protein is involved in Sal-like protein 4 (SALL4)-mediated transcriptional repression in hematopoietic stem cells. The Journal of Biological Chemistry.

[88] Rice KL, Hormaeche I, Licht JD. Epigenetic regulation of normal and malignant hemato-

[89] Goyama S, Kitamura T. Epigenetics in normal and malignant hematopoiesis: An overview and update 2017. Cancer Science. 2017;**108**(4):553-562. PubMed PMID: 28100030;

[90] Ding LW, Sun QY, Tan KT, Chien W, Mayakonda A, Yeoh AEJ, et al. Mutational landscape of pediatric acute lymphoblastic leukemia. Cancer Research. 2017;**77**(2):390-400.

[91] Wouters BJ, Delwel R. Epigenetics and approaches to targeted epigenetic therapy in acute myeloid leukemia. Blood. 2016;**127**(1):42-52. PubMed PMID: 26660432

poiesis. Oncogene. 2007;**26**(47):6697-6714. PubMed PMID: 17934479

PubMed PMID: 27872090; PubMed Central PMCID: PMCPMC5243866

1996-2005. PubMed PMID: 22128185; PubMed Central PMCID: PMC3265879

alpha. The Journal of Clinical Investigation. 2007;**117**(3):773-783

28538178; PubMed Central PMCID: PMCPMC5510986

2009;**460**(7252):287-291. PubMed PMID: 19483677

PubMed Central PMCID: PMCPMC5406607

2013;**288**(48):34719-34728

PMCID: PMC3578956

32 Transcriptional and Post-transcriptional Regulation

Central PMCID: PMCPMC3238789

PMID: 25737450


**Chapter 3**

**Provisional chapter**

**The Glucocorticoid Receptor and Certain KRÜPPEL-Like**

Bovine herpesvirus 1 (BoHV-1), an important bovine pathogen, establishes life-long latency in sensory neurons within trigeminal ganglia (TG). Stress, as mimicked by the synthetic corticosteroid dexamethasone, consistently induces reactivation in calves latently infected with BoHV-1. Dexamethasone induces expression of several transcription factors in TG neurons during early stages of reactivation, including Krüppel-like transcription factors (KLF): KLF4, KLF6, KLF15, and promyelocytic leukemia zinc finger. Furthermore, the glucocorticoid receptor (GR) is consistently detected in TG neurons expressing viral regulatory proteins during reactivation from latency. The viral immediate early transcription unit 1 (IEtu1) promoter that drives expression of two viral transcription factors (bICP0 and bICP4) contains two GR response elements (GREs) and is stimulated by DEX. KLF15 and the GR form a feed forward transcription loop that synergistically stimulates productive infection and IEtu1 promoter activity. New studies demonstrate the GR and KLF6 synergistically stimulate productive infection and IEtu1 promoter activity if the GREs are intact. Furthermore, the GR and KLF6 interact with wild-type GREs within the IEtu1 promoter, but not GRE mutants. These studies suggest that certain KLF family members and the GR can convert a silent viral genome in latently infected neurons into an actively transcribing genome during reactivation from latency.

**Keywords:** bovine herpesvirus 1, immediate early transcription, reactivation from latency, sensory neurons, glucocorticoid receptors, Krüppel-like transcription factors

**The Glucocorticoid Receptor and Certain KRÜPPEL-**

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

DOI: 10.5772/intechopen.75451

**Transcription Factors have the Potential to**

**Synergistically Stimulate Bovine Herpesvirus 1**

**Synergistically Stimulate Bovine Herpesvirus 1** 

**Like Transcription Factors have the Potential to** 

**Transcription and Reactivation from Latency**

**Transcription and Reactivation from Latency**

Fouad S. El-mayet, Ayman S. El-Habbaa, Gabr F. El-Bagoury, Saad S.A. Sharawi, Ehab M. El-Nahas and Clinton Jones

Fouad S. El-mayet, Ayman S. El-Habbaa, Gabr F. El-Bagoury, Saad S.A. Sharawi, Ehab M. El-Nahas and Clinton Jones

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.75451

**Abstract**

#### **The Glucocorticoid Receptor and Certain KRÜPPEL-Like Transcription Factors have the Potential to Synergistically Stimulate Bovine Herpesvirus 1 Transcription and Reactivation from Latency The Glucocorticoid Receptor and Certain KRÜPPEL-Like Transcription Factors have the Potential to Synergistically Stimulate Bovine Herpesvirus 1 Transcription and Reactivation from Latency**

DOI: 10.5772/intechopen.75451

Fouad S. El-mayet, Ayman S. El-Habbaa, Gabr F. El-Bagoury, Saad S.A. Sharawi, Ehab M. El-Nahas and Clinton Jones Fouad S. El-mayet, Ayman S. El-Habbaa, Gabr F. El-Bagoury, Saad S.A. Sharawi, Ehab M. El-Nahas and Clinton Jones

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.75451

#### **Abstract**

Bovine herpesvirus 1 (BoHV-1), an important bovine pathogen, establishes life-long latency in sensory neurons within trigeminal ganglia (TG). Stress, as mimicked by the synthetic corticosteroid dexamethasone, consistently induces reactivation in calves latently infected with BoHV-1. Dexamethasone induces expression of several transcription factors in TG neurons during early stages of reactivation, including Krüppel-like transcription factors (KLF): KLF4, KLF6, KLF15, and promyelocytic leukemia zinc finger. Furthermore, the glucocorticoid receptor (GR) is consistently detected in TG neurons expressing viral regulatory proteins during reactivation from latency. The viral immediate early transcription unit 1 (IEtu1) promoter that drives expression of two viral transcription factors (bICP0 and bICP4) contains two GR response elements (GREs) and is stimulated by DEX. KLF15 and the GR form a feed forward transcription loop that synergistically stimulates productive infection and IEtu1 promoter activity. New studies demonstrate the GR and KLF6 synergistically stimulate productive infection and IEtu1 promoter activity if the GREs are intact. Furthermore, the GR and KLF6 interact with wild-type GREs within the IEtu1 promoter, but not GRE mutants. These studies suggest that certain KLF family members and the GR can convert a silent viral genome in latently infected neurons into an actively transcribing genome during reactivation from latency.

**Keywords:** bovine herpesvirus 1, immediate early transcription, reactivation from latency, sensory neurons, glucocorticoid receptors, Krüppel-like transcription factors

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

## **1. Introduction**

Bovine herpesvirus 1 (BoHV-1), an alpha-herpesvirinae subfamily member, is an important bovine pathogen that causes conjunctivitis and/or upper respiratory tract disease [1–3]. BoHV-1 is a significant cofactor in the polymicrobial disease referred to as bovine respiratory disease complex (BRDC), which is the most important disease of cattle. BoHV-1 infection impairs cell-mediated immunity, CD8+ T cell recognition of infected cells, and induces apoptosis in CD4+ T cells [4]. Viral proteins, VP8, bICP0 and bICP27, inhibit interferon dependent transcription [4–8]. Infection also erodes mucosal surfaces of the upper respiratory tract, which promotes establishment of the bacterial pathogen, *Mannheimia haemolytica (MH)* in the lower respiratory tract [9]. BoHV-1 productive infection increases neutrophil adhesion and activation [10], thus amplifying the pathogenic potential of *MH. MH,* a gram negative bacterium, exists as normal flora within the upper respiratory tract of healthy ruminants [11]. Stress and/or co-infections disrupt this commensal relationship; consequently *MH* becomes the predominant organism that causes life-threatening bronchopneumonia in BRDC cases [9]. BRDC is the most important disease in cattle because it costs the US cattle industry more than one billion dollars in losses each year [9, 12, 13]. A BoHV-1 entry protein is a BRDC susceptibility gene for Holstein calves [14] confirming BoHV-1 is a significant BRDC cofactor.

**2. Acute infection leads to a life-long latent infection in sensory** 

Acute infection of calves induces programmed cell death, inflammation and high levels of virus production [1–3]. BoHV-1 genes are expressed in three distinct phases during acute infection or productive infection of cultured cells: immediate early (IE), early (E), or late (L) [1–3]. IE gene expression is specifically stimulated by viral protein 16 (VP16), a tegument protein. IE transcription unit 1 (IEtu1) encodes two transcriptional regulatory proteins, BoHV-1 infected cell protein 0 (bICP0) and bICP4, because a single IE transcript is differentially spliced and subsequently translated into bICP0 or bICP4 (**Figure 1**). The bICP0 protein is also translated from an E mRNA (E2.6) because a separate E promoter drives expression of the bICP0 E transcript. During acute infection of calves, infectious virus particles enter the peripheral nervous system via cell–cell spread. If infection is initiated within the oral, nasal, or ocular cavity, the primary site for latency is sensory neurons located in trigeminal ganglia (TG) [1–3]. Viral gene expression and infectious virus are detected in TG from 2 to 6 days after infection. Lytic cycle viral gene expression is then extinguished, a significant number of infected neurons survive, and these neurons harbor viral genomes, which is operationally defined as the establishment of latency. Abundant expression of the BoHV-1 encoded latency related (LR) gene occurs in latently infected neurons, but infectious virus is not detected (maintenance of latency) [1–3]. LR-RNA is anti-sense to and overlaps the BoHV-1 infected cell protein 0 (bICP0) gene. The LR gene has two open reading frames (ORF1 and ORF2), and two reading frames lacking an initiating methionine (RF-B and RF-C). In addition, the LR gene encodes two micro-RNAs that interfere with bICP0 expression in transfected cells [17]. A LR mutant virus strain with three stop codons at the N-terminus of ORF2 exhibits diminished clinical symptoms, and reduced virus shedding from

The Glucocorticoid Receptor and Certain KRÜPPEL-Like Transcription Factors have the Potential…

http://dx.doi.org/10.5772/intechopen.75451

37

**Figure 1.** Location of IE transcripts and promoters actively expressed during productive infection. The mRNA IE/4.2 encodes the bICP4 protein and IE/2.9 encodes the bICP0 protein [58, 59, 72]. A single IE promoter activates expression of IE/4.2 and IE/2.9 and is designated IEtu1 (black rectangle). E/2.6 is the early transcript that encodes bICP0 and an early promoter activates expression of this transcript (bICP0 E pro; gray rectangle). All bICP0 protein-coding sequences are contained in Exon 2 (e2). The origin of replication (ORI) separates IEtu1 from IEtu2. The IEtu2 promoter (IEtu2 pro) regulates expression of the IE1.7 mRNA that is translated into the bICP22 protein. Solid lines in the transcript position

map represent exons (e1, e2, or e3) and dashed lines denote introns.

**neurons**

Like most alpha-herpesvirinae subfamily members, including human herpes simplex virus 1 (HSV-1) and HSV2, BoHV-1 initiates acute infection on mucosal surfaces [1–3]. High levels of infectious virus are produced; consequently BoHV-1, HSV-1, or HSV-2, spread to the peripheral nervous system via cell-to-cell spread. Latency is subsequently established in sensory neurons, but periodically reactivates from latency, and thus is widespread in cattle throughout the world. Reactivation of the virus from the latent state is initiated by external stimuli (e.g. stress and immunosuppression). During reactivation, viral gene expression is stimulated and infectious virus is produced and transported back to mucosal surfaces. The ability of alphaherpesvirinae subfamily members to reactivate from the latent state is critical for virus transmission. Regulation of the complex virus host interactions controlling the latency-reactivation cycle is not well understood, which hinders developing therapeutic strategies that prevent reactivation from latency.

BoHV-1 is an excellent model to study these events because the natural host can be used and the synthetic corticosteroid dexamethasone (DEX) consistently initiates reactivation from latency in infected calves [2]. We have used experimentally infected calves treated with DEX to initiate reactivation from latency in order to identify virus-host interactions important for the latency-reactivation cycle. These studies identified host cellular factors and pathways that may be crucial for latency maintenance [15] and reactivation [16]. The following discussion focuses on the mechanisms by which BoHV-1 "escapes" a latent infection following a stressful stimulus and subsequently successfully reactivates from latency. Certain steps during BoHV-1 reactivation from latency are likely to be similar during reactivation of latency of other alpha-herpesvirinae subfamily members.

## **2. Acute infection leads to a life-long latent infection in sensory neurons**

**1. Introduction**

36 Transcriptional and Post-transcriptional Regulation

BRDC cofactor.

reactivation from latency.

other alpha-herpesvirinae subfamily members.

Bovine herpesvirus 1 (BoHV-1), an alpha-herpesvirinae subfamily member, is an important bovine pathogen that causes conjunctivitis and/or upper respiratory tract disease [1–3]. BoHV-1 is a significant cofactor in the polymicrobial disease referred to as bovine respiratory disease complex (BRDC), which is the most important disease of cattle. BoHV-1 infection impairs cell-mediated immunity, CD8+ T cell recognition of infected cells, and induces apoptosis in CD4+ T cells [4]. Viral proteins, VP8, bICP0 and bICP27, inhibit interferon dependent transcription [4–8]. Infection also erodes mucosal surfaces of the upper respiratory tract, which promotes establishment of the bacterial pathogen, *Mannheimia haemolytica (MH)* in the lower respiratory tract [9]. BoHV-1 productive infection increases neutrophil adhesion and activation [10], thus amplifying the pathogenic potential of *MH. MH,* a gram negative bacterium, exists as normal flora within the upper respiratory tract of healthy ruminants [11]. Stress and/or co-infections disrupt this commensal relationship; consequently *MH* becomes the predominant organism that causes life-threatening bronchopneumonia in BRDC cases [9]. BRDC is the most important disease in cattle because it costs the US cattle industry more than one billion dollars in losses each year [9, 12, 13]. A BoHV-1 entry protein is a BRDC susceptibility gene for Holstein calves [14] confirming BoHV-1 is a significant

Like most alpha-herpesvirinae subfamily members, including human herpes simplex virus 1 (HSV-1) and HSV2, BoHV-1 initiates acute infection on mucosal surfaces [1–3]. High levels of infectious virus are produced; consequently BoHV-1, HSV-1, or HSV-2, spread to the peripheral nervous system via cell-to-cell spread. Latency is subsequently established in sensory neurons, but periodically reactivates from latency, and thus is widespread in cattle throughout the world. Reactivation of the virus from the latent state is initiated by external stimuli (e.g. stress and immunosuppression). During reactivation, viral gene expression is stimulated and infectious virus is produced and transported back to mucosal surfaces. The ability of alphaherpesvirinae subfamily members to reactivate from the latent state is critical for virus transmission. Regulation of the complex virus host interactions controlling the latency-reactivation cycle is not well understood, which hinders developing therapeutic strategies that prevent

BoHV-1 is an excellent model to study these events because the natural host can be used and the synthetic corticosteroid dexamethasone (DEX) consistently initiates reactivation from latency in infected calves [2]. We have used experimentally infected calves treated with DEX to initiate reactivation from latency in order to identify virus-host interactions important for the latency-reactivation cycle. These studies identified host cellular factors and pathways that may be crucial for latency maintenance [15] and reactivation [16]. The following discussion focuses on the mechanisms by which BoHV-1 "escapes" a latent infection following a stressful stimulus and subsequently successfully reactivates from latency. Certain steps during BoHV-1 reactivation from latency are likely to be similar during reactivation of latency of Acute infection of calves induces programmed cell death, inflammation and high levels of virus production [1–3]. BoHV-1 genes are expressed in three distinct phases during acute infection or productive infection of cultured cells: immediate early (IE), early (E), or late (L) [1–3]. IE gene expression is specifically stimulated by viral protein 16 (VP16), a tegument protein. IE transcription unit 1 (IEtu1) encodes two transcriptional regulatory proteins, BoHV-1 infected cell protein 0 (bICP0) and bICP4, because a single IE transcript is differentially spliced and subsequently translated into bICP0 or bICP4 (**Figure 1**). The bICP0 protein is also translated from an E mRNA (E2.6) because a separate E promoter drives expression of the bICP0 E transcript.

During acute infection of calves, infectious virus particles enter the peripheral nervous system via cell–cell spread. If infection is initiated within the oral, nasal, or ocular cavity, the primary site for latency is sensory neurons located in trigeminal ganglia (TG) [1–3]. Viral gene expression and infectious virus are detected in TG from 2 to 6 days after infection. Lytic cycle viral gene expression is then extinguished, a significant number of infected neurons survive, and these neurons harbor viral genomes, which is operationally defined as the establishment of latency. Abundant expression of the BoHV-1 encoded latency related (LR) gene occurs in latently infected neurons, but infectious virus is not detected (maintenance of latency) [1–3]. LR-RNA is anti-sense to and overlaps the BoHV-1 infected cell protein 0 (bICP0) gene. The LR gene has two open reading frames (ORF1 and ORF2), and two reading frames lacking an initiating methionine (RF-B and RF-C). In addition, the LR gene encodes two micro-RNAs that interfere with bICP0 expression in transfected cells [17]. A LR mutant virus strain with three stop codons at the N-terminus of ORF2 exhibits diminished clinical symptoms, and reduced virus shedding from

**Figure 1.** Location of IE transcripts and promoters actively expressed during productive infection. The mRNA IE/4.2 encodes the bICP4 protein and IE/2.9 encodes the bICP0 protein [58, 59, 72]. A single IE promoter activates expression of IE/4.2 and IE/2.9 and is designated IEtu1 (black rectangle). E/2.6 is the early transcript that encodes bICP0 and an early promoter activates expression of this transcript (bICP0 E pro; gray rectangle). All bICP0 protein-coding sequences are contained in Exon 2 (e2). The origin of replication (ORI) separates IEtu1 from IEtu2. The IEtu2 promoter (IEtu2 pro) regulates expression of the IE1.7 mRNA that is translated into the bICP22 protein. Solid lines in the transcript position map represent exons (e1, e2, or e3) and dashed lines denote introns.

the eye, TG, or tonsils of infected calves [1–3]. ORF1, ORF2, and RF-C are expressed when bovine cells are infected with wild-type or the LR-rescued virus, but these proteins have reduced or no expression following infection with the LR mutant virus [1–3]. Wild-type (wt) BoHV-1, but not the LR mutant virus, reactivates from latency after treatment with the synthetic corticosteroid DEX. The anti-apoptosis activity of ORF2 is predicted to increase the survival of infected neurons and thus would be important for the latency-reactivation cycle [1–3].

The finding that four KLF family members (KLF4, KLF6, KLF15, and PLZF) are stimulated during DEX induced reactivation from latency is intriguing because KLF family members resemble the SP1 transcription factor family and both family of transcription factors interact with guanine-cytosine (GC) rich motifs, reviewed in [40, 41]. Genomes of alpha-herpesvirinae subfamily members, including BoHV-1, are GC rich and many viral promoters contain Sp1 consensus binding sites as well as other GC rich motifs [40]. In fact, HSV-1 gene expression is activated by Sp1 [42]. HSV-1 and probably BoHV-1 genomes exist as silent chromatin during latency, [43]: however, HSV-1 DNA is associated with unstable chromatin during productive infection [44–46]. Regardless of the stimulus that initiates reactivation from latency, silent viral heterochromatin must be converted into an actively transcribing template for reactivation from latency to be successful suggesting cellular transcription factors initially stimulate lytic cycle viral gene expression. To test whether the GR and certain stress-induced transcription factors can cooperate to stimulate viral transcription, the IEtu1 promoter and BoHV-1 DNA fragments (less than 400 bp) containing potential GR and KLF binding sites were identified and examined for transcriptional activation by stress-induced transcription factors. The rational for testing intergenic regions of the BoHV-1 genome is the viral genome contains more than 100 putative GRE binding sites [26] and a subset of GREs in cellular chromatin can activate transcription from greater than 5 kb to the nearest promoter [47]. KLF15 cooperated with the GR to stimulate the IEtu1 promoter activity and productive infection [48]. Furthermore, intergenic regions within the unique long 52 gene (UL-52; component of DNA primase/helicase complex), bICP4, IEtu2 that expresses the regulatory protein (bICP22), and unique short region were stimulated by KLF15 and the GR. In contrast to KLF15, the other stress-induced transcription factors only have a modest effect on IEtu1 promoter activity. The GR and KLF15 interact with sequences within wild-type IEtu1 GREs and UL-52 fragment, but not GRE mutants. Co-immunoprecipitation studies indicated that KLF15 and the GR are stably associated with each other. Interestingly, the GR and KLF15 can synergistically regulate gene expression by a feed-forward transcription loop [49–51]. Hallmarks of a feed-forward loop are a primary factor (GR in this example) induces expression of a second factor, KLF15 [16, 49–54], and the two factors synergistically activate expression of genes in a specific pathway. Adipogenesis [55] and amino acid metabolizing enzymes are also synergistically regulated by the GR and KLF15 [50, 51]. In summary, these studies suggest that activation of BoHV-1 gene expression during DEX induced reactivation from latency is, in part,

The Glucocorticoid Receptor and Certain KRÜPPEL-Like Transcription Factors have the Potential…

http://dx.doi.org/10.5772/intechopen.75451

39

regulated by a feed-forward transcription loop containing the GR and KLF15.

**4. The GR and KLF6 cooperate to stimulate productive infection**

To test whether KLF6 and the activated GR have a cooperative effect on productive infection, a mouse neuroblastoma cell line (Neuro-2A) was cotransfected with gCblue genomic DNA and KLF6 and/or the GR. The gCblue virus grows to similar titers as the wt parental virus and expresses the Lac Z gene from the gC locus during productive infection (**Figure 2A**). Neuro-2A cells were used for these studies because they have neuronal like properties [56], can be readily transfected, and are semi-permissive for BoHV-1 [57]. Neuro-2A cells were transfected with gCblue DNA instead of infecting cells because VP16 and other viral regulatory proteins in the virion particle can diminish the stimulatory effects of DEX on productive infection (data not shown). KLF6 and the GR plus DEX treatment increased the number of β-Gal+ Neuro-2A cells

Recent studies demonstrated that during latency, the canonical Wnt/β-catenin signaling is active and ORF2 appears to be important for maintaining this important signaling pathway [15, 18]. Although dysregulation of the Wnt/β-catenin signaling is frequently associated with many types of cancer [19, 20], this signaling pathway has the potential to promote the establishment and maintenance of latency in sensory neurons because it enhances cell survival, axonal growth, and directs axons to their proper synaptic targets [21–25].

## **3. Stress-induced reactivation from latency**

Increased corticosteroid levels, due to increased stress, correlates with increasing the incidence of BoHV-1 reactivation from latency [1–3]. DEX can also stimulate productive infection [26], and initiate reactivation from latency in calves or rabbits latently infected with BoHV-1 [1–3]. Six hours after DEX treatment lytic cycle viral RNA expression is detected in neurons of latently infected calves [27, 28]. Certain lytic cycle viral proteins, bICP0 and VP16 for example, are readily detected in TG neurons within hours after DEX treatment [29, 30]. The glucocorticoid receptor (GR) and mineralocorticoid receptor (MR), which are present in subpopulations of sensory neurons [31, 32], are activated by interacting with corticosteroids. The GR is frequently detected in TG neurons that express bICP0 or VP16 [31, 32]. IEtu1 promoter activity is stimulated by the GR and the synthetic corticosteroid DEX because there are two consensus GREs in the promoter [26] suggesting this promoter is activated by the GR and/or MR following stressful stimuli. Since the IEtu1 promoter drives expression of two viral transcriptional regulatory proteins (bICP0 and bICP4; **Figure 1**), activation of this promoter may stimulate productive infection in certain latently infected neurons.

DEX treatment of latently infected calves induces apoptosis of T cells that persist in TG after infection [27]. T cells also persist in TG of humans or mice latently infected with HSV-1 and may promote maintenance of latency [33–37]. Within 3 h after DEX treatment, 11 cellular genes are induced more than ten fold in TG [16]. Pentraxin 3, a regulator of innate immunity and neurodegeneration, is stimulated 35–63 fold at 3 or 6 h after DEX treatment. Furthermore, expression of a soluble Wnt antagonist, Dickkopf-1 is induced more than 10 fold [15, 16]. Dickkopf-1 is responsible for stress-induced neuronal death [38, 39] indicating there is a correlation between disrupting the Wnt signaling pathway and activation of lytic cycle viral gene expression during reactivation. Two transcription factors, promyelocytic leukemia zinc finger (PLZF) and Slug are induced more than 15-fold 3 h after DEX treatment. PLZF or Slug stimulates BoHV-1 productive infection 20-fold or 5-fold respectively, and Slug stimulates the late glycoprotein C promoter more than 10-fold. Additional DEX induced transcription factors, SPDEF (Sam-pointed domain containing Ets transcription factor), Kruppel-like transcription factor 15 (KLF15), KLF4, KLF6, and GATA6, stimulate productive infection and certain key viral promoters.

The finding that four KLF family members (KLF4, KLF6, KLF15, and PLZF) are stimulated during DEX induced reactivation from latency is intriguing because KLF family members resemble the SP1 transcription factor family and both family of transcription factors interact with guanine-cytosine (GC) rich motifs, reviewed in [40, 41]. Genomes of alpha-herpesvirinae subfamily members, including BoHV-1, are GC rich and many viral promoters contain Sp1 consensus binding sites as well as other GC rich motifs [40]. In fact, HSV-1 gene expression is activated by Sp1 [42]. HSV-1 and probably BoHV-1 genomes exist as silent chromatin during latency, [43]: however, HSV-1 DNA is associated with unstable chromatin during productive infection [44–46]. Regardless of the stimulus that initiates reactivation from latency, silent viral heterochromatin must be converted into an actively transcribing template for reactivation from latency to be successful suggesting cellular transcription factors initially stimulate lytic cycle viral gene expression.

the eye, TG, or tonsils of infected calves [1–3]. ORF1, ORF2, and RF-C are expressed when bovine cells are infected with wild-type or the LR-rescued virus, but these proteins have reduced or no expression following infection with the LR mutant virus [1–3]. Wild-type (wt) BoHV-1, but not the LR mutant virus, reactivates from latency after treatment with the synthetic corticosteroid DEX. The anti-apoptosis activity of ORF2 is predicted to increase the survival of infected neu-

Recent studies demonstrated that during latency, the canonical Wnt/β-catenin signaling is active and ORF2 appears to be important for maintaining this important signaling pathway [15, 18]. Although dysregulation of the Wnt/β-catenin signaling is frequently associated with many types of cancer [19, 20], this signaling pathway has the potential to promote the establishment and maintenance of latency in sensory neurons because it enhances cell survival,

Increased corticosteroid levels, due to increased stress, correlates with increasing the incidence of BoHV-1 reactivation from latency [1–3]. DEX can also stimulate productive infection [26], and initiate reactivation from latency in calves or rabbits latently infected with BoHV-1 [1–3]. Six hours after DEX treatment lytic cycle viral RNA expression is detected in neurons of latently infected calves [27, 28]. Certain lytic cycle viral proteins, bICP0 and VP16 for example, are readily detected in TG neurons within hours after DEX treatment [29, 30]. The glucocorticoid receptor (GR) and mineralocorticoid receptor (MR), which are present in subpopulations of sensory neurons [31, 32], are activated by interacting with corticosteroids. The GR is frequently detected in TG neurons that express bICP0 or VP16 [31, 32]. IEtu1 promoter activity is stimulated by the GR and the synthetic corticosteroid DEX because there are two consensus GREs in the promoter [26] suggesting this promoter is activated by the GR and/or MR following stressful stimuli. Since the IEtu1 promoter drives expression of two viral transcriptional regulatory proteins (bICP0 and bICP4; **Figure 1**), activation of this promoter may

DEX treatment of latently infected calves induces apoptosis of T cells that persist in TG after infection [27]. T cells also persist in TG of humans or mice latently infected with HSV-1 and may promote maintenance of latency [33–37]. Within 3 h after DEX treatment, 11 cellular genes are induced more than ten fold in TG [16]. Pentraxin 3, a regulator of innate immunity and neurodegeneration, is stimulated 35–63 fold at 3 or 6 h after DEX treatment. Furthermore, expression of a soluble Wnt antagonist, Dickkopf-1 is induced more than 10 fold [15, 16]. Dickkopf-1 is responsible for stress-induced neuronal death [38, 39] indicating there is a correlation between disrupting the Wnt signaling pathway and activation of lytic cycle viral gene expression during reactivation. Two transcription factors, promyelocytic leukemia zinc finger (PLZF) and Slug are induced more than 15-fold 3 h after DEX treatment. PLZF or Slug stimulates BoHV-1 productive infection 20-fold or 5-fold respectively, and Slug stimulates the late glycoprotein C promoter more than 10-fold. Additional DEX induced transcription factors, SPDEF (Sam-pointed domain containing Ets transcription factor), Kruppel-like transcription factor 15 (KLF15), KLF4, KLF6,

rons and thus would be important for the latency-reactivation cycle [1–3].

axonal growth, and directs axons to their proper synaptic targets [21–25].

stimulate productive infection in certain latently infected neurons.

and GATA6, stimulate productive infection and certain key viral promoters.

**3. Stress-induced reactivation from latency**

38 Transcriptional and Post-transcriptional Regulation

To test whether the GR and certain stress-induced transcription factors can cooperate to stimulate viral transcription, the IEtu1 promoter and BoHV-1 DNA fragments (less than 400 bp) containing potential GR and KLF binding sites were identified and examined for transcriptional activation by stress-induced transcription factors. The rational for testing intergenic regions of the BoHV-1 genome is the viral genome contains more than 100 putative GRE binding sites [26] and a subset of GREs in cellular chromatin can activate transcription from greater than 5 kb to the nearest promoter [47]. KLF15 cooperated with the GR to stimulate the IEtu1 promoter activity and productive infection [48]. Furthermore, intergenic regions within the unique long 52 gene (UL-52; component of DNA primase/helicase complex), bICP4, IEtu2 that expresses the regulatory protein (bICP22), and unique short region were stimulated by KLF15 and the GR. In contrast to KLF15, the other stress-induced transcription factors only have a modest effect on IEtu1 promoter activity. The GR and KLF15 interact with sequences within wild-type IEtu1 GREs and UL-52 fragment, but not GRE mutants. Co-immunoprecipitation studies indicated that KLF15 and the GR are stably associated with each other. Interestingly, the GR and KLF15 can synergistically regulate gene expression by a feed-forward transcription loop [49–51]. Hallmarks of a feed-forward loop are a primary factor (GR in this example) induces expression of a second factor, KLF15 [16, 49–54], and the two factors synergistically activate expression of genes in a specific pathway. Adipogenesis [55] and amino acid metabolizing enzymes are also synergistically regulated by the GR and KLF15 [50, 51]. In summary, these studies suggest that activation of BoHV-1 gene expression during DEX induced reactivation from latency is, in part, regulated by a feed-forward transcription loop containing the GR and KLF15.

## **4. The GR and KLF6 cooperate to stimulate productive infection**

To test whether KLF6 and the activated GR have a cooperative effect on productive infection, a mouse neuroblastoma cell line (Neuro-2A) was cotransfected with gCblue genomic DNA and KLF6 and/or the GR. The gCblue virus grows to similar titers as the wt parental virus and expresses the Lac Z gene from the gC locus during productive infection (**Figure 2A**). Neuro-2A cells were used for these studies because they have neuronal like properties [56], can be readily transfected, and are semi-permissive for BoHV-1 [57]. Neuro-2A cells were transfected with gCblue DNA instead of infecting cells because VP16 and other viral regulatory proteins in the virion particle can diminish the stimulatory effects of DEX on productive infection (data not shown). KLF6 and the GR plus DEX treatment increased the number of β-Gal+ Neuro-2A cells

**5. KLF6 and GR synergistically trans-activates the IEtu1 promoter**

Transient transfection studies were performed in Neuro-2A cells to test whether KLF6 and the GR synergistically trans-activate the IEtu1 promoter because this promoter contains two consensus GR binding sites (**Figure 3A**) required for DEX mediated transactivation [26]. The

The Glucocorticoid Receptor and Certain KRÜPPEL-Like Transcription Factors have the Potential…

http://dx.doi.org/10.5772/intechopen.75451

41

**Figure 3.** KLF6 and the GR cooperatively transactivate the IEtu1 promoter. **Panel A:** The full length IEtu1 promoter was cloned as an XhoI-SphI restriction site. Start site of transcription (arrow), TATA box, binding site for VP16/Oct1 complex is denoted as TAATGARAT [74], and location of GRE#1 and GRE#2 (black and grey rectangles) are shown. Numbers are genomic coordinates of the first nucleotide of each respective motif or restriction enzyme site. GenScript synthesized the IEtu1 collapsed promoter construct and genomic coordinates are included: this fragment is inserted at KpnI and HindIII restriction sites of pGL3-Basic Vector. A 280 bp fragment (IEtu1 GREs) was cloned into the pGL3-Promoter Vector at unique KpnI and XhoI restriction sites [48]. **Panel B:** Neuro-2A cells were transfected with 0.5 ug DNA of the IEtu1 collapsed promoter (Collapsed) or IEtu1 GREs plasmid (GREs) and where indicated a plasmid that expresses the mouse GR protein (1.0 ug DNA) and/or KLF6 (0.5 ug DNA). To maintain equal plasmid amounts in the transfection mixtures, the empty expression vector was added as needed. Designated cultures were treated with water-soluble DEX (10 uM; Sigma) or DEX + RU486 (10 uM; Sigma) at 24 h after transfection. At 48 h after transfection, cells were harvested, and protein lysate subjected to dual-luciferase assay using a commercially available kit (E1910; Promega). Luminescence was measured by using a GloMax 20/20 luminometer (E5331; Promega). All transfections contained a plasmid encoding *Renilla* luciferase under the control of a minimal herpesvirus thymidine kinase (TK) promoter (0.050 ug DNA) as an internal control. Promoter activity in the empty luciferase vector (pGL3-Promoter Vector) was normalized to a value of 1 and fold activation for other samples presented. The results are the average of three independent experiments and error bars denote the standard error. A single asterisk denotes a significant difference (*P <* 0.05) between the IEtu1 collapsed or IEtu1 GREs when cotransfected with GR and KLF6 plus DEX treatment when compared to promoter activity of the respective promoter construct cotransfected with GR plus DEX treatment. Two asterisks denote a significant difference (*P <* 0.05) between the IEtu1 collapsed or IEtu1 GREs when cotransfected with GR and KLF6 and DEX treatment versus the same study conducted but treated with DEX+ RU486 or no DEX.A (#) denotes a significant difference between IEtu1 collapsed or IEtu1 GREs cotransfected with the GR and treated with DEX when compared to the same luciferase reporter cotransfected

with GR and treated with DEX+ RU486 or no DEX. Statistical analysis was performed using the Student *t* test.

**Figure 2.** KLF6 and the GR cooperate to stimulate productive infection. Neuro-2A cells were transfected with 2 ug BoHV-1 gCblue genomic DNA and where indicated a plasmid that expresses the mouse GR protein (1.0 ug DNA) and/ or KLF6 (0.5 ug DNA) using Lipofectamine 3000 (catalog no. L3000075; Invitrogen). A mouse GR expression vector was obtained from Dr. Joseph Cidlowski, NIH and the KLF6 expression vector was obtained from Bin Guo (North Dakota State University). Neuro-2A cells were grown in Eagle's minimal essential medium (EMEM) supplemented with 10% FCS, penicillin (10 U/ml), and streptomycin (100 μg/ml). The BoHV-1 mutant containing the β-Gal gene in place of the viral gC gene was obtained from S. Chowdury (LSU School of Veterinary Medicine) (gCblue virus) and stocks of this virus grown in bovine kidney cells (CRIB). The gCblue virus grows to similar titers as the wt parental virus and expresses the Lac Z gene. Procedures for preparing genomic DNA were described previously [73]. To maintain the same amount of DNA in each sample, empty vector was included in samples. Cells were incubated with stripped fetal calf serum 24 h after transfection and then treated with water soluble DEX (10 μM; Sigma, D2915). At 40 h after transfection, cells were fixed and stained for counting the number of β-Gal+ cells as previously described [48]. Representative cultures stained for Lac Z expression are shown in (**Panel A**). The value for the control (gCblue virus DNA treated with PBS after transfection) was set at 1. The results from DEX treated cultures were compared to the control and are an average of three independent studies (**Panel B**). The asterisk denotes a significant difference between the control and samples transfected with the GR or KLF6 and treated with DEX (P < 0.05) using the student's T test.

more than 4-fold, which was significantly higher than GR + DEX and the GR or KLF6 alone (**Figure 2A** and **B**). Cotransfection of gCblue and the GR + KLF6 stimulated productive infection 2-fold even when cultures were not treated with DEX, which was similar to the effects observed when gCblue genomic DNA was cotransfected with the GR and DEX treatment.

## **5. KLF6 and GR synergistically trans-activates the IEtu1 promoter**

Transient transfection studies were performed in Neuro-2A cells to test whether KLF6 and the GR synergistically trans-activate the IEtu1 promoter because this promoter contains two consensus GR binding sites (**Figure 3A**) required for DEX mediated transactivation [26]. The

**Figure 3.** KLF6 and the GR cooperatively transactivate the IEtu1 promoter. **Panel A:** The full length IEtu1 promoter was cloned as an XhoI-SphI restriction site. Start site of transcription (arrow), TATA box, binding site for VP16/Oct1 complex is denoted as TAATGARAT [74], and location of GRE#1 and GRE#2 (black and grey rectangles) are shown. Numbers are genomic coordinates of the first nucleotide of each respective motif or restriction enzyme site. GenScript synthesized the IEtu1 collapsed promoter construct and genomic coordinates are included: this fragment is inserted at KpnI and HindIII restriction sites of pGL3-Basic Vector. A 280 bp fragment (IEtu1 GREs) was cloned into the pGL3-Promoter Vector at unique KpnI and XhoI restriction sites [48]. **Panel B:** Neuro-2A cells were transfected with 0.5 ug DNA of the IEtu1 collapsed promoter (Collapsed) or IEtu1 GREs plasmid (GREs) and where indicated a plasmid that expresses the mouse GR protein (1.0 ug DNA) and/or KLF6 (0.5 ug DNA). To maintain equal plasmid amounts in the transfection mixtures, the empty expression vector was added as needed. Designated cultures were treated with water-soluble DEX (10 uM; Sigma) or DEX + RU486 (10 uM; Sigma) at 24 h after transfection. At 48 h after transfection, cells were harvested, and protein lysate subjected to dual-luciferase assay using a commercially available kit (E1910; Promega). Luminescence was measured by using a GloMax 20/20 luminometer (E5331; Promega). All transfections contained a plasmid encoding *Renilla* luciferase under the control of a minimal herpesvirus thymidine kinase (TK) promoter (0.050 ug DNA) as an internal control. Promoter activity in the empty luciferase vector (pGL3-Promoter Vector) was normalized to a value of 1 and fold activation for other samples presented. The results are the average of three independent experiments and error bars denote the standard error. A single asterisk denotes a significant difference (*P <* 0.05) between the IEtu1 collapsed or IEtu1 GREs when cotransfected with GR and KLF6 plus DEX treatment when compared to promoter activity of the respective promoter construct cotransfected with GR plus DEX treatment. Two asterisks denote a significant difference (*P <* 0.05) between the IEtu1 collapsed or IEtu1 GREs when cotransfected with GR and KLF6 and DEX treatment versus the same study conducted but treated with DEX+ RU486 or no DEX.A (#) denotes a significant difference between IEtu1 collapsed or IEtu1 GREs cotransfected with the GR and treated with DEX when compared to the same luciferase reporter cotransfected with GR and treated with DEX+ RU486 or no DEX. Statistical analysis was performed using the Student *t* test.

**Figure 2.** KLF6 and the GR cooperate to stimulate productive infection. Neuro-2A cells were transfected with 2 ug BoHV-1 gCblue genomic DNA and where indicated a plasmid that expresses the mouse GR protein (1.0 ug DNA) and/ or KLF6 (0.5 ug DNA) using Lipofectamine 3000 (catalog no. L3000075; Invitrogen). A mouse GR expression vector was obtained from Dr. Joseph Cidlowski, NIH and the KLF6 expression vector was obtained from Bin Guo (North Dakota State University). Neuro-2A cells were grown in Eagle's minimal essential medium (EMEM) supplemented with 10% FCS, penicillin (10 U/ml), and streptomycin (100 μg/ml). The BoHV-1 mutant containing the β-Gal gene in place of the viral gC gene was obtained from S. Chowdury (LSU School of Veterinary Medicine) (gCblue virus) and stocks of this virus grown in bovine kidney cells (CRIB). The gCblue virus grows to similar titers as the wt parental virus and expresses the Lac Z gene. Procedures for preparing genomic DNA were described previously [73]. To maintain the same amount of DNA in each sample, empty vector was included in samples. Cells were incubated with stripped fetal calf serum 24 h after transfection and then treated with water soluble DEX (10 μM; Sigma, D2915). At 40 h after transfection, cells were fixed and stained for counting the number of β-Gal+ cells as previously described [48]. Representative cultures stained for Lac Z expression are shown in (**Panel A**). The value for the control (gCblue virus DNA treated with PBS after transfection) was set at 1. The results from DEX treated cultures were compared to the control and are an average of three independent studies (**Panel B**). The asterisk denotes a significant difference between the control and samples transfected

more than 4-fold, which was significantly higher than GR + DEX and the GR or KLF6 alone (**Figure 2A** and **B**). Cotransfection of gCblue and the GR + KLF6 stimulated productive infection 2-fold even when cultures were not treated with DEX, which was similar to the effects observed when gCblue genomic DNA was cotransfected with the GR and DEX treatment.

with the GR or KLF6 and treated with DEX (P < 0.05) using the student's T test.

40 Transcriptional and Post-transcriptional Regulation

IEtu1 promoter drives IE expression of bICP0 and bICP4, the most important viral transcriptional regulatory proteins encoded by BoHV-1 [58–60] (**Figure 1**). The IEtu1 collapsed promoter construct (**Figure 3A**) was initially used to test whether sequences adjacent to the GREs were trans-activated by KLF6 and the GR. The full-length IEtu1 promoter construct contains extensive sequences downstream from the start site of transcription and has sequences between the TATA box and the GREs that are important for KLF trans-activation [16]: consequently the collapsed IEtu1 collapsed promoter construct was used for these studies. We have consistently found that the GR+ DEX stimulated promoter activity more than 15 fold and GR + KLF6 + DEX stimulated promoter activity more than 50 fold (**Figure 3B**). RU486 antagonizes corticosteroid/GR signaling [61, 62] and as expected RU486 significantly reduced the ability of KLF6 and GR to transactivate the IEtu1 collapsed construct.

or DEX. As shown in **Figure 5A**, ChIP studies demonstrated that the GR and KLF6 occupied the GRE region of the IEtu1 GREs (lanes 2–4). No specific PCR product was amplified from ChIPs of cells transfected with the IEtu1 GREs from IPs using the control IgG (IgG C Panel) or cells transfected with the ∆2XGRE∆KLF construct (**Figure 5C** and **D**). Treatment with DEX had little effect on the levels of GR bound to IEtu1 GRE sequences (**Figure 5A** and **B**); however, we detected an increase in KLF6 bound to the IEtu1 GREs when cotransfected with KLF6 and GR in the absence of DEX when compared to DEX treatment. At least three reasons may have led to this unexpected result. First, we suggest that low levels of corticosteroids in media containing

The Glucocorticoid Receptor and Certain KRÜPPEL-Like Transcription Factors have the Potential…

http://dx.doi.org/10.5772/intechopen.75451

43

**Figure 4.** Identification of sequences in the IEtu1 GREs that are responsive to KLF6 and the GR. **Panel A:** Schematic of IEtu1 promoter and location of TATA box, TAATGARAT motif, and the two GREs. Numbers denote the genomic location of the first nucleotide of each motif. **Panel B:** Schematic of 280 bp fragment that contains the IEtu1 GREs and putative KLF-binding sites. **Panel C:** Nucleotide sequence of motifs in the IEtu1 GREs and mutations that were prepared. Mutations in GRE#1 and GRE#2 were previously described and were shown to disrupt trans-activation by the GR in transient transfection studies [26, 48]. **Panel D:** Neuro-2A cells were transfected with the designated luciferase plasmid (0.5 ug DNA) and where indicated a plasmid that expresses the mouse GR protein (1.0 ug DNA) and/or KLF6 (0.5 ug DNA). To maintain the same amount of DNA in each sample, empty vector was included in certain samples. Cultures were then treated with 2% "stripped" fetal calf serum and then water soluble DEX (10 uM; Sigma) at 24 h after transfection. At 48 h after transfection, cells were harvested, and protein lysate was subjected to dual-luciferase assay as described in **Figure 3B**. The level of promoter activity in the empty luciferase vector (pGL3-Promoter Vector) was normalized to a value of 1 and the fold activation values for other samples are presented. The results are the average of three independent experiments and error bars denote the standard error. The asterisks denote a significant difference (*P <* 0.05) between IEtu1 GREs (wt) and the ∆KLF mutant when compared to the other mutants (∆GRE1, ∆GRE1∆KLF and ∆2XGRE∆KLF) after cotransfection with GR + KLF6 and treated with DEX, as determined by the Student *t* test.

A 280 bp fragment containing both GREs within the IEtu1 promoter and flanking sequences was cloned upstream of the minimal SV40 early promoter and designated IEtu1 GREs [48] (**Figure 3A**). This construct was examined for its ability to be activated by KLF6 and the GRE as a comparison to the IEtu1 collapsed promoter construct. KLF6 and the GR consistently stimulated the IEtu1 GREs construct approximately 16-fold whereas the GR + DEX stimulated this construct only 6-fold (**Figure 3B**). RU486 also significantly reduced the ability of KLF6 and GR to transactivate the IEtu1 GREs construct. Although the IEtu1 collapsed construct was trans-activated more by the GR + KLF6+ DEX relative to the IEtu1 GREs construct, the overall trends were similar.

## **6. The GREs are necessary for transactivation by the GR and KLF6**

To identify sequences in the IEtu1 GREs that mediate transactivation by KLF6 and the GR, constructs containing site-specific mutations in GRE#1, GRE#2, and KLF like binding sites were compared to the wt IEtu1 GREs (**Figure 4A**–**C**) [48]. Mutagenesis of GRE1 (∆GRE1) or both GREs and the KLF binding sites (∆2xGRE∆KLF) significantly reduced cooperative activation by KLF6 and the GR when DEX was added to the cultures (**Figure 4D**). Mutagenesis of the 2 putative KLF sites (∆KLF) had no effect on trans-activation by KLF6 and the GR when cultures were treated with DEX. As previously reported [48] and shown in **Figure 4D**, the effect of DEX and the GR was significantly reduced when GRE#1 (∆GRE1) was mutated and abolished when both GREs and putative KLF sites (∆2xGRE∆KLF) were mutated. In summary, mutagenesis of the GRE#1 significantly reduced synergistic transactivation by KLF6 and the GR when cultures were treated with DEX.

## **7. KLF6 and the GR interact with sequences located in the IEtu1 GREs**

To test whether KLF6 and the GR interact with sequences located in the IEtu1 GREs, chromatin immuno-precipitation (ChIP) studies were performed in Neuro-2A cells. Cells were transfected with the promoter construct containing the IEtu1 GREs followed by treatment with Vehicle or DEX. As shown in **Figure 5A**, ChIP studies demonstrated that the GR and KLF6 occupied the GRE region of the IEtu1 GREs (lanes 2–4). No specific PCR product was amplified from ChIPs of cells transfected with the IEtu1 GREs from IPs using the control IgG (IgG C Panel) or cells transfected with the ∆2XGRE∆KLF construct (**Figure 5C** and **D**). Treatment with DEX had little effect on the levels of GR bound to IEtu1 GRE sequences (**Figure 5A** and **B**); however, we detected an increase in KLF6 bound to the IEtu1 GREs when cotransfected with KLF6 and GR in the absence of DEX when compared to DEX treatment. At least three reasons may have led to this unexpected result. First, we suggest that low levels of corticosteroids in media containing

IEtu1 promoter drives IE expression of bICP0 and bICP4, the most important viral transcriptional regulatory proteins encoded by BoHV-1 [58–60] (**Figure 1**). The IEtu1 collapsed promoter construct (**Figure 3A**) was initially used to test whether sequences adjacent to the GREs were trans-activated by KLF6 and the GR. The full-length IEtu1 promoter construct contains extensive sequences downstream from the start site of transcription and has sequences between the TATA box and the GREs that are important for KLF trans-activation [16]: consequently the collapsed IEtu1 collapsed promoter construct was used for these studies. We have consistently found that the GR+ DEX stimulated promoter activity more than 15 fold and GR + KLF6 + DEX stimulated promoter activity more than 50 fold (**Figure 3B**). RU486 antagonizes corticosteroid/GR signaling [61, 62] and as expected RU486 significantly reduced

A 280 bp fragment containing both GREs within the IEtu1 promoter and flanking sequences was cloned upstream of the minimal SV40 early promoter and designated IEtu1 GREs [48] (**Figure 3A**). This construct was examined for its ability to be activated by KLF6 and the GRE as a comparison to the IEtu1 collapsed promoter construct. KLF6 and the GR consistently stimulated the IEtu1 GREs construct approximately 16-fold whereas the GR + DEX stimulated this construct only 6-fold (**Figure 3B**). RU486 also significantly reduced the ability of KLF6 and GR to transactivate the IEtu1 GREs construct. Although the IEtu1 collapsed construct was trans-activated more by the GR + KLF6+ DEX relative to the IEtu1 GREs construct, the overall

**6. The GREs are necessary for transactivation by the GR and KLF6**

**7. KLF6 and the GR interact with sequences located in the IEtu1** 

To test whether KLF6 and the GR interact with sequences located in the IEtu1 GREs, chromatin immuno-precipitation (ChIP) studies were performed in Neuro-2A cells. Cells were transfected with the promoter construct containing the IEtu1 GREs followed by treatment with Vehicle

and the GR when cultures were treated with DEX.

To identify sequences in the IEtu1 GREs that mediate transactivation by KLF6 and the GR, constructs containing site-specific mutations in GRE#1, GRE#2, and KLF like binding sites were compared to the wt IEtu1 GREs (**Figure 4A**–**C**) [48]. Mutagenesis of GRE1 (∆GRE1) or both GREs and the KLF binding sites (∆2xGRE∆KLF) significantly reduced cooperative activation by KLF6 and the GR when DEX was added to the cultures (**Figure 4D**). Mutagenesis of the 2 putative KLF sites (∆KLF) had no effect on trans-activation by KLF6 and the GR when cultures were treated with DEX. As previously reported [48] and shown in **Figure 4D**, the effect of DEX and the GR was significantly reduced when GRE#1 (∆GRE1) was mutated and abolished when both GREs and putative KLF sites (∆2xGRE∆KLF) were mutated. In summary, mutagenesis of the GRE#1 significantly reduced synergistic transactivation by KLF6

the ability of KLF6 and GR to transactivate the IEtu1 collapsed construct.

trends were similar.

42 Transcriptional and Post-transcriptional Regulation

**GREs**

**Figure 4.** Identification of sequences in the IEtu1 GREs that are responsive to KLF6 and the GR. **Panel A:** Schematic of IEtu1 promoter and location of TATA box, TAATGARAT motif, and the two GREs. Numbers denote the genomic location of the first nucleotide of each motif. **Panel B:** Schematic of 280 bp fragment that contains the IEtu1 GREs and putative KLF-binding sites. **Panel C:** Nucleotide sequence of motifs in the IEtu1 GREs and mutations that were prepared. Mutations in GRE#1 and GRE#2 were previously described and were shown to disrupt trans-activation by the GR in transient transfection studies [26, 48]. **Panel D:** Neuro-2A cells were transfected with the designated luciferase plasmid (0.5 ug DNA) and where indicated a plasmid that expresses the mouse GR protein (1.0 ug DNA) and/or KLF6 (0.5 ug DNA). To maintain the same amount of DNA in each sample, empty vector was included in certain samples. Cultures were then treated with 2% "stripped" fetal calf serum and then water soluble DEX (10 uM; Sigma) at 24 h after transfection. At 48 h after transfection, cells were harvested, and protein lysate was subjected to dual-luciferase assay as described in **Figure 3B**. The level of promoter activity in the empty luciferase vector (pGL3-Promoter Vector) was normalized to a value of 1 and the fold activation values for other samples are presented. The results are the average of three independent experiments and error bars denote the standard error. The asterisks denote a significant difference (*P <* 0.05) between IEtu1 GREs (wt) and the ∆KLF mutant when compared to the other mutants (∆GRE1, ∆GRE1∆KLF and ∆2XGRE∆KLF) after cotransfection with GR + KLF6 and treated with DEX, as determined by the Student *t* test.

2% stripped fetal bovine serum may be a reason why the GR was associated with the IEtu1 GREs in the absence of DEX. Secondly, independent studies concluded that the GR can be associated with GREs in the absence of corticosteroids [61, 63]. Thirdly, treatment of cells with DEX reduces GR levels and the availability of GR to bind to DNA [26, 64]. All input samples (whole lysate prior to IP) yielded the specific 107 bp PCR product except Neuro-2A cells not transfected with the IEtu1 GREs construct (**Figure 5A**, Input panel, lane 1). In summary, the GR and KLF6 were specifically recruited to IEtu1 GRE sequences when the GREs were intact.

The Glucocorticoid Receptor and Certain KRÜPPEL-Like Transcription Factors have the Potential…

http://dx.doi.org/10.5772/intechopen.75451

45

Co-immunoprecipitation (co-IP) studies were used to test whether GR and KLF6 physically interact. Neuro-2A cells were cotransfected with plasmids that express KLF6 and the GR. Following IP with the GR antibody, we were unable to detect KLF6 in the immunoprecipitate regardless of DEX treatment (**Figure 6**). As expected, both proteins were detected in whole cell lysate (input). Furthermore, the GR was detected in the immunoprecipitate after IP was performed with the GR antibody. When KLF6 was used to IP whole cell lysate, the GR was not detected in the immunoprecipitate (data not shown). The same experimental conditions revealed that KLF15 and the GR were stably associated in transfected Neuro-2A cells [48]. In summary, co-IP studies suggested KLF6 and the GR were not stably associated with each other.

**Figure 6.** The GR does not physically interact with KLF6. Neuro-2A cells were grown to confluence on 100 mm dishes. Cells were cotransfected with plasmids that express KLF6 (1.5 μg) and the GR (2 μg). Cultures were treated with DEX (10 μM) in 2% stripped serum medium for 4 h before harvesting of transfected cells and other cultures were not treated DEX. Whole cell lysate was prepared with RIPA lysis buffer with 1× Protease Inhibitor cocktail (Thermo-scientific, cat. No: 78430) and protein concentration quantified. Protein extracts (500 μg) were combined with anti-GR (Cell Signaling; 3660) and /or anti-KLF6 (5 μg) antibodies (Thermo Fisher Scientific, 39–6900) and reactions were incubated for overnight at 4°C on rotator. Co-IP and Western blot studies were performed as described previously [48]. The secondary donkey anti-rabbit antibody (NA9340V) was purchased from GE Healthcare and secondary sheep anti-mouse antibody was purchased from GE Healthcare. Following immunoprecipitation with the GR antibody, KLF6 was not detected in the immune-precipitate by western blotting in samples treated with or without DEX. Input lanes are (whole cell lysate) used as positive controls

for expression of the both proteins. Molecular weight markers (lane M) are shown to the left of the panels.

**8. The GR does not stably interact with KLF6**

**Figure 5.** Interaction between GR and KLF6 with IEtu1 GREs. Neuro-2A cells were cotransfected with the IEtu1 GREs construct (**Panel A**; 4 ug DNA) or ∆2XGRE∆KLF fragment (**Panel C**; 4 ug DNA), KLF6 expression plasmid (1.5 ug DNA) and/or the GR plasmid (2 ug DNA). Empty vector was added to maintain the same concentration of DNA in each transfection assay. Designated cultures were treated with DEX (10 uM; Sigma) 4 h before cells were harvested. ChIP studies were performed as previously described in Neuro-2A cells [48]. Polymerase chain reaction (PCR) was performed using primers that amplify the IEtu1 GREs and ∆2XGRE∆KLF: forward primer is 5′- CCCACTTTTGCCTGTGTG-3′ and reverse primer is 5'-TTTTCCTCCTCCTTCCCC-3′. These primers yield a product of 107 base pairs. Input was 10% of the total DNA: protein complexes that used for IP and then PCR performed using PCR primers described in the materials and methods. Arrows denote the specific PCR product, 107 bp for IEtu1 GREs or for ∆2XGRE∆KLF, and the circle denotes the position of primer dimers. Estimation of the level of binding to wild-type IEtu1 GREs sequences (**Panel B**) or ∆2XGRE∆KLF (**Panel D**) is shown. The results are representative of three independent studies.

2% stripped fetal bovine serum may be a reason why the GR was associated with the IEtu1 GREs in the absence of DEX. Secondly, independent studies concluded that the GR can be associated with GREs in the absence of corticosteroids [61, 63]. Thirdly, treatment of cells with DEX reduces GR levels and the availability of GR to bind to DNA [26, 64]. All input samples (whole lysate prior to IP) yielded the specific 107 bp PCR product except Neuro-2A cells not transfected with the IEtu1 GREs construct (**Figure 5A**, Input panel, lane 1). In summary, the GR and KLF6 were specifically recruited to IEtu1 GRE sequences when the GREs were intact.

## **8. The GR does not stably interact with KLF6**

**Figure 5.** Interaction between GR and KLF6 with IEtu1 GREs. Neuro-2A cells were cotransfected with the IEtu1 GREs construct (**Panel A**; 4 ug DNA) or ∆2XGRE∆KLF fragment (**Panel C**; 4 ug DNA), KLF6 expression plasmid (1.5 ug DNA) and/or the GR plasmid (2 ug DNA). Empty vector was added to maintain the same concentration of DNA in each transfection assay. Designated cultures were treated with DEX (10 uM; Sigma) 4 h before cells were harvested. ChIP studies were performed as previously described in Neuro-2A cells [48]. Polymerase chain reaction (PCR) was performed using primers that amplify the IEtu1 GREs and ∆2XGRE∆KLF: forward primer is 5′- CCCACTTTTGCCTGTGTG-3′ and reverse primer is 5'-TTTTCCTCCTCCTTCCCC-3′. These primers yield a product of 107 base pairs. Input was 10% of the total DNA: protein complexes that used for IP and then PCR performed using PCR primers described in the materials and methods. Arrows denote the specific PCR product, 107 bp for IEtu1 GREs or for ∆2XGRE∆KLF, and the circle denotes the position of primer dimers. Estimation of the level of binding to wild-type IEtu1 GREs sequences (**Panel B**) or

∆2XGRE∆KLF (**Panel D**) is shown. The results are representative of three independent studies.

44 Transcriptional and Post-transcriptional Regulation

Co-immunoprecipitation (co-IP) studies were used to test whether GR and KLF6 physically interact. Neuro-2A cells were cotransfected with plasmids that express KLF6 and the GR. Following IP with the GR antibody, we were unable to detect KLF6 in the immunoprecipitate regardless of DEX treatment (**Figure 6**). As expected, both proteins were detected in whole cell lysate (input). Furthermore, the GR was detected in the immunoprecipitate after IP was performed with the GR antibody. When KLF6 was used to IP whole cell lysate, the GR was not detected in the immunoprecipitate (data not shown). The same experimental conditions revealed that KLF15 and the GR were stably associated in transfected Neuro-2A cells [48]. In summary, co-IP studies suggested KLF6 and the GR were not stably associated with each other.

**Figure 6.** The GR does not physically interact with KLF6. Neuro-2A cells were grown to confluence on 100 mm dishes. Cells were cotransfected with plasmids that express KLF6 (1.5 μg) and the GR (2 μg). Cultures were treated with DEX (10 μM) in 2% stripped serum medium for 4 h before harvesting of transfected cells and other cultures were not treated DEX. Whole cell lysate was prepared with RIPA lysis buffer with 1× Protease Inhibitor cocktail (Thermo-scientific, cat. No: 78430) and protein concentration quantified. Protein extracts (500 μg) were combined with anti-GR (Cell Signaling; 3660) and /or anti-KLF6 (5 μg) antibodies (Thermo Fisher Scientific, 39–6900) and reactions were incubated for overnight at 4°C on rotator. Co-IP and Western blot studies were performed as described previously [48]. The secondary donkey anti-rabbit antibody (NA9340V) was purchased from GE Healthcare and secondary sheep anti-mouse antibody was purchased from GE Healthcare. Following immunoprecipitation with the GR antibody, KLF6 was not detected in the immune-precipitate by western blotting in samples treated with or without DEX. Input lanes are (whole cell lysate) used as positive controls for expression of the both proteins. Molecular weight markers (lane M) are shown to the left of the panels.

## **9. Discussion and summary**

In this study, we provided evidence that KLF6 and the GR synergistically stimulate productive infection and IEtu1 promoter activity. The IEtu1 promoter must be activated for productive infection because it encodes two viral transcriptional regulators, bICP0 and bICP4 (**Figure 7A**) [2]. During reactivation from latency, stress, as mimicked by the synthetic corticosteroid DEX, activates the GR and induces expression of several KLF family members (KLF4, KLF6, KLF15, and PLZF) [16]. A previous study demonstrated that KLF15, but not KLF4, and the GR synergistically stimulate IEtu1 promoter activity [48]. In contrast to KLF6, KLF15 stably interacts with the GR to establish a feed-forward transcriptional loop [48, 51, 53, 65, 66] (**Figure 7B**). Although KLF6 and KLF15 can both positively regulate promoter activity, they also can repress transcription in a promoter-specific manner [67, 68]. One study concluded there is a synergistic effect between the GR and transcriptional factors that recognize CACCC motifs [69], a known KLF6 binding site [70, 71]. There are no CACCC motifs on the positive strand of the IEtu1 GREs fragment; however, there are 2 CACCC motifs on the negative strand (KLF-1 like; **Figure 7B**). When these motifs were mutated (∆KLF mutant), there was no difference in KLF6 and GR mediated trans-activation suggesting there may be KLF binding sites located between GRE#2 and GRE#1. Relative to GRE#2, mutating GRE#1 was more important for GR mediated trans-activation [26, 48]. To ablate DEX induction of the IEtu1 promoter or the IEtu1 GREs, both GREs must be mutated [26, 48]. This is consistent with the results demonstrating there are cooperative effects between KLF15 [48] or KLF6 and the GR. ChIP results demonstrated that mutagenesis of both GREs interfered with KLF6 binding to sequences spanning the IEtu1 GREs, suggesting: 1) an unknown GR or KLF6 coactivator functions as a bridge between the GR and KLF6, which allows interactions between these two transcription factors (**Figure 7C**; left scenario at GRE#2), or 2) GR interactions with GRE#1 and/or GRE#2 influence adjacent sequences that are necessary for KLF6 to bind DNA **Figure 7B**; right scenario at GRE#1). Since KLF family members can bind to several GC or CA rich motifs, it is difficult to predict which sequences

The Glucocorticoid Receptor and Certain KRÜPPEL-Like Transcription Factors have the Potential…

http://dx.doi.org/10.5772/intechopen.75451

47

adjacent to GRE#1 or GRE#2 are important for interacting with KLF6 and/or KLF15.

The BoHV-1 genome contains approximately 100 putative GREs [26]. We identified 13 intergenic regions in the viral genome that contain at least 2 putative GREs and potential KLF binding sites within 400 base pairs. KLF15 and the GR significantly transactivate fragments present in unique long (UL)-52, bICP4, IEtu2, and Us fragments when DEX was added to cultures [48]. In contrast, KLF6 and the GR were unable to transactivate these intergenic fragments in the presence or absence of DEX (data not shown) confirming KLF15 has novel properties relative to KLF6.

KLF4, KLF6, and KLF15 expression are induced in TG neurons of calves that are latently infected with BoHV-1 during early stages of DEX induced reactivation from latency [16]. Cellular, not viral encoded, transcription factors are predicted to be crucial for initiating viral transcription during initial stages of reactivation from latency because lytic cycle viral gene expression is not readily detected in TG of latently infected calves [29, 30]. Thus, activation of the IEtu1 promoter by the GR and DEX-induced transcription factors, KLF6 and KLF15 for example, may be sufficient to trigger lytic cycle viral gene expression in a subset of latently

This research was supported by grants from the USDA-NIFA Competitive Grants Program (13-01041 and 16-09370), funds derived from the Sitlington Endowment, and support from the Oklahoma Center for Respiratory and Infectious Diseases (National Institutes of Health

infected neurons following a stressful stimulus, as shown in **Figure 7B** and **C**.

**Acknowledgements**

**Figure 7.** The GR and certain KLF family members stimulate BoHV-1 replication and IEtu1 promoter activity. **Panel A:**  Stress activates the GR, which in turn stimulates expression of four stress-induced KLF family members in TG neurons [16]. Recent studies demonstrated that stress, as mimicked by DEX plus the GR, activates IEtu1 promoter activity because two GREs are located in the promoter [26]. KLF6 and KLF15 cooperate with the GR to activate IEtu1 promoter activity. Stress mediated activation of the IEtu1 promoter is crucial for productive infection because this promoter drives expression of two viral regulatory proteins (bIC0 and bICP4). **Panel B:** KLF15 stably interacts with the GR: consequently, this complex synergistically stimulates IEtu1 promoter activity by binding to the GREs [48]. **Panel C:** KLF6 and the GR cooperate to stimulate expression of IEtu1 promoter activity and productive infection. In contrast, to KLF15, KLF6 did not stably interact with the GR. Consequently, we propose that a KLF6 indirectly interacts with the GR via an unknown GR coactivator (X) or binding of the GR to a GRE promotes KLF6 interactions with sequences between GRE#1 and GRE#2. This schematic does not suggest that the interactions occur at independent GREs within the IEtu1 promoter; it merely suggests that these are the two likely mechanisms by which KLF6 cooperates with the GR to stimulate IEtu1 promoter activity.

[2]. During reactivation from latency, stress, as mimicked by the synthetic corticosteroid DEX, activates the GR and induces expression of several KLF family members (KLF4, KLF6, KLF15, and PLZF) [16]. A previous study demonstrated that KLF15, but not KLF4, and the GR synergistically stimulate IEtu1 promoter activity [48]. In contrast to KLF6, KLF15 stably interacts with the GR to establish a feed-forward transcriptional loop [48, 51, 53, 65, 66] (**Figure 7B**). Although KLF6 and KLF15 can both positively regulate promoter activity, they also can repress transcription in a promoter-specific manner [67, 68]. One study concluded there is a synergistic effect between the GR and transcriptional factors that recognize CACCC motifs [69], a known KLF6 binding site [70, 71]. There are no CACCC motifs on the positive strand of the IEtu1 GREs fragment; however, there are 2 CACCC motifs on the negative strand (KLF-1 like; **Figure 7B**). When these motifs were mutated (∆KLF mutant), there was no difference in KLF6 and GR mediated trans-activation suggesting there may be KLF binding sites located between GRE#2 and GRE#1.

Relative to GRE#2, mutating GRE#1 was more important for GR mediated trans-activation [26, 48]. To ablate DEX induction of the IEtu1 promoter or the IEtu1 GREs, both GREs must be mutated [26, 48]. This is consistent with the results demonstrating there are cooperative effects between KLF15 [48] or KLF6 and the GR. ChIP results demonstrated that mutagenesis of both GREs interfered with KLF6 binding to sequences spanning the IEtu1 GREs, suggesting: 1) an unknown GR or KLF6 coactivator functions as a bridge between the GR and KLF6, which allows interactions between these two transcription factors (**Figure 7C**; left scenario at GRE#2), or 2) GR interactions with GRE#1 and/or GRE#2 influence adjacent sequences that are necessary for KLF6 to bind DNA **Figure 7B**; right scenario at GRE#1). Since KLF family members can bind to several GC or CA rich motifs, it is difficult to predict which sequences adjacent to GRE#1 or GRE#2 are important for interacting with KLF6 and/or KLF15.

The BoHV-1 genome contains approximately 100 putative GREs [26]. We identified 13 intergenic regions in the viral genome that contain at least 2 putative GREs and potential KLF binding sites within 400 base pairs. KLF15 and the GR significantly transactivate fragments present in unique long (UL)-52, bICP4, IEtu2, and Us fragments when DEX was added to cultures [48]. In contrast, KLF6 and the GR were unable to transactivate these intergenic fragments in the presence or absence of DEX (data not shown) confirming KLF15 has novel properties relative to KLF6.

KLF4, KLF6, and KLF15 expression are induced in TG neurons of calves that are latently infected with BoHV-1 during early stages of DEX induced reactivation from latency [16]. Cellular, not viral encoded, transcription factors are predicted to be crucial for initiating viral transcription during initial stages of reactivation from latency because lytic cycle viral gene expression is not readily detected in TG of latently infected calves [29, 30]. Thus, activation of the IEtu1 promoter by the GR and DEX-induced transcription factors, KLF6 and KLF15 for example, may be sufficient to trigger lytic cycle viral gene expression in a subset of latently infected neurons following a stressful stimulus, as shown in **Figure 7B** and **C**.

## **Acknowledgements**

**Figure 7.** The GR and certain KLF family members stimulate BoHV-1 replication and IEtu1 promoter activity. **Panel A:**  Stress activates the GR, which in turn stimulates expression of four stress-induced KLF family members in TG neurons [16]. Recent studies demonstrated that stress, as mimicked by DEX plus the GR, activates IEtu1 promoter activity because two GREs are located in the promoter [26]. KLF6 and KLF15 cooperate with the GR to activate IEtu1 promoter activity. Stress mediated activation of the IEtu1 promoter is crucial for productive infection because this promoter drives expression of two viral regulatory proteins (bIC0 and bICP4). **Panel B:** KLF15 stably interacts with the GR: consequently, this complex synergistically stimulates IEtu1 promoter activity by binding to the GREs [48]. **Panel C:** KLF6 and the GR cooperate to stimulate expression of IEtu1 promoter activity and productive infection. In contrast, to KLF15, KLF6 did not stably interact with the GR. Consequently, we propose that a KLF6 indirectly interacts with the GR via an unknown GR coactivator (X) or binding of the GR to a GRE promotes KLF6 interactions with sequences between GRE#1 and GRE#2. This schematic does not suggest that the interactions occur at independent GREs within the IEtu1 promoter; it merely suggests that these are

In this study, we provided evidence that KLF6 and the GR synergistically stimulate productive infection and IEtu1 promoter activity. The IEtu1 promoter must be activated for productive infection because it encodes two viral transcriptional regulators, bICP0 and bICP4 (**Figure 7A**)

the two likely mechanisms by which KLF6 cooperates with the GR to stimulate IEtu1 promoter activity.

**9. Discussion and summary**

46 Transcriptional and Post-transcriptional Regulation

This research was supported by grants from the USDA-NIFA Competitive Grants Program (13-01041 and 16-09370), funds derived from the Sitlington Endowment, and support from the Oklahoma Center for Respiratory and Infectious Diseases (National Institutes of Health Centers for Biomedical Research Excellence Grant # P20GM103648). Research reported in this publication was also partially supported by the National Institute Of Neurological Disorders And Stroke of the National Institutes of Health under Award Number R21NS102290. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Fouad S. El-mayet was supported by a fellowship from the Egyptian Ministry of Higher Education, Mission Sector (JS-3541).

[8] Afroz S, Brownlie R, Fodjec M, van Drunen Littel-van den Hurk S. VP8, the major tegument protein of bovine herpesvirus 1, interacts with cellular STAT1 and inhibits inter-

The Glucocorticoid Receptor and Certain KRÜPPEL-Like Transcription Factors have the Potential…

http://dx.doi.org/10.5772/intechopen.75451

49

[9] Highlander SK. Molecular genetic analysis of virulence in *Mannheimia (Pasteurella) hae-*

[10] Rivera-Rivas JJ, Kisiela D, Czuprynski CJ. Bovine herpesvirus type 1 infection of bovine bronchial epithelial cells increases neutrophil adhesion and activation. Veterinary

[11] Frank GH, editor. Bacteria as etiologic agents in bovine respiratory disease. College

[12] Hodgson PD, Aich P, Manuja A, Hokamp K, Roche FM, Brinkman FSL, Potter A, Babiuk LA, Griebel PJ. Effect of stress on viral-bacterial synergy in bovine respiratoryt disease: novel mechanisms to regulate inflammation. Comparative and Functional Genomics. 2005;**6**:

[13] Jones C, Chowdhury S. Bovine herpesvirus type 1 (BHV-1) is an important cofactor in the bovine respiratory disease complex. In: Broderson VLCB, editor. Veterinary Clinics of North America, Food Animal Practice, Bovine Respiratory Disease, vol 26. New York,

[14] Neibergs HL, Seabury CM, Wojtowicz AJ, Wang Z, Scraggs E, Kiser JN, Neupane M, Womack JE, Van Eenennaam A, Hagevortm GR, Lehenbauer TW, Aly S, Davis J, Taylor JF, the Bovine Respiratory Disease Complex Coordinatefd Agricultural Research Team. Susceptibility loci revealed for bovine respiratory disease complex in pre-weaned hol-

[15] Liu Y, Hancock M, Workman A, Doster A, Jones C. Beta-catenin, a transcription factor activated by canonical Wnt signaling, is expressed in sensory neurons of calves latently

[16] Workman A, Eudy J, Smith L, Frizzo da Silva L, Sinani D, Bricker H, Cook E, Doster A, Jones C. Cellular transcription factors induced in trigeminal ganglia during dexamethasone-induced reactivation from latency stimulate bovine herpesvirus 1 productive infec-

[17] Jaber T, Workman A, Jones C. Small noncoding RNAs encoded within the bovine herpesvirus 1 latency-related gene can reduce steady-state levels of infected cell protein 0

[18] Zhu L, Workman A, Jones C. A potential role for a beta-catenin coactivator (high mobility group AT-hook 1 protein) during the latency-reactivation cycle of bovine herpesvirus

[20] Polakis P. Wnt signaling in cancer. In: Nusse R, He X, van Amerongen R, editor. Cold Spring Harbor Perspectives in Biology. Cold Spring Harbor, NY: Cold Spring Harbor

[19] Clevers H, Nusse R. Wnt/B-catenin signaling and disease. Cell. 2012;**149**:1192-1205

infected with bovine herpesvirus 1. Journal of Virology. 2016;**90**:3148-3159

tion and certain viral promoters. Journal of Virology. 2012;**86**:2459-2473

feron beta signaling. Journal of Virology. 2016;**90**:4889-4904

*molytica*. Frontiers in Bioscience. 2001:D1128-D1150

Immunology and Immunopathology. 2009;**131**:167-176

Station, TX: Texas A&M University Press; 1984

NY: Elsevier; 2010. pp. 303-321

stein calves. BMC Genomics.2014;**15:**1-19

(bICP0). Journal of Virology. 2010;**84**:6297-6307

1. Journal of Virology. 2017;**91**:e02132-e20136

Laboratory Press; 2012

244-250

## **Author details**

Fouad S. El-mayet1,2, Ayman S. El-Habbaa2 , Gabr F. El-Bagoury2 , Saad S.A. Sharawi2 , Ehab M. El-Nahas2 and Clinton Jones1 \*

\*Address all correspondence to: clint.jones10@okstate.edu

1 Department of Veterinary Pathobiology, Center for Veterinary Health Sciences, Oklahoma State University, Stillwater, OK, United States

2 Department of Virology, Faculty of Veterinary Medicine, Benha University, Kaliobeya, Egypt

## **References**


[8] Afroz S, Brownlie R, Fodjec M, van Drunen Littel-van den Hurk S. VP8, the major tegument protein of bovine herpesvirus 1, interacts with cellular STAT1 and inhibits interferon beta signaling. Journal of Virology. 2016;**90**:4889-4904

Centers for Biomedical Research Excellence Grant # P20GM103648). Research reported in this publication was also partially supported by the National Institute Of Neurological Disorders And Stroke of the National Institutes of Health under Award Number R21NS102290. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Fouad S. El-mayet was supported by a fellowship

, Gabr F. El-Bagoury2

1 Department of Veterinary Pathobiology, Center for Veterinary Health Sciences, Oklahoma

[1] Jones C. Bovine herpes virus 1 (BHV-1) and herpes simplex virus type 1 (HSV-1) promote survival of latently infected sensory neurons, in part by inhibiting apoptosis. Journal of

[2] Jones C. Reactivation from latency by alpha-herpesvirinae submfamily members: A

[3] Jones, C. Latency of bovine Herpesvirus 1 (BoHV-1) in Sensory Neurons, Herpesviridae.

[4] Jones C. Regulation of innate immune responses by bovine herpesvirus 1 and infected

[5] Henderson G, Zhang Y, Jones C. The bovine herpesvirus 1 gene encoding infected cell protein 0 (bICP0) can inhibit interferon-dependent transcription in the absence of other

[6] Saira K, Zhou Y, Jones C. The infected cell protein 0 encoded by bovine herpesvirus 1 (bICP0) induces degradation of interferon response factor 3 (IRF3), and consequently

[7] Saira K, Jones C. The infected cell protein 0 encoded by bovine herpesvirus 1 (bICP0) associates with interferon regulatory factor 7 (IRF7), and consequently inhibits beta inter-

inhibits beta interferon promoter activity. Journal of Virology. 2007;**81**:3077-3086

stressful situation. Current Topics in Virology. 2014;**12**:99-118

In: Joseph O, editor. Rijeka: InTech; 2016. DOI: 10.5772/63750

viral genes. The Journal of General Virology. 2005;**86**:2697-2702

feron promoter activity. Journal of Virology. 2009;**83**:3977-3981

2 Department of Virology, Faculty of Veterinary Medicine, Benha University, Kaliobeya,

, Saad S.A. Sharawi2

,

from the Egyptian Ministry of Higher Education, Mission Sector (JS-3541).

\*

**Author details**

Ehab M. El-Nahas2

Egypt

**References**

Cell Death. 2013;**6**:1-16

cell protein 0. Virus. 2009;**1**:255-275

Fouad S. El-mayet1,2, Ayman S. El-Habbaa2

48 Transcriptional and Post-transcriptional Regulation

State University, Stillwater, OK, United States

and Clinton Jones1

\*Address all correspondence to: clint.jones10@okstate.edu


[21] Salinas PC. Wnt signaling in the vertebrate central nervous system: From axon guidance to synaptic function. Cold Spring Harbor Perspectives in Biology. 2012;**4**:a008003

[35] Khanna KM, Bonneau RH, Kinchington PR, Hendricks RL. Herpes simplex virus-specific memory CD8+ T cells are selectively activated and retained in latently infected sen-

The Glucocorticoid Receptor and Certain KRÜPPEL-Like Transcription Factors have the Potential…

http://dx.doi.org/10.5772/intechopen.75451

51

[36] Prbhakaran K, Sheridan BS, Kinchington PR, Khanna KM, Decman V, Lathrop K, Hendricks RL. Sensory neurons regulate the effector functions of CD8+ T cells in con-

[37] Knickelbein JE, Khanna KM, Yee MB, Baty CJ, Kinchington PR, Hendricks RL. Noncytotoxic lytic granule-mediated CD8+ T cell inhibition of HSV-1 reactivation from

[38] Matrisciano F, Buscetti CL, Bucci D, Orlando R, Caruso A, Molinaro G, Cappuccion I, Riozzi B, Gradini R, Motolese M, Caraci F, Copani A, Scaccianoce S, Melchiorri D, Bruno V, Battaglia G, Nicoletti F. Induction of the Wnt antagonist Dickkopf-1 is involved in stress-

[39] Moors M, Bose R, Johansson-Haque K, Edoff K, Okret S, Ceccatelli S. Dickkopf mediates glucocorticoid-induced changes in human neural progenitor cell proliferation and dif-

[40] Kaczynski J, Cook T, Urrutia R. Sp1- and Kruppel-like transcription factors. Genome

[41] Bieker JJ. Kruppel-like factors: three fingers in many pies. The Journal of Biological

[42] Jones KA, Tjian R. Sp1 binds to promoter sequences and activates herpes simples virus

[43] Knipe DM, Cliffe A. Chromatin control of herpes simplex virus lytic and latent infection.

[44] Lacasse JL, Schang LM. Herpes simplex virus 1 DNA is in unstable nucleosomes throughout the lytic infection cycle, and the instability of the nucleosomes is indepen-

[45] Lacasse JL, Schang LM. During lytic infection, herpes simplex virus type 1 DNA is in complexes with the properties of unstable nucleosomes. Journal of Virology. 2010;**84**:1920-1933

[46] Rock D, Lokensgard J, Lewis T, Kutish G. Characterization of dexamethasone-induced reactivation of latent bovine herpesvirus 1. Journal of Virology. 1992;**66**:2484-2490

[47] Welten PJAJE, Bosch DS, de Jonge RT, Balog J, van der Maarel SM, de Kloet ER, Datson NA. A genome-wide signature of glucocorticoid receptor binding in neuronal PC12

[48] El-Mayet FS, Sawant L, Thungunutla P, Jones C. Combinatorial effects of the glucocorticoid receptor and Krüppel-like transcription factor 15 on bovine herpesvirus 1 transcrip-

tion and productive infection. Journal of Virology. 2017;**91**(91):e00904-00917

'immediate-early' gene transcription in vitro. Nature. 1985;**317**:179-182

dent of DNA replication. Journal of Virology. 2012;**86**:112870-111300

sory ganglia. Immunity. 2003;**18**:593-603

neuronal latency. Science. 2008;**322**:268-272

trolling HSV-1 latency ex vivo. Immunity. 2005;**23**:515-523

induced hippocampal damage. PLoS One. 2011;**6**:e16447

ferentiation. Toxicological Sciences. 2012;**125**:488-495

Nature Reviews. Microbiology. 2008;**6**:211-221

cells. BMC Neuroscience. 2012;**13**:118-125

Biology. 2003;**4**:206.201-206.208

Chemistry. 2001;**276**:34355-34358


[35] Khanna KM, Bonneau RH, Kinchington PR, Hendricks RL. Herpes simplex virus-specific memory CD8+ T cells are selectively activated and retained in latently infected sensory ganglia. Immunity. 2003;**18**:593-603

[21] Salinas PC. Wnt signaling in the vertebrate central nervous system: From axon guidance to synaptic function. Cold Spring Harbor Perspectives in Biology. 2012;**4**:a008003

[22] Purro SA, Galli S, Salinas PC. Dysfunction of Wnt signaling and synaptic disassembly in

[23] Bhardwaji D, Nager M, Camats J, David M, Benguira A, dopazo A, Canti C, Herreros J. Chemokines induce axon outgrowth downstream of hepatocyte growth factor and

[24] Murase S, Mosser E, Schuman EM. Depolarization drives beta-catenin into neuronal spines promoting changes in synaptic structure and function. Neuron. 2002;**35**:91-105

[25] Bamji SX, Rico B, Kimes N, Reichardt LF. BDNF mobilizes synaptic vesicles and enhances synaptic vesicles and enhances synapse formation by disrupting cadherin-beta-catenin

[26] Kook ICH, Meyer F, Hoffmann F, Jones C. Bovine herpesvirus 1 productive infection and the immediate early transcription unit 1 are stimulated by the synthetic corticoste-

[27] Winkler MT, Doster A, Sur JH, Jones C. Analysis of bovine trigeminal ganglia following infection with bovine herpesvirus 1. Veterinary Microbiology. 2002;**86**:139-155

[28] Winkler MT, Doster A, Jones C. Persistence and reactivation of bovine herpesvirus 1 in

[29] Frizzo da Silva L, Kook I, Doster A, Jones C. Bovine herpesvirus 1 regulatory proteins, bICP0 and VP16, are readily detected in trigeminal ganglionic neurons expressing the glucocorticoid receptor during the early stages of reactivation from latency. Journal of

[30] Kook I, Doster A, Jones C. Bovine herpesvirus 1 regulatory proteins are detected in trigeminal ganglionic neurons during the early stages of stress-induced escape from

[31] DeLeon M, Covenas R, Chadi G, Narvaez JA, Fuxe K, Cintra A. Subpopulations of primary sensory neurons show coexistence of neuropeptides and glucocorticoid receptors

[32] Arriza JL, Simerly RB, Swanson LW, Evans RM. The neuronal mieralocorticoid receptor

[33] Liu T, Khanna KM, Chen X, Fink DJ, Hendricks RL. CD8(+) T cells can block herpes simplex virus type 1 (HSV-1) reactivation from latency in sensory neurons [In Process

[34] Liu T, Khanna KM, Carriere BN, Hendricks RL. Gamma interferon can prevent herpes simplex virus type 1 reactivation from latency in sensory neurons. Journal of Virology.

in the rat spinal and trigeminal gnaglia. Brain Research. 1994;**14**:338-342

as a mediator of glucocorticoid response. Neuron. 1988;**1**:887-900

Citation]. The Journal of Experimental Medicine. 2000;**191**:1459-1466

the tonsil of latently infected calves. Journal of Virology. 2000;**74**:5337-5346

neurodegenerative diseases. Journal of Molecular Cell Biology. 2014;**6**:75-80

TCF/beta-catenin signaling. Frontiers in Cellular Neuroscience. 2013;**7**:1-10

interactions. The Journal of Cell Biology. 2006;**174**:289-299

roid dexamethasone. Virology. 2015;**484**:377-385

latency. Journal of Neurovirology. 2015;**21**:585-591

Virology. 2013;**87**:11214-11222

50 Transcriptional and Post-transcriptional Regulation

2001;**75**:11178-11184


[49] Mangan S, Alon U. Structure and function of the feed-forward loop network motif. Proceedings of the National Academy of Sciences of the United States of America. 2003; **100**:11980-11985

[61] Pandit S, Geissler W, Harris G, Sitlani A. Allosteric effects of dexamethasone and RU486 on glucocorticoid receptor-DNA interactions. The Journal of Biological Chemistry.

The Glucocorticoid Receptor and Certain KRÜPPEL-Like Transcription Factors have the Potential…

http://dx.doi.org/10.5772/intechopen.75451

53

[62] Schulz M, Eggert M, Baniahmad A, Dostert A, Heinzel T, Renkatz R. RU486-induced glococorticoid receptor agonism is controlled by the receptor N terminus and by core-

[63] Schmitt J, Stunnenberg HG. The glucocorticoid receptor hormone binding domain mediates transcriptional activation in vitro in the absence of ligand. Nucleic Acids Research.

[64] Nishimura K, Nonomura N, Satoh E, Harada Y, Nakayama M, Tokizane T, Fuki T, Ono Y, Inoue H, Shin M, Tsujimoto Y, Takayama H, Aozasa K, Okuyama A. Potential mechansim for the effects of dexamethasone on growth of androgen-independent pros-

[65] Takeda K, Yahagi N, Aita Y, Murayama Y, Sawada Y, Piao X, Toya N, Oya Y, Shikama A, Takarada A, Masuda Y, Nishi M, Kuobota M, Izumida Y, Yamamoto T, Sekiya M, Matsuzaka T, Nakagawa Y, Urayama O, Kawakami Y, Iizuka Y, Gotoda T, Itaka K, Kataoka K, Nagai R, Kadowaki T, yamada N, Lin Y, Jain MK, Shimano H. KLF15 enables switching between lipogenesis aand gluconeogenesis during fasting. Cell Reports. 2016;**16**:2373-2386

[66] Yamamoto J, Ikeda Y, Iguchi H, Fujino T, Tanaka T, Asaba H, Iwasaki S, Ioka RX, Kaneko IW, Magoori K, Takahashi S, Mori T, Sakaue H, Kodama T, Yanagisawa M, Yamamoto TT, Ito S, Sakai J. A Kruppel-like factor KLF15 contributes fasting-induced transcriptional activation of mitochondrial acetyl-CoA synthtase gene AceCS2. The Journal of Biological

[67] Otteson DC, Lai H, Liu Y, Zack DJ. Zinc-finger domains of the transcriptional repressor KLF15 binds multiple sites in rhodopsin and IRBP promoters including the CRS-1 and G-rich elements. BMC Molecular Biology. 2005;**6**:1-16. DOI: 10.1186/1471-2199-1186-1115

[68] Calderon MR, Verway M, An B-S, DiFeo A, Bismar TA, Ann DK, Martignetti JA, Shalom-Barak T, White JH. Ligand-dependent corepressor (LCoR) recruitment by Kruppel-like factor 6 (KLF6) regulates expression of the cyclin dependent kinase inhibitor CDKN1A

[69] Strahle U, Schmid W, Schutz G. Synergistic action of the glucocorticoid receptor with

[70] Chiambaretta F, Blanchon L, Rabier B, Kao WW-Y, Liu JJ, Dastuge B, Rigal D, Sapin V. Regulation of corneal keratin-12 gene expression by the human Kruppel-like transcription factor 6. Investigative ophtalmology and Visual. Science. 2002;**43**:3422-3429

[71] Koritschoner N, Bocco JL, Panzetta-Dutari GM, Dumar CI, Flury A, Patrito LC. A novel human zinc finger protein that interacts with the core promoter element of a TATA box-

gene. The Journal of Biological Chemistry. 2012;**287**:8662-8674

less gene. The Journal of Biological Chemistry. 1997;**272**:9573-9580

transcription factors. The EMBO Journal. 1988;**7**:3389-3395

pressor binding. The Journal of Biological Chemistry. 2002;**277**:26238-26243

tate cancer. Journal of the National Cancer Institute. 2014;**93**:1739-1746

2002;**277**:1538-1543

1993;**21**:2673-2681

Chemistry. 2004;**279**:16954-16962


[61] Pandit S, Geissler W, Harris G, Sitlani A. Allosteric effects of dexamethasone and RU486 on glucocorticoid receptor-DNA interactions. The Journal of Biological Chemistry. 2002;**277**:1538-1543

[49] Mangan S, Alon U. Structure and function of the feed-forward loop network motif. Proceedings of the National Academy of Sciences of the United States of America. 2003;

[50] Sasse S, Zuo Z, Kadiyala V, Zhang L, Pufall MA, Jain MK, Phang TL, Stormo GD, Gerber AN. Response element composition governs correlations between binding site affinity and transcription in glucocorticoid receptor feed-forward loops. The Journal of Biological

[51] Sasse S, Mailoux CM, Barczak AJ, Wang Q, Altonsy MO, Jain MK, Haldar SM, Gerber AN. The glucocorticoid receptor and KLF15 regulate gene expression dynamics and integrate signals through feed-forward circuitry. Molecular Cell Biology. 2013;**33**:2104-2115

[52] Alon U. Network motifs: theory and experimental approaches. Nature Reviews. Genetics.

[53] Masuno K, Haldar SM, Jeyaraji D, Mailoux C, Huang X, Panettieri RA, Jain MK, Gerber AN. Expression profiling identifies Klf15 as a glucocorticoid target that regulates airway hyperresponsiveness. American Journal of Respiratory Cell and Molecular Biology. 2011;**10**:1165

[54] Sinani D, Cordes E, Workman A, Thunuguntia P, Jones C. Stress induced cellular transcription factors expressed in trigeminal ganglionic neurons stimulate the herpes simplex virus type 1 (HSV-1) infected cell protein 0 (ICP0) promoter. Journal of Virology. 2013;

[55] Asada M, Rauch A, Shimizu H, Maruyama H, Miaki S, Shigamori M, Kawasome H, Ishiyama H, Tuckermann J, Asahara H. DNA-binding dependent glucocorticoid receptor activity promotes adipogenesis via Kruppel-like factor 15 gene expression. Laboratory

[56] Tremblay R, Sikorska M, Sandhu JK, Lanthier P, Ribecco-Lutkiewicz M, Bani-Yaghoub M. Differentiation of mouse Neuro-2A cells into dopamine neurons. Journal of

[57] Thunuguntla P, El-mayet FS, Jones C. Bovine herpesvirus 1 can efficiently infect the human (SH-SY5Y) but not the mouse neuroblastoma cell line (Neuro-2A). Virus

[58] Wirth UV, Fraefel C, Vogt B, Vlcek C, Paces V, Schwyzer M. Immediate-early RNA 2.9 and early RNA 2.6 of bovine herpesvirus 1 are 3′ coterminal and encode a putative zinc

[59] Wirth UV, Vogt B, Schwyzer M. The three major immediate-early transcripts of bovine herpesvirus 1 arise from two divergent and spliced transcription units. Journal of Virology.

[60] Fraefel C, Zeng J, Choffat Y, Engels M, Schwyzer M, Ackermann M. Identification and zinc dependence of the bovine herpesvirus 1 transactivator protein BICP0. Journal of

finger transactivator protein. Journal of Virology. 1992;**66**:2763-2772

**100**:11980-11985

52 Transcriptional and Post-transcriptional Regulation

2007;**8**:450-461

**87**:1183-1192

Investigation. 2011;**91**:203-215

Research. 2017;**232**:1-5

1991;**65**:195-205

Virology. 1994;**68**:3154-3162

Neuroscience Methods. 2010;**186**:60-67

Chemistry. 2015;**290**:19756-19769


[72] Wirth UV, Gunkel K, Engels M, Schwyzer M. Spatial and temporal distribution of bovine herpesvirus 1 transcripts. Journal of Virology. 1989;**63**:4882-4889

**Chapter 4**

**Provisional chapter**

**Roles of Non-Coding RNAs in Transcriptional**

**Roles of Non-Coding RNAs in Transcriptional** 

DOI: 10.5772/intechopen.76125

Non-coding RNAs (ncRNAs) are functional RNA molecules that are transcribed from mammalian genome but lack protein coding capacity. Nearly 80% of the human genome constitutes non-coding elements such as small non-coding RNAs, sncRNAs (miRNA, piRNA, SiRNA, SnRNA) and long non-coding RNAs, lncRNAs (linc RNA, NAT, eRNA, circ RNA, ceRNAs, PROMPTS). These ncRNAs have been extensively studied and are known to mediate the regulation of gene expression. In recent decades, lncRNAs have emerged as pivotal molecules that participate in the post-transcriptional regulation by acting as a signal, guide, scaffold and decoy molecules in addition to their role(s) in transcription. ncRNAs are known to play critical roles in defining DNA methylation patterns, imprinting as well as chromatin remodeling, thus having a substantial effect in epigenetic signaling. The expression of lncRNAs is regulated in a tissue specific and developmental stage specific manner and their mis-regulation is often associated with tumorigenesis. Henceforth, this chapter focuses mainly on the role(s) of ncRNAs in transcriptional and post-transcriptional regulation and their relevance in cancers. **Keywords:** lncRNAs, miRNAs, DNA methylation, epigenetic signaling, transcriptional

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

According to "RNA world hypothesis", early life was started with RNA molecules. Later with time, storage of information evolved to more stable DNA and RNA which emerged as a

Loudu Srijyothi, Saravanaraman Ponne, Talukdar Prathama, Cheemala Ashok and

Loudu Srijyothi, Saravanaraman Ponne, Talukdar Prathama, Cheemala Ashok and

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.76125

**Regulation**

**Regulation**

Sudhakar Baluchamy

Sudhakar Baluchamy

**Abstract**

regulation, cancer

**1.1. The incredible RNA molecules**

**1. Introduction**


#### **Roles of Non-Coding RNAs in Transcriptional Regulation Roles of Non-Coding RNAs in Transcriptional Regulation**

DOI: 10.5772/intechopen.76125

Loudu Srijyothi, Saravanaraman Ponne, Talukdar Prathama, Cheemala Ashok and Sudhakar Baluchamy Loudu Srijyothi, Saravanaraman Ponne, Talukdar Prathama, Cheemala Ashok and Sudhakar Baluchamy

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.76125

#### **Abstract**

[72] Wirth UV, Gunkel K, Engels M, Schwyzer M. Spatial and temporal distribution of bovine

[73] Inman M, Lovato L, Doster A, Jones C. A mutation in the latency-related gene of bovine herpesvirus 1 leads to impaired ocular shedding in acutely infected calves. Journal of

[74] Misra V, Bratanich AC, Carpenter D, O'Hare P. Protein and DNA elements involved in transactivation of the promoter of the bovine herpesvirus (BHV) 1 IE-1 transcription unit by the BHV alpha gene trans-inducing factor. Journal of Virology. 1994;**68**:4898-4909

herpesvirus 1 transcripts. Journal of Virology. 1989;**63**:4882-4889

Virology. 2001;**75**:8507-8515

54 Transcriptional and Post-transcriptional Regulation

Non-coding RNAs (ncRNAs) are functional RNA molecules that are transcribed from mammalian genome but lack protein coding capacity. Nearly 80% of the human genome constitutes non-coding elements such as small non-coding RNAs, sncRNAs (miRNA, piRNA, SiRNA, SnRNA) and long non-coding RNAs, lncRNAs (linc RNA, NAT, eRNA, circ RNA, ceRNAs, PROMPTS). These ncRNAs have been extensively studied and are known to mediate the regulation of gene expression. In recent decades, lncRNAs have emerged as pivotal molecules that participate in the post-transcriptional regulation by acting as a signal, guide, scaffold and decoy molecules in addition to their role(s) in transcription. ncRNAs are known to play critical roles in defining DNA methylation patterns, imprinting as well as chromatin remodeling, thus having a substantial effect in epigenetic signaling. The expression of lncRNAs is regulated in a tissue specific and developmental stage specific manner and their mis-regulation is often associated with tumorigenesis. Henceforth, this chapter focuses mainly on the role(s) of ncRNAs in transcriptional and post-transcriptional regulation and their relevance in cancers.

**Keywords:** lncRNAs, miRNAs, DNA methylation, epigenetic signaling, transcriptional regulation, cancer

#### **1. Introduction**

#### **1.1. The incredible RNA molecules**

According to "RNA world hypothesis", early life was started with RNA molecules. Later with time, storage of information evolved to more stable DNA and RNA which emerged as a

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

messenger of stored information thereby completing the central dogma of life. Though 80% of the human genome is transcribed into RNA, majority of RNA lacks protein coding potential and referred as "non-coding RNA" (ncRNA). Further, genome sequencing technologies have revealed that the mammalian transcriptome is much more complex and their transcription is regulated by developmental stages [1]. The continuing discovery of new classes of regulatory ncRNAs suggests that RNA has continued to evolve along with proteins and DNA.

copies of coding genes harboring mutations render lncRNAs non-coding [7]. Many lncRNAs are known to overlap coding genes [8]. A lncRNA might encompass either the entire gene or only a part of it and these lncRNA may originate from either the sense or antisense strand [9, 10]. The lncRNAs were termed based on their mechanism of action, such as intergenic (lincRNA), natural antisense transcripts (NATs), enhancer RNA (eRNA), circular RNA (circRNA), promoter associated long RNA (pRNA), etc. LncRNAs act at different levels of gene expression to exhibit diverse cellular functions. This functional diversity reflects the versatility of ncRNA and its interaction with a large number of substrates in a highly specific manner. Moreover, the expression of ncRNA is dynamic and can be rapidly up-regulated or down-regulated during developmental stages or differentiation without being translated [11]. Henceforth, in this chapter, we will discuss mainly on the gene regulatory roles of lncRNAs and miRNAs in dis-

Roles of Non-Coding RNAs in Transcriptional Regulation http://dx.doi.org/10.5772/intechopen.76125 57

The sncRNAs are extensively studied in the last decade and have been associated with RNA interference (RNAi) pathways, which lead to silencing of specific genes and protection of the cell or genome against viruses, mobile repetitive DNA sequences, retro-elements and trans-

Both the siRNAs and miRNAs are 20–30 nucleotides long and generated from sense and antisense DNA strands, pseudogenes and inverted repeats. These molecules induce mRNA degradation or translational repression, which in turn result in the alteration of gene expression. About 60% of translated protein coding genes are negatively regulated by miRNAs [13]. Some transcripts are regulated by a single miRNA, while others are regulated by more than one miRNAs [14]. In addition to the transcriptional gene regulation, miRNAs play important roles in pivotal biological processes such as cell proliferation, cell differentiation, development, and

The process of miRNA biogenesis is quite characteristic for the ncRNAs subclass. Based on cellular requirement, the primary miRNA transcript (pri-miRNA) is first transcribed from the DNA by RNA polymerase II and characterized by one or many stem-loop hairpins which encompass the functional mature miRNA in their stem. In animals, the first step occurs in nucleus, in which the pri-miRNA upon recognition by two nuclear enzymes, Drosha and DGCR8 is processed into dsRNA molecule containing one or more hairpins of approximately 70 nucleotides long, which are called as precursor miRNAs (pre-miRNAs). Then they are exported to the cytoplasm by the nuclear export protein exportin-5 [19]. In cytoplasm, the pre-miRNA is recognized and processed by the RNase III enzyme, Dicer which removes the hairpin loop resulting in 20–23 nt dsRNA (miRNA-miRNA\*) molecule. In case of siRNAs, the small RNA

tinct cellular functions and developmental regulation.

**2. The small non-coding RNAs (sncRNAs)**

**2.2. miRNA and siRNA biogenesis and mechanism of action**

posons [12].

**2.1. miRNAs and siRNAs**

cell death [15–18].

ncRNAs are divided into two major groups based on an arbitrary threshold of 200 nucleotides (nt) namely short ncRNAs (sncRNA) and long ncRNAs (lncRNAs) (**Figure 1**). sncRNAs include functional RNAs such as t-RNAs, r-RNAs and snRNAs which are involved in transcriptional and translational regulation. In addition to these conventional RNAs, short ncRNAs also include different regulatory RNAs such as microRNAs (miRNAs) [2, 3], small interfering RNAs (siRNAs) and P-element-induced wimpy testis (PIWI) interacting RNAs (piRNAs) [4], all of which regulate gene expression. In contrast to sncRNAs, the lncRNAs are a group of large, heterogeneous ncRNAs of unknown function. Similar to coding RNA transcripts, lncRNAs contains epigenetic marks indicating their ability to express differentially [5] and the presence of introns in lncRNAs emphasizes the existence of splice variants. These lncRNAs exist in both polyadenylated and non-polyadenylated forms and hence are termed "bimorphic" [6]. LncRNAs include many different types of RNA and exhibit a wide range of secondary and tertiary structures compared to the coding transcriptome. Some pseudogenes and

**Figure 1.** Classification of non-coding RNA (ncRNA).

copies of coding genes harboring mutations render lncRNAs non-coding [7]. Many lncRNAs are known to overlap coding genes [8]. A lncRNA might encompass either the entire gene or only a part of it and these lncRNA may originate from either the sense or antisense strand [9, 10]. The lncRNAs were termed based on their mechanism of action, such as intergenic (lincRNA), natural antisense transcripts (NATs), enhancer RNA (eRNA), circular RNA (circRNA), promoter associated long RNA (pRNA), etc. LncRNAs act at different levels of gene expression to exhibit diverse cellular functions. This functional diversity reflects the versatility of ncRNA and its interaction with a large number of substrates in a highly specific manner. Moreover, the expression of ncRNA is dynamic and can be rapidly up-regulated or down-regulated during developmental stages or differentiation without being translated [11]. Henceforth, in this chapter, we will discuss mainly on the gene regulatory roles of lncRNAs and miRNAs in distinct cellular functions and developmental regulation.

## **2. The small non-coding RNAs (sncRNAs)**

The sncRNAs are extensively studied in the last decade and have been associated with RNA interference (RNAi) pathways, which lead to silencing of specific genes and protection of the cell or genome against viruses, mobile repetitive DNA sequences, retro-elements and transposons [12].

### **2.1. miRNAs and siRNAs**

messenger of stored information thereby completing the central dogma of life. Though 80% of the human genome is transcribed into RNA, majority of RNA lacks protein coding potential and referred as "non-coding RNA" (ncRNA). Further, genome sequencing technologies have revealed that the mammalian transcriptome is much more complex and their transcription is regulated by developmental stages [1]. The continuing discovery of new classes of regulatory

ncRNAs are divided into two major groups based on an arbitrary threshold of 200 nucleotides (nt) namely short ncRNAs (sncRNA) and long ncRNAs (lncRNAs) (**Figure 1**). sncRNAs include functional RNAs such as t-RNAs, r-RNAs and snRNAs which are involved in transcriptional and translational regulation. In addition to these conventional RNAs, short ncRNAs also include different regulatory RNAs such as microRNAs (miRNAs) [2, 3], small interfering RNAs (siRNAs) and P-element-induced wimpy testis (PIWI) interacting RNAs (piRNAs) [4], all of which regulate gene expression. In contrast to sncRNAs, the lncRNAs are a group of large, heterogeneous ncRNAs of unknown function. Similar to coding RNA transcripts, lncRNAs contains epigenetic marks indicating their ability to express differentially [5] and the presence of introns in lncRNAs emphasizes the existence of splice variants. These lncRNAs exist in both polyadenylated and non-polyadenylated forms and hence are termed "bimorphic" [6]. LncRNAs include many different types of RNA and exhibit a wide range of secondary and tertiary structures compared to the coding transcriptome. Some pseudogenes and

ncRNAs suggests that RNA has continued to evolve along with proteins and DNA.

56 Transcriptional and Post-transcriptional Regulation

**Figure 1.** Classification of non-coding RNA (ncRNA).

Both the siRNAs and miRNAs are 20–30 nucleotides long and generated from sense and antisense DNA strands, pseudogenes and inverted repeats. These molecules induce mRNA degradation or translational repression, which in turn result in the alteration of gene expression. About 60% of translated protein coding genes are negatively regulated by miRNAs [13]. Some transcripts are regulated by a single miRNA, while others are regulated by more than one miRNAs [14]. In addition to the transcriptional gene regulation, miRNAs play important roles in pivotal biological processes such as cell proliferation, cell differentiation, development, and cell death [15–18].

#### **2.2. miRNA and siRNA biogenesis and mechanism of action**

The process of miRNA biogenesis is quite characteristic for the ncRNAs subclass. Based on cellular requirement, the primary miRNA transcript (pri-miRNA) is first transcribed from the DNA by RNA polymerase II and characterized by one or many stem-loop hairpins which encompass the functional mature miRNA in their stem. In animals, the first step occurs in nucleus, in which the pri-miRNA upon recognition by two nuclear enzymes, Drosha and DGCR8 is processed into dsRNA molecule containing one or more hairpins of approximately 70 nucleotides long, which are called as precursor miRNAs (pre-miRNAs). Then they are exported to the cytoplasm by the nuclear export protein exportin-5 [19]. In cytoplasm, the pre-miRNA is recognized and processed by the RNase III enzyme, Dicer which removes the hairpin loop resulting in 20–23 nt dsRNA (miRNA-miRNA\*) molecule. In case of siRNAs, the small RNA duplex molecules produced by the action of Dicer, creates a RNA duplexes with 2-nt overhangs at their 3′ ends and phosphate groups at their 5′ ends [19]. Only one of the two strands of dsRNA acts as a guide strand and directs gene-silencing while, the other strand incorporates into the RNA-induced silencing complex (RISC) containing the Argonaute proteins (Ago1/2) and the GW182, where the anti-guide or passenger strand is degraded resulting in 20–23 nt mature miRNA (**Figure 2**). The siRNAs are recognized by Argonaute protein 2 (Ago2) [18, 20], and the selection of the different Ago proteins are based on the small interfering RNA duplex structure. Generally, siRNAs that are perfect duplexes in terms of base pairing are loaded into Ago2, whereas duplexes presenting mismatches as in the case of miRNAs, are driven by Argonaute 1 (Ago1) [21, 22]. When the complementarity between the miRNA bound to Ago1 and the target m-RNA is high, miRNA tailing and 3′–5′ trimming occurs. The discrimination between Ago1 and Ago2 depends on the action of Hen1; an enzyme that adds the 2′-*O*-methyl group at the 3′ ends of small RNAs bound to Ago2, but not those bound to Ago1 [23]. This methyl group is known to block tailing and trimming of the miRNA. The RISC complex then targets the mRNA transcript based on sequence complementarity between the

miRNA sequence and nucleotides in the 3′ untranslated regions (3′ UTR) of the target mRNAs [24]. The binding of the RISC complex to its target leads to direct Ago-mediated cleavage of the target and causes mRNA degradation if the homology between miRNA and its target mRNA is extensive or to deadenylation followed by translation prevention if the homology between the miRNA and its target is less extensive [20, 25]. Efficient targeting requires continuous base pairing of the miRNA seed region (which is a stretch of 6–8 nucleotides of the mature miRNA) with its target mRNA [25, 26]. Unlike miRNA, siRNA base pairs perfectly and induce mRNA cleavage only in a single specific target. Initially, it has been showed that miRNAs mainly target the 3′ UTRs of mRNAs [20], but recently, it was found that miRNA target sites also been located in the 5′ UTRs and even in coding regions of some of the target mRNAs [20, 27]. For

Roles of Non-Coding RNAs in Transcriptional Regulation http://dx.doi.org/10.5772/intechopen.76125 59

miRNAs have been shown to be involved in several human diseases including cancer, neurodegenerative, cardiovascular and autoimmune diseases [14]. Differential expression of specific miRNA will result in the up-regulation or down-regulation of their targets leading to the

**i.** Altered functions of the enzymes involved in the miRNA biogenesis pathway. For exam-

**ii.** Transcriptional repression of miRNAs by promoter hypermethylation [28]. For example, the miR-200 family is involved in the control of the epithelial-mesenchymal transition

**iii.** Genetic alterations in miRNA genes or in their regulatory motifs which can have deleterious consequences [29]. The deletion of chromosome 13q14 in chronic lymphocytic leukemia (CLL) patients is the best studied example in which the deleted area contains the miR-15a and miR-16-1 genes that target the anti-apoptotic/pro-survival gene BCL-2 (B-cell lymphoma 2) and thus deletion of this region contributes to the greater survival

LncRNAs are defined as a heterogeneous group of transcripts that are >200 nucleotides (nt) in length. These lncRNAs do not exhibit coding potential [30–32] and are transcribed from DNA. These lncRNAs can be intergenic, exonic, in enhancer regions or in the regions distal to protein-coding genes [11, 33]. Like mRNAs, lncRNAs are transcribed by RNA polymerase II (RNA PolII) and undergo post-transcriptional processing such as alternative splicing, 5′ capping, polyadenylation and RNA editing and also carry single nucleotide polymorphisms

In human diseases, expression of miRNAs could be differentially regulated by:

ple, DiGeorge syndrome results due to haploinsufficiency of DGCR8 [18].

example, mir-148 targets on the coding regions of DNMT3B.

**2.3. Role of miRNA in cancer and diseases**

deregulation of cellular pathways.

(EMT) [18].

(SNPs) [31, 34].

of cancerous cells [18].

**3. The long non-coding RNAs (lncRNAs)**

**Figure 2.** Biogenesis of miRNA and its mechanism of action (modified from Hrdlickova B *et al*. [18]).

miRNA sequence and nucleotides in the 3′ untranslated regions (3′ UTR) of the target mRNAs [24]. The binding of the RISC complex to its target leads to direct Ago-mediated cleavage of the target and causes mRNA degradation if the homology between miRNA and its target mRNA is extensive or to deadenylation followed by translation prevention if the homology between the miRNA and its target is less extensive [20, 25]. Efficient targeting requires continuous base pairing of the miRNA seed region (which is a stretch of 6–8 nucleotides of the mature miRNA) with its target mRNA [25, 26]. Unlike miRNA, siRNA base pairs perfectly and induce mRNA cleavage only in a single specific target. Initially, it has been showed that miRNAs mainly target the 3′ UTRs of mRNAs [20], but recently, it was found that miRNA target sites also been located in the 5′ UTRs and even in coding regions of some of the target mRNAs [20, 27]. For example, mir-148 targets on the coding regions of DNMT3B.

#### **2.3. Role of miRNA in cancer and diseases**

duplex molecules produced by the action of Dicer, creates a RNA duplexes with 2-nt overhangs at their 3′ ends and phosphate groups at their 5′ ends [19]. Only one of the two strands of dsRNA acts as a guide strand and directs gene-silencing while, the other strand incorporates into the RNA-induced silencing complex (RISC) containing the Argonaute proteins (Ago1/2) and the GW182, where the anti-guide or passenger strand is degraded resulting in 20–23 nt mature miRNA (**Figure 2**). The siRNAs are recognized by Argonaute protein 2 (Ago2) [18, 20], and the selection of the different Ago proteins are based on the small interfering RNA duplex structure. Generally, siRNAs that are perfect duplexes in terms of base pairing are loaded into Ago2, whereas duplexes presenting mismatches as in the case of miRNAs, are driven by Argonaute 1 (Ago1) [21, 22]. When the complementarity between the miRNA bound to Ago1 and the target m-RNA is high, miRNA tailing and 3′–5′ trimming occurs. The discrimination between Ago1 and Ago2 depends on the action of Hen1; an enzyme that adds the 2′-*O*-methyl group at the 3′ ends of small RNAs bound to Ago2, but not those bound to Ago1 [23]. This methyl group is known to block tailing and trimming of the miRNA. The RISC complex then targets the mRNA transcript based on sequence complementarity between the

58 Transcriptional and Post-transcriptional Regulation

**Figure 2.** Biogenesis of miRNA and its mechanism of action (modified from Hrdlickova B *et al*. [18]).

miRNAs have been shown to be involved in several human diseases including cancer, neurodegenerative, cardiovascular and autoimmune diseases [14]. Differential expression of specific miRNA will result in the up-regulation or down-regulation of their targets leading to the deregulation of cellular pathways.

In human diseases, expression of miRNAs could be differentially regulated by:


## **3. The long non-coding RNAs (lncRNAs)**

LncRNAs are defined as a heterogeneous group of transcripts that are >200 nucleotides (nt) in length. These lncRNAs do not exhibit coding potential [30–32] and are transcribed from DNA. These lncRNAs can be intergenic, exonic, in enhancer regions or in the regions distal to protein-coding genes [11, 33]. Like mRNAs, lncRNAs are transcribed by RNA polymerase II (RNA PolII) and undergo post-transcriptional processing such as alternative splicing, 5′ capping, polyadenylation and RNA editing and also carry single nucleotide polymorphisms (SNPs) [31, 34].

In comparison to protein coding RNAs, lncRNAs have few, but longer exons [30, 35]. Other characteristics of lncRNAs include: (i) well conserved lncRNA promoter regions between vertebrates; (ii) unique promoters, DNA-binding motifs and preferred transcription factors (TFs), (iii) less conserved lncRNA exons between species and (iv) tissue specific expression profiles [5, 31, 36–38]. Compared with protein coding genes, only 11–29% of lncRNAs are ubiquitously expressed in all tissues and they are expressed at very minimum levels [31, 39]. Computational analysis of RNA-Seq data has suggested that lncRNA transcription is independent and influence the transcription of neighboring protein coding genes [31, 38]. The origin of lncRNAs is still under debate. A recent study [40], has reported that more than two-thirds of mature lncRNA transcripts contain transposable elements (TEs). This observation has led to the postulation that the majority of lncRNAs might have arisen via insertion of TEs [41].

#### **3.1. Classification of lncRNAs**

LncRNAs have been classified based on their: (i) genomic location, (ii) mechanism of action, and (iii) effects on DNA sequences.

#### *3.1.1. Classification of lncRNAs based on genomic location*

LncRNAs could be classified into four broad categories based on their relative position to the nearest protein coding genes (**Figure 3**). The first class is the "long intergenic non-coding RNAs" (lincRNAs) which is the largest group of lncRNAs and these genes do not overlap or lie in close proximity to protein coding genes [5, 42]. The second most prevalent class of lncRNA is the "antisense lncRNA" that is transcribed from the antisense strand and are overlapping. Based on their overlap, the antisense lncRNAs are subdivided into two:(i) "intronic antisense lncRNAs" where the lncRNA transcript falls completely within the boundaries of an opposing intron, and (ii) "natural antisense transcripts" (NATs) which partially overlaps around the promoter or at the terminator site of the coding gene [43, 44]. The third class of lncRNAs comprises the "sense lncRNA" transcripts which can be "sense intronic or "sense overlapping." Such transcripts are located on the same strand and transcribed in the same direction as a protein coding gene. The fourth class of lncRNAs is the "bidirectional lncRNAs" or "divergent lncRNAs." These transcripts are located on the antisense strand and have their transcription start site (TSS) close to the TSS of the protein-coding gene, but are transcribed in the opposite direction [45–47].

Some of the examples of lncRNAs displaying the signaling archetype are lncRNAs involved in embryonic development (HOTAIR and HOTTIP), DNA damage response (lincRNA-p21 and PANDA), stress responses (COLDAIR and COOLAIR), etc. [18]. The second category is the "decoy archetype" where the lncRNAs act as decoys that bind to and interfere with the function of other RNAs or proteins. They act by competing with their sequences or structures for binding and are considered to be negative regulators (**Figure 4B**). For example, PANDA binds to the transcription factor NF-YA and prevents the activation of NF-YA induced proapoptotic targets [18]. The "guide archetype" is the third class, in which the lncRNAs binds to specific proteins and transport them to the specific targets. The interaction may be direct (between lncRNA-protein complex and the DNA) or indirect (between lncRNA-protein and protein-DNA complexes) (**Figure 4C**). These lncRNAs may interact as activators or repressors with neighboring (cis-acting) or distant (trans-acting) genes. Examples of lncRNAs employing this mechanism are HOTAIR, lincRNAp21, Xist, COLDAIR and Jpx (just proximal to XIST). The fourth archetype is "scaffold archetype" (**Figure 4D**), where the lncRNAs act by bringing the bound proteins into a complex or in spatial proximity. Examples of this lncRNAs are ANRIL (antisense ncRNA in the INK4 locus) which functions as a scaffold for the chromatin remodeling complexes PRC1 and PRC2, HOTAIR (scaffold for PRC2 binding it to the LSD1 complex) and TERC (telomerase RNA component) that scaffolds the telomer-

**Figure 3.** Classification of lncRNAs based on position relative to the nearest protein coding gene (modified from

Roles of Non-Coding RNAs in Transcriptional Regulation http://dx.doi.org/10.5772/intechopen.76125 61

ase complex [18].

Hrdlickova B *et al*. [18]).

#### *3.1.2. Classification of lncRNAs based on their mechanism of action*

LncRNAs can interact with DNA, RNA as well as proteins. LncRNAs have been implicated mainly in post-transcriptional gene regulation by controlling processes like protein synthesis, RNA sequestration, RNA transport and have been shown to control transcriptional gene silencing via epigenetic regulation and chromatin remodeling [48, 49]. LncRNAs are divided into four archetypes based on their molecular mechanism (**Figure 4**) [18]. LncRNAs that belongs to the "signaling archetype" acts as a molecular signal for a particular biological condition and may activate or silence the genes depending on the stimulus (**Figure 4A**).

In comparison to protein coding RNAs, lncRNAs have few, but longer exons [30, 35]. Other characteristics of lncRNAs include: (i) well conserved lncRNA promoter regions between vertebrates; (ii) unique promoters, DNA-binding motifs and preferred transcription factors (TFs), (iii) less conserved lncRNA exons between species and (iv) tissue specific expression profiles [5, 31, 36–38]. Compared with protein coding genes, only 11–29% of lncRNAs are ubiquitously expressed in all tissues and they are expressed at very minimum levels [31, 39]. Computational analysis of RNA-Seq data has suggested that lncRNA transcription is independent and influence the transcription of neighboring protein coding genes [31, 38]. The origin of lncRNAs is still under debate. A recent study [40], has reported that more than two-thirds of mature lncRNA transcripts contain transposable elements (TEs). This observation has led to the postulation that the majority of lncRNAs

LncRNAs have been classified based on their: (i) genomic location, (ii) mechanism of action,

LncRNAs could be classified into four broad categories based on their relative position to the nearest protein coding genes (**Figure 3**). The first class is the "long intergenic non-coding RNAs" (lincRNAs) which is the largest group of lncRNAs and these genes do not overlap or lie in close proximity to protein coding genes [5, 42]. The second most prevalent class of lncRNA is the "antisense lncRNA" that is transcribed from the antisense strand and are overlapping. Based on their overlap, the antisense lncRNAs are subdivided into two:(i) "intronic antisense lncRNAs" where the lncRNA transcript falls completely within the boundaries of an opposing intron, and (ii) "natural antisense transcripts" (NATs) which partially overlaps around the promoter or at the terminator site of the coding gene [43, 44]. The third class of lncRNAs comprises the "sense lncRNA" transcripts which can be "sense intronic or "sense overlapping." Such transcripts are located on the same strand and transcribed in the same direction as a protein coding gene. The fourth class of lncRNAs is the "bidirectional lncRNAs" or "divergent lncRNAs." These transcripts are located on the antisense strand and have their transcription start site (TSS) close to the TSS of the protein-coding gene, but are transcribed in

LncRNAs can interact with DNA, RNA as well as proteins. LncRNAs have been implicated mainly in post-transcriptional gene regulation by controlling processes like protein synthesis, RNA sequestration, RNA transport and have been shown to control transcriptional gene silencing via epigenetic regulation and chromatin remodeling [48, 49]. LncRNAs are divided into four archetypes based on their molecular mechanism (**Figure 4**) [18]. LncRNAs that belongs to the "signaling archetype" acts as a molecular signal for a particular biological condition and may activate or silence the genes depending on the stimulus (**Figure 4A**).

might have arisen via insertion of TEs [41].

*3.1.1. Classification of lncRNAs based on genomic location*

*3.1.2. Classification of lncRNAs based on their mechanism of action*

**3.1. Classification of lncRNAs**

the opposite direction [45–47].

and (iii) effects on DNA sequences.

60 Transcriptional and Post-transcriptional Regulation

**Figure 3.** Classification of lncRNAs based on position relative to the nearest protein coding gene (modified from Hrdlickova B *et al*. [18]).

Some of the examples of lncRNAs displaying the signaling archetype are lncRNAs involved in embryonic development (HOTAIR and HOTTIP), DNA damage response (lincRNA-p21 and PANDA), stress responses (COLDAIR and COOLAIR), etc. [18]. The second category is the "decoy archetype" where the lncRNAs act as decoys that bind to and interfere with the function of other RNAs or proteins. They act by competing with their sequences or structures for binding and are considered to be negative regulators (**Figure 4B**). For example, PANDA binds to the transcription factor NF-YA and prevents the activation of NF-YA induced proapoptotic targets [18]. The "guide archetype" is the third class, in which the lncRNAs binds to specific proteins and transport them to the specific targets. The interaction may be direct (between lncRNA-protein complex and the DNA) or indirect (between lncRNA-protein and protein-DNA complexes) (**Figure 4C**). These lncRNAs may interact as activators or repressors with neighboring (cis-acting) or distant (trans-acting) genes. Examples of lncRNAs employing this mechanism are HOTAIR, lincRNAp21, Xist, COLDAIR and Jpx (just proximal to XIST). The fourth archetype is "scaffold archetype" (**Figure 4D**), where the lncRNAs act by bringing the bound proteins into a complex or in spatial proximity. Examples of this lncRNAs are ANRIL (antisense ncRNA in the INK4 locus) which functions as a scaffold for the chromatin remodeling complexes PRC1 and PRC2, HOTAIR (scaffold for PRC2 binding it to the LSD1 complex) and TERC (telomerase RNA component) that scaffolds the telomerase complex [18].

regulation, translation, protein trafficking and cellular signaling [33, 34]. Growing number of evidences implicate lncRNAs in transcriptional gene regulation, thereby suggesting a significant role(s) for lncRNAs in such tightly regulated process [52, 53]. The mechanisms of transcrip-

Roles of Non-Coding RNAs in Transcriptional Regulation http://dx.doi.org/10.5772/intechopen.76125 63

Regulation of transcription is considered to be an interplay of transcription factors (TFs) and chromatin modifying factors at the gene promoters. LncRNAs modulate gene expression by specifically associating with other molecules; DNA, RNA and protein, either at the promoters or at the enhancers of their target genes. LncRNAs regulate transcription by various mecha-

Enhancer RNAs (eRNAs) are a category of lncRNAs derived from enhancer regions of genes, which interact with DNA to upregulate gene transcription through two possible mechanisms such as enhancer-promoter looping and tracking of transcriptional machinery [54]. While studying the enhancers activated by calcium signaling in mouse neurons, Kim et al. for the first time, identified a eRNA of about 2 kb transcribed bidirectionally from active enhancers. The expression of this eRNA correlated with the activity of the enhancer region [55, 56], which suggests that eRNAs contribute to enhancer function and influence the transcription

Activating ncRNAs are a class of lncRNAs which are transcribed from independent loci, but not from enhancers and have a transcriptional activation function [57, 58]. Activating ncRNAs specifically activate the transcription of neighboring coding genes in an RNA-dependent fashion, and require the activity of the coding gene promoter [58]. These activating ncRNAs are functionally similar to eRNAs. However, in contrast to eRNAs, activating ncRNAs are spliced, polyadenylated stable transcripts. Gene activation mediated by the activating ncRNAs requires a change in chromosomal conformation to bring the activating ncRNAs locus close to the promoter of its target gene [59]. A number of activating ncRNAs have been shown to be associated with the mediator complex which is involved in bridging promoters with enhancers; and depletion of this complex inhibits looping between the activating ncRNAs locus and its target gene. Thus, eRNA and activating ncRNAs function by interacting with the same set of molecules, forming a scaffold for a protein complex that bridges the enhancer-like element

As discussed earlier in this chapter, lncRNAs mediate epigenetic changes by DNA methylation, histone modification and by recruiting chromatin remodeling complexes to specific genomic loci mainly to the promoter regions and causes repression or activation of the target genes. It

tional and post-transcriptional regulation by lncRNAs is discussed below.

**4.1. Transcriptional regulation**

nisms and some are shown below.

*4.1.1. Enhancer RNAs*

*4.1.2. Activating ncRNAs*

and the promoter of a coding gene (**Figure 5**) [60].

*4.1.3. Transcriptional regulation by recruitment of chromatin modifiers*

of genes.

**Figure 4.** Classification of lncRNAs based on the mechanism of action.

#### *3.1.3. Classification of lncRNAs based on their effects on DNA sequence*

LncRNAs could be divided into "cis-acting" and "trans-acting" based on the effects exerted on DNA sequences. The effects of cis-acting lncRNAs are restricted to genes in close genomic proximity (usually the genes in the chromosome from which they are transcribed from), whereas trans-acting lncRNAs affect distant genes (the genes on other chromosomes) [50]. The action of both cis and trans lncRNAs is locus specific and in both cases, the lncRNA binds epigenetic modifiers through a specific sequence or structure and targets them to promoter regions to regulate the expression of respective genes. For example, HOTTIP and HOTAIR lncRNAs [51]. The major example of general cis-regulation is induction of X inactivation by the Xist lncRNA in female mammals. Xist is expressed from one of the two X chromosomes and induces silencing of the whole chromosome [50]. Example of trans-regulation is the B2 lncRNA that binds to RNA PolII and inhibits phosphorylation of its carboxy-terminal domain (CTD), thus affecting RNA polymerase reaction [50].

## **4. Gene regulation by lncRNAs**

LncRNAs have diverse regulatory functions and might regulate gene expression by modulating chromatin remodeling, cis and trans gene expression, gene transcription, post-transcriptional regulation, translation, protein trafficking and cellular signaling [33, 34]. Growing number of evidences implicate lncRNAs in transcriptional gene regulation, thereby suggesting a significant role(s) for lncRNAs in such tightly regulated process [52, 53]. The mechanisms of transcriptional and post-transcriptional regulation by lncRNAs is discussed below.

#### **4.1. Transcriptional regulation**

Regulation of transcription is considered to be an interplay of transcription factors (TFs) and chromatin modifying factors at the gene promoters. LncRNAs modulate gene expression by specifically associating with other molecules; DNA, RNA and protein, either at the promoters or at the enhancers of their target genes. LncRNAs regulate transcription by various mechanisms and some are shown below.

#### *4.1.1. Enhancer RNAs*

Enhancer RNAs (eRNAs) are a category of lncRNAs derived from enhancer regions of genes, which interact with DNA to upregulate gene transcription through two possible mechanisms such as enhancer-promoter looping and tracking of transcriptional machinery [54]. While studying the enhancers activated by calcium signaling in mouse neurons, Kim et al. for the first time, identified a eRNA of about 2 kb transcribed bidirectionally from active enhancers. The expression of this eRNA correlated with the activity of the enhancer region [55, 56], which suggests that eRNAs contribute to enhancer function and influence the transcription of genes.

#### *4.1.2. Activating ncRNAs*

*3.1.3. Classification of lncRNAs based on their effects on DNA sequence*

**Figure 4.** Classification of lncRNAs based on the mechanism of action.

62 Transcriptional and Post-transcriptional Regulation

(CTD), thus affecting RNA polymerase reaction [50].

**4. Gene regulation by lncRNAs**

LncRNAs could be divided into "cis-acting" and "trans-acting" based on the effects exerted on DNA sequences. The effects of cis-acting lncRNAs are restricted to genes in close genomic proximity (usually the genes in the chromosome from which they are transcribed from), whereas trans-acting lncRNAs affect distant genes (the genes on other chromosomes) [50]. The action of both cis and trans lncRNAs is locus specific and in both cases, the lncRNA binds epigenetic modifiers through a specific sequence or structure and targets them to promoter regions to regulate the expression of respective genes. For example, HOTTIP and HOTAIR lncRNAs [51]. The major example of general cis-regulation is induction of X inactivation by the Xist lncRNA in female mammals. Xist is expressed from one of the two X chromosomes and induces silencing of the whole chromosome [50]. Example of trans-regulation is the B2 lncRNA that binds to RNA PolII and inhibits phosphorylation of its carboxy-terminal domain

LncRNAs have diverse regulatory functions and might regulate gene expression by modulating chromatin remodeling, cis and trans gene expression, gene transcription, post-transcriptional Activating ncRNAs are a class of lncRNAs which are transcribed from independent loci, but not from enhancers and have a transcriptional activation function [57, 58]. Activating ncRNAs specifically activate the transcription of neighboring coding genes in an RNA-dependent fashion, and require the activity of the coding gene promoter [58]. These activating ncRNAs are functionally similar to eRNAs. However, in contrast to eRNAs, activating ncRNAs are spliced, polyadenylated stable transcripts. Gene activation mediated by the activating ncRNAs requires a change in chromosomal conformation to bring the activating ncRNAs locus close to the promoter of its target gene [59]. A number of activating ncRNAs have been shown to be associated with the mediator complex which is involved in bridging promoters with enhancers; and depletion of this complex inhibits looping between the activating ncRNAs locus and its target gene. Thus, eRNA and activating ncRNAs function by interacting with the same set of molecules, forming a scaffold for a protein complex that bridges the enhancer-like element and the promoter of a coding gene (**Figure 5**) [60].

#### *4.1.3. Transcriptional regulation by recruitment of chromatin modifiers*

As discussed earlier in this chapter, lncRNAs mediate epigenetic changes by DNA methylation, histone modification and by recruiting chromatin remodeling complexes to specific genomic loci mainly to the promoter regions and causes repression or activation of the target genes. It

*4.2.1. LncRNA as a source of miRNA*

*4.2.2. LncRNA as a negative regulator of miRNA*

from Dykes IM *et al*. [66]).

Most pri-miRNAs are generally greater than 1 kb in length [67]; and therefore may be regarded as a form of lncRNA. There are two major sources of pri-miRNAs in the genome: (i) pri-miR-NAs that are embedded within another gene and whose expression is usually but not always linked to the expression of the parent transcript, and (ii) pri-miRNAs that are transcribed independently from miRNA genes which contain promoters that regulate their transcription mainly by RNA polymerase II (RNA PolII) in a manner similar to mRNA [66]. Approximately 50% of miRNAs are produced from non-coding transcripts [68]; however, with miRNAs embedded in coding genes many miRNAs are also located within introns of non-coding genes (**Figure 6**) [66]. Such a genomic organization suggests that the host lncRNA does not simply act as a pri-miRNA but may have other additional roles encoded by the exons. For example, DLEU2 is the host gene of the tumor suppressor miRNA, miR-15a/16.1 cluster located within its third intron [66].

Roles of Non-Coding RNAs in Transcriptional Regulation http://dx.doi.org/10.5772/intechopen.76125 65

miRNAs are known to act as negative regulators of gene expression. Transcripts are targeted through binding of a short 6–8 nt seed sequence within the miRNA to a miRNA response element (MRE) in the 3′ UTR regions of targets. Computational predictions based on miRNA seed sequences found that many lncRNAs contain miRNA binding sites. This raises an interesting possibility that many lncRNAs function to regulate gene expression by sequestering miRNAs, thus limiting their concentration within the cell and thereby reducing the pool of available miRNA in the cell. In this way, the lncRNA acts as a negative regulator of miRNA function and thereby a positive regulator of gene expression. This is known as the "competing endogenous RNA (ceRNA)" hypothesis (**Figure 7**) [69, 70]. For example, the intergenic lincRNA-ROR, which inhibits miR-145 in pluripotent embryonic stem cells [66]. Competitive endogenous RNAs (ceRNAs) are lncRNAs that sequester miRNAs and inhibit miRNA functions and have two structurally distinct forms such as linear and circular. Non-circular or linear lncRNAs are single-stranded molecules that bind to miRNAs and regulate gene expression by promoting it to degradation [71]. Circular RNAs (circRNAs) are a type of ring-forming lncRNA that form

**Figure 6.** LncRNA as a source of miRNA. LncRNA genes contain embedded miRNA sequences (red hexagonal boxes) which may be located within an exon (orange box) or an intron (line) or occur in clusters within the genome. Though the sources are different, the pathways converge at the level of pre-miRNA structure which produce miRNA (modified

**Figure 5.** Models of transcriptional regulation. (A) Bridging scaffold model: lncRNAs (red line) transcribed from enhancer-like non-coding genes are required to recruit the mediator complex. (B) Tethered scaffold model: lncRNA (red line) recognizes specific DNA motifs and recruits histone modifying enzymes.

was found that the lncRNA might serve two functions. (i) lncRNAs act as a bridging scaffold and binds to a protein or protein complex to facilitate chromatin conformational changes [61]. (ii) lncRNAs act as tethered scaffold that targets chromatin modifying enzymes to specific DNA motifs (**Figure 5**). For example, the lncRNA HOTAIR (Hox transcript antisense RNA) acts as an epigenetic-protein scaffold and possess multiple binding domains for distinct proteins. At the 3′ end, HOTAIR contributes to the demethylation of H3K4 by interacting with lysine-specific histone demethylase 1A (LSD1), restrictive element 1-silencing transcription factor (REST), and REST corepressor1. At the 5′ end, *HOTAIR* originated from the *HOXC* locus and causes transcriptional gene silencing across 40 kb of the *HOXD* locus in *trans* by inducing a repressive chromatin state, by recruitment of the Polycomb chromatin remodeling complex PRC2 and reinforcing H3K27 methylation [34, 62].

#### *4.1.4. Genomic imprinting and X-chromosome inactivation*

Genomic imprinting is the phenomenon of epigenetic silencing of an allele inherited from either of the parents [63]. Imprinting Control Regions (ICRs) are short stretches of DNA that play a critical role in imprinting of multiple genes [64]. Interestingly, it has been observed that the imprinted regions show significant association with ncRNAs, which mediate the silencing by diverse mechanisms like chromatin remodeling and enhancer competition [65]. X chromosome inactivation is a process mediated by the long ncRNA- *Xist,* in which one copy of the X chromosome in females is inactivated. From the *Xist* locus, a small internal non-coding transcript *RepA* recruits PRC2 to silence one X chromosome [61]; whereas PRC2 is formed from the remaining active X chromosome by the antisense transcript *Tsix*. However, an alternative mechanism is described by another study in which *Xist* and *Tsix* anneal to form an RNA duplex that is processed by Dicer to generate small interfering RNAs (siRNAs) which are required for the repressive chromatin modifications on the inactive X chromosome [1].

#### **4.2. Post-transcriptional regulation**

At post-transcriptional level, lncRNAs regulate by acting as competing endogenous RNAs that regulate microRNA levels which in turn modulate mRNA levels by altering mRNA stability, mRNA decay, and translation [66].

#### *4.2.1. LncRNA as a source of miRNA*

was found that the lncRNA might serve two functions. (i) lncRNAs act as a bridging scaffold and binds to a protein or protein complex to facilitate chromatin conformational changes [61]. (ii) lncRNAs act as tethered scaffold that targets chromatin modifying enzymes to specific DNA motifs (**Figure 5**). For example, the lncRNA HOTAIR (Hox transcript antisense RNA) acts as an epigenetic-protein scaffold and possess multiple binding domains for distinct proteins. At the 3′ end, HOTAIR contributes to the demethylation of H3K4 by interacting with lysine-specific histone demethylase 1A (LSD1), restrictive element 1-silencing transcription factor (REST), and REST corepressor1. At the 5′ end, *HOTAIR* originated from the *HOXC* locus and causes transcriptional gene silencing across 40 kb of the *HOXD* locus in *trans* by inducing a repressive chromatin state, by recruitment of the Polycomb chromatin remodeling complex PRC2 and

**Figure 5.** Models of transcriptional regulation. (A) Bridging scaffold model: lncRNAs (red line) transcribed from enhancer-like non-coding genes are required to recruit the mediator complex. (B) Tethered scaffold model: lncRNA (red

Genomic imprinting is the phenomenon of epigenetic silencing of an allele inherited from either of the parents [63]. Imprinting Control Regions (ICRs) are short stretches of DNA that play a critical role in imprinting of multiple genes [64]. Interestingly, it has been observed that the imprinted regions show significant association with ncRNAs, which mediate the silencing by diverse mechanisms like chromatin remodeling and enhancer competition [65]. X chromosome inactivation is a process mediated by the long ncRNA- *Xist,* in which one copy of the X chromosome in females is inactivated. From the *Xist* locus, a small internal non-coding transcript *RepA* recruits PRC2 to silence one X chromosome [61]; whereas PRC2 is formed from the remaining active X chromosome by the antisense transcript *Tsix*. However, an alternative mechanism is described by another study in which *Xist* and *Tsix* anneal to form an RNA duplex that is processed by Dicer to generate small interfering RNAs (siRNAs) which are required for the repressive chromatin modifications on the inactive X

At post-transcriptional level, lncRNAs regulate by acting as competing endogenous RNAs that regulate microRNA levels which in turn modulate mRNA levels by altering mRNA sta-

reinforcing H3K27 methylation [34, 62].

64 Transcriptional and Post-transcriptional Regulation

chromosome [1].

**4.2. Post-transcriptional regulation**

bility, mRNA decay, and translation [66].

*4.1.4. Genomic imprinting and X-chromosome inactivation*

line) recognizes specific DNA motifs and recruits histone modifying enzymes.

Most pri-miRNAs are generally greater than 1 kb in length [67]; and therefore may be regarded as a form of lncRNA. There are two major sources of pri-miRNAs in the genome: (i) pri-miR-NAs that are embedded within another gene and whose expression is usually but not always linked to the expression of the parent transcript, and (ii) pri-miRNAs that are transcribed independently from miRNA genes which contain promoters that regulate their transcription mainly by RNA polymerase II (RNA PolII) in a manner similar to mRNA [66]. Approximately 50% of miRNAs are produced from non-coding transcripts [68]; however, with miRNAs embedded in coding genes many miRNAs are also located within introns of non-coding genes (**Figure 6**) [66]. Such a genomic organization suggests that the host lncRNA does not simply act as a pri-miRNA but may have other additional roles encoded by the exons. For example, DLEU2 is the host gene of the tumor suppressor miRNA, miR-15a/16.1 cluster located within its third intron [66].

#### *4.2.2. LncRNA as a negative regulator of miRNA*

miRNAs are known to act as negative regulators of gene expression. Transcripts are targeted through binding of a short 6–8 nt seed sequence within the miRNA to a miRNA response element (MRE) in the 3′ UTR regions of targets. Computational predictions based on miRNA seed sequences found that many lncRNAs contain miRNA binding sites. This raises an interesting possibility that many lncRNAs function to regulate gene expression by sequestering miRNAs, thus limiting their concentration within the cell and thereby reducing the pool of available miRNA in the cell. In this way, the lncRNA acts as a negative regulator of miRNA function and thereby a positive regulator of gene expression. This is known as the "competing endogenous RNA (ceRNA)" hypothesis (**Figure 7**) [69, 70]. For example, the intergenic lincRNA-ROR, which inhibits miR-145 in pluripotent embryonic stem cells [66]. Competitive endogenous RNAs (ceRNAs) are lncRNAs that sequester miRNAs and inhibit miRNA functions and have two structurally distinct forms such as linear and circular. Non-circular or linear lncRNAs are single-stranded molecules that bind to miRNAs and regulate gene expression by promoting it to degradation [71]. Circular RNAs (circRNAs) are a type of ring-forming lncRNA that form

**Figure 6.** LncRNA as a source of miRNA. LncRNA genes contain embedded miRNA sequences (red hexagonal boxes) which may be located within an exon (orange box) or an intron (line) or occur in clusters within the genome. Though the sources are different, the pathways converge at the level of pre-miRNA structure which produce miRNA (modified from Dykes IM *et al*. [66]).

by linking the 3′ and 5′ ends with a back splicing covalent bond [72, 73]. In addition, lncRNAs can facilitate the inhibition of mRNA translation or decay by partial base pairing with the 3′ UTR sequences through their Alu elements in Staufen-mediated manner [74]. A non-coding transcript that shares a high degree of homology with a coding gene is likely to share many of its MREs and therefore pseudogenes are considered as good candidates to act as ceRNAs [7, 75, 76]. Example of such lncRNA include a pseudogene homologous to the gene encoding tumor suppressor phosphatase and tensin homolog (PTEN), which contains multiple MREs with in the 3′ UTR shared with the coding gene [76].

**5. Roles of LncRNA in diseases**

**5.2. LncRNAs in cancer and other diseases**

cerebellar ataxia type 8 [96–98].

**6. Conclusion**

Aging is a complex physiological phenomenon with a progressive decline in functional capacities and environmental adaptations. The expression of lncRNAs is known to be affected during aging process and in turn, many lncRNAs govern major senescent pathways and senescenceassociated secretory phenotype [78–80]. In human fibroblasts, senescence-associated lncRNA-SAL-RNA1 delays senescence and reduced levels of this lncRNA enhances senescence traits such as enlarged morphology, increased p53 levels and positive β-galactosidase activity [81]. Another example is the lncRNA MIR31HG, which is upregulated in oncogene-induced senescence, and its knockdown promotes a strong tumor-suppressor p16-dependent senescence

Roles of Non-Coding RNAs in Transcriptional Regulation http://dx.doi.org/10.5772/intechopen.76125 67

Altered lncRNA function is identified as one of the causes for the dysregulation of gene expression which leads to several human diseases including cancer. One such lncRNA is MALAT1 also known as NEAT2, (nuclear-enriched abundant transcript2) which was identified as a predictive biomarker for metastasis development in lung cancer [83, 84]. It acts by inducing the expression of metastasis-associated genes [85]; and recently it was shown that in vitro metastasis of EBC-1 cells (human lung cancer cells) can be inhibited by antisense oligonucleotides directed to MALAT1 [85, 86]. Another example is lncRNA HOTAIR that interacts with PRC2 and alters chromatin to a metastasis-promoting state [87]; and causes cancers such as breast, colon, colorectal, gastrointestinal, pancreatic and liver cancer [88–91]. The lncRNAs αHIF (antisense to hypoxia inducible factor α (HIFα)) and tie-1AS (tyrosine kinase containing immunoglobulin and epidermal growth factor homology domain-1 antisense) are known to induce angiogenesis [42, 92]. PCGEM1 (prostate-specific transcript 1), UCA1 (urothelial cancer associated 1), SPRY4-IT1 (SPRY4 intronic transcript 1) and PANDA are involved in suppressing apoptosis [93–95]. LncRNAs also have roles in other diseases like neurogenetic Angelman syndrome and Beckwith-Wiedemann syndrome (BWS) [96]. LncRNAs have also been associated with cardiovascular diseases and other neurological disorders such as BACE1-AS or BC200 in Alzheimer disease, HAR1 (human accelerated region 1 lncRNA) in Huntington disease and ATXN8OS (Ataxin8 opposite strand lncRNA) in spino-

The highly diverse biological functions of lncRNAs reflect the versatility of RNA molecules in the cell. Studies on different classes of ncRNAs, their biogenesis and functional overlaps suggest their complexity and their ability to operate as an integrated and regulated network. In this chapter, we have highlighted different mechanisms of regulation of gene expression by lncRNAs at transcriptional and post-transcriptional level by their ability to interact with

**5.1. LncRNAs and aging**

phenotype [82].

#### *4.2.3. LncRNA-mediated and miRNA-independent mRNA degradation*

In addition to regulating gene expression through interaction with miRNAs, some lncRNAs directly targets mRNA for degradation. For example, Staufen 1 (STAU1) is a protein that recognizes a specific motif in the 3′ UTR of mRNAs and mediates their degradation by nonsense mediated mRNA decay (NMD) [77]. STAU1 binds to a double-stranded RNA motif within the 3′ UTR of the mRNA encoding ADP-ribosylation factor 1 (ARF1), where it forms a stem loop structure. However, some mRNAs targeted by Staufen-mediated decay, lacks the stem loop structure and contains only a single stranded binding site within the 3′ UTR, e.g., serpin peptidase inhibitor-clade E member1 (SERPINE1). Interestingly, such mRNAs are targeted by a lncRNA carrying a complementary single stranded binding site and imperfect binding of lncRNA to the mRNA create a double-stranded RNA binding motif for STAU1. This class of lncRNAs are called as half STAU1 binding site RNAs [74].

**Figure 7.** The ceRNA hypothesis. miRNA binds to identical MREs (hexagonal) which are usually present in a number of ncRNA species such as pseudogenes, circRNAs and other forms of lncRNAs and independently transcribed mRNA 3'UTRs. All of these RNAs compete for a limited pool of miRNA, thus positively regulating gene expression.

## **5. Roles of LncRNA in diseases**

#### **5.1. LncRNAs and aging**

by linking the 3′ and 5′ ends with a back splicing covalent bond [72, 73]. In addition, lncRNAs can facilitate the inhibition of mRNA translation or decay by partial base pairing with the 3′ UTR sequences through their Alu elements in Staufen-mediated manner [74]. A non-coding transcript that shares a high degree of homology with a coding gene is likely to share many of its MREs and therefore pseudogenes are considered as good candidates to act as ceRNAs [7, 75, 76]. Example of such lncRNA include a pseudogene homologous to the gene encoding tumor suppressor phosphatase and tensin homolog (PTEN), which contains multiple MREs

In addition to regulating gene expression through interaction with miRNAs, some lncRNAs directly targets mRNA for degradation. For example, Staufen 1 (STAU1) is a protein that recognizes a specific motif in the 3′ UTR of mRNAs and mediates their degradation by nonsense mediated mRNA decay (NMD) [77]. STAU1 binds to a double-stranded RNA motif within the 3′ UTR of the mRNA encoding ADP-ribosylation factor 1 (ARF1), where it forms a stem loop structure. However, some mRNAs targeted by Staufen-mediated decay, lacks the stem loop structure and contains only a single stranded binding site within the 3′ UTR, e.g., serpin peptidase inhibitor-clade E member1 (SERPINE1). Interestingly, such mRNAs are targeted by a lncRNA carrying a complementary single stranded binding site and imperfect binding of lncRNA to the mRNA create a double-stranded RNA binding motif for STAU1. This class of

**Figure 7.** The ceRNA hypothesis. miRNA binds to identical MREs (hexagonal) which are usually present in a number of ncRNA species such as pseudogenes, circRNAs and other forms of lncRNAs and independently transcribed mRNA

3'UTRs. All of these RNAs compete for a limited pool of miRNA, thus positively regulating gene expression.

with in the 3′ UTR shared with the coding gene [76].

66 Transcriptional and Post-transcriptional Regulation

*4.2.3. LncRNA-mediated and miRNA-independent mRNA degradation*

lncRNAs are called as half STAU1 binding site RNAs [74].

Aging is a complex physiological phenomenon with a progressive decline in functional capacities and environmental adaptations. The expression of lncRNAs is known to be affected during aging process and in turn, many lncRNAs govern major senescent pathways and senescenceassociated secretory phenotype [78–80]. In human fibroblasts, senescence-associated lncRNA-SAL-RNA1 delays senescence and reduced levels of this lncRNA enhances senescence traits such as enlarged morphology, increased p53 levels and positive β-galactosidase activity [81]. Another example is the lncRNA MIR31HG, which is upregulated in oncogene-induced senescence, and its knockdown promotes a strong tumor-suppressor p16-dependent senescence phenotype [82].

#### **5.2. LncRNAs in cancer and other diseases**

Altered lncRNA function is identified as one of the causes for the dysregulation of gene expression which leads to several human diseases including cancer. One such lncRNA is MALAT1 also known as NEAT2, (nuclear-enriched abundant transcript2) which was identified as a predictive biomarker for metastasis development in lung cancer [83, 84]. It acts by inducing the expression of metastasis-associated genes [85]; and recently it was shown that in vitro metastasis of EBC-1 cells (human lung cancer cells) can be inhibited by antisense oligonucleotides directed to MALAT1 [85, 86]. Another example is lncRNA HOTAIR that interacts with PRC2 and alters chromatin to a metastasis-promoting state [87]; and causes cancers such as breast, colon, colorectal, gastrointestinal, pancreatic and liver cancer [88–91]. The lncRNAs αHIF (antisense to hypoxia inducible factor α (HIFα)) and tie-1AS (tyrosine kinase containing immunoglobulin and epidermal growth factor homology domain-1 antisense) are known to induce angiogenesis [42, 92]. PCGEM1 (prostate-specific transcript 1), UCA1 (urothelial cancer associated 1), SPRY4-IT1 (SPRY4 intronic transcript 1) and PANDA are involved in suppressing apoptosis [93–95]. LncRNAs also have roles in other diseases like neurogenetic Angelman syndrome and Beckwith-Wiedemann syndrome (BWS) [96]. LncRNAs have also been associated with cardiovascular diseases and other neurological disorders such as BACE1-AS or BC200 in Alzheimer disease, HAR1 (human accelerated region 1 lncRNA) in Huntington disease and ATXN8OS (Ataxin8 opposite strand lncRNA) in spinocerebellar ataxia type 8 [96–98].

## **6. Conclusion**

The highly diverse biological functions of lncRNAs reflect the versatility of RNA molecules in the cell. Studies on different classes of ncRNAs, their biogenesis and functional overlaps suggest their complexity and their ability to operate as an integrated and regulated network. In this chapter, we have highlighted different mechanisms of regulation of gene expression by lncRNAs at transcriptional and post-transcriptional level by their ability to interact with enhancers, promoters, chromatin-modifying complexes and miRNAs. Due to environmental exposures, genetic mutations and other causes, deregulation of lncRNAs are associated with various human diseases such as cancer, neurological disorders like Alzheimer's disease, cardiovascular diseases, and autoimmune diseases. This chapter along with recent evidences emphasizes the significance of lncRNA as novel therapeutic targets in aging and aging-related human diseases.

**References**

Jan;**116**(2):281-297

Genetics. 2013 Jun;**9**(6):e1003569

2004 Jan;**32**(16):4812-4820

2008 Oct;**32**(2):232-246

2009 Jan;**457**(7228):413

expression. Frontiers in Genetics. 2015 Feb;**5**:476

[1] Mercer TR, Dinger ME, Mattick JS. Long non-coding RNAs: Insights into functions.

Roles of Non-Coding RNAs in Transcriptional Regulation http://dx.doi.org/10.5772/intechopen.76125 69

[2] Bartel DP. MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell. 2004

[3] Winter J, Jung S, Keller S, Gregory RI, Diederichs S. Many roads to maturity: microRNA biogenesis pathways and their regulation. Nature Cell Biology. 2009 Mar;**11**(3):228

[4] Siomi MC, Sato K, Pezic D, Aravin AA. PIWI-interacting small RNAs: The vanguard of genome defence. Nature Reviews Molecular Cell Biology. 2011 Apr;**12**(4):246

[5] Guttman M, Amit I, Garber M, French C, Lin MF, Feldser D, Huarte M, Zuk O, Carey BW, Cassady JP, Cabili MN. Chromatin signature reveals over a thousand highly con-

[6] Hangauer MJ, Vaughn IW, McManus MT. Pervasive transcription of the human genome produces thousands of previously unidentified long intergenic noncoding RNAs. PLoS

[7] Milligan MJ, Lipovich L. Pseudogene-derived lncRNAs: Emerging regulators of gene

[8] Chen J, Sun M, Kent WJ, Huang X, Xie H, Wang W, Zhou G, Shi RZ, Rowley JD. Over 20% of human transcripts might form sense–antisense pairs. Nucleic Acids Research.

[9] Pandey RR, Mondal T, Mohammad F, Enroth S, Redrup L, Komorowski J, Nagano T, Mancini-DiNardo D, Kanduri C. Kcnq1ot1 antisense noncoding RNA mediates lineagespecific transcriptional silencing through chromatin-level regulation. Molecular Cell.

[10] Pastori C, Peschansky VJ, Barbouth D, Mehta A, Silva JP, Wahlestedt C. Comprehensive analysis of the transcriptional landscape of the human FMR1 gene reveals two new long noncoding RNAs differentially expressed in Fragile X syndrome and Fragile

[11] Geisler S, Coller J. RNA in unexpected places: Long non-coding RNA functions in diverse cellular contexts. Nature Reviews Molecular Cell Biology. 2013 Nov;**14**(11):699

[12] Moazed D. Small RNAs in transcriptional gene silencing and genome defence. Nature.

[13] Lewis BP, Burge CB, Bartel DP. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005 Jan;**120**(1):15-20

X-associated tremor/ataxia syndrome. Human Genetics. 2014 Jan;**133**(1):59-67

served large non-coding RNAs in mammals. Nature. 2009 Mar;**458**(7235):223

Nature Reviews Genetics. 2009 Mar;**10**(3):155

## **7. Future perspectives**

Mounting evidences suggest significant roles of ncRNAs in physiological and pathological processes, which have expanded our basic understanding of gene expression. However, on the other hand, we have also realized the increasing complexity in the structure and organization of genome and gene networks. Recently, our laboratory identified a novel non-coding RNA of DNMT3B variant (DNMT3B9) from leukemic cell lines and the exact roles in hematopoiesis study is underway. This chapter recommends future research on the structural motifs and gene regulatory network of ncRNAs and their stability and degradation process, which we believe will expand the horizons of ncRNAs biology to establish potential diagnostic and therapeutic strategies in this field. Another challenging avenue is to explore the mechanisms underlying the functions of ncRNAs, which still remain elusive. Also, studies on the interplay between various ncRNAs might shed light on the usage of ncRNAs as potential biomarkers for early detection and improve the treatment of various diseases including cancer. With increasing discovery of ncRNAs and advancing technologies, ncRNA based therapies would be an effective health-care strategy.

## **Acknowledgements**

LS and TP thank Pondicherry University for their doctoral research fellowship. SP acknowledges DST-SERB-NPDF (2739) for providing post-doctoral research assistance and CA is a recipient of CSIR-UGC fellowship for doctoral research. Prof. SB thank DST-SERB, INDIA (SB/EMEQ-038/2013) for financial support.

## **Author details**

Loudu Srijyothi, Saravanaraman Ponne, Talukdar Prathama, Cheemala Ashok and Sudhakar Baluchamy\*

\*Address all correspondence to: sudhakar.dbt@pondiuni.edu.in

Department of Biotechnology, Pondicherry University, Puducherry, India

## **References**

enhancers, promoters, chromatin-modifying complexes and miRNAs. Due to environmental exposures, genetic mutations and other causes, deregulation of lncRNAs are associated with various human diseases such as cancer, neurological disorders like Alzheimer's disease, cardiovascular diseases, and autoimmune diseases. This chapter along with recent evidences emphasizes the significance of lncRNA as novel therapeutic targets in aging and aging-related

Mounting evidences suggest significant roles of ncRNAs in physiological and pathological processes, which have expanded our basic understanding of gene expression. However, on the other hand, we have also realized the increasing complexity in the structure and organization of genome and gene networks. Recently, our laboratory identified a novel non-coding RNA of DNMT3B variant (DNMT3B9) from leukemic cell lines and the exact roles in hematopoiesis study is underway. This chapter recommends future research on the structural motifs and gene regulatory network of ncRNAs and their stability and degradation process, which we believe will expand the horizons of ncRNAs biology to establish potential diagnostic and therapeutic strategies in this field. Another challenging avenue is to explore the mechanisms underlying the functions of ncRNAs, which still remain elusive. Also, studies on the interplay between various ncRNAs might shed light on the usage of ncRNAs as potential biomarkers for early detection and improve the treatment of various diseases including cancer. With increasing discovery of ncRNAs and advancing technologies, ncRNA based therapies would

LS and TP thank Pondicherry University for their doctoral research fellowship. SP acknowledges DST-SERB-NPDF (2739) for providing post-doctoral research assistance and CA is a recipient of CSIR-UGC fellowship for doctoral research. Prof. SB thank DST-SERB, INDIA

Loudu Srijyothi, Saravanaraman Ponne, Talukdar Prathama, Cheemala Ashok and

\*Address all correspondence to: sudhakar.dbt@pondiuni.edu.in

Department of Biotechnology, Pondicherry University, Puducherry, India

human diseases.

**7. Future perspectives**

68 Transcriptional and Post-transcriptional Regulation

be an effective health-care strategy.

(SB/EMEQ-038/2013) for financial support.

**Acknowledgements**

**Author details**

Sudhakar Baluchamy\*


[14] Esteller M. Non-coding RNAs in human disease. Nature Reviews Genetics. 2011 Dec;**12**(12):861

genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proceedings of the

Roles of Non-Coding RNAs in Transcriptional Regulation http://dx.doi.org/10.5772/intechopen.76125 71

[30] Harrow J, Frankish A, Gonzalez JM, Tapanari E, Diekhans M, Kokocinski F, Aken BL, Barrell D, Zadissa A, Searle S, Barnes I. Gencode: The reference human genome annota-

[31] Derrien T, Johnson R, Bussotti G, Tanzer A, Djebali S, Tilgner H, Guernec G, Martin D, Merkel A, Knowles DG, Lagarde J. The Gencode v7 catalog of human long noncoding RNAs: Analysis of their gene structure, evolution, and expression. Genome Research.

[32] Guttman M, Russell P, Ingolia NT, Weissman JS, Lander ES. Ribosome profiling provides evidence that large noncoding RNAs do not encode proteins. Cell. 2013 Jul;**154**(1):240-251

[33] Wang KC, Chang HY. Molecular mechanisms of long noncoding RNAs. Molecular Cell.

[34] Karlsson O, Baccarelli AA. Environmental health and long non-coding RNAs. Current

[35] Cabili MN, Trapnell C, Goff L, Koziol M, Tazon-Vega B, Regev A, Rinn JL. Integrative annotation of human large intergenic noncoding RNAs reveals global properties and

[36] Novikova IV, Hennelly SP, Sanbonmatsu KY. Sizing up long non-coding RNAs: Do lncRNAs have secondary and tertiary structure? BioArchitecture. 2012 Nov;**2**(6):189-199

[37] Alam T, Medvedeva YA, Jia H, Brown JB, Lipovich L, Bajic VB. Promoter analysis reveals globally differential regulation of human long non-coding RNA and protein-coding

[38] Popadin K, Gutierrez-Arcelus M, Dermitzakis ET, Antonarakis SE. Genetic and epigenetic regulation of human lincRNA gene expression. The American Journal of Human

[39] Djebali S, Davis CA, Merkel A, Dobin A, Lassmann T, Mortazavi A, Tanzer A, Lagarde J, Lin W, Schlesinger F, Xue C. Landscape of transcription in human cells. Nature. 2012

[40] Kapusta A, Kronenberg Z, Lynch VJ, Zhuo X, Ramsay L, Bourque G, Yandell M, Feschotte C. Transposable elements are major contributors to the origin, diversification, and regulation of vertebrate long noncoding RNAs. PLoS Genetics. 2013 Apr;**9**(4):e1003470

[41] Nekrutenko A, Li WH. Transposable elements are found in a large number of human

[42] Thrash-Bingham CA, Tartof KD. aHIF: A natural antisense transcript overexpressed in human renal cancer and during hypoxia. Journal of the National Cancer Institute. 1999

protein-coding genes. Trends in Genetics. 2001 Nov;**17**(11):619-621

specific subclasses. Genes & Development. 2011 Sep;**25**(18):1915-1927

tion for the Encode project. Genome Research. 2012 Sep;**22**(9):1760-1774

National Academy of Sciences. 2002 Nov;**99**(24):15524-15529

Environmental Health Reports. 2016 Sep;**3**(3):178-187

genes. PLoS One. 2014 Oct;**9**(10):e109443

Genetics. 2013 Dec;**93**(6):1015-1026

Sep;**489**(7414):101

Jan;**91**(2):143-151

2012 Sep;**22**(9):1775-1789

2011 Sep;**43**(6):904-914


genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proceedings of the National Academy of Sciences. 2002 Nov;**99**(24):15524-15529

[30] Harrow J, Frankish A, Gonzalez JM, Tapanari E, Diekhans M, Kokocinski F, Aken BL, Barrell D, Zadissa A, Searle S, Barnes I. Gencode: The reference human genome annotation for the Encode project. Genome Research. 2012 Sep;**22**(9):1760-1774

[14] Esteller M. Non-coding RNAs in human disease. Nature Reviews Genetics. 2011

[15] Jovanovic M, Hengartner MO. miRNAs and apoptosis: RNAs to die for. Oncogene. 2006

[16] Büssing I, Slack FJ, Großhans H. Let-7 microRNAs in development, stem cells and can-

[17] Schickel R, Boyerinas B, Park SM, Peter ME. MicroRNAs: Key players in the immune system, differentiation, tumorigenesis and cell death. Oncogene. 2008 Oct;**27**(45):5959 [18] Hrdlickova B, de Almeida RC, Borek Z, Withoff S. Genetic variation in the non-coding genome: Involvement of micro-RNAs and long non-coding RNAs in disease. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease. 2014 Oct;**1842**(10):1910-1922 [19] Sun W, Julie Li YS, Huang HD, Shyy JY, Chien S. microRNA: A master regulator of cellular processes for bioengineering systems. Annual Review of Biomedical Engineering.

[20] Pasquinelli AE. MicroRNAs and their targets: Recognition, regulation and an emerging

[21] Förstemann K, Horwich MD, Wee L, Tomari Y, Zamore PD. Drosophila microRNAs are sorted into functionally distinct argonaute complexes after production by dicer-1. Cell.

[22] Tomari Y, Du T, Zamore PD. Sorting of Drosophila small silencing RNAs. Cell. 2007

[23] Ameres SL, Horwich MD, Hung JH, Xu J, Ghildiyal M, Weng Z, Zamore PD. Target RNA–directed trimming and tailing of small silencing RNAs. Science. 2010

[24] Krol J, Loedige I, Filipowicz W. The widespread regulation of microRNA biogenesis,

[25] Bartel DP. MicroRNAs: Target recognition and regulatory functions. Cell. 2009

[26] Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, Bettinger JC, Rougvie AE, Horvitz HR, Ruvkun G. The 21-nucleotide let-7 RNA regulates developmental timing in caenorhab-

[27] Wang WX, Wilfred BR, Xie K, Jennings MH, Hu Y, Stromberg AJ, Nelson P. Individual microRNAs (miRNAs) display distinct mRNA targeting "rules". RNA Biology. 2010

[28] Lopez-Serra P, Esteller M. DNA methylation-associated silencing of tumor-suppressor

[29] Calin GA, Dumitru CD, Shimizu M, Bichi R, Zupo S, Noch E, Aldler H, Rattan S, Keating M, Rai K, Rassenti L. Frequent deletions and down-regulation of micro-RNA

reciprocal relationship. Nature Reviews Genetics. 2012 Apr;**13**(4):271

function and decay. Nature Reviews Genetics. 2010 Sep;**11**(9):597

ditis elegans. Nature. 2000 Feb;**403**(6772):901

microRNAs in cancer. Oncogene. 2012 Mar;**31**(13):1609

cer. Trends in Molecular Medicine. 2008 Sep;**14**(9):400-409

Dec;**12**(12):861

70 Transcriptional and Post-transcriptional Regulation

Oct;**25**(46):6176

2010 Aug;**12**:1-27

2007 Jul;**130**(2):287-297

Jun;**328**(5985):1534-1539

Jul;**130**(2):299-308

Jan;**136**(2):215-233

May;**7**(3):373-380


[43] Lapidot M, Pilpel Y. Genome-wide natural antisense transcription: Coupling its regulation to its different regulatory mechanisms. EMBO Reports. 2006 Dec;**7**(12):1216-1222

[58] Yang Y, Su Z, Song X, Liang B, Zeng F, Chang X, Huang D. Enhancer RNA-driven looping enhances the transcription of the long noncoding RNA DHRS4-AS1, a controller of

Roles of Non-Coding RNAs in Transcriptional Regulation http://dx.doi.org/10.5772/intechopen.76125 73

[59] Lai F, Orom UA, Cesaroni M, Beringer M, Taatjes DJ, Blobel GA, Shiekhattar R.Activating RNAs associate with mediator to enhance chromatin architecture and transcription.

[60] Malik S, Roeder RG. The metazoan mediator co-activator complex as an integrative hub for transcriptional regulation. Nature Reviews Genetics. 2010 Nov;**11**(11):761

[61] Tsai MC, Manor O, Wan Y, Mosammaparast N, Wang JK, Lan F, Shi Y, Segal E, Chang HY. Long noncoding RNA as modular scaffold of histone modification complexes.

[62] Luco RF, Pan Q, Tominaga K, Blencowe BJ, Pereira-Smith OM, Misteli T. Regulation of alternative splicing by histone modifications. Science. 2010 Feb;**327**(5968):996-1000 [63] Wood AJ, Oakey RJ. Genomic imprinting in mammals: Emerging themes and estab-

[64] Bartolomei MS. Genomic imprinting: Employing and avoiding epigenetic processes.

[65] Wan LB, Bartolomei MS. Regulation of imprinting in clusters: Noncoding RNAs versus

[66] Dykes IM, Emanueli C. Transcriptional and post-transcriptional gene regulation by long non-coding RNA. Genomics, Proteomics & Bioinformatics. 2017 Jun;**15**(3):177-186 [67] Kim VN, Han J, Siomi MC. Biogenesis of small RNAs in animals. Nature Reviews

[68] Saini HK, Griffiths-Jones S, Enright AJ. Genomic analysis of human microRNA transcripts. Proceedings of the National Academy of Sciences. 2007 Nov;**104**(45):17719-17724

[69] Thomas M, Lieberman J, Lal A. Desperately seeking microRNA targets. Nature Structural

[70] Salmena L, Poliseno L, Tay Y, Kats L, Pandolfi PP. A ceRNA hypothesis: The Rosetta

[71] Dempsey JL, Cui JY. Long non-coding RNAs: A novel paradigm for toxicology.

[72] Ashwal-Fluss R, Meyer M, Pamudurti NR, Ivanov A, Bartok O, Hanan M, Evantal N, Memczak S, Rajewsky N, Kadener S. circRNA biogenesis competes with pre-mRNA

[73] Ebbesen KK, Kjems J, Hansen TB. Circular RNAs: Identification, biogenesis and function. Biochimica et Biophysica Acta (BBA)-Gene Regulatory Mechanisms. 2016 Jan;

Stone of a hidden RNA language? Cell. 2011 Aug;**146**(3):353-358

the DHRS4 gene cluster. Scientific Reports. 2016 Feb;**6**:20961

Nature. 2013 Feb;**494**(7438):497

Science. 2010 Aug;**329**(5992):689-693

lished theories. PLoS Genetics. 2006 Nov;**2**(11):e147

Genes & Development. 2009 Sep;**23**(18):2124-2133

Molecular Cell Biology. 2009 Feb;**10**(2):126

and Molecular Biology. 2010 Oct;**17**(10):1169

Toxicological Sciences. 2016 Nov;**155**(1):3-21

splicing. Molecular Cell. 2014 Oct;**56**(1):55-66

**1859**(1):163-168

insulators. Advances in Genetics. 2008 Jan;**61**:207-223


[58] Yang Y, Su Z, Song X, Liang B, Zeng F, Chang X, Huang D. Enhancer RNA-driven looping enhances the transcription of the long noncoding RNA DHRS4-AS1, a controller of the DHRS4 gene cluster. Scientific Reports. 2016 Feb;**6**:20961

[43] Lapidot M, Pilpel Y. Genome-wide natural antisense transcription: Coupling its regulation to its different regulatory mechanisms. EMBO Reports. 2006 Dec;**7**(12):1216-1222 [44] Faghihi MA, Wahlestedt C. Regulatory roles of natural antisense transcripts. Nature

[45] Chen J, Sun M, Hurst LD, Carmichael GG, Rowley JD. Genome-wide analysis of coordinate expression and evolution of human cis-encoded sense-antisense transcripts. Trends

[46] Khalil AM, Faghihi MA, Modarresi F, Brothers SP, Wahlestedt C. A novel RNA transcript with antiapoptotic function is silenced in fragile X syndrome. PLoS One. 2008

[47] Rapicavoli NA, Poth EM, Zhu H, Blackshaw S. The long noncoding RNA Six3OS acts in trans to regulate retinal development by modulating Six3 activity. Neural Development.

[48] Whitehead J, Pandey GK, Kanduri C. Regulation of the mammalian epigenome by long noncoding RNAs. Biochimica et Biophysica Acta (BBA)-General Subjects. 2009 Sep;

[49] Bernstein E, Allis CD. RNA meets chromatin. Genes & Development. 2005 Jul;**19**(14):

[50] Kornienko AE, Guenzl PM, Barlow DP, Pauler FM. Gene regulation by the act of long

[51] Minks J, Baldry SE, Yang C, Cotton AM, Brown CJ. XIST-induced silencing of flanking genes is achieved by additive action of repeat a monomers in human somatic cells.

[52] Noble D. Physiology is rocking the foundations of evolutionary biology. Experimental

[53] Mattick JS, Taft RJ, Faulkner GJ. A global view of genomic information–moving beyond

[54] Li W, Notani D, Rosenfeld MG. Enhancers as non-coding RNA transcription units: Recent insights and future perspectives. Nature Reviews Genetics. 2016 Apr;**17**(4):207 [55] Kim TK, Hemberg M, Gray JM, Costa AM, Bear DM, Wu J, Harmin DA, Laptewicz M, Barbara-Haley K, Kuersten S, Markenscoff-Papadimitriou E. Widespread transcription

[56] Andersson R, Gebhard C, Miguel-Escalada I, Hoof I, Bornholdt J, Boyd M, Chen Y, Zhao X, Schmidl C, Suzuki T, Ntini E. An atlas of active enhancers across human cell types and

[57] Ørom UA, Derrien T, Beringer M, Gumireddy K, Gardini A, Bussotti G, Lai F, Zytnicki M, Notredame C, Huang Q, Guigo R. Long noncoding RNAs with enhancer-like func-

the gene and the master regulator. Trends in Genetics. 2010 Jan;**26**(1):21-28

at neuronal activity-regulated enhancers. Nature. 2010 May;**465**(7295):182

non-coding RNA transcription. BMC Biology. 2013 Dec;**11**(1):59

Epigenetics & Chromatin. 2013 Dec;**6**(1):23

Physiology. 2013 Aug;**98**(8):1235-1243

tissues. Nature. 2014 Mar;**507**(7493):455

tion in human cells. Cell. 2010 Oct;**143**(1):46-58

Reviews Molecular Cell Biology. 2009 Sep;**10**(9):637

in Genetics. 2005 Jun;**21**(6):326-329

72 Transcriptional and Post-transcriptional Regulation

Jan;**3**(1):e1486

2011 Dec;**6**(1):32

**1790**(9):936-947

1635-1655


[74] Gong C, Maquat LE. LncRNAs transactivate STAU1-mediated mRNA decay by duplexing with 3′ UTRs via Alu elements. Nature. 2011 Feb;**470**(7333):284

non-coding RNA MALAT1 is compatible with life and development. RNA Biology. 2012

Roles of Non-Coding RNAs in Transcriptional Regulation http://dx.doi.org/10.5772/intechopen.76125 75

[88] Kim K, Jutooru I, Chadalapaka G, Johnson G, Frank J, Burghardt R, Kim S, Safe S. HOTAIR is a negative prognostic factor and exhibits pro-oncogenic activity in pancre-

[89] Kogo R, Shimamura T, Mimori K, Kawahara K, Imoto S, Sudo T, Tanaka F, Shibata K, Suzuki A, Komune S, Miyano S. Long non-coding RNA HOTAIR regulates Polycombdependent chromatin modification and is associated with poor prognosis in colorectal

[90] Niinuma T, Suzuki H, Nojima M, Nosho K, Yamamoto H, Takamaru H, Yamamoto E, Maruyama R, Nobuoka T, Miyazaki Y, Nishida T. Upregulation of miR-196a and HOTAIR drive malignant character in gastrointestinal stromal tumors. Cancer Research.

[91] Yang Z, Zhou L, Wu LM, Lai MC, Xie HY, Zhang F, Zheng SS.Overexpression of long noncoding RNA HOTAIR predicts tumor recurrence in hepatocellular carcinoma patients following liver transplantation. Annals of Surgical Oncology. 2011 May;**18**(5):1243-1250

[92] Li K, Blum Y, Verma A, Liu Z, Pramanik K, Leigh NR, Chun CZ, Samant GV, Zhao B, Garnaas MK, Horswill MA. A noncoding antisense RNA in tie-1 locus regulates tie-1

[93] Fu X, Ravindranath L, Tran N, Petrovics G, Srivastava S. Regulation of apoptosis by a prostate-specific and prostate cancer-associated noncoding gene, PCGEM1. DNA and

[94] Tsang WP, Wong TW, Cheung AH, Kwok TT. Induction of drug resistance and transformation in human cancer cells by the noncoding RNA CUDR.RNA. 2007 Jun;**13**(6):890-898

[95] Khaitan D, Dinger ME, Mazar J, Crawford J, Smith MA, Mattick JS, Perera RJ. The melanoma-upregulated long noncoding RNA SPRY4-IT1 modulates apoptosis and invasion.

[96] Batista PJ, Chang HY. Long noncoding RNAs: Cellular address codes in development

[97] Johnson R, Richter N, Jauch R, Gaughwin PM, Zuccato C, Cattaneo E, Stanton LW. Human accelerated region 1 noncoding RNA is repressed by REST in Huntington's

[98] Daughters RS, Tuttle DL, Gao W, Ikeda Y, Moseley ML, Ebner TJ, Swanson MS, Ranum LP. RNA gain-of-function in spinocerebellar ataxia type 8. PLoS Genetics. 2009

Aug;**9**(8):1076-1087

2012 Mar;**72**(5):1126-1136

atic cancer. Oncogene. 2013 Mar;**32**(13):1616

cancers. Cancer Research. 2011 Oct;**71**(20):6320-6326

function in vivo. Blood. 2010 Jan;**115**(1):133-139

Cell Biology. 2006 Mar;**25**(3):135-141

Cancer Research. 2011 Jun;**71**(11):3852-3862

and disease. Cell. 2013 Mar;**152**(6):1298-1307

Aug;**5**(8):e1000600

disease. Physiological Genomics. 2010 Feb;**41**(3):269-274


non-coding RNA MALAT1 is compatible with life and development. RNA Biology. 2012 Aug;**9**(8):1076-1087

[88] Kim K, Jutooru I, Chadalapaka G, Johnson G, Frank J, Burghardt R, Kim S, Safe S. HOTAIR is a negative prognostic factor and exhibits pro-oncogenic activity in pancreatic cancer. Oncogene. 2013 Mar;**32**(13):1616

[74] Gong C, Maquat LE. LncRNAs transactivate STAU1-mediated mRNA decay by duplex-

[75] An Y, Furber KL, Ji S. Pseudogenes regulate parental gene expression via ceRNA net-

[76] Poliseno L, Salmena L, Zhang J, Carver B, Haveman WJ, Pandolfi PP. A coding-independent function of gene and pseudogene mRNAs regulates tumour biology. Nature. 2010

[77] Park E, Maquat LE. Staufen-mediated mRNA decay. Wiley Interdisciplinary Reviews:

[78] Abdelmohsen K, Gorospe M. Noncoding RNA control of cellular senescence. Wiley

[79] Costa MC, Leitão AL, Enguita FJ. Noncoding transcriptional landscape in human aging. In: Long Non-coding RNAs in Human Disease. Cham: Springer; 2015. pp. 177-202 [80] Grammatikakis I, Panda AC, Abdelmohsen K, Gorospe M. Long noncoding RNAs (lncRNAs) and the molecular hallmarks of aging. Aging (Albany NY). 2014 Dec;**6**(12):992

[81] Abdelmohsen K, Panda A, Kang MJ, Xu J, Selimyan R, Yoon JH, Martindale JL, De S, Wood WH, Becker KG, Gorospe M. Senescence-associated lncRNAs: Senescence-

[82] Montes M, Nielsen MM, Maglieri G, Jacobsen A, Højfeldt J, Agrawal-Singh S, Hansen K, Helin K, Van De Werken HJ, Pedersen JS, Lund AH. The lncRNA MIR31HG regulates p16 INK4A expression to modulate senescence. Nature Communications. 2015

[83] Ji P, Diederichs S, Wang W, Böing S, Metzger R, Schneider PM, Tidow N, Brandt B, Buerger H, Bulk E, Thomas M. MALAT-1, a novel noncoding RNA, and thymosin β4 predict metastasis and survival in early-stage non-small cell lung cancer. Oncogene.

[84] Tripathi V, Ellis JD, Shen Z, Song DY, Pan Q, Watt AT, Freier SM, Bennett CF, Sharma A, Bubulya PA, Blencowe BJ. The nuclear-retained noncoding RNA MALAT1 regulates alternative splicing by modulating SR splicing factor phosphorylation. Molecular Cell.

[85] Gutschner T, Hämmerle M, Eißmann M, Hsu J, Kim Y, Hung G, Revenko A, Arun G, Stentrup M, Groß M, Zörnig M. The noncoding RNA MALAT1 is a critical regulator of the metastasis phenotype of lung cancer cells. Cancer Research. 2013 Feb;**73**(3):1180-1189

[86] Gutschner T, Hämmerle M, Diederichs S. MALAT1—A paradigm for long noncoding RNA function in cancer. Journal of Molecular Medicine. 2013 Jul;**91**(7):791-801

[87] Eißmann M, Gutschner T, Hämmerle M, Günther S, Caudron-Herger M, Groß M, Schirmacher P, Rippe K, Braun T, Zörnig M, Diederichs S. Loss of the abundant nuclear

associated long noncoding RNAs. Aging Cell. 2013 Oct;**12**(5):890-900

ing with 3′ UTRs via Alu elements. Nature. 2011 Feb;**470**(7333):284

Interdisciplinary Reviews: RNA. 2015 Nov;**6**(6):615-629

Jun;**465**(7301):1033

Apr;**6**:6967

2003 Sep;**22**(39):8031

2010 Sep;**39**(6):925-938

RNA. 2013 Jul;**4**(4):423-435

74 Transcriptional and Post-transcriptional Regulation

work. Journal of Cellular and Molecular Medicine. 2017 Jan;**21**(1):185-192


**Chapter 5**

**Provisional chapter**

**MicroRNAs in Bone Diseases: Progress and Prospects**

With 19–25 nucleotides long, microRNAs (miRNAs) are small noncoding RNA molecules which play crucial roles in major cellular functions such as cell cycle control, apoptosis, metabolism, cell proliferation, and cell differentiation. Changes in the expression of miRNAs can cause significant effects to normal and aberrant cells. The dysregulation of miRNAs has been implicated in various human diseases such as brain tumor, osteoarthritis, schizophrenia, and breast cancer. Generally, miRNAs negatively regulate gene expression by binding to their specific mRNAs, thereby blocking their translation of the mRNAs. However, a few studies have reported that miRNAs could also upregulate the translation of certain proteins. This shows the important roles of miRNAs in various cell functions. This chapter will focus on the role of miRNAs in normal osteoblast and osteosarcoma cells. In addition, the great potential of miRNA as a new therapeutic approach

**Keywords:** microRNAs, bone diseases, osteoblasts, osteoclasts, bone homeostasis, gene

MicroRNAs (miRNAs) are short (19–25 nucleotides) single-stranded noncoding RNA molecules that regulate protein expression by complementary binding to mRNA targets with the aid of RNA-induced silencing complex (RISC) [1]. When miRNAs pair perfectly with mRNA targets, mRNAs degradation will occur. Translational repression of gene will happen when miRNAs bind partially complementary to mRNA targets [2]. Since the discovery of the first miRNA, lin-4 in *Caenorhabditis elegans* in 1993, thousands of miRNAs have been identified in animals and plants [3]. These miRNAs play crucial roles in biological processes such

**MicroRNAs in Bone Diseases: Progress and Prospects**

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

DOI: 10.5772/intechopen.79275

Hui-Yi Loh, Yuin-Yee Lau, Kok-Song Lai and

Hui-Yi Loh, Yuin-Yee Lau, Kok-Song Lai and

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

to treat human bone diseases will also be discussed.

http://dx.doi.org/10.5772/intechopen.79275

Mohd Azuraidi Osman

Mohd Azuraidi Osman

**Abstract**

regulation

**1. Introduction**

#### **MicroRNAs in Bone Diseases: Progress and Prospects MicroRNAs in Bone Diseases: Progress and Prospects**

DOI: 10.5772/intechopen.79275

Hui-Yi Loh, Yuin-Yee Lau, Kok-Song Lai and Mohd Azuraidi Osman Hui-Yi Loh, Yuin-Yee Lau, Kok-Song Lai and Mohd Azuraidi Osman

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.79275

#### **Abstract**

With 19–25 nucleotides long, microRNAs (miRNAs) are small noncoding RNA molecules which play crucial roles in major cellular functions such as cell cycle control, apoptosis, metabolism, cell proliferation, and cell differentiation. Changes in the expression of miRNAs can cause significant effects to normal and aberrant cells. The dysregulation of miRNAs has been implicated in various human diseases such as brain tumor, osteoarthritis, schizophrenia, and breast cancer. Generally, miRNAs negatively regulate gene expression by binding to their specific mRNAs, thereby blocking their translation of the mRNAs. However, a few studies have reported that miRNAs could also upregulate the translation of certain proteins. This shows the important roles of miRNAs in various cell functions. This chapter will focus on the role of miRNAs in normal osteoblast and osteosarcoma cells. In addition, the great potential of miRNA as a new therapeutic approach to treat human bone diseases will also be discussed.

**Keywords:** microRNAs, bone diseases, osteoblasts, osteoclasts, bone homeostasis, gene regulation

#### **1. Introduction**

MicroRNAs (miRNAs) are short (19–25 nucleotides) single-stranded noncoding RNA molecules that regulate protein expression by complementary binding to mRNA targets with the aid of RNA-induced silencing complex (RISC) [1]. When miRNAs pair perfectly with mRNA targets, mRNAs degradation will occur. Translational repression of gene will happen when miRNAs bind partially complementary to mRNA targets [2]. Since the discovery of the first miRNA, lin-4 in *Caenorhabditis elegans* in 1993, thousands of miRNAs have been identified in animals and plants [3]. These miRNAs play crucial roles in biological processes such

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

as cell growth, cell formation and differentiation, apoptosis, and cell metabolism. MiRNAs also regulate bone cells such as osteoblasts, osteoclasts, and osteocytes, which function in the mechanism of bone modeling and bone remodeling [4]. Osteoblasts play important roles in bone formation and osteoclasts function in bone resorption, whereas osteocytes regulate osteoblasts and osteoclasts activities by controlling signaling pathways [4] (**Figure 1**). Expression of many miRNAs has been found to be upregulated or downregulated in bone cancer cells compared to normal bone cells. Some of these miRNAs act as oncogenes such as miR-27, which promote the migration and invasion ability in the osteosarcoma [5]. Some other miRNAs act as tumor repressor genes such as miR-192 and miR-215, which play major roles in cell cycle arrest in cancer cells [6]. Dysregulation of miRNA expression by specific translation regulation such as DNA methylation, which leads to miRNA silencing, has been associated with bone diseases such as osteoporosis, osteogenesis imperfecta, and osteoarthritis [4, 7]. Therefore, understanding the roles of miRNAs in bone cells will provide the opportunity to develop miRNA-based therapy for bone diseases. In this chapter, we highlight the roles of various miRNAs that involve in the formation, resorption, and maintenance of bone in various bone diseases.

bone formation. MiRNAs are known to be involved in the osteoclast-mediated bone resorption by regulating macrophage colony-stimulating factor (M-CSF) and receptor activator of NF-κB ligand (RANKL)-induced signaling pathways, which involved in the commitment of

MicroRNAs in Bone Diseases: Progress and Prospects http://dx.doi.org/10.5772/intechopen.79275 79

The receptor activator of NF-κB ligand (RANKL) and macrophage colony-stimulating factor (M-CSF) signaling pathway are the principle operating pathways that regulate osteoclast differentiation and activation in bone remodeling [16]. These signaling pathways are tightly regulated by microRNAs. Hence, the involvement of miRNAs in the process of osteoclasts

MiR-31 has been identified to be significantly upregulated in mice bone marrow cells under RANKL-induced osteoclast formation. The suppression of miR-31 by specific antagomirs under receptor activator of NF-κB ligand (RANKL) treatment decreased the number of tartrate-resistant acid phosphatase (TRAP)-positive multinucleated osteoblastic cells and ringshaped mature osteoclastic cells. Additionally, less efficient resorption of synthetic calcium phosphate matrix and impaired actin ring formation for the development bone resorption sealing zone were also reported following the miR-31 antagomir transfection. In this situation of impaired osteoclastogenesis, the Ras homolog gene family member A (RhoA), which is the target of miR-31, was upregulated. Interestingly, treatment with RhoA inhibitor, coenzyme C<sup>3</sup> was able to rescue the decrease in number of ring-shaped TRAP-positive multinucleated cells

During the late stage of osteoclastogenesis, the osteoclasts undergo apoptosis to allow the reversal phase of bone remodeling, which allows the transition of bone resorption to bone formation [8]. At this stage, there is a significant upregulation of miR-26a under RANKL stimulation. Treatment with an miR-26a mimic in preosteoclast cells (pre-OCs) significantly inhibited the formation of osteoclast, peripheral actin ring, and resorption pit, whereas treatment with miR-26a inhibitor dramatically reversed these observations. The study proposed that miR-26a suppressed osteoclasts formation in the late stage of bone remodeling by targeting connective tissue growth factor/CCN family 2 (CTGF/CCN2), which plays an important role in promoting osteoclast formation via upregulation of dendritic cell-specific transmembrane protein

Another miRNA, miR-21 has been shown to be upregulated by RANKL-induced osteoclastogenesis in mouse osteoclast precursor cells' bone marrow-derived macrophages (BMMs). MiR-21 downregulates the expression of programmed cell death 4 (PDCD4), which is a repressor for c-Fos. The activated c-Fos, an important transcription factor for osteoclastogenesis, allows RANKL to induce nuclear factor of activated T-cells cytoplasmic 1 (NFATc1) mRNA expression and stimulates osteoclast-specific markers such as tartrate-resistant acid phosphatase (TRAP) and cathepsin K. The silencing of miR-21 by transduction of BMMs with antisense oligonucleotides of miR-21 inserted in a lentiviral vector increased the expression of

osteoclasts from osteoclast progenitors [16].

**2.1. MicroRNA roles in normal bone resorption**

differentiation is crucial for normal bone resorption.

and potentially revert the osteoclastogenesis impairment [17].

PDCD4 and impaired the RANKL-induced osteoclastogenesis [19].

(DC-STAMP) [18].

## **2. Regulatory role of microRNAs in normal bone growth and maintenance**

Bone is a dynamic tissue that undergoes constant processes of modeling and remodeling throughout life. Bone modeling is the process where bones resculpture or rechange its overall size and shape as an adaptive mechanism against physiological processes or biomechanical influences, customizing or adjusting the skeleton toward the actions in which it encounters [8]. Bones may widen, change axis, or alter curvature by an independent action of osteoblasts and osteoclasts in response to biomechanical forces [9]. Bone modeling aids in the prevention of damage or injury to the bone [10] and regulates growth phase such as facilitating the increase in a child's skull size to accommodate the bigger brain as a child grows and undergoes marked change in the facial features of a child to that as an adult [11].

Meanwhile, bone remodeling is a sequential process, which involves the removal of the old bone (bone resorption) and the deposition of new bone (bone formation) [10, 12]. This process is ultimately important for the maintenance of the bone's strength and integrity by modulating the reshaping or replacement of bone during growth, preventing the accumulation of bone microdamage and regulating mineral homeostasis [8]. Bone remodeling is a lifelong, bone turnover [13] that is tightly regulated by two main population of bone cells: the boneresorbing osteoclasts of hematopoietic lineage and the bone-forming osteoblasts of mesenchymal lineage [14, 15]. This tightly coupled process requires synchronized activities, balanced by both of these effector cells [8].

MicroRNAs serve as positive and/or negative regulators for various musculoskeletal signaling pathways or mechanisms by regulating bone biology such as in osteoblastic or osteoclastic differentiation, in accordance with the orchestrated balance between bone resorption and bone formation. MiRNAs are known to be involved in the osteoclast-mediated bone resorption by regulating macrophage colony-stimulating factor (M-CSF) and receptor activator of NF-κB ligand (RANKL)-induced signaling pathways, which involved in the commitment of osteoclasts from osteoclast progenitors [16].

### **2.1. MicroRNA roles in normal bone resorption**

as cell growth, cell formation and differentiation, apoptosis, and cell metabolism. MiRNAs also regulate bone cells such as osteoblasts, osteoclasts, and osteocytes, which function in the mechanism of bone modeling and bone remodeling [4]. Osteoblasts play important roles in bone formation and osteoclasts function in bone resorption, whereas osteocytes regulate osteoblasts and osteoclasts activities by controlling signaling pathways [4] (**Figure 1**). Expression of many miRNAs has been found to be upregulated or downregulated in bone cancer cells compared to normal bone cells. Some of these miRNAs act as oncogenes such as miR-27, which promote the migration and invasion ability in the osteosarcoma [5]. Some other miRNAs act as tumor repressor genes such as miR-192 and miR-215, which play major roles in cell cycle arrest in cancer cells [6]. Dysregulation of miRNA expression by specific translation regulation such as DNA methylation, which leads to miRNA silencing, has been associated with bone diseases such as osteoporosis, osteogenesis imperfecta, and osteoarthritis [4, 7]. Therefore, understanding the roles of miRNAs in bone cells will provide the opportunity to develop miRNA-based therapy for bone diseases. In this chapter, we highlight the roles of various miRNAs that involve in the formation, resorption, and maintenance of bone

**2. Regulatory role of microRNAs in normal bone growth and** 

goes marked change in the facial features of a child to that as an adult [11].

Bone is a dynamic tissue that undergoes constant processes of modeling and remodeling throughout life. Bone modeling is the process where bones resculpture or rechange its overall size and shape as an adaptive mechanism against physiological processes or biomechanical influences, customizing or adjusting the skeleton toward the actions in which it encounters [8]. Bones may widen, change axis, or alter curvature by an independent action of osteoblasts and osteoclasts in response to biomechanical forces [9]. Bone modeling aids in the prevention of damage or injury to the bone [10] and regulates growth phase such as facilitating the increase in a child's skull size to accommodate the bigger brain as a child grows and under-

Meanwhile, bone remodeling is a sequential process, which involves the removal of the old bone (bone resorption) and the deposition of new bone (bone formation) [10, 12]. This process is ultimately important for the maintenance of the bone's strength and integrity by modulating the reshaping or replacement of bone during growth, preventing the accumulation of bone microdamage and regulating mineral homeostasis [8]. Bone remodeling is a lifelong, bone turnover [13] that is tightly regulated by two main population of bone cells: the boneresorbing osteoclasts of hematopoietic lineage and the bone-forming osteoblasts of mesenchymal lineage [14, 15]. This tightly coupled process requires synchronized activities, balanced

MicroRNAs serve as positive and/or negative regulators for various musculoskeletal signaling pathways or mechanisms by regulating bone biology such as in osteoblastic or osteoclastic differentiation, in accordance with the orchestrated balance between bone resorption and

in various bone diseases.

78 Transcriptional and Post-transcriptional Regulation

by both of these effector cells [8].

**maintenance**

The receptor activator of NF-κB ligand (RANKL) and macrophage colony-stimulating factor (M-CSF) signaling pathway are the principle operating pathways that regulate osteoclast differentiation and activation in bone remodeling [16]. These signaling pathways are tightly regulated by microRNAs. Hence, the involvement of miRNAs in the process of osteoclasts differentiation is crucial for normal bone resorption.

MiR-31 has been identified to be significantly upregulated in mice bone marrow cells under RANKL-induced osteoclast formation. The suppression of miR-31 by specific antagomirs under receptor activator of NF-κB ligand (RANKL) treatment decreased the number of tartrate-resistant acid phosphatase (TRAP)-positive multinucleated osteoblastic cells and ringshaped mature osteoclastic cells. Additionally, less efficient resorption of synthetic calcium phosphate matrix and impaired actin ring formation for the development bone resorption sealing zone were also reported following the miR-31 antagomir transfection. In this situation of impaired osteoclastogenesis, the Ras homolog gene family member A (RhoA), which is the target of miR-31, was upregulated. Interestingly, treatment with RhoA inhibitor, coenzyme C<sup>3</sup> was able to rescue the decrease in number of ring-shaped TRAP-positive multinucleated cells and potentially revert the osteoclastogenesis impairment [17].

During the late stage of osteoclastogenesis, the osteoclasts undergo apoptosis to allow the reversal phase of bone remodeling, which allows the transition of bone resorption to bone formation [8]. At this stage, there is a significant upregulation of miR-26a under RANKL stimulation. Treatment with an miR-26a mimic in preosteoclast cells (pre-OCs) significantly inhibited the formation of osteoclast, peripheral actin ring, and resorption pit, whereas treatment with miR-26a inhibitor dramatically reversed these observations. The study proposed that miR-26a suppressed osteoclasts formation in the late stage of bone remodeling by targeting connective tissue growth factor/CCN family 2 (CTGF/CCN2), which plays an important role in promoting osteoclast formation via upregulation of dendritic cell-specific transmembrane protein (DC-STAMP) [18].

Another miRNA, miR-21 has been shown to be upregulated by RANKL-induced osteoclastogenesis in mouse osteoclast precursor cells' bone marrow-derived macrophages (BMMs). MiR-21 downregulates the expression of programmed cell death 4 (PDCD4), which is a repressor for c-Fos. The activated c-Fos, an important transcription factor for osteoclastogenesis, allows RANKL to induce nuclear factor of activated T-cells cytoplasmic 1 (NFATc1) mRNA expression and stimulates osteoclast-specific markers such as tartrate-resistant acid phosphatase (TRAP) and cathepsin K. The silencing of miR-21 by transduction of BMMs with antisense oligonucleotides of miR-21 inserted in a lentiviral vector increased the expression of PDCD4 and impaired the RANKL-induced osteoclastogenesis [19].

In another study, the overexpression of miR-148a was observed during M-CSF and RANKLstimulated osteoclast differentiation in CD14+ peripheral blood mononuclear cell (PBMCs). The overexpression of miR-148a induced the formation of osteoclast, whereas suppression of miR-148a showed an opposite outcome. *In vivo* study using ovariectomized (OVX) mice that undergoes intravenous injection with specific miR-148a silencing antagomir showed reduction in bone resorption and increase in bone mass density (BMD). Furthermore, osteoclasts number and the levels of osteoclast activity markers such as tryptophan-regulated attenuation protein (TRAP) and nuclear factor of activated T-cells, cytoplasmic 1 (NFATc1) mRNA in bone tissue were also decreased following antagomiR-148a treatment. This finding shows that decreased miR-148a levels impaired bone resorption through suppression of osteoclast activity. MiR-148a performs its regulatory role by targeting 3′UTR of V-maf musculoaponeurotic fibrosarcoma oncogene homolog B (MAFB), a negative regulator of osteoclastogenesis and resulted in an inhibited expression of MAFB protein [20]. Additionally, MAFB serves as a negative regulator in RANKL-induced osteoclastogenesis by interfering the DNA binding capability of the three major transcription factors; NFATc1, c-Fos, and MITF in osteoclast differentiation [21].

On the other hand, bone morphogenetic protein (BMP)-signaling pathway is crucial for the differentiation of myoblastic cell lines into osteoblast lineage and bone formation [16]. MiR-133 and miR-135 are downregulated in BMP-2-induced osteoblastic differentiation of C2C12 pluripotent mesenchymal cell line. MiR-133 is a negative regulator of Runt-related transcription factor 2 (Runx2), a transcription factor required for osteoblast differentiation, while miR-135 represses the osteoblastic differentiation of C2C12 cells by acting toward mothers against decapentaplegic homolog 5 (Smad5), an intracellular Runx2 co-receptor. Hence, downregulation of miR-133 and miR-135 will increase the expression of Runx2 and Smad5, promoting the BMP-2-induced osteoblast differentiation. Moreover, the overexpression of these miRNAs will suppress the expression of BMP-induced osteoblast-specific protein markers such as alkaline phosphatase (ALP), osteocalcin, and homeobox A10 (HOXA10) [26]. Another miRNA, miR-20 has been shown to involve in the transformation of osteoblast from human MSCs by downregulating the expression of silencing peroxisome proliferatoractivated receptor γ (PPARγ), bone morphogenetic protein and activin membrane-bound inhibitor (Bambi), and cysteine-rich transmembrane BMP regulator 1 (Crim1) and therefore,

MicroRNAs in Bone Diseases: Progress and Prospects http://dx.doi.org/10.5772/intechopen.79275 81

Another report showed that miR-2861 expression was elevated in primary mice osteoblasts. Overexpression of miR-2861 in mice bone marrow stromal cells (BMSCs) has been reported to promote BMP2-induced osteoblast differentiation. Conversely, the inhibition of miR-2861 expression results in the decrease in osteoblast differentiation. *In vivo* knockdown of miR-2861 in OVX mice resulted in enhanced decrement of bone volume and bone formation rate. Furthermore, histone deacetylase 5 (HDAC5) has been identified as the direct target of miR-2861. HDAC5 deacetylates Runx2 and allow the deacetylated Runx2 to undergo SMAD specific E3 ubiquitin protein ligase 1 (Smurf1)-mediated degradation, decreasing the rate of osteoblast differentiation. Therefore, the abundance of acetylated Runx2 will increase upon HDAC5 suppression by miR-2861 and promote osteoblast differentiation [28]. MiR-3960 is generated

**Figure 1.** The process of bone remodeling begins with the recruitment of osteoclast progenitor cells to the site of bone remodeling, followed by osteoclast progenitor cells differentiation into mature osteoclasts. Reversal phase allows the transition from bone resorption phase to bone formation phase. In bone formation phase, mesenchymal stem cells differentiate into mature osteoblast and secrete collagenous components for bone formation. Bone remodeling process is completed after the mineralization of collagen fibril matrix and subsequent transformation of osteoblasts into osteocytes.

activated the BMP-2/Runx2 signaling [27].

The relative expression of miR-340 was downregulated upon M-CSF and RANKL-induced osteoblast differentiation in BMMs. It has been reported that the overexpression of miR-340 inhibits osteoclast differentiation and reduced the number of osteoclasts cells by targeting 3′UTR of microphthalmia-associated transcription factor (MITF), a transcription factor involved in osteoclast differentiation, leading to the reduced level of MITF mRNA and protein. MITF knockdown will inhibit TRAP, calcitonin receptor, V-ATPase d2, and cathepsin K expression, and thus, suggested that miR-340 may suppress osteoclast differentiation by targeting MITF [22].

#### **2.2. MicroRNAs in normal bone formation**

Canonical wnt/β-catenin signaling pathway is a major pathway required for the commitment of mesenchymal stem cells into osteoblast lineage [15]. The stabilization of β-catenin is important for the expression of wnt-responsive gene [16]. The miR-29 family is one of the well-known miRNA families that regulate osteoblast function, which plays a key role in the positive regulation of osteoblast differentiation by targeting several wnt-signaling pathway inhibitors. The expression of miR-29a is induced by canonical wnt signaling during osteoblast differentiation and has been shown to target dikkopf-1 (Dkk1), Kringle domain-containing transmembrane protein (Kremen2), and secreted frizzled related protein 2 (sFRP2), which acts as inhibitors of wnt receptor complex [23]. Moreover, miR-29b was also found to target several other inhibitors of bone formation such as histone deacetylase 4 (HDAC4), transforming growth factor beta 3 (TGFβ3), activin receptor type-2A (AcvR2A), beta-catenin-interacting protein 1 (CTNNBIP1), and dual specific phosphatase 2 (DUSP2) by binding to their mRNA 3'UTR [24]. Furthermore, the expression level of miR-29 is low during the early phase of osteoblastogenesis and increases at late phase, as miR-29 targets α1 and α2(I)collagen, α1(III)collagen, fibrillin 1, and osteonectin, which are important for the formation of collagen fibril matrix secreted by osteoblasts, and thus allowed for collagen matrix deposition before subsequent mineralization in bone formation process [25]. Therefore, miR-29 family is important in the promotion of osteoblastogenesis by repressing the inhibitors of osteogenesis and in the meanwhile plays crucial regulatory role in the attenuation of collagen synthesis in mineralized bone.

On the other hand, bone morphogenetic protein (BMP)-signaling pathway is crucial for the differentiation of myoblastic cell lines into osteoblast lineage and bone formation [16]. MiR-133 and miR-135 are downregulated in BMP-2-induced osteoblastic differentiation of C2C12 pluripotent mesenchymal cell line. MiR-133 is a negative regulator of Runt-related transcription factor 2 (Runx2), a transcription factor required for osteoblast differentiation, while miR-135 represses the osteoblastic differentiation of C2C12 cells by acting toward mothers against decapentaplegic homolog 5 (Smad5), an intracellular Runx2 co-receptor. Hence, downregulation of miR-133 and miR-135 will increase the expression of Runx2 and Smad5, promoting the BMP-2-induced osteoblast differentiation. Moreover, the overexpression of these miRNAs will suppress the expression of BMP-induced osteoblast-specific protein markers such as alkaline phosphatase (ALP), osteocalcin, and homeobox A10 (HOXA10) [26]. Another miRNA, miR-20 has been shown to involve in the transformation of osteoblast from human MSCs by downregulating the expression of silencing peroxisome proliferatoractivated receptor γ (PPARγ), bone morphogenetic protein and activin membrane-bound inhibitor (Bambi), and cysteine-rich transmembrane BMP regulator 1 (Crim1) and therefore, activated the BMP-2/Runx2 signaling [27].

In another study, the overexpression of miR-148a was observed during M-CSF and RANKLstimulated osteoclast differentiation in CD14+ peripheral blood mononuclear cell (PBMCs). The overexpression of miR-148a induced the formation of osteoclast, whereas suppression of miR-148a showed an opposite outcome. *In vivo* study using ovariectomized (OVX) mice that undergoes intravenous injection with specific miR-148a silencing antagomir showed reduction in bone resorption and increase in bone mass density (BMD). Furthermore, osteoclasts number and the levels of osteoclast activity markers such as tryptophan-regulated attenuation protein (TRAP) and nuclear factor of activated T-cells, cytoplasmic 1 (NFATc1) mRNA in bone tissue were also decreased following antagomiR-148a treatment. This finding shows that decreased miR-148a levels impaired bone resorption through suppression of osteoclast activity. MiR-148a performs its regulatory role by targeting 3′UTR of V-maf musculoaponeurotic fibrosarcoma oncogene homolog B (MAFB), a negative regulator of osteoclastogenesis and resulted in an inhibited expression of MAFB protein [20]. Additionally, MAFB serves as a negative regulator in RANKL-induced osteoclastogenesis by interfering the DNA binding capability of the three

major transcription factors; NFATc1, c-Fos, and MITF in osteoclast differentiation [21].

targeting MITF [22].

**2.2. MicroRNAs in normal bone formation**

80 Transcriptional and Post-transcriptional Regulation

The relative expression of miR-340 was downregulated upon M-CSF and RANKL-induced osteoblast differentiation in BMMs. It has been reported that the overexpression of miR-340 inhibits osteoclast differentiation and reduced the number of osteoclasts cells by targeting 3′UTR of microphthalmia-associated transcription factor (MITF), a transcription factor involved in osteoclast differentiation, leading to the reduced level of MITF mRNA and protein. MITF knockdown will inhibit TRAP, calcitonin receptor, V-ATPase d2, and cathepsin K expression, and thus, suggested that miR-340 may suppress osteoclast differentiation by

Canonical wnt/β-catenin signaling pathway is a major pathway required for the commitment of mesenchymal stem cells into osteoblast lineage [15]. The stabilization of β-catenin is important for the expression of wnt-responsive gene [16]. The miR-29 family is one of the well-known miRNA families that regulate osteoblast function, which plays a key role in the positive regulation of osteoblast differentiation by targeting several wnt-signaling pathway inhibitors. The expression of miR-29a is induced by canonical wnt signaling during osteoblast differentiation and has been shown to target dikkopf-1 (Dkk1), Kringle domain-containing transmembrane protein (Kremen2), and secreted frizzled related protein 2 (sFRP2), which acts as inhibitors of wnt receptor complex [23]. Moreover, miR-29b was also found to target several other inhibitors of bone formation such as histone deacetylase 4 (HDAC4), transforming growth factor beta 3 (TGFβ3), activin receptor type-2A (AcvR2A), beta-catenin-interacting protein 1 (CTNNBIP1), and dual specific phosphatase 2 (DUSP2) by binding to their mRNA 3'UTR [24]. Furthermore, the expression level of miR-29 is low during the early phase of osteoblastogenesis and increases at late phase, as miR-29 targets α1 and α2(I)collagen, α1(III)collagen, fibrillin 1, and osteonectin, which are important for the formation of collagen fibril matrix secreted by osteoblasts, and thus allowed for collagen matrix deposition before subsequent mineralization in bone formation process [25]. Therefore, miR-29 family is important in the promotion of osteoblastogenesis by repressing the inhibitors of osteogenesis and in the meanwhile plays crucial regulatory role in the attenuation of collagen synthesis in mineralized bone.

Another report showed that miR-2861 expression was elevated in primary mice osteoblasts. Overexpression of miR-2861 in mice bone marrow stromal cells (BMSCs) has been reported to promote BMP2-induced osteoblast differentiation. Conversely, the inhibition of miR-2861 expression results in the decrease in osteoblast differentiation. *In vivo* knockdown of miR-2861 in OVX mice resulted in enhanced decrement of bone volume and bone formation rate. Furthermore, histone deacetylase 5 (HDAC5) has been identified as the direct target of miR-2861. HDAC5 deacetylates Runx2 and allow the deacetylated Runx2 to undergo SMAD specific E3 ubiquitin protein ligase 1 (Smurf1)-mediated degradation, decreasing the rate of osteoblast differentiation. Therefore, the abundance of acetylated Runx2 will increase upon HDAC5 suppression by miR-2861 and promote osteoblast differentiation [28]. MiR-3960 is generated

**Figure 1.** The process of bone remodeling begins with the recruitment of osteoclast progenitor cells to the site of bone remodeling, followed by osteoclast progenitor cells differentiation into mature osteoclasts. Reversal phase allows the transition from bone resorption phase to bone formation phase. In bone formation phase, mesenchymal stem cells differentiate into mature osteoblast and secrete collagenous components for bone formation. Bone remodeling process is completed after the mineralization of collagen fibril matrix and subsequent transformation of osteoblasts into osteocytes.

from the same genetic locus as the miR-2861 due to the transcription from the same primary microRNA (pri-miRNA). MiR-3960 was found to directly target homeobox A2 (HOXA2), a negative regulator of Runx2. Hence, the miR-3960-mediated suppression of HOXA2 by miR-3960 will increase Runx2 expression and osteoblast differentiation [29]. The summary of the MicroRNAs involved in the regulation of normal bone development is shown in **Table 1**.

**3. MicroRNAs' expression in various bone diseases**

and pathway that lead to the diseases.

**3.1. Benign bone tumor: giant cell tumor**

becomes a potential approach to cure GCTBs [30].

**3.2. Bone remodeling abnormality: osteoporosis**

and proliferation in GCTBs.

Dysregulation of miRNAs affects critical pathways and biological processes, which lead to various bone diseases. MiRNA profiling studies have revealed that miRNA expression patterns are specific to various types of bone diseases, and it reflects the developmental lineage

MicroRNAs in Bone Diseases: Progress and Prospects http://dx.doi.org/10.5772/intechopen.79275 83

Giant cell tumor of bone (GCTB) is an aggressive benign tumor that is able to metastasize, and up to 6% of GCTB patients grow pulmonary metastases (metastatic spread via blood or lymphatics) [30]. GCTBs are characterized by the presence of numerous multinucleated osteoclastlike giant cells distributed among mononuclear stromal cells [31]. GCTBs are also characterized by extensive bone resorption, which results in regional pain and bone destruction, mostly occurring in distal femur, proximal tibia, distal radius, and sacrum [32, 33]. Histologically, GCTBs can be classified into three main types, which are osteoclast-like multinucleated giant cells, monocytic round cells, and spindle-like stromal cells [34]. Current treatments of GCTBs are ranging from intralesional curettage to wide resection [33]. Since the cause of GCTBs is extensive bone resorption by aggressive lytic process, the repression of osteoclastogenesis

A study reveals that treatments with miR-16-5p mimic repressed RANKL-induced osteoclastogenesis in GCTBs. However, the formation of RANKL-induced osteoclast was enhanced with miR-16-5p inhibitor. Furthermore, the osteoclastogenesis-related genes like cathepsin K (CK), tartrate-resistant acidic phosphatase (TRAP), and matrix metallopeptidase 9 (MMP9) were also upregulated by miR-16-5p inhibitor. This finding shows that miR-16-5p inhibits osteoclastogenesis; hence, it has the potential to be used as a therapeutic target to control the excessive bone resorption in GCTBs [30]. Another study by Wang et al. found that miR-106b is another microRNA that target RANKL to inhibit osteoclastogenesis and osteolysis in GCTBs [32].

Parathyroid hormone 1 receptor (PTH1R) is a transmembrane receptor that binds to G proteins. The activation of pathways that promote osteoclastogenesis in osteoblasts is induced when PTH binds to parathyroid hormone 1 receptor (PTH1R). Wu et al. reported that miR-125b directly targets the 3′UTR of PTH1R. Overexpression of tumor suppressor miR-125b inhibits the osteoclastogenesis and also PTH1R downstream target such as RANKL and IL-8 [35]. The downregulation of miR-125b in GCTBs revealed that it suppressed the cell growth

Osteoporosis is a multifactorial bone disorder characterized by low bone mass, impaired bone quality, and a more susceptibility to fracture [36]. The recent global statistics from the International Osteoporosis Foundation reported that 1 in 3 women and 1 in 5 men above the


**Table 1.** MicroRNAs involved in the regulation of normal bone development.

## **3. MicroRNAs' expression in various bone diseases**

Dysregulation of miRNAs affects critical pathways and biological processes, which lead to various bone diseases. MiRNA profiling studies have revealed that miRNA expression patterns are specific to various types of bone diseases, and it reflects the developmental lineage and pathway that lead to the diseases.

### **3.1. Benign bone tumor: giant cell tumor**

from the same genetic locus as the miR-2861 due to the transcription from the same primary microRNA (pri-miRNA). MiR-3960 was found to directly target homeobox A2 (HOXA2), a negative regulator of Runx2. Hence, the miR-3960-mediated suppression of HOXA2 by miR-3960 will increase Runx2 expression and osteoblast differentiation [29]. The summary of the MicroRNAs involved in the regulation of normal bone development is shown in **Table 1**.

MiR-31 RhoA Promotes osteoclast differentiation by targeting RhoA

MiR-21 PDCD4 Promotes osteoclast differentiation by targeting PDCD4

MiR-148a MAFB Promotes osteoclast differentiation by targeting MAFB

MiR-340 MITF Inhibits osteoclast differentiation by targeting MITF [22]

matrix

pathway

MiR-133 Runx2 Inhibits osteoblast differentiation by targeting Runx2 [26]

CTNNBIP1, and DUSP2

PPARγ, Bambi and Crim1

HDAC5, which represses Runx2

Hoxa5, which represses Runx2

MiR-29a Dkk1, Kremen2, sFRP2 Promotes osteoblasts differentiation by targeting

MiR-135 Smad5 Inhibits osteoblast differentiation by targeting Smad5

MiR-20 PPARγ, Bambi, Crim1 Promotes osteoblast differentiation by targeting

MiR-2861 HDAC5 Promotes osteoblasts differentiation by targeting

MiR-3960 Hoxa5 Promotes osteoblasts differentiation by targeting

**Table 1.** MicroRNAs involved in the regulation of normal bone development.

MiR-26a CTGF/CCN2 Inhibits osteoclast differentiation by targeting CTGF/ CCN2

**Associated event Reference**

Downregulated during the early phase of bone formation and upregulated during the late phase by targets COL1A1, COL3A1, fibrillin 1, and osteonectin to allow the formation of collagen fibril

Dkk1, Kremen2, sFRP2 inhibitors of wnt signaling

Promotes osteoblasts differentiation by inhibitors of bone formation such as HDAC4, TGFβ3, AcvR2A,

[17]

[18]

[19]

[20]

[25]

[23]

[24]

[26]

[27]

[28]

[29]

**MicroRNAs Target gene or protein encoded**

82 Transcriptional and Post-transcriptional Regulation

*MicroRNAs associated with bone resorption*

*MicroRNAs associated with bone formation* MiR-29 COL1A1, COL3A1,

MiR-29b HDAC4, TGFβ3,

DUSP2

fibrillin 1, osteonectin

AcvR2A, CTNNBIP1,

Giant cell tumor of bone (GCTB) is an aggressive benign tumor that is able to metastasize, and up to 6% of GCTB patients grow pulmonary metastases (metastatic spread via blood or lymphatics) [30]. GCTBs are characterized by the presence of numerous multinucleated osteoclastlike giant cells distributed among mononuclear stromal cells [31]. GCTBs are also characterized by extensive bone resorption, which results in regional pain and bone destruction, mostly occurring in distal femur, proximal tibia, distal radius, and sacrum [32, 33]. Histologically, GCTBs can be classified into three main types, which are osteoclast-like multinucleated giant cells, monocytic round cells, and spindle-like stromal cells [34]. Current treatments of GCTBs are ranging from intralesional curettage to wide resection [33]. Since the cause of GCTBs is extensive bone resorption by aggressive lytic process, the repression of osteoclastogenesis becomes a potential approach to cure GCTBs [30].

A study reveals that treatments with miR-16-5p mimic repressed RANKL-induced osteoclastogenesis in GCTBs. However, the formation of RANKL-induced osteoclast was enhanced with miR-16-5p inhibitor. Furthermore, the osteoclastogenesis-related genes like cathepsin K (CK), tartrate-resistant acidic phosphatase (TRAP), and matrix metallopeptidase 9 (MMP9) were also upregulated by miR-16-5p inhibitor. This finding shows that miR-16-5p inhibits osteoclastogenesis; hence, it has the potential to be used as a therapeutic target to control the excessive bone resorption in GCTBs [30]. Another study by Wang et al. found that miR-106b is another microRNA that target RANKL to inhibit osteoclastogenesis and osteolysis in GCTBs [32].

Parathyroid hormone 1 receptor (PTH1R) is a transmembrane receptor that binds to G proteins. The activation of pathways that promote osteoclastogenesis in osteoblasts is induced when PTH binds to parathyroid hormone 1 receptor (PTH1R). Wu et al. reported that miR-125b directly targets the 3′UTR of PTH1R. Overexpression of tumor suppressor miR-125b inhibits the osteoclastogenesis and also PTH1R downstream target such as RANKL and IL-8 [35]. The downregulation of miR-125b in GCTBs revealed that it suppressed the cell growth and proliferation in GCTBs.

#### **3.2. Bone remodeling abnormality: osteoporosis**

Osteoporosis is a multifactorial bone disorder characterized by low bone mass, impaired bone quality, and a more susceptibility to fracture [36]. The recent global statistics from the International Osteoporosis Foundation reported that 1 in 3 women and 1 in 5 men above the age of 50 will suffer from osteoporotic fractures in their lifetime [37]. The primary osteoporosis is generally arising due to the postmenopausal deficiency or loss of sex hormones such as estrogen, while the secondary osteoporosis is due to the presence of underlying diseases and medication of treatments with glucocorticoids, hyperthyroidism, diabetes mellitus, and gastrointestinal disorders [37, 38]. The bone mineral density peaks during adolescence stage of puberty, which then maintained throughout an individual middle age for some decades and subsequently begins to loss upon aging. Bone tissue undergoes continuous process of resorption and formation throughout in an individual lifetime. Osteoporosis occurs when bone resorption rate exceeds the bone formation rate, resulting in a net loss of bone [39]. Studies revealed that osteoporosis incidences may be linked to bone mass-related genetic determinants including low-density lipoprotein receptor-related protein 5 (LRP5), osteoprotegerin (OPG), sclerostin (SOST), estrogen receptor 1, and the receptor activator of RANK/ NF-κB signaling pathway [40].

TNF-α in MSCs. Furthermore, *in vivo* treatment with anti-TNF-α in OVX mice has increased bone formation by upregulating miR-21 expression, suppressing Spry1 expression and remediating the inflammatory conditions. Thus, this study indicated that TNF-α impairs osteoblastic bone formation by suppressing miR-21 expression in estrogen deficiency-induced

MicroRNAs in Bone Diseases: Progress and Prospects http://dx.doi.org/10.5772/intechopen.79275 85

A study conducted by Wang et al. showed that glucocorticoid-treated mice experienced low bone mass density (BMD) and bone mass content (BMC). Glucocorticoid treatment also significantly resulted in the decrease of bone matrix COL1A1 expression, an increase in dickkopf-1 (Dkk-1) expression and a reduction in miR-29a expression [46]. MiR-29a plays important role in osteoblast differentiation and bone homeostasis by regulating the expression of Wnt inhibitor Dkk-1 [23]. *In vivo* miR-29a precursor treatment was able to reduce the glucocorticoidstimulated BMD and BMC, attenuate glucocorticoid-induced loss of trabecular bone volume fraction, decrease the porosity of cortical bone, and rescue the adverse effect of glucocorticoid on peak load of bone tissue. The treatment with miR-29a inhibitor, however, provided opposite effects [46]. Thus, miR-29a is important in protection against glucocorticoid-induced osteopenia, which may lead to osteoporosis by regulating the activity of Wnt signaling and

Osteogenesis imperfecta (OI) is a heterogeneous group of inherited connective tissue disorder that occurs in about 1 in 10,000 to 20,000 live births [47]. OI is characterized with clinical features such as susceptibility to bone fractures due to low bone mass, reduced bone strength, or quality and bone deformity [48]. In addition, blue sclerae, short stature, dentinogenesis imperfecta (DI), and hearing loss are other clinical manifestations of OI [49]. The pathogenesis of OI involves the most prevalent autosomal dominant mutation of COL1A1 and COL1A2 genes encoding the alpha1 and alpha2 chains of type I procollagen [50]. Type I procollagen is the major bone structural protein, and therefore, the mutation of COL1A1 and COL1A2 genes may have direct link with serious defects or abnormalities including deformities of collagen primary structure, insufficient bone collagen quantity, deviated posttranslational modification, folding, intracellular transport or matrix incorporation, and bone mineralization. Recessive OI is caused by defects in genes that encode for protein products, which interact with type I collagen [51]. There are four well characterized types (I, II, III, and IV) of COL1A1/

Wang et al. performed the preliminary screening of more than 100 bone-related miRNAs in serum of 22 OI patients. The results showed that three miRNAs (miR-26a, miR-30e, and miR-21) were upregulated and eight miRNAs (miR-34c, miR-29a, miR-29b, miR-489, miR-133a, miR-145, miR-210, and miR-1297) were downregulated in OI patients compared to healthy controls. MiR-29a has a universal lower level in the patient group, whereas miR-26a had a universal upper level. This discovery of altered expression of bone-related miRNAs in OI patients' serum profile may become promising miRNA biomarkers for the diagnosis of OI. Although this study did not verify on the relationships of these differentially expressed miRNAs and their potential target genes, the previous studies have showed that these miR-NAs may target a range of gene involved in osteogenic signaling pathways such as BMP, Wnt,

Dkk-1 in osteoblast differentiation and bone mineralization [23, 47].

COL1A2-linked OI based on different clinical and genetic presentations [52].

RANKL, and TGFβ/activin [53].

**3.3. Bone collagen matrix retardation: osteogenesis imperfecta**

osteoporosis [45].

Receptor activator of nuclear factor kappa-Β ligand (RANKL) binds to the receptor activator of nuclear factor κB (RANK) that is present on the surface of the osteoclast mononuclear precursor cells and facilitates the formation of fully differentiated osteoclasts [41]. The expression of mirR-503 is significantly reduced in progenitors of osteoclasts-CD14+ peripheral blood mononuclear cells (PBMCs) of postmenopausal osteoporosis patients compared to healthy postmenopausal controls. The overexpression of miR-503 in human PBMCs had dramatically inhibited RANKL-induced osteoclast differentiation in PBMCs of postmenopausal osteoporosis samples. *In vivo* transfection of miR-503 silencing antagomir into a postmenopausalstimulated ovariectomized (OVX) mice resulted in the increase in RANK protein expression, an increase of bone resorption rate, a decrease in bone mass, and an aggravation of bone loss. Contrastingly, the transfection of the OVX mice with miR-503 overexpressing pre-miR-503 leads to the decrease in RANK protein expression and thus a decrease in bone resorption and an increase in bone mass. Therefore, it is suggested that the low miR-503 expression in postmenopausal osteoporosis patients will promote RANKL-induced osteoclastogenesis, and consequently, bone resorption rate will increase leading to net bone loss [42].

MiR-221 expression is downregulated in postmenopausal osteoporotic bone samples compared to nonosteoporotic bones. In BMP-2-induced osteoblastogenesis, the overexpression of miR-221 resulted in reduced expression of key osteoblast markers, including osteocalcin (OC), alkaline phosphatase (ALP), and collagen type Iα 1 (COL1A1), whereas knockdown of miR-221 promoted the activity of OC, ALP, and COL1A1 [43]. The later study identified Runx2 as a potential target of miR-221. Therefore, this provided an evidence that miR-221 serves as the negative regulator of osteoblast differentiation and contributes to the osteoporosis pathogenesis through the regulation of Runx2 action [44].

Tumor necrosis factor α (TNF-α) inhibits MSC osteogenic differentiation and bone formation in estrogen deficiency-induced osteoporosis with a poorly understood mechanism. A study conducted by Yang et al. showed that the expression of miR-21 is dramatically downregulated in mesenchymal stem cells (MSCs), and this downregulation is due to the suppression by TNF-α during the osteogenesis of MSCs. Moreover, miR-21 has been proved to stimulate the osteoblast differentiation of MSCs by targeting protein sprouty homolog 1 (Spry1), a negative regulator of osteoblast differentiation from MSCs. The later study also demonstrated that the overexpression of miR-21 is able to partially rescue the osteogenic impairment induced by TNF-α in MSCs. Furthermore, *in vivo* treatment with anti-TNF-α in OVX mice has increased bone formation by upregulating miR-21 expression, suppressing Spry1 expression and remediating the inflammatory conditions. Thus, this study indicated that TNF-α impairs osteoblastic bone formation by suppressing miR-21 expression in estrogen deficiency-induced osteoporosis [45].

A study conducted by Wang et al. showed that glucocorticoid-treated mice experienced low bone mass density (BMD) and bone mass content (BMC). Glucocorticoid treatment also significantly resulted in the decrease of bone matrix COL1A1 expression, an increase in dickkopf-1 (Dkk-1) expression and a reduction in miR-29a expression [46]. MiR-29a plays important role in osteoblast differentiation and bone homeostasis by regulating the expression of Wnt inhibitor Dkk-1 [23]. *In vivo* miR-29a precursor treatment was able to reduce the glucocorticoidstimulated BMD and BMC, attenuate glucocorticoid-induced loss of trabecular bone volume fraction, decrease the porosity of cortical bone, and rescue the adverse effect of glucocorticoid on peak load of bone tissue. The treatment with miR-29a inhibitor, however, provided opposite effects [46]. Thus, miR-29a is important in protection against glucocorticoid-induced osteopenia, which may lead to osteoporosis by regulating the activity of Wnt signaling and Dkk-1 in osteoblast differentiation and bone mineralization [23, 47].

#### **3.3. Bone collagen matrix retardation: osteogenesis imperfecta**

age of 50 will suffer from osteoporotic fractures in their lifetime [37]. The primary osteoporosis is generally arising due to the postmenopausal deficiency or loss of sex hormones such as estrogen, while the secondary osteoporosis is due to the presence of underlying diseases and medication of treatments with glucocorticoids, hyperthyroidism, diabetes mellitus, and gastrointestinal disorders [37, 38]. The bone mineral density peaks during adolescence stage of puberty, which then maintained throughout an individual middle age for some decades and subsequently begins to loss upon aging. Bone tissue undergoes continuous process of resorption and formation throughout in an individual lifetime. Osteoporosis occurs when bone resorption rate exceeds the bone formation rate, resulting in a net loss of bone [39]. Studies revealed that osteoporosis incidences may be linked to bone mass-related genetic determinants including low-density lipoprotein receptor-related protein 5 (LRP5), osteoprotegerin (OPG), sclerostin (SOST), estrogen receptor 1, and the receptor activator of RANK/

Receptor activator of nuclear factor kappa-Β ligand (RANKL) binds to the receptor activator of nuclear factor κB (RANK) that is present on the surface of the osteoclast mononuclear precursor cells and facilitates the formation of fully differentiated osteoclasts [41]. The expression of mirR-503 is significantly reduced in progenitors of osteoclasts-CD14+ peripheral blood mononuclear cells (PBMCs) of postmenopausal osteoporosis patients compared to healthy postmenopausal controls. The overexpression of miR-503 in human PBMCs had dramatically inhibited RANKL-induced osteoclast differentiation in PBMCs of postmenopausal osteoporosis samples. *In vivo* transfection of miR-503 silencing antagomir into a postmenopausalstimulated ovariectomized (OVX) mice resulted in the increase in RANK protein expression, an increase of bone resorption rate, a decrease in bone mass, and an aggravation of bone loss. Contrastingly, the transfection of the OVX mice with miR-503 overexpressing pre-miR-503 leads to the decrease in RANK protein expression and thus a decrease in bone resorption and an increase in bone mass. Therefore, it is suggested that the low miR-503 expression in postmenopausal osteoporosis patients will promote RANKL-induced osteoclastogenesis, and

consequently, bone resorption rate will increase leading to net bone loss [42].

sis pathogenesis through the regulation of Runx2 action [44].

MiR-221 expression is downregulated in postmenopausal osteoporotic bone samples compared to nonosteoporotic bones. In BMP-2-induced osteoblastogenesis, the overexpression of miR-221 resulted in reduced expression of key osteoblast markers, including osteocalcin (OC), alkaline phosphatase (ALP), and collagen type Iα 1 (COL1A1), whereas knockdown of miR-221 promoted the activity of OC, ALP, and COL1A1 [43]. The later study identified Runx2 as a potential target of miR-221. Therefore, this provided an evidence that miR-221 serves as the negative regulator of osteoblast differentiation and contributes to the osteoporo-

Tumor necrosis factor α (TNF-α) inhibits MSC osteogenic differentiation and bone formation in estrogen deficiency-induced osteoporosis with a poorly understood mechanism. A study conducted by Yang et al. showed that the expression of miR-21 is dramatically downregulated in mesenchymal stem cells (MSCs), and this downregulation is due to the suppression by TNF-α during the osteogenesis of MSCs. Moreover, miR-21 has been proved to stimulate the osteoblast differentiation of MSCs by targeting protein sprouty homolog 1 (Spry1), a negative regulator of osteoblast differentiation from MSCs. The later study also demonstrated that the overexpression of miR-21 is able to partially rescue the osteogenic impairment induced by

NF-κB signaling pathway [40].

84 Transcriptional and Post-transcriptional Regulation

Osteogenesis imperfecta (OI) is a heterogeneous group of inherited connective tissue disorder that occurs in about 1 in 10,000 to 20,000 live births [47]. OI is characterized with clinical features such as susceptibility to bone fractures due to low bone mass, reduced bone strength, or quality and bone deformity [48]. In addition, blue sclerae, short stature, dentinogenesis imperfecta (DI), and hearing loss are other clinical manifestations of OI [49]. The pathogenesis of OI involves the most prevalent autosomal dominant mutation of COL1A1 and COL1A2 genes encoding the alpha1 and alpha2 chains of type I procollagen [50]. Type I procollagen is the major bone structural protein, and therefore, the mutation of COL1A1 and COL1A2 genes may have direct link with serious defects or abnormalities including deformities of collagen primary structure, insufficient bone collagen quantity, deviated posttranslational modification, folding, intracellular transport or matrix incorporation, and bone mineralization. Recessive OI is caused by defects in genes that encode for protein products, which interact with type I collagen [51]. There are four well characterized types (I, II, III, and IV) of COL1A1/ COL1A2-linked OI based on different clinical and genetic presentations [52].

Wang et al. performed the preliminary screening of more than 100 bone-related miRNAs in serum of 22 OI patients. The results showed that three miRNAs (miR-26a, miR-30e, and miR-21) were upregulated and eight miRNAs (miR-34c, miR-29a, miR-29b, miR-489, miR-133a, miR-145, miR-210, and miR-1297) were downregulated in OI patients compared to healthy controls. MiR-29a has a universal lower level in the patient group, whereas miR-26a had a universal upper level. This discovery of altered expression of bone-related miRNAs in OI patients' serum profile may become promising miRNA biomarkers for the diagnosis of OI. Although this study did not verify on the relationships of these differentially expressed miRNAs and their potential target genes, the previous studies have showed that these miR-NAs may target a range of gene involved in osteogenic signaling pathways such as BMP, Wnt, RANKL, and TGFβ/activin [53].

MiR-29b has been shown to modulate osteoblast differentiation by downregulating the activity of COL1A1, COL5A3, and COL4A2 and attenuate the collagen protein accumulation during the mineralization phase of bone formation [24]. Kaneto et al. performed a sequence analysis on the coding region and intron/exon junctions of COL1A1 and COL1A2 genes in five independent patients with type I and type III OI. The sequence analysis has identified eight novel mutations, which may contribute to OI phenotype. Interestingly, Kaneto et al. also determined that the expression levels of COL1A1 and miR-29b are reduced in both type I and type III OI patients. Therefore, it is speculated that miR-29b expression is not an essential for sustaining osteoblastogenesis [54].

magic bullet. The side effects arise from current conventional treatments of bone cancer that also lead to the path of translating the bone cancer miRNA-based therapeutic approaches

MicroRNAs in Bone Diseases: Progress and Prospects http://dx.doi.org/10.5772/intechopen.79275 87

MRX34, a miRNA mimic encapsulated by liposomal nanoparticle developed by Mirna Therapeutics, appeared as the first miRNA mimic that had reached phase 1 clinical study in year 2013 for the treatment of primary liver cancer and other malignancies including multiple myeloma through functional restoration of endogenous miR-34a as an oncosuppressor (ClinicalTrials.gov Identifier: NCT01829971) [60]. MiR-34a is often suppressed or showed to reduce expression in various cancer types, coupled with the loss of p53 function that transcriptionally control its expression [61]. There are a wide varieties of oncogenes such as cyclin-dependent kinase (CDK) 4/6, Wnt 1/3, B-cell lymphoma 2 (BCL2), MYC, cyclin D1 (CCND1), CD44, and histone deacetylase 1 (HDAC1) that are responsible for unregulated cell cycle progression and proliferation, anti-apoptosis, metastasis, chemoresistance, cancer cell self-renewal, and oncogenic transcription, which can be downregulated by miR-34a [62, 63]. In a phase I clinical trial, adult patients with advanced solid tumors refractory to standard conventional treatment were given a standard 3 + 3 dose escalation trial by which MRX34 was infused to the patients twice a week (BIW) for a period of 3 weeks in a four-week-cycle. The phase 1 results showed that MRX34 has a tolerable toxicity or safety profile and supportive evidence of anti-tumor activity in a subset of patients with refractory advanced solid tumors. The patients generally experienced mild adverse effects such as fever, fatigue, back pain, nau-

To date, there has been no available miRNA-based diagnostic tests or treatments for bone cancers' management. However, miR-34 anti-tumor activity had been demonstrated in numerous cancer types including bone cancer and multiple myeloma, and therefore, providing a fascinating insight into the introduction of miR-34a mimic for the treatment of bone cancers. The expression of tumor suppressive mir-34 and miR-122 are downregulated in osteosarcoma cells contrasting to healthy normal cells. Xiao et al. has introduced miRNA response elements (MREs) of miR 34 and miR 122 in osteosarcoma cells through the employment of adenovirus to enable the selective expression of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL). This study reported that the adenovirus (Ad) TRAIL-34-122 resulted in higher apoptotic and cytotoxicity levels in the osteosarcoma cells, compared to the normal cells by selectively expressing TRAIL in miR-34 and miR-122 modulated fashion. The following *in vivo* study in BALB/c nude mice further indicated that Ad-TRAIL-34-122 is able to reduce osteosarcoma xenografts' growth without causing significant liver toxicity [65]. Additionally, Gaur et al. reported that chitosan nanoparticle-mediated delivery of miR-34a mimic preserves bone integrity and reduces tumor growth in a tumor established, intrafemoral nude mice

Furthermore, Martino et al. has evaluated the activity of synthetic miR-34a in multiple myeloma cells. This study demonstrated that transfection with miR-34a mimic tends to inactivate the early expression of prosurvival and proliferative kinases Erk-2 and Akt. The reduced expression of Erk-2 and Akt is followed by the downregulation of caspase-6/3 expression, which can next induce apoptosis in multiple myeloma cells. Martino et al. subsequently tested the efficiency of miR-34a mimic delivery by encapsulating the mimic in stable nucleic acid

from the benchworks to the clinical settings.

sea, anorexia, diarrhea, and vomiting after the treatment [64].

model that represented prostate cancer bone metastasis [66].

#### **3.4. Enlarged, weak bone deformation: Paget's disease of bone**

Paget's disease of bone (PDB) is a localized disorder of highly exaggerated bone turnover characterized by excessive bone resorption action by osteoclasts within pagetic lesions, followed by an increase in disorganized new bone formation by osteoblasts [55]. This action will eventually result in marrow fibrosis, highly vascular, weak, enlarged, and disorganized bone deformation [55, 56]. The highly fibrous woven bone with reduced mechanical strength and disorganized structural integrity tends to increase the risk of bone deformity and fracture [56]. Frequently, PDB patients are elderly aged more than 50 years and tend to slightly predominate in males [57]. Mutations in genes encoding for the components that modulate the RANK/ NF-κB signaling pathway are most likely to contribute to the development of PDB. These genes are sequestosome 1 gene (SQSTM1), tumor necrosis factor receptor superfamily member IIA (TNFRSF11A), valosine-containing protein (VCP), and tumor necrosis factor receptor superfamily member IIB (TNFRSF11B) [55].

However, the regulatory roles of miRNAs in PDB remain unknown. Bianciardi et al. performed a serum miRNA expression profile in peripheral blood mononuclear cells (PBMCs) from 20 PDB patients. The results showed that 22 miRNAs were significantly upregulated with a fold change above three (miR-31, miR-32, miR-124a, miR-132, miR-182, miR-221, miR-339, miR-345, miR-410, miR-451, miR-485.3p) or between 2 and 3 (miR-19a, miR-30b, miR-30c, miR-27a, miR-125a, miR-146a, miR-148a, miR-200c, miR-223, miR-301, miR-365) when compared to nonpagetic controls. Among the 22 miRNAs, these 14 miRNAs (miR-19a, miR-miR-27a, miR-30c, miR-32, miR-125a, miR-132, miR-200c, miR-221, miR-223, miR-301, miR-345, miR-365, miR-410, and miR-485-3p) showed significantly higher expression in patients that experienced Q16STM1 mutation [58].

## **4. Current status and perspectives of microRNA in bone cancer diagnosis and therapy**

In 2010, the first microRNA-targeting drug—miravirsen (SPC3649), a locked nucleic acid (LNAs) ribonucleotides antagomir that targets miR-122 had entered clinical trial and is currently in phase II clinical trial to treat chronic hepatitis C (HCV+) patients (ClinicalTrials.gov Identifier: NCT02508090) [59]. The occurrence of the first miRNA-based clinical trial had led to the insight that miRNAs can serve as promising therapeutic tools and perhaps as the next magic bullet. The side effects arise from current conventional treatments of bone cancer that also lead to the path of translating the bone cancer miRNA-based therapeutic approaches from the benchworks to the clinical settings.

MiR-29b has been shown to modulate osteoblast differentiation by downregulating the activity of COL1A1, COL5A3, and COL4A2 and attenuate the collagen protein accumulation during the mineralization phase of bone formation [24]. Kaneto et al. performed a sequence analysis on the coding region and intron/exon junctions of COL1A1 and COL1A2 genes in five independent patients with type I and type III OI. The sequence analysis has identified eight novel mutations, which may contribute to OI phenotype. Interestingly, Kaneto et al. also determined that the expression levels of COL1A1 and miR-29b are reduced in both type I and type III OI patients. Therefore, it is speculated that miR-29b expression is not an essential for

Paget's disease of bone (PDB) is a localized disorder of highly exaggerated bone turnover characterized by excessive bone resorption action by osteoclasts within pagetic lesions, followed by an increase in disorganized new bone formation by osteoblasts [55]. This action will eventually result in marrow fibrosis, highly vascular, weak, enlarged, and disorganized bone deformation [55, 56]. The highly fibrous woven bone with reduced mechanical strength and disorganized structural integrity tends to increase the risk of bone deformity and fracture [56]. Frequently, PDB patients are elderly aged more than 50 years and tend to slightly predominate in males [57]. Mutations in genes encoding for the components that modulate the RANK/ NF-κB signaling pathway are most likely to contribute to the development of PDB. These genes are sequestosome 1 gene (SQSTM1), tumor necrosis factor receptor superfamily member IIA (TNFRSF11A), valosine-containing protein (VCP), and tumor necrosis factor receptor

However, the regulatory roles of miRNAs in PDB remain unknown. Bianciardi et al. performed a serum miRNA expression profile in peripheral blood mononuclear cells (PBMCs) from 20 PDB patients. The results showed that 22 miRNAs were significantly upregulated with a fold change above three (miR-31, miR-32, miR-124a, miR-132, miR-182, miR-221, miR-339, miR-345, miR-410, miR-451, miR-485.3p) or between 2 and 3 (miR-19a, miR-30b, miR-30c, miR-27a, miR-125a, miR-146a, miR-148a, miR-200c, miR-223, miR-301, miR-365) when compared to nonpagetic controls. Among the 22 miRNAs, these 14 miRNAs (miR-19a, miR-miR-27a, miR-30c, miR-32, miR-125a, miR-132, miR-200c, miR-221, miR-223, miR-301, miR-345, miR-365, miR-410, and miR-485-3p) showed significantly higher expression in patients that experienced Q16STM1

**4. Current status and perspectives of microRNA in bone cancer** 

In 2010, the first microRNA-targeting drug—miravirsen (SPC3649), a locked nucleic acid (LNAs) ribonucleotides antagomir that targets miR-122 had entered clinical trial and is currently in phase II clinical trial to treat chronic hepatitis C (HCV+) patients (ClinicalTrials.gov Identifier: NCT02508090) [59]. The occurrence of the first miRNA-based clinical trial had led to the insight that miRNAs can serve as promising therapeutic tools and perhaps as the next

sustaining osteoblastogenesis [54].

86 Transcriptional and Post-transcriptional Regulation

superfamily member IIB (TNFRSF11B) [55].

mutation [58].

**diagnosis and therapy**

**3.4. Enlarged, weak bone deformation: Paget's disease of bone**

MRX34, a miRNA mimic encapsulated by liposomal nanoparticle developed by Mirna Therapeutics, appeared as the first miRNA mimic that had reached phase 1 clinical study in year 2013 for the treatment of primary liver cancer and other malignancies including multiple myeloma through functional restoration of endogenous miR-34a as an oncosuppressor (ClinicalTrials.gov Identifier: NCT01829971) [60]. MiR-34a is often suppressed or showed to reduce expression in various cancer types, coupled with the loss of p53 function that transcriptionally control its expression [61]. There are a wide varieties of oncogenes such as cyclin-dependent kinase (CDK) 4/6, Wnt 1/3, B-cell lymphoma 2 (BCL2), MYC, cyclin D1 (CCND1), CD44, and histone deacetylase 1 (HDAC1) that are responsible for unregulated cell cycle progression and proliferation, anti-apoptosis, metastasis, chemoresistance, cancer cell self-renewal, and oncogenic transcription, which can be downregulated by miR-34a [62, 63]. In a phase I clinical trial, adult patients with advanced solid tumors refractory to standard conventional treatment were given a standard 3 + 3 dose escalation trial by which MRX34 was infused to the patients twice a week (BIW) for a period of 3 weeks in a four-week-cycle. The phase 1 results showed that MRX34 has a tolerable toxicity or safety profile and supportive evidence of anti-tumor activity in a subset of patients with refractory advanced solid tumors. The patients generally experienced mild adverse effects such as fever, fatigue, back pain, nausea, anorexia, diarrhea, and vomiting after the treatment [64].

To date, there has been no available miRNA-based diagnostic tests or treatments for bone cancers' management. However, miR-34 anti-tumor activity had been demonstrated in numerous cancer types including bone cancer and multiple myeloma, and therefore, providing a fascinating insight into the introduction of miR-34a mimic for the treatment of bone cancers.

The expression of tumor suppressive mir-34 and miR-122 are downregulated in osteosarcoma cells contrasting to healthy normal cells. Xiao et al. has introduced miRNA response elements (MREs) of miR 34 and miR 122 in osteosarcoma cells through the employment of adenovirus to enable the selective expression of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL). This study reported that the adenovirus (Ad) TRAIL-34-122 resulted in higher apoptotic and cytotoxicity levels in the osteosarcoma cells, compared to the normal cells by selectively expressing TRAIL in miR-34 and miR-122 modulated fashion. The following *in vivo* study in BALB/c nude mice further indicated that Ad-TRAIL-34-122 is able to reduce osteosarcoma xenografts' growth without causing significant liver toxicity [65]. Additionally, Gaur et al. reported that chitosan nanoparticle-mediated delivery of miR-34a mimic preserves bone integrity and reduces tumor growth in a tumor established, intrafemoral nude mice model that represented prostate cancer bone metastasis [66].

Furthermore, Martino et al. has evaluated the activity of synthetic miR-34a in multiple myeloma cells. This study demonstrated that transfection with miR-34a mimic tends to inactivate the early expression of prosurvival and proliferative kinases Erk-2 and Akt. The reduced expression of Erk-2 and Akt is followed by the downregulation of caspase-6/3 expression, which can next induce apoptosis in multiple myeloma cells. Martino et al. subsequently tested the efficiency of miR-34a mimic delivery by encapsulating the mimic in stable nucleic acid lipid particles (SNALPs). SNALP-encapsulated miR-34a mimic is highly efficient with its antitumor activity in both multiple myeloma cells and in *in vivo* SCID mice bearing human multiple myeloma xenografts by showing reduced expression of miR-34a target notch 1 homolog (NOTCH1) and the absence of cytotoxicity effect [67].

Li et al. identified potential miRNA biomarkers for the early diagnosis and relapse prediction of osteosarcoma by developing a serum-based miRNA profile. All the putative miRNAs were verified through RT-qPCR, and the expression of seven miRNAs (miR-106a-5p, miR-16-5p, miR-20a-5p, miR-425-5p, miR-451a, miR-25-3p, and miR-139-5p) was found to be downregulated in the serum of OS patients compared to the healthy control. These miRNAs are also correlated with other type of cancer pathogeneses such as lung carcinoma, colorectal carcinoma,

MicroRNAs in Bone Diseases: Progress and Prospects http://dx.doi.org/10.5772/intechopen.79275 89

Yuan et al. demonstrated that miR-21 expression was significantly higher in serum from osteosarcoma patients compared to healthy controls as measured by RT-qPCR. The high expression of miR-21 is associated with aggressive Enneking tumor staging, neoadjuvant chemotherapeutic resistance, and reduced overall survival rate [71]. Previous studies indicated that miR-21 has influences on the cell proliferation, cell cycle progression, tumor metastatic behavior, and susceptibility to chemotherapeutic treatment [43, 72–74]. These tumor-promoting behaviors of miR-21 was due to its targeting regulatory roles on a vast number of tumor suppressive genes such as phosphatase and tensin homolog protein (PTEN) [72], myristoylated alanine-rich protein kinase C substrate protein (MARCKS) [43], programmed cell death 4 protein (PDCD4) [73], and cell division cycle 25 homolog A protein (CDC25A) [74].

Dong et al. showed that expression of miR-223 was significantly reduced in the serum of osteosarcoma patients and osteosarcoma cell lines compared to healthy controls as measured by RT-qPCR. Osteosarcoma patients with lower expression of serum miR-223 tend to have distant metastasis, more advanced clinical stages, and shorter survival time [75]. Furthermore, it has been demonstrated that miR-223 may play an important role in the regulation of epithelial cell transforming sequence 2 (Ect2) signaling, an important pathway for osteosarcoma pathogenesis in terms of cell cycle progression, proliferation, recurrence, and poor chemo-

Lian et al. performed TaqMan low-density array (TLDA) and RT-qPCR on plasma samples derived from osteosarcoma patients before surgery, patients after 1 month of surgery and healthy individuals. The results showed that four plasma miRNAs (miR-195-5p, miR-199a-3p, miR-320a, and miR-374a-5p) were significantly upregulated in the presurgical osteosarcoma patients. The expression level of these four plasma miRNAs were decreased after surgical removal of the tumors, suggesting the potential of these miRNAs as the biomarkers for osteosarcoma. Additionally, circulating miR-195-5p and miR-199a-3p were correlated with metastasis status whereas miR-199a-3p and miR-320a were correlated with histological subtype [77]. Besides, it has been discovered that miR-195-5p involved in the inhibition of osteosarcoma cell migration and invasion by targeting fatty acid synthase (FASN) [78], while miR-199a-3p regulated the p53 signaling pathway and inhibits osteosarcoma cell growth, migration, and

Growing lists of *in vitro* and *in vivo* studies on the regulatory roles of microRNAs in bone disorders, which conducted by various research teams, have supported miRNAs as the potential therapeutics candidates. However, specific, efficient, and safe delivery of miRNA to its target

breast carcinoma, nasopharyngeal carcinoma, etc. [70].

therapeutic responses [76].

induce apoptosis [79, 80].

**5.2. MicroRNAs as therapeutic agents or targets**

## **5. Future prospects of microRNAs in the treatment of bone disorders and its potential**

Although the publication of research findings on microRNAs in bone disorders are still limited, the fast-growing list of literatures indicates the significance of miRNAs in the regulation of bone biology and bone disorders. This has led to the advancement of research to explore potential relevance of miRNAs as diagnostic biomarkers and therapeutics. In this section, the potential of miRNAs as the biomarkers and therapeutic agents will be focused on cancerrelated bone disorder (osteosarcoma) and noncancer-related bone disorder (osteoporosis).

#### **5.1. MicroRNAs as diagnostic biomarkers**

The comprehensive expression profile of key microRNAs in different bone disorders has the potential to increase the accuracy of the prognosis and diagnosis of bone disorders in combination with other conventional diagnostic approaches.

Hu et al. reported that a total of 268 miRNAs were dramatically dysregulated between human osteosarcoma cell line, MG-63, and human osteoblast HOB cell line. Five miRNAs (miR-9, miR-99, miR-195, miR-148a, and miR-181a) were validated to be overexpressed and four of these miRNAs (miR-143, miR-145, miR-335, and miR-539) were validated to be downregulated in the human OS MG-63 cell lines compared to osteoblast HOB cell lines. The bioinformatics analysis showed that the target genes of these nine miRNAs are associated with multiple cancer-related events including cell proliferation, differentiation, cell cycle, apoptosis, signaling, migration, and invasion [68].

Another study by Jones et al. using pretreatment biopsy samples from conventional (osteoblastic/fibroblastic) osteosarcoma patients and control samples of healthy bone tissue showed that 34 miRNAs were significantly dysregulated with 11 having higher expression and 23 having lower expression among the osteosarcoma group. MiR-181a and miR-181b were the most upregulated miRNAs in osteosarcoma group while miR-29b, miR-451, and miR-16 were among the most downregulated. The miRNA signature profile in the sample of metastatic osteosarcoma group compared to nonmetastatic osteosarcoma group showed that higher expression of miR-27a and miR-181c\* was found in patients with metastatic tumor. Additionally, higher expression of miR-451 and miR-15b was associated with chemosensitive patients compared to chemoresistant samples. *In vitro* and *in vivo* functional validation in osteosarcoma cell lines confirmed the tumor suppressive role of miR-16 and the pro-metastatic role of miR-27a. The analysis of target genes of these miRNAs indicated that these miRNAs may target several known osteosarcoma-related genes that regulate transcription, cell cycle control, and cancer signaling pathways [69].

Li et al. identified potential miRNA biomarkers for the early diagnosis and relapse prediction of osteosarcoma by developing a serum-based miRNA profile. All the putative miRNAs were verified through RT-qPCR, and the expression of seven miRNAs (miR-106a-5p, miR-16-5p, miR-20a-5p, miR-425-5p, miR-451a, miR-25-3p, and miR-139-5p) was found to be downregulated in the serum of OS patients compared to the healthy control. These miRNAs are also correlated with other type of cancer pathogeneses such as lung carcinoma, colorectal carcinoma, breast carcinoma, nasopharyngeal carcinoma, etc. [70].

lipid particles (SNALPs). SNALP-encapsulated miR-34a mimic is highly efficient with its antitumor activity in both multiple myeloma cells and in *in vivo* SCID mice bearing human multiple myeloma xenografts by showing reduced expression of miR-34a target notch 1 homolog

**5. Future prospects of microRNAs in the treatment of bone disorders** 

Although the publication of research findings on microRNAs in bone disorders are still limited, the fast-growing list of literatures indicates the significance of miRNAs in the regulation of bone biology and bone disorders. This has led to the advancement of research to explore potential relevance of miRNAs as diagnostic biomarkers and therapeutics. In this section, the potential of miRNAs as the biomarkers and therapeutic agents will be focused on cancerrelated bone disorder (osteosarcoma) and noncancer-related bone disorder (osteoporosis).

The comprehensive expression profile of key microRNAs in different bone disorders has the potential to increase the accuracy of the prognosis and diagnosis of bone disorders in combi-

Hu et al. reported that a total of 268 miRNAs were dramatically dysregulated between human osteosarcoma cell line, MG-63, and human osteoblast HOB cell line. Five miRNAs (miR-9, miR-99, miR-195, miR-148a, and miR-181a) were validated to be overexpressed and four of these miRNAs (miR-143, miR-145, miR-335, and miR-539) were validated to be downregulated in the human OS MG-63 cell lines compared to osteoblast HOB cell lines. The bioinformatics analysis showed that the target genes of these nine miRNAs are associated with multiple cancer-related events including cell proliferation, differentiation, cell cycle, apoptosis, signal-

Another study by Jones et al. using pretreatment biopsy samples from conventional (osteoblastic/fibroblastic) osteosarcoma patients and control samples of healthy bone tissue showed that 34 miRNAs were significantly dysregulated with 11 having higher expression and 23 having lower expression among the osteosarcoma group. MiR-181a and miR-181b were the most upregulated miRNAs in osteosarcoma group while miR-29b, miR-451, and miR-16 were among the most downregulated. The miRNA signature profile in the sample of metastatic osteosarcoma group compared to nonmetastatic osteosarcoma group showed that higher expression of miR-27a and miR-181c\* was found in patients with metastatic tumor. Additionally, higher expression of miR-451 and miR-15b was associated with chemosensitive patients compared to chemoresistant samples. *In vitro* and *in vivo* functional validation in osteosarcoma cell lines confirmed the tumor suppressive role of miR-16 and the pro-metastatic role of miR-27a. The analysis of target genes of these miRNAs indicated that these miRNAs may target several known osteosarcoma-related genes that regulate transcription,

(NOTCH1) and the absence of cytotoxicity effect [67].

88 Transcriptional and Post-transcriptional Regulation

**5.1. MicroRNAs as diagnostic biomarkers**

ing, migration, and invasion [68].

nation with other conventional diagnostic approaches.

cell cycle control, and cancer signaling pathways [69].

**and its potential**

Yuan et al. demonstrated that miR-21 expression was significantly higher in serum from osteosarcoma patients compared to healthy controls as measured by RT-qPCR. The high expression of miR-21 is associated with aggressive Enneking tumor staging, neoadjuvant chemotherapeutic resistance, and reduced overall survival rate [71]. Previous studies indicated that miR-21 has influences on the cell proliferation, cell cycle progression, tumor metastatic behavior, and susceptibility to chemotherapeutic treatment [43, 72–74]. These tumor-promoting behaviors of miR-21 was due to its targeting regulatory roles on a vast number of tumor suppressive genes such as phosphatase and tensin homolog protein (PTEN) [72], myristoylated alanine-rich protein kinase C substrate protein (MARCKS) [43], programmed cell death 4 protein (PDCD4) [73], and cell division cycle 25 homolog A protein (CDC25A) [74].

Dong et al. showed that expression of miR-223 was significantly reduced in the serum of osteosarcoma patients and osteosarcoma cell lines compared to healthy controls as measured by RT-qPCR. Osteosarcoma patients with lower expression of serum miR-223 tend to have distant metastasis, more advanced clinical stages, and shorter survival time [75]. Furthermore, it has been demonstrated that miR-223 may play an important role in the regulation of epithelial cell transforming sequence 2 (Ect2) signaling, an important pathway for osteosarcoma pathogenesis in terms of cell cycle progression, proliferation, recurrence, and poor chemotherapeutic responses [76].

Lian et al. performed TaqMan low-density array (TLDA) and RT-qPCR on plasma samples derived from osteosarcoma patients before surgery, patients after 1 month of surgery and healthy individuals. The results showed that four plasma miRNAs (miR-195-5p, miR-199a-3p, miR-320a, and miR-374a-5p) were significantly upregulated in the presurgical osteosarcoma patients. The expression level of these four plasma miRNAs were decreased after surgical removal of the tumors, suggesting the potential of these miRNAs as the biomarkers for osteosarcoma. Additionally, circulating miR-195-5p and miR-199a-3p were correlated with metastasis status whereas miR-199a-3p and miR-320a were correlated with histological subtype [77]. Besides, it has been discovered that miR-195-5p involved in the inhibition of osteosarcoma cell migration and invasion by targeting fatty acid synthase (FASN) [78], while miR-199a-3p regulated the p53 signaling pathway and inhibits osteosarcoma cell growth, migration, and induce apoptosis [79, 80].

#### **5.2. MicroRNAs as therapeutic agents or targets**

Growing lists of *in vitro* and *in vivo* studies on the regulatory roles of microRNAs in bone disorders, which conducted by various research teams, have supported miRNAs as the potential therapeutics candidates. However, specific, efficient, and safe delivery of miRNA to its target sites is crucial for the translation of miRNA-based therapeutics strategies. Effective delivery systems in various bone disorder models had been observed by the application of biomaterial constructs, viral vectors, nanoparticles, and polymers with the potential to restore the normal functions of bone homeostasis and carcinogenesis.

inhibit osteosarcoma cell proliferation and apoptosis. The results showed that DDP and MTX induce apoptosis and inhibit the cell cycle of osteosarcoma cell lines at a greater efficiency in miR-126 overexpressing manner. Nonetheless, DDP and MTX did not significantly impact the apoptosis and cell proliferation in the miR-126 silenced group. On that account, it is suggested that miR-126 may strengthen the sensitivity of osteosarcoma cell to DDP and MTX. However,

MicroRNAs in Bone Diseases: Progress and Prospects http://dx.doi.org/10.5772/intechopen.79275 91

Cai et al. developed polyurethane (PU) nanomicelles drug carrier modified with Asp8 acidic peptide (Asp8-PU-anti-miR214) for targeted delivery of anti-miR-214. Polyurethane (PU) is a linear polymer composed of organic units molecularly linked by carbamate (urethane) group [85]. Besides, it is known that PU tends to have high compatibility in living system by not being toxic or reactive and have high mechanical flexibility [85–88]. The highly negatively charged peptide Asp8 has also been accounted as an excellent targeting tool of bone resorption area [89]. In this study, miR-214 was chosen due to its regulatory role in bone remodeling by which the elevated expression *in vivo* was associated with reduced bone formation in aged patients. This is due to the direct targeting action of miR-214 on activating transcription factor 4 (ATF4), which enable the inhibition of osteoblast activity [90]. Apart from that, miR-214 also modulates osteoclast differentiation by targeting the PTEN-PI3k-Akt pathway [91]. Asp8-PU-anti-miR214 delivery system to osteoclasts at the bone resorption surface of ovariectomized (OVX) osteoporosis mice model was able to improve the bone microarchitecture, increased bone mass, and decreased osteoclast number. Above and beyond, a number of osteoclast-related genes including tryptophan RNA-binding attenuation protein (TRAP) and cathepsin K (CTSK) were successfully downregulated by the anti-miR-214. Interestingly, Asp8-PU-anti-miR214 was also proven as a potential drug delivery candidate that does not overt toxicity or elicit an immune response. Therefore, Asp8-PU serves as a potential bone-resorption surface-targeting delivery system for the treatment of postmenopausal osteoporosis and osteoclast-stimulated bone disorders [85].

Zhang et al. designed a hyperbranched polymer (HP) and miR-26a (HP/miRNA) nanosized polyplexes, which were encapsulated in biodegradable microspheres to overcome problems with uncontrolled release and achieved the controllable two-stage delivery strategy (microspheres and polyplexes). Microspheres attach to cell-free nanofibrous polymer 3D scaffolds to prevent off-target effects of the miRNA delivery. The 3D scaffolds were implanted into osteoporotic mice model, and the results showed that this technology was able to regenerate critical-sized bone with low cytotoxicity effect by targeting glycogen synthase kinase 3 beta

Overexpression of miR-140\* and miR-214 was detected in bone marrow-derived MSCs isolated from ovariectomized rats (OVX-BMSCs). Li et al. demonstrated that engineered OVX-BMSCs expressing the hybrid baculovirus-mediated miRNA sponges can continuously antagonize cellular miR-140\* and miR-214 levels *in vitro*. At the same time, the attenuation of miR-140\* and miR-214 expression can also efficiently support the osteogenesis of OVX-BMSCs and intensify the capability of OVX-BMSCs to suppress osteoclast maturation. Remarkably, the osteoinductive effect of suppressing miR-214 was more potent compared to miR-140\* suppression. This study also discovered that the allotransplantation of miR-214 sponges-expressing OVX-BMSCs in osteoporotic rat models with a femoral metaphysis found with critical-size bone defect was able to improve the likelihood of bone healing, remodeling,

(Gsk-3β) to activate the osteoblastic activity of endogenous stem cells [92].

the regulatory mechanisms behind this process still remain to be discovered [84].

The expression of miR-199a-3p, which may inhibit tumor cell growth, is reduced in osteosarcoma cells. Zhang et al. developed a lipid-modified dextran-based polymeric nanoparticle platform for encapsulation of miR-199a-3p and another potent tumor suppressive miRNA, let-7a, and transfected into osteosarcoma cells lines, KHOS and U-2OS. Western blot analysis and 3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide (MTT) assay showed that dextran nanoparticles loaded with miRNAs could efficiently downregulate the expression of mechanistic target of rapamycin (mTOR) and Met proteins and effectively inhibit the growth and proliferation of osteosarcoma cells [81].

MiR-143 expression is downregulated in 143B human osteosarcoma cell line, an osteosarcoma cell line with high metastatic tendency to the lung. Osaki et al. inoculated the 143B osteosarcoma cells transfected with firefly luciferase gene (143B-luc) into athymic mice in order to develop a primary tumor and spontaneous lung metastasis. Then, systemic administration of miR-143 mimic and miR-negative control 1 (NC1) mixed with atelocollagen was performed on the osteosarcoma mice model to study the therapeutic potential of miR-143 against spontaneous lung metastasis of osteosarcoma. After 1 week, the luciferase signal was detected only at the right knee primary lesion where 143B-luc cells were inoculated. After 2 weeks, one out of four mice administered with miR-NC1 was detected with luciferase signal at the pulmonary area indicating lung metastasis, whereas no luciferase signal was observed in mice injected with miR-143 mimic. After days 19–20, two out of 10 mice injected with the miR-NC1 control died due to lung metastasis. At third week, six of the eight live mice administered with miR-NC1 control were identified with lung metastasis, while contrastingly, only two out of 10 mice injected with miR-143 mimic displayed lung metastasis. Furthermore, the tumor weight and the expression of proliferative cell nuclear antigen in primary tumor showed no significant difference between both groups (miR-143 mimic and miR-NC1 control). Therefore, all these data showed that miR-143 mimic suppresses lung metastasis from a primary tumor but did not have effect on the primary tumor cell proliferation. Additionally, it is speculated that the downregulation of miR-143 may promote lung metastasis of human osteosarcoma cells by promoting MMP-13 upregulation [82]. Shimbo et al. introduced synthetic miR-143 into MSC cells and increased the amount of exosome-formed miR-143 in the conditioned medium. The transfection of 143B osteosarcoma cell lines with extracellular miR-143 in the conditioned medium from MSCs (exosome-formed miR-143) reduced the migration ability of osteosarcoma cells compared to the control. In addition, Shimbo et al. also showed that the transfection efficiency of exosome-formed miR-143 was less than that attained with the lipofection. Nevertheless, migration assay performed on the 143B osteosarcoma cells showed that the inhibitory effect on cell migration was similar between exosome and lipofection method [83].

Jiang et al. constructed lentiviral vectors overexpressing and silencing miR-126. Both of the miR 126 overexpressing and silencing lentiviral vectors were then transfected into MG63 and U-2 OS osteosarcoma cell lines. This study aimed to determine the interlink between cisplatin (DDP) and methotrexate (MTX) osteosarcoma chemotherapeutic drugs and miR-126 on the effect to inhibit osteosarcoma cell proliferation and apoptosis. The results showed that DDP and MTX induce apoptosis and inhibit the cell cycle of osteosarcoma cell lines at a greater efficiency in miR-126 overexpressing manner. Nonetheless, DDP and MTX did not significantly impact the apoptosis and cell proliferation in the miR-126 silenced group. On that account, it is suggested that miR-126 may strengthen the sensitivity of osteosarcoma cell to DDP and MTX. However, the regulatory mechanisms behind this process still remain to be discovered [84].

sites is crucial for the translation of miRNA-based therapeutics strategies. Effective delivery systems in various bone disorder models had been observed by the application of biomaterial constructs, viral vectors, nanoparticles, and polymers with the potential to restore the normal

The expression of miR-199a-3p, which may inhibit tumor cell growth, is reduced in osteosarcoma cells. Zhang et al. developed a lipid-modified dextran-based polymeric nanoparticle platform for encapsulation of miR-199a-3p and another potent tumor suppressive miRNA, let-7a, and transfected into osteosarcoma cells lines, KHOS and U-2OS. Western blot analysis and 3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide (MTT) assay showed that dextran nanoparticles loaded with miRNAs could efficiently downregulate the expression of mechanistic target of rapamycin (mTOR) and Met proteins and effectively inhibit the growth

MiR-143 expression is downregulated in 143B human osteosarcoma cell line, an osteosarcoma cell line with high metastatic tendency to the lung. Osaki et al. inoculated the 143B osteosarcoma cells transfected with firefly luciferase gene (143B-luc) into athymic mice in order to develop a primary tumor and spontaneous lung metastasis. Then, systemic administration of miR-143 mimic and miR-negative control 1 (NC1) mixed with atelocollagen was performed on the osteosarcoma mice model to study the therapeutic potential of miR-143 against spontaneous lung metastasis of osteosarcoma. After 1 week, the luciferase signal was detected only at the right knee primary lesion where 143B-luc cells were inoculated. After 2 weeks, one out of four mice administered with miR-NC1 was detected with luciferase signal at the pulmonary area indicating lung metastasis, whereas no luciferase signal was observed in mice injected with miR-143 mimic. After days 19–20, two out of 10 mice injected with the miR-NC1 control died due to lung metastasis. At third week, six of the eight live mice administered with miR-NC1 control were identified with lung metastasis, while contrastingly, only two out of 10 mice injected with miR-143 mimic displayed lung metastasis. Furthermore, the tumor weight and the expression of proliferative cell nuclear antigen in primary tumor showed no significant difference between both groups (miR-143 mimic and miR-NC1 control). Therefore, all these data showed that miR-143 mimic suppresses lung metastasis from a primary tumor but did not have effect on the primary tumor cell proliferation. Additionally, it is speculated that the downregulation of miR-143 may promote lung metastasis of human osteosarcoma cells by promoting MMP-13 upregulation [82]. Shimbo et al. introduced synthetic miR-143 into MSC cells and increased the amount of exosome-formed miR-143 in the conditioned medium. The transfection of 143B osteosarcoma cell lines with extracellular miR-143 in the conditioned medium from MSCs (exosome-formed miR-143) reduced the migration ability of osteosarcoma cells compared to the control. In addition, Shimbo et al. also showed that the transfection efficiency of exosome-formed miR-143 was less than that attained with the lipofection. Nevertheless, migration assay performed on the 143B osteosarcoma cells showed that the inhibitory effect on

cell migration was similar between exosome and lipofection method [83].

Jiang et al. constructed lentiviral vectors overexpressing and silencing miR-126. Both of the miR 126 overexpressing and silencing lentiviral vectors were then transfected into MG63 and U-2 OS osteosarcoma cell lines. This study aimed to determine the interlink between cisplatin (DDP) and methotrexate (MTX) osteosarcoma chemotherapeutic drugs and miR-126 on the effect to

functions of bone homeostasis and carcinogenesis.

90 Transcriptional and Post-transcriptional Regulation

and proliferation of osteosarcoma cells [81].

Cai et al. developed polyurethane (PU) nanomicelles drug carrier modified with Asp8 acidic peptide (Asp8-PU-anti-miR214) for targeted delivery of anti-miR-214. Polyurethane (PU) is a linear polymer composed of organic units molecularly linked by carbamate (urethane) group [85]. Besides, it is known that PU tends to have high compatibility in living system by not being toxic or reactive and have high mechanical flexibility [85–88]. The highly negatively charged peptide Asp8 has also been accounted as an excellent targeting tool of bone resorption area [89]. In this study, miR-214 was chosen due to its regulatory role in bone remodeling by which the elevated expression *in vivo* was associated with reduced bone formation in aged patients. This is due to the direct targeting action of miR-214 on activating transcription factor 4 (ATF4), which enable the inhibition of osteoblast activity [90]. Apart from that, miR-214 also modulates osteoclast differentiation by targeting the PTEN-PI3k-Akt pathway [91]. Asp8-PU-anti-miR214 delivery system to osteoclasts at the bone resorption surface of ovariectomized (OVX) osteoporosis mice model was able to improve the bone microarchitecture, increased bone mass, and decreased osteoclast number. Above and beyond, a number of osteoclast-related genes including tryptophan RNA-binding attenuation protein (TRAP) and cathepsin K (CTSK) were successfully downregulated by the anti-miR-214. Interestingly, Asp8-PU-anti-miR214 was also proven as a potential drug delivery candidate that does not overt toxicity or elicit an immune response. Therefore, Asp8-PU serves as a potential bone-resorption surface-targeting delivery system for the treatment of postmenopausal osteoporosis and osteoclast-stimulated bone disorders [85].

Zhang et al. designed a hyperbranched polymer (HP) and miR-26a (HP/miRNA) nanosized polyplexes, which were encapsulated in biodegradable microspheres to overcome problems with uncontrolled release and achieved the controllable two-stage delivery strategy (microspheres and polyplexes). Microspheres attach to cell-free nanofibrous polymer 3D scaffolds to prevent off-target effects of the miRNA delivery. The 3D scaffolds were implanted into osteoporotic mice model, and the results showed that this technology was able to regenerate critical-sized bone with low cytotoxicity effect by targeting glycogen synthase kinase 3 beta (Gsk-3β) to activate the osteoblastic activity of endogenous stem cells [92].

Overexpression of miR-140\* and miR-214 was detected in bone marrow-derived MSCs isolated from ovariectomized rats (OVX-BMSCs). Li et al. demonstrated that engineered OVX-BMSCs expressing the hybrid baculovirus-mediated miRNA sponges can continuously antagonize cellular miR-140\* and miR-214 levels *in vitro*. At the same time, the attenuation of miR-140\* and miR-214 expression can also efficiently support the osteogenesis of OVX-BMSCs and intensify the capability of OVX-BMSCs to suppress osteoclast maturation. Remarkably, the osteoinductive effect of suppressing miR-214 was more potent compared to miR-140\* suppression. This study also discovered that the allotransplantation of miR-214 sponges-expressing OVX-BMSCs in osteoporotic rat models with a femoral metaphysis found with critical-size bone defect was able to improve the likelihood of bone healing, remodeling, and bone quality at 4 weeks postimplantation. Moreover, co-expression of bone morphogenic protein 2 (BMP2) and miR-214 sponges in OVX-BMSCs can synergistically enhance the bone formation and healing in osteoporotic rats [93].

quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) and microarray analysis, and there is no standardized techniques to measure the miRNA expression levels [38]. Further techniques need to be optimized for better miRNA detection and analysis.

MicroRNAs in Bone Diseases: Progress and Prospects http://dx.doi.org/10.5772/intechopen.79275 93

Despite there are many challenges, the potentials of miRNA as a diagnostic tool and treatment for bone diseases look promising. We believe that in the next few years, researches will be able to develop efficient delivery methods of the miRNA to its specific target site with

As a conclusion, microRNA plays important roles in bone development and maintenance. MiRNA dysregulation leads to the pathogenesis of various bone diseases. Nowadays, miRNAs are being excavated as new directions for diagnostic biomarkers and drug targets to cure bone diseases. However, there are still many limitations and barriers for the development of miRNAbased biomarkers and therapeutics. Further investigations are needed to understand the miRNA gene regulation in bone and to overcome the challenges faced in miRNA delivery systems. MiRNA studies not only provide new eras of basic bone biology researches, but also contribute to new diagnostic and therapeutic methods into clinical practice to various bone diseases.

The authors thank Fundamental Research Grant Scheme (FRGS/1/2015/ST03/UPM/02/5) from

Department of Cell and Molecular Biology, Faculty of Biotechnology and Biomolecular

[1] Nugent M. MicroRNA function and dysregulation in bone tumors: The evidence to date.

[2] Filipowicz W, Bhattacharyya SN, Sonenberg N. Mechanisms of post-transcriptional regulation by microRNAs: Are the answers in sight? Nature Reviews. Genetics. 2008;**9**:

minimum or no side effect.

**Acknowledgements**

**Author details**

**References**

102-114

Ministry of Higher Education, Malaysia for the support.

\*Address all correspondence to: azuraidi@upm.edu.my

Sciences, Universiti Putra Malaysia, Selangor, Malaysia

Cancer Management and Research. 2014;**6**(1):15-25

Hui-Yi Loh, Yuin-Yee Lau, Kok-Song Lai and Mohd Azuraidi Osman\*

**7. Conclusions**

## **6. Challenges**

Although recent studies reveal that microRNA has the potential to become diagnostic biomarker and effective therapeutic agents for bone diseases, there are still challenges for developing miRNA-based treatment. Since each miRNA may regulate many different mRNA targets and the expression of target genes might be controlled by different miRNAs, it became an obstacle to identify all targets and miRNAs involved in bone diseases [94]. Moreover, miR-NAs are cancer type specific, they may perform as oncogene or tumor suppressor in different cell types, and thus result in off-target effects of miRNAs [95]. Garzon et al. reveals that miR-29 mimics serve as anticancer agents and regulate in bone growth; meanwhile, they target several tumorigenesis pathways like proliferation (CDK6), methylation (DNMT1, DNMT3a and b), and apoptosis (MCL-1) [96].

Currently, one of the major challenges facing by the researches is the mechanism of *in vivo* delivery. There are lots of mechanical and biological barriers to cope with for success transferring of miRNA into the target genes. The first barrier is the abnormal tumor vessels in leaky structure, which cause the poor blood perfusion and affect the delivery of naked miRNA. In addition, the extracellular matrix is very complex, consisting of tumor-associated macrophages and monocytes, which can trap miRNA in capsule and have the ability to hinder the miRNA to target the cancer cells. MiRNA is also susceptible to nucleases such as serum RNase A-type nucleases, which break phosphodiester bonds between nucleotides [97]. Furthermore, the small-sized miRNA is easily filtered by kidney and cleared in the blood circulation [98]. Hence, the instability of miRNAs needs to be overcome in order for the miRNAs to reach the target genes. Even if miRNAs are successfully transferred into the target tissue, the uptake of miRNAs into the cells is not guaranteed. The miRNA oligonucleotides consist of negative charges, and it prevents them from passing through the plasma membranes of the target cells [96]. Strategy to improve endosomal escape should also be taken in consideration since the endocytosis mechanism that capsulated miRNA causing degradation might be happened [97].

Besides delivery considerations, the autoimmunological pathways are necessary to be emphasized. MiRNAs are recognized as foreign particles by immune system in the body, which will trigger the adaptive or innate immune responses causing unpredictable toxicities [99]. Chen et al. reported that miRNA duplexes can trigger toll-like receptors (TLRs) to secrete the inflammatory cytokines and type I interferons. Activation of TLRs 3, 7, and 8 by single- or double-stranded RNAs promotes innate and adaptive immune systems and also prepare the surrounding immune cells, for instance, natural killer cells, dendritic cells, monocytes, B cells, etc., to increase the sensitivity to RNA stimulation [97]. The immune responses toward the miRNA still required further studies.

Numerous findings of miRNA are based on *in vitro* studies using cell lines and are not fully validated in *in vivo*. In addition, the major methods used to measure miRNA levels are quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) and microarray analysis, and there is no standardized techniques to measure the miRNA expression levels [38]. Further techniques need to be optimized for better miRNA detection and analysis.

Despite there are many challenges, the potentials of miRNA as a diagnostic tool and treatment for bone diseases look promising. We believe that in the next few years, researches will be able to develop efficient delivery methods of the miRNA to its specific target site with minimum or no side effect.

## **7. Conclusions**

and bone quality at 4 weeks postimplantation. Moreover, co-expression of bone morphogenic protein 2 (BMP2) and miR-214 sponges in OVX-BMSCs can synergistically enhance the bone

Although recent studies reveal that microRNA has the potential to become diagnostic biomarker and effective therapeutic agents for bone diseases, there are still challenges for developing miRNA-based treatment. Since each miRNA may regulate many different mRNA targets and the expression of target genes might be controlled by different miRNAs, it became an obstacle to identify all targets and miRNAs involved in bone diseases [94]. Moreover, miR-NAs are cancer type specific, they may perform as oncogene or tumor suppressor in different cell types, and thus result in off-target effects of miRNAs [95]. Garzon et al. reveals that miR-29 mimics serve as anticancer agents and regulate in bone growth; meanwhile, they target several tumorigenesis pathways like proliferation (CDK6), methylation (DNMT1, DNMT3a

Currently, one of the major challenges facing by the researches is the mechanism of *in vivo* delivery. There are lots of mechanical and biological barriers to cope with for success transferring of miRNA into the target genes. The first barrier is the abnormal tumor vessels in leaky structure, which cause the poor blood perfusion and affect the delivery of naked miRNA. In addition, the extracellular matrix is very complex, consisting of tumor-associated macrophages and monocytes, which can trap miRNA in capsule and have the ability to hinder the miRNA to target the cancer cells. MiRNA is also susceptible to nucleases such as serum RNase A-type nucleases, which break phosphodiester bonds between nucleotides [97]. Furthermore, the small-sized miRNA is easily filtered by kidney and cleared in the blood circulation [98]. Hence, the instability of miRNAs needs to be overcome in order for the miRNAs to reach the target genes. Even if miRNAs are successfully transferred into the target tissue, the uptake of miRNAs into the cells is not guaranteed. The miRNA oligonucleotides consist of negative charges, and it prevents them from passing through the plasma membranes of the target cells [96]. Strategy to improve endosomal escape should also be taken in consideration since the endocytosis mechanism that capsulated miRNA causing

Besides delivery considerations, the autoimmunological pathways are necessary to be emphasized. MiRNAs are recognized as foreign particles by immune system in the body, which will trigger the adaptive or innate immune responses causing unpredictable toxicities [99]. Chen et al. reported that miRNA duplexes can trigger toll-like receptors (TLRs) to secrete the inflammatory cytokines and type I interferons. Activation of TLRs 3, 7, and 8 by single- or double-stranded RNAs promotes innate and adaptive immune systems and also prepare the surrounding immune cells, for instance, natural killer cells, dendritic cells, monocytes, B cells, etc., to increase the sensitivity to RNA stimulation [97]. The immune responses toward the

Numerous findings of miRNA are based on *in vitro* studies using cell lines and are not fully validated in *in vivo*. In addition, the major methods used to measure miRNA levels are

formation and healing in osteoporotic rats [93].

92 Transcriptional and Post-transcriptional Regulation

and b), and apoptosis (MCL-1) [96].

degradation might be happened [97].

miRNA still required further studies.

**6. Challenges**

As a conclusion, microRNA plays important roles in bone development and maintenance. MiRNA dysregulation leads to the pathogenesis of various bone diseases. Nowadays, miRNAs are being excavated as new directions for diagnostic biomarkers and drug targets to cure bone diseases. However, there are still many limitations and barriers for the development of miRNAbased biomarkers and therapeutics. Further investigations are needed to understand the miRNA gene regulation in bone and to overcome the challenges faced in miRNA delivery systems. MiRNA studies not only provide new eras of basic bone biology researches, but also contribute to new diagnostic and therapeutic methods into clinical practice to various bone diseases.

## **Acknowledgements**

The authors thank Fundamental Research Grant Scheme (FRGS/1/2015/ST03/UPM/02/5) from Ministry of Higher Education, Malaysia for the support.

## **Author details**

Hui-Yi Loh, Yuin-Yee Lau, Kok-Song Lai and Mohd Azuraidi Osman\*

\*Address all correspondence to: azuraidi@upm.edu.my

Department of Cell and Molecular Biology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, Selangor, Malaysia

## **References**


[3] Paranjape T, Slack FJ, Weidhaas JB. MicroRNAs: Tools for cancer diagnostics. Gut. 2009; **58**(11):1546-1554

[18] Kim KS, Kim JH, Kim IY, Lee JW, Seong SM, Park YW, et al. MicroRNA-26a regulates RANKL-induced osteoclast formation. Molecules and Cells. 2015;**38**(1):75-80

MicroRNAs in Bone Diseases: Progress and Prospects http://dx.doi.org/10.5772/intechopen.79275 95

[19] Sugatani T, Vacher J, Hruska KA. A microRNA expression signature of osteoclastogen-

[20] Cheng P, Chen C, He HB, Hu R, Zhou HD, Xie H, et al. MiR-148a regulates osteoclastogenesis by targeting V-maf musculoaponeurotic fibrosarcoma oncogene homolog B.

[21] Kim KS, Kim JH, Lee JW, Jin HM, Kook H, Kim KK, et al. MafB negatively regulates

[22] Zhao HY, Zhang J, Shao HY, Liu JW, Jin MR, Chen JP, et al. MiRNA-340 inhibits osteoclast differentiation via repression of MITF. Bioscience Reports. 2017;**37**(4):BSR20170302

[23] Kapinas K, Kessler C, Ricks T, Gronowicz G, Delany AM. MiR-29 modulates Wnt signaling in human osteoblasts through a positive feedback loop. The Journal of Biological

[24] Li ZY, Hassan MQ, Jafferji M, Aqeilan RI, Garzon R, Croce CM, et al. Biological functions of miR-29b contribute to positive regulation of osteoblast differentiation. The Journal of

[25] Kapinas K, Kessler CB, Delany AM. MiR-29 suppression of osteonectin in osteoblasts: Regulation during differentiation and by canonical Wnt tumour. Journal of Cellular Bio-

[26] Li ZY, Hassan MQ, Volinia S, van Wijnen AJ, Stein JL, Croce CM, et al. A microRNA signature for a BMP2-induced osteoblast lineage commitment program. Proceedings of

[27] Zhang JF, Fu WM, He ML, Xie WD, Lv Q, Wan G, et al. MiRNA-20a promotes osteogenic differentiation of human mesenchymal stem cells by co-regulating BMP signaling. RNA

[28] Li H, Xie H, Liu W, Hu R, Huang B, Tan YF, et al. A novel microRNA targeting HDAC5 regulates osteoblast differentiation in mice and contributes to primary osteoporosis in

[29] Hu R, Liu W, Li H, Yang L, Chen C, Xia ZY, et al. A Runx2/miR-3960/miR-2861 regulatory feedback loop during mouse osteoblast differentiation. The Journal of Biological

[30] Sang S, Zhang ZC, Qin S, Li CW, Dong Y. MicroRNA-16-5p inhibits osteoclastogenesis

[31] Cowan RW, Singh G. Giant cell tumor of bone: A basic science perspective. Bone.

in giant cell tumor of bone. BioMed Research International. 2017;**2017**:1-6

humans. The Journal of Clinical Investigation. 2009;**119**(12):3666-3677

RANKL-mediated osteoclast differentiation. Blood. 2007;**109**(8):3253-3259

Journal of Bone and Mineral Research. 2013;**28**(5):1180-1190

esis. Blood. 2012;**117**(13):3648-3657

Chemistry. 2010;**285**(33):25221-25231

chemistry. 2010;**108**(1):216-224

Biology. 2011;**8**(5):829-838

2013;**52**(1):238-246

Chemistry. 2011;**286**(14):12328-12339

Biological Chemistry. 2009;**284**(23):15676-15684

the National Academy of Sciences. 2008;**105**(37):13906-13911


[18] Kim KS, Kim JH, Kim IY, Lee JW, Seong SM, Park YW, et al. MicroRNA-26a regulates RANKL-induced osteoclast formation. Molecules and Cells. 2015;**38**(1):75-80

[3] Paranjape T, Slack FJ, Weidhaas JB. MicroRNAs: Tools for cancer diagnostics. Gut. 2009;

[5] Lin T, Ma QP, Zhang YF, Zhang HF, Yan JP, Gao CH. MicroRNA-27a functions as an oncogene in human osteosarcoma by targeting CCNG1. Oncology Letters. 2018;**15**(1):

[6] Braun CJ, Zhang X, Savelyeva I, Wolff S, Moll UM, Schepeler T, et al. p53-responsive microRNAs 192 and 215 are capable of inducing cell cycle arrest. Cancer Research. 2008;

[7] Sun MG, Zhou XY, Chen LL, Huang SS, Leung V, Wu N, et al. The regulatory roles of microRNAs in bone remodeling and perspectives as biomarkers in osteoporosis. BioMed

[8] Clarke B. Normal bone anatomy and physiology. Clinical Journal of the American

[9] Pathria MN, Chung CB, Resnick DL. Acute and stress-related injuries of bone and cartilage: Pertinent anatomy, basic biomechanics, and imaging perspective. Radiology. 2016;

[10] Martin TJ, Seeman E. Bone remodelling: Its local regulation and the emergence of bone fragility. Best Practice & Research. Clinical Endocrinology & Metabolism. 2008;**22**(5):

[11] Martin RB, Burr DB, Sharkey NA, Fyhrie DP. Growth, modelling and remodelling of bone. In: Martin RB, Burr DB, Sharkey NA, Fyhrie DP, editors. Skeletal Tissue Mechanics.

[12] Raggatt LJ, Partridge NC. Cellular and molecular mechanisms of bone remodeling. The

[13] Langdahl B, Ferrari S, Dempster DW. Bone modeling and remodeling: Potential as therapeutic targets for the treatment of osteoporosis. Therapeutic Advances in Muscu-

[14] Feng X, McDonald JM. Disorders of bone remodelling. Annual Review of Pathology.

[15] Eriksen EF. Cellular mechanisms of bone remodeling. Reviews in Endocrine & Metabolic

[16] Proff P, Römer P. The molecular mechanism behind bone remodelling: A review. Clinical

[17] Mizoguchi F, Murakami Y, Saito T, Miyasaka N, Kohsaka H. MiR-31 controls osteoclast formation and bone resorption by targeting RhoA. Arthritis Research & Therapy.

[4] Moore BT, Xiao P. MiRNAs in bone diseases. MicroRNA. 2013;**2**(1):20-31

**58**(11):1546-1554

94 Transcriptional and Post-transcriptional Regulation

**68**(24):10094-10104

Research International. 2016;**2016**:1652417

Society of Nephrology. 2008;**3**(Suppl 3):131-139

2nd ed. New York: Springer; 2015. pp. 95-173

loskeletal Disease. 2016;**8**(6):225-235

Oral Investigations. 2009;**13**(4):355-362

Disorders. 2010;**11**(4):219-227

Journal of Biological Chemistry. 2010;**285**(33):25103-25108

1067-1071

**280**(1):21-38

2011;**6**:121-145

2013;**15**(5):R102

701-722


[32] Wang T, Yin HB, Wang J, Li ZX, Wei HF, Liu Z, Wu ZP, Yan WJ, et al. MicroRNA-106b inhibits osteoclastogenesis and osteolysis by targeting RANKL in giant cell tumor of bone. Oncotarget. 2015;**6**(22):18980-18996

[46] Wang FS, Chung PC, Lin CL, Chen MW, Ke HJ, Chang YH, et al. MicroRNA-29a protects against glucocorticoid-induced bone loss and fragility in rats by orchestrating bone

MicroRNAs in Bone Diseases: Progress and Prospects http://dx.doi.org/10.5772/intechopen.79275 97

[47] Monti E, Mottes M, Fraschini P, Brunelli PC, Forlino A, Giacomo V, et al. Current and emerging treatments for the management of osteogenesis imperfecta. Therapeutics and

[48] Shaker JL, Albert C, Fritz J, Harris G. Recent developments in osteogenesis imperfecta.

[49] Abukabbos H, Al-Sineedi F. Clinical manifestations and dental management of dentinogenesis imperfecta associated with osteogenesis imperfecta: Case report. Saudi Dental

[50] Marini JC, Forlino A, Cabral WA, Barnes AM, Antonio JDS, Milgrom S, et al. Consortium for osteogenesis imperfecta mutations in the helical domain of type I collagen: Regions rich in lethal mutations align with collagen binding sites for integrins and proteogly-

[51] Forlino A, Cabral WA, Barnes AM, Marini JC. New perspectives on osteogenesis imper-

[52] Van Dijk FS, Sillence DO. Osteogenesis imperfecta: Clinical diagnosis, nomenclature and severity assessment. American Journal of Medical Genetics Part A. 2014;**164**(6):1470-1481

[53] Wang ZQ, Lu YQ, Zhang XM, Ren XZ, Wang YZ, Li ZL, et al. Serum microRNA is a promising biomarker for osteogenesis imperfecta. Intractable & Rare Diseases Research.

[54] Kaneto CM, Lima PSP, Zanette DL, Prata KL, Pina Neto JM, de Paula FJ, et al. COL1A1 and miR-29b show lower expression levels during osteoblast differentiation of bone marrow stromal cells from Osteogenesis Imperfecta patients. BMC Medical Genetics.

[55] Sabharwal R, Gupta S, Sepolia S, Panigrahi R, Mohanty S, Subudhi SK, et al. An insight in to paget's disease of bone. Nigerian Journal of Surgery: Official Publication of the

[56] Ralston SH, Layfield R. Pathogenesis of paget disease of bone. Calcified Tissue Inter-

[57] Roodman G, Windle J. Science in medicine-paget disease of bone. The Journal of Clinical

[58] Bianciardi S, Merlotti D, Sebastiani G, Valentini M, Gonnelli S, Caffarelli C, et al. Micro-RNA expression profiling in paget's disease of bone. Bone Abstracts. 2016;**5**:452

[59] Gebert LFR, Rebhan MAE, Crivelli SEM, Denzler R, Stoffel M, Hall J.Miravirsen (SPC3649) can inhibit the biogenesis of miR-122. Nucleic Acids Research. 2014;**42**(1):609-621

acquisition and resorption. Arthritis and Rheumatism. 2013;**65**(6):1530-1540

Clinical Risk Management. 2010;**6**:367-381

cans. Human Mutation. 2007;**28**:209-221

fecta. Nature Reviews. Endocrinology. 2011;**7**(9):540-557

Nigerian Surgical Research Society. 2014;**20**(1):9-15

F1000Research. 2015;**4**:2-11

Journal. 2013;**25**(4):159-165

2012;**1**(2):81-85

2014;**15**(1):45

national. 2012;**91**(2):97-113

Investigation. 2005;**115**(2):200-207


[46] Wang FS, Chung PC, Lin CL, Chen MW, Ke HJ, Chang YH, et al. MicroRNA-29a protects against glucocorticoid-induced bone loss and fragility in rats by orchestrating bone acquisition and resorption. Arthritis and Rheumatism. 2013;**65**(6):1530-1540

[32] Wang T, Yin HB, Wang J, Li ZX, Wei HF, Liu Z, Wu ZP, Yan WJ, et al. MicroRNA-106b inhibits osteoclastogenesis and osteolysis by targeting RANKL in giant cell tumor of

[33] Sobti A, Agrawal P, Agarwala S, Agarwal M. Giant cell tumor of bone—An overview.

[34] Zhang J, Xiao XJ, Liu J. The role of circulating miRNAs in multiple myeloma. Science

[35] Wu PF, Liang JY, Yu F, Zhou ZB, Tang JY, Li KH. MiR-125b inhibits stromal cell proliferation in giant cell tumor of bone by targeting parathyroid hormone 1 receptor. Iranian

[36] Johnell O, Kanis J. Epidemiology of osteoporotic fractures. Osteoporosis International.

[37] Sozen T, Ozisik L, Basaran NC.An overview and management of osteoporosis. European

[38] Mirza F, Canalis E. Management of endocrine disease: Secondary osteoporosis: Pathophysiology and management. European Journal of Endocrinology. 2015;**173**(3):

[39] Zaheer S, LeBoff MS. Osteoporosis: Prevention and treatment. [Updated 2016 Aug 3]. In: De Groot LJ, Chrousos G, Dungan K, et al., editors. Endotext [Internet]. South Dartmouth (MA): MDText.com, Inc.; 2000. Available from: https://www.ncbi.nlm.nih.gov/

[40] Ji MX, Yu Q. Primary osteoporosis in postmenopausal women. Chronic Diseases and

[41] Lian JB, Stein GS, Van Wijnen AJ, Stein JL, Hassan MQ, Gaur T, et al. MicroRNA control of bone formation and homeostasis. Nature Reviews. Endocrinology. 2012;**8**(4):212-227

[42] Chen C, Cheng P, Xie H, Zhou HD, Wu XP, Liao EY, et al. MiR-503 regulates osteoclastogenesis via targeting RANK. Journal of Bone and Mineral Research. 2014;**29**(2):338-347

[43] Li T, Li D, Sha JJ, Sun P, Huang YR. MicroRNA-21 directly targets MARCKS and promotes apoptosis resistance and invasion in prostate cancer cells. Biochemical and Bio-

[44] Zhang YQ, Gao YL, Cai LJ, Li FN, Lou Y, Xu N, et al. MicroRNA-221 is involved in the regulation of osteoporosis through regulates RUNX2 protein expression and osteoblast

[45] Yang N, Wang G, Hu CH, Shi YY, Liao L, Shi ST, et al. Tumor necrosis factor α suppresses the mesenchymal stem cell osteogenesis promoter miR-21 in estrogen deficiency-

induced osteoporosis. Journal of Bone and Mineral Research. 2013;**28**(3):559-573

differentiation. American Journal of Translational Research. 2017;**9**(1):126-135

physical Research Communications. 2009;**383**(3):280-285

bone. Oncotarget. 2015;**6**(22):18980-18996

96 Transcriptional and Post-transcriptional Regulation

China. Life Sciences. 2015;**58**(12):1262-1269

Journal of Rheumatology. 2017;**4**(1):46-56

Translational Medicine. 2015;**1**(1):9-13

2005;**16**(Suppl 2):6-10

R131-R151

books/NBK279073/

Archives of Bone and Joint Surgery. 2016;**4**(1):2-9

Journal of Basic Medical Sciences. 2015;**18**:705-709


[60] Shah MY, Ferrajoli A, Sood AK, Lopez-Berestein G, Calin GA. microRNA therapeutics in cancer—An emerging concept. eBioMedicine. 2016;**12**:34-42

[74] Wang P, Zou FD, Zhang XD, Li H, Dulak A, Robert J, et al. MiR21 negatively regulates CDC25A and cell cylce progression in colon cancer cells. Cancer Research.

MicroRNAs in Bone Diseases: Progress and Prospects http://dx.doi.org/10.5772/intechopen.79275 99

[75] Dong JB, Liu YL, Liao WS, Liu R, Shi P, Wang LM. MiRNA-223 is a potential diagnostic and prognostic marker for osteosarcoma. Journal of Bone Oncology. 2016;**5**(2):74-79 [76] Xu JL, Yao Q, Hou Y, Xu M, Liu S, Yang LQ, et al. MiR-223/Ect2/p21 signaling regulates osteosarcoma cell cycle progression and proliferation. Biomedicine & Pharmacotherapy.

[77] Lian F, Cui Y, Zhou CL, Gao KW, Wu LW. Identification of a plasma four-microRNA panel as potential noninvasive biomarker for osteosarcoma. PLoS One. 2015;**10**(3):1-12

[78] Mao JH, Zhou RP, Peng AF, Liu ZL, Huang SH, Long XH, et al. MicroRNA-195 suppresses osteosarcoma cell invasion and migration in vitro by targeting FASN. Oncology

[79] Tian Y, Zhang YZ, Chen W. MicroRNA-199a-3p and microRNA-34a regulate apoptosis in human osteosarcoma cells. Bioscience Reports. 2014;**34**(4). DOI: 10.1042/

[80] Duan ZF, Choy E, Harmon D, Liu XZ, Susa M, Mankin H, et al. MicroRNA-199a-3p is down regulated in human osteosarcoma and regulates cell proliferation and migration.

[81] Zhang LL, Iyer AK, Yang XQ, Kobayashi E, Guo YQ, Mankin H, et al. Polymeric nanoparticle-based delivery of microRNA-199a-3p inhibits proliferation and growth of

[82] Osaki M, Takeshita F, Sugimoto Y, Kosaka N, Yamamoto Y, Yoshioka Y, et al. Micro-RNA-143 regulates human osteosarcoma metastasis by regulating matrix metalloprote-

[83] Shimbo K, Miyaki S, Ishitobi H, Kato Y, Kubo T, Shimose S, et al. Exosome-formed synthetic microRNA-143 is transferred to osteosarcoma cells and inhibits their migration.

[84] Jiang LD, He AY, He XJ, Tao C. MicroRNA-126 enhances the sensitivity of osteosarcoma

[85] Cai MX, Yang L, Zhang SF, Liu JF, Sun Y, Wang XG. A bone-resorption surface-targeting nanoparticle to deliver anti-miR214 for osteoporosis therapy. International Journal of

[86] Yu SJ, Ding JX, He CL, Cao Y, Xu WG, Chen XS. Disulfide cross-linked polyurethane micelles as a reduction-t riggered drug delivery system for cancer therapy. Advanced

[87] Gencturk A, Kahraman E, Güngör S, Ozhan G, Ozsoy Y, Sarac AS. Polyurethane/hydroxypropyl cellulose electrospun nanofiber mats as potential transdermal drug delivery

Biochemical and Biophysical Research Communications. 2014;**445**(2):381-387

cells to cisplatin and methotrexate. Oncology Letters. 2015;**10**(6):3769-3778

osteosarcoma cells. International Journal of Nanomedicine. 2015;**10**:2913-2924

Molecular Cancer Therapeutics. 2011;**10**(8):1337-1345

ase-13 expression. Molecular Therapy. 2011;**19**(6):1123-1130

2009;**69**(20):8157-8165

2013;**67**(5):381-386

BSR20140084

Letters. 2012;**4**(5):1125-1129

Nanomedicine. 2017;**12**:7469-7482

Healthcare Materials. 2014;**3**(5):752-760


[74] Wang P, Zou FD, Zhang XD, Li H, Dulak A, Robert J, et al. MiR21 negatively regulates CDC25A and cell cylce progression in colon cancer cells. Cancer Research. 2009;**69**(20):8157-8165

[60] Shah MY, Ferrajoli A, Sood AK, Lopez-Berestein G, Calin GA. microRNA therapeutics in

[61] Slabáková E, Culig Z, Remšík J, Souček K. Alternative mechanisms of MiR-34a regula-

[62] Bouchie A. First microRNA mimic enters clinic. Nature Biotechnology. 2013;**31**(7):577-577 [63] Bader AG. MiR-34—A microRNA replacement therapy is headed to the clinic. Frontiers

[64] Beg MS, Brenner AJ, Sachdev J, Borad M, Kang YK, Stoudemire J, et al. Phase I study of MRX34, a liposomal miR-34a mimic, administered twice weekly in patients with

[65] Xiao F, Chen JW, Lian CJ, Han PC, Zhang CY. Tumor necrosis factor-related apoptosisinducing ligand induces cytotoxicity specific to osteosarcoma by microRNA response

[66] Gaur S, Wen YF, Song JH, Parikh NU, Mangala LS, Blessing AM, et al. Chitosan nanoparticle-mediated delivery of miRNA-34a decreases prostate tumor growth in the bone and its expression induces non-canonical autophagy. Oncotarget. 2015;**6**(30):29161-29177 [67] Di Martino MT, Campani V, Misso G, Gallo Cantafio ME, Gullà A, Foresta U, et al. In vivo activity of MiR-34a mimics delivered by stable nucleic acid lipid particles (SNALPs)

[68] Hu H, Zhang Y, Cai XH, Huang JF, Cai L. Changes in microRNA expression in the MG-63 osteosarcoma cell line compared with osteoblasts. Oncology Letters. 2012;**4**(5):1037-1042

[69] Jones KB, Salah Z, Sara DM, Galasso M, Gaudio E, Nuovo GJ, et al. MicroRNA signatures associate with pathogenesis and progression of osteosarcoma. Cancer research.

[70] Li H, Zhang K, Liu LH, Ouyang Y, Guo HB, Zhang H, et al. MicroRNA screening identifies circulating microRNAs as potential biomarkers for osteosarcoma. Oncology Letters.

[71] Yuan J, Chen L, Chen X, Sun W, Zhou X. Identification of serum microRNA-21 as a biomarker for chemosensitivity and prognosis in human osteosarcoma. The Journal of

[72] Lou YH, Yang XS, Wang FL, Cui ZM, Huang Y. MicroRNA-21 promotes the cell proliferation, invasion and migration abilities in ovarian epithelial carcinomas through inhibiting the expression of PTEN protein. International Journal of Molecular Medicine.

[73] Fassan M, Pizzi M, Giacomelli L, Mescoli C, Ludwig K, Pucciarelli S, et al. PDCD4 nuclear loss inversely correlates with miR-21 levels in colon carcinogenesis. Virchows

advanced solid tumors. Investigational New Drugs. 2017;**35**(2):180-188

elements. Molecular Medicine Reports. 2015;**11**(1):739-745

against multiple myeloma. PLoS One. 2014;**9**(2):1-10

International Medical Research. 2012;**40**(6):2090-2097

cancer—An emerging concept. eBioMedicine. 2016;**12**:34-42

tion in cancer. Cell Death & Disease. 2017;**8**(10):1-10

in Genetics. 2012;**3**(120):1-9

98 Transcriptional and Post-transcriptional Regulation

2013;**72**(7):1865-1877

2015;**10**(3):1662-1668

2010;**26**:819-827

Archiv. 2011;**458**(4):413-419


system: Characterization studies and in vitro assays. Artificial Cells, Nanomedicine, and Biotechnology. 2017;**45**(3):655-664

**Section 2**

**The Interplay Between Transcription Factors and**

**MicroRNAs**


**The Interplay Between Transcription Factors and MicroRNAs**

system: Characterization studies and in vitro assays. Artificial Cells, Nanomedicine,

[88] Akduman C, Ozgüney I, Kumbasar EP. Preparation and characterization of naproxenloaded electrospun thermoplastic polyurethane nanofibers as a drug delivery system. Materials Science & Engineering. C, Materials for Biological Applications. 2016;**64**:383-390

[89] Carinci F. Restoration of incisor area using one-piece implants: Evaluation of crestal

[90] Wang XG, Guo BS, Li Q, Peng J, Yang ZJ, Wang AY, et al. MiR-214 targets ATF4 to inhibit

[91] Zhao CY, Sun WJ, Zhang PF, Ling SK, Li YH, Zhao DS, et al. MiR-214 promotes osteoclastogenesis by targeting Pten/PI3k/Akt pathway. RNA Biology. 2015;**12**(3):343-353 [92] Zhang XJ, Li Y, Chen YE, Chen JH, Ma PX. Cell-free 3D scaffold with two-stage delivery of miRNA-26a to regenerate critical-sized bone defects. Nature Communications.

[93] Li KC, Chang YH, Yeh CL, Hu YC. Healing of osteoporotic bone defects by baculovirusengineered bone marrow-derived MSCs expressing MicroRNA sponges. Biomaterials.

[94] Kumar RMR, Boro A, Fuchs B. Involvement and clinical aspects of microRNA in osteo-

[95] Sampson VB, Yoo SM, Kumar A, Vetter NS, Kolb EA. MicroRNAs and potential targets

[96] Garzon R, Marcucci G, Croce CM. Targeting microRNAs in cancer: Rationale, strategies

[97] Chen YC, Gao DY, Huang L. In vivo delivery of miRNAs for cancer therapy: Challenges

[98] Sand M, Gambichler T, Sand D, Skrygan M, Altmeyer P, Bechara FG. MicroRNAs and the skin: Tiny players in the body's largest organ. Journal of Dermatological Science.

[99] Greco SJ, Munoz JL, Rameshwar P. MicroRNA cancer therapeutics and the challenge of drug delivery. In: Singh SR, Rameshwar P, editors. MicroRNA in Development and in

sarcoma. International Journal of Molecular Sciences. 2016;**17**(6):1-5

in osteosarcoma: Review. Frontiers in Pediatrics. 2015;**3**(August):1-9

and challenges. Nature Reviews. Drug Discovery. 2010;**9**(10):775-789

and strategies. Advanced Drug Delivery Reviews. 2015;**81**:128-141

the Progression of Cancer. New York: Springer; 2014. pp. 349-358

bone resorption. Dental Research Journal. 2012;**9**(Suppl 2):S151-S154

bone formation. Nature Medicine. 2013;**19**(1):93-100

and Biotechnology. 2017;**45**(3):655-664

100 Transcriptional and Post-transcriptional Regulation

2016;**7**:1-15

2016;**74**:155-166

2009;**53**(3):169-175

**Chapter 6**

**Provisional chapter**

**Transcription Factors and MicroRNA Interplay: A New**

**Transcription Factors and MicroRNA Interplay: A New** 

MicroRNAs (miRNAs) and transcription factors are master regulators of the cellular system. Plant genomes contain thousands of protein-coding and non-coding RNA genes; which are differentially expressed in different tissues at different times during growth and development. Complex regulatory networks that are controlled by transcription factors and microRNAs, which coordinate gene expression. Transcription factors, the key regulators of plant growth and development, are the targets of the miRNAs families. The combinatorial regulation of transcription factors and miRNAs guides the appropriate implementation of biological events and developmental processes. The resources on the regulatory cascades of transcription factors and miRNAs are available in the context of human diseases, but these resources are meager in case of plant diseases. On the other hand, it is also important to understand the cellular and physiological events needed to operate the miRNAs networks. The relationship between transcription factors and miRNA in different plant species described in this chapter will be of great interest to plant scientists, providing better insights into the mechanism of action and interactions among transcription factors (TFs) and miRNA networks culminating in improving key agronomic traits for crop improvement to meet the future global food demands. **Keywords:** transcription factors, microRNA, regulatory network, interplay, gene

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

In the recent years, various regulatory complex networks have been identified in plants [1]. Identification of these networks has led to better understanding gene regulation at

DOI: 10.5772/intechopen.75942

**Strategy for Crop Improvement**

**Strategy for Crop Improvement**

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

Sumit Jangra, Vrantika Chaudhary and

Sumit Jangra, Vrantika Chaudhary and

http://dx.doi.org/10.5772/intechopen.75942

Neelam R. Yadav

**Abstract**

expression

**1. Introduction**

Neelam R. Yadav

#### **Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement**

DOI: 10.5772/intechopen.75942

Sumit Jangra, Vrantika Chaudhary and Neelam R. Yadav Sumit Jangra, Vrantika Chaudhary and Neelam R. Yadav

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.75942

#### **Abstract**

MicroRNAs (miRNAs) and transcription factors are master regulators of the cellular system. Plant genomes contain thousands of protein-coding and non-coding RNA genes; which are differentially expressed in different tissues at different times during growth and development. Complex regulatory networks that are controlled by transcription factors and microRNAs, which coordinate gene expression. Transcription factors, the key regulators of plant growth and development, are the targets of the miRNAs families. The combinatorial regulation of transcription factors and miRNAs guides the appropriate implementation of biological events and developmental processes. The resources on the regulatory cascades of transcription factors and miRNAs are available in the context of human diseases, but these resources are meager in case of plant diseases. On the other hand, it is also important to understand the cellular and physiological events needed to operate the miRNAs networks. The relationship between transcription factors and miRNA in different plant species described in this chapter will be of great interest to plant scientists, providing better insights into the mechanism of action and interactions among transcription factors (TFs) and miRNA networks culminating in improving key agronomic traits for crop improvement to meet the future global food demands.

**Keywords:** transcription factors, microRNA, regulatory network, interplay, gene expression

#### **1. Introduction**

In the recent years, various regulatory complex networks have been identified in plants [1]. Identification of these networks has led to better understanding gene regulation at

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

transcriptional and post-transcriptional level. In this chapter, we will be emphasizing on interplay of TFs and miRNAs as a major regulatory mechanism during and after mRNA synthesis. TFs interact with enhancers at transcriptional level to regulate gene expression and have been well recognized in the last decade [2]. This is also supported by the discovery of diverse family of TFs playing various roles in plants [3]. Post-transcriptional gene regulation involving small non-coding RNAs called miRNAs has also been discovered a few decades ago. These miRNAs are involved in the regulation of various genes in animal and plant system by upregulating and downregulating mRNAs [4]. With the escalating gene regulating complexity, it is fascinating to monitor and recognize a vibrant connection among small noncoding RNAs (miRNAs), transcription factors (TFs) and messenger RNAs (mRNAs).

**Database Acronym Public URL Description**

PlantTFDB http://planttfdb.cbi.pku. edu.cn/

PlnTFDB http://plntfdb.bio.uni-

PlantTFDB https://www.ebi.ac.uk/

PlantTFDB http://planttfdb.cbi.pku. edu.cn/

PpTFDB http://14.139.229.199/

PvTFDB http://www.multiomics. in/PvTFDB/

CicerTransDB http://www.cicertransdb.

html

DRTF http://planttfdb.cbi.pku. edu.cn/

RiceSRTFDB http://www.nipgr.res.in/ RiceSRTFDB.html

DPTF http://planttfdb.cbi.pku. edu.cn/

DMTF http://planttfdb.cbi.pku. edu.cn/

DTTF http://planttfdb.cbi.pku. edu.cn/

wDBTF http://wwwappli.nantes.

STIFDB http://caps.ncbs.res.in/ stifdb2/

inra.fr:8180/wDBFT/

AGRIS http://agris-

AtTFDB http://agris-

potsdam.de/v3.0/index. php?sp\_id=ATH

miriam/main/datatypes/ MIR:00000579

PpTFDB/Home.aspx

esy.es/documents/about.

knowledgebase.org/

knowledgebase.org/

PlantTFDB contains 320,370 TFs from 165

http://dx.doi.org/10.5772/intechopen.75942

105

PlnTFDB contains 2657 protein models, 2451 distinct protein sequences of *A. thaliana*

Systematically identifies TFs for plant species

A database of functional and evolutionary

Provides a range of information about pigeon pea TFs, encompasses about 1829 TFs and classifies them into 55 TF families

Provides comprehensive information about each of the identified TF, encompasses 2370 TFs and classifies them into 49 TF families

Facilitates uses with a platform for unified and comprehensive study of chickpea TFs

Provides information about Arabidopsis promoter sequences, TFs and their target

Contains information about 1770 TFs and group them into 50 families on the basis of

2048 TFs have been identified and are grouped into 56 families from subsp.

4287 TFs have been identified and are

3308 TFs have been identified and are

1845 TFs have been identified and are

It contains about 1127 predicted TFs from

It is a comprehensive collection of biotic and abiotic stress-responsive genes in

grouped into 58 families

grouped into 56 families

grouped into 58 families

Arabidopsis and rice

bread wheat

Provides most comprehensive information about the expression pattern of rice TFs during drought and salinity stress conditions

plant species

Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement

study of TFs

gene

japonica

conserved domains

Plant transcription factor

*Arabidopsis thaliana*— Plant transcription factor

Database collection: Plant transcription factor

Plant TFDB| Transcription factor data: Sequence

Pigeon pea transcription factor database

Chickpea transcription factor database

Arabidopsis gene regulatory information

*Arabidopsis thaliana* transcription factor

Database of rice transcription factors

Rice stress-responsive transcription factor

Database of populus transcription factors

Database of maize transcription factors

Database of tomato transcription factors

Database of wheat transcription factor

Stress-responsive transcription factor

database

*Phaseolus vulgaris* transcription factor

database

database

database

database

database

server

database

database

MiRNAs are small non-coding (22 nucleotides) RNA molecules present in viruses, plants and animals and are involved in post-transcriptional and post-translational regulation of gene expression. First miRNA molecule (lin-4) was discovered in *C. elegans* by Lee et al. [5]. Later on, second miRNA (let-7) was characterized by Reinhart et al. [6]. Both plants and animals undergo a similar biogenesis mechanism. A two-step procedure catalyzed by RNA pol III like enzyme is required in the miRNA processing of primary precursor. For further processing, these miRNAs are loaded into a protein complex known as RNA induced silencing complex (RISC) [4]. An open access miRNA database is managed by Griffiths-Jones Lab, University of Manchester (http://www.mirbase.org/index.shtml). This public database contains a total of 28,685 miRNAs from viruses, animals and plants [7] and is involved in regulation and modification of several biological pathways by controlling particular genes [8]. Therefore, identifying possible miRNA targets is an effective methodology to thoroughly study miRNA-mediated regulatory function at post-transcriptional level. Earlier studies carried out in Arabidopsis to explore some experimental parameters and procedures inferred for known miRNA-target interaction using bioinformatics tools have been utilized to reveal miRNA target genes in other plants [9]. Wet lab experiments like PAGE, Northern Blot, RAPD and Degradome sequencing were carried out to further validate the computational predictions [10].

Presently, 320,370 TFs have been identified from 58 families of 165 plant species [11]. Various repositories for plant TFs are available, which identify and collect TF from various plant species and are publically available for use (**Table 1**). MiRNAs and TFs are involved in upregulation and downregulation of the target genes, ultimately determine the destiny of specific gene, by turning "on/off" [12]. Mainly, miRNAs are involved in targeting DNA-binding proteins (TFs) [13]. Since a great impact on plant genetic system is exhibited by both the regulators, the interplay of miRNA-TFs will help in understanding the organization of several biological pathways.

Recently, miRNA-based research is focused on biotic and abiotic stress tolerance in plants. These stresses have a significant effect on plant growth and development and cause a great loss to yield. This chapter will provide deeper insights into miRNA-mediated gene regulation and their crosstalk with TFs, which will provide better understanding of plant responses to


transcriptional and post-transcriptional level. In this chapter, we will be emphasizing on interplay of TFs and miRNAs as a major regulatory mechanism during and after mRNA synthesis. TFs interact with enhancers at transcriptional level to regulate gene expression and have been well recognized in the last decade [2]. This is also supported by the discovery of diverse family of TFs playing various roles in plants [3]. Post-transcriptional gene regulation involving small non-coding RNAs called miRNAs has also been discovered a few decades ago. These miRNAs are involved in the regulation of various genes in animal and plant system by upregulating and downregulating mRNAs [4]. With the escalating gene regulating complexity, it is fascinating to monitor and recognize a vibrant connection among small non-

coding RNAs (miRNAs), transcription factors (TFs) and messenger RNAs (mRNAs).

predictions [10].

104 Transcriptional and Post-transcriptional Regulation

pathways.

MiRNAs are small non-coding (22 nucleotides) RNA molecules present in viruses, plants and animals and are involved in post-transcriptional and post-translational regulation of gene expression. First miRNA molecule (lin-4) was discovered in *C. elegans* by Lee et al. [5]. Later on, second miRNA (let-7) was characterized by Reinhart et al. [6]. Both plants and animals undergo a similar biogenesis mechanism. A two-step procedure catalyzed by RNA pol III like enzyme is required in the miRNA processing of primary precursor. For further processing, these miRNAs are loaded into a protein complex known as RNA induced silencing complex (RISC) [4]. An open access miRNA database is managed by Griffiths-Jones Lab, University of Manchester (http://www.mirbase.org/index.shtml). This public database contains a total of 28,685 miRNAs from viruses, animals and plants [7] and is involved in regulation and modification of several biological pathways by controlling particular genes [8]. Therefore, identifying possible miRNA targets is an effective methodology to thoroughly study miRNA-mediated regulatory function at post-transcriptional level. Earlier studies carried out in Arabidopsis to explore some experimental parameters and procedures inferred for known miRNA-target interaction using bioinformatics tools have been utilized to reveal miRNA target genes in other plants [9]. Wet lab experiments like PAGE, Northern Blot, RAPD and Degradome sequencing were carried out to further validate the computational

Presently, 320,370 TFs have been identified from 58 families of 165 plant species [11]. Various repositories for plant TFs are available, which identify and collect TF from various plant species and are publically available for use (**Table 1**). MiRNAs and TFs are involved in upregulation and downregulation of the target genes, ultimately determine the destiny of specific gene, by turning "on/off" [12]. Mainly, miRNAs are involved in targeting DNA-binding proteins (TFs) [13]. Since a great impact on plant genetic system is exhibited by both the regulators, the interplay of miRNA-TFs will help in understanding the organization of several biological

Recently, miRNA-based research is focused on biotic and abiotic stress tolerance in plants. These stresses have a significant effect on plant growth and development and cause a great loss to yield. This chapter will provide deeper insights into miRNA-mediated gene regulation and their crosstalk with TFs, which will provide better understanding of plant responses to


MYB (myeloblastosis), a huge family protein, is characteristic of all eukaryotes and plays a diverse role in gene networking. Generally, MYB functions as transcription factor and their DNA-binding ability varies with the number of MYB domains [33]. In plants, MYB proteins are classified in four different classes depending upon the number of DNA-binding MYB domains: MYB-related, R2R3-MYBs, R1R2R3-MYBs and atypical MYBs [34]. The first plant MYB gene C1 was identified from maize [35]. Since their identification, they have been found to be extensively dispersed in plants and communicate with additional transcription factors [36]. MYB transcription factors are involved in the regulation of plant growth and development in various species like in soybean, they are involved in regulation of flower color [37] and regulation of signal transduction pathways in Arabidopsis, rice and cassava [38]. Biosynthesis of secondary metabolites is regulated in Arabidopsis and Medicago [36]. In Arabidopsis, sugarcane, potato, cotton, wheat, rice and *Camelina sativa*, they are involved in drought tolerance [39]. Chilling tolerance is imparted in Arabidopsis, wheat and rice [40]. MYB transcription

Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement

http://dx.doi.org/10.5772/intechopen.75942

107

Arabidopsis transcription factor APETALA2 (AP2) is involved in the regulation of complicated processes of plant growth and development, which includes seed development, maintenance of stem cells and flower development [42]. APETALA2 family, also known as "A" class, acts together with B and C class to determine the final floral organ development, and this interaction of transcription factors forms the well-known ABC model of flower development [43]. Pandey et al. identified an APETALA2 (AP2) domain TF in Arabidopsis that suppresses ABA response during seed germination and ABA and stress-induced gene expression. They also observed that *abr1* mutant plants were hypersensitive to osmotic stress and higher level of ABA was found in mutant plants; this supports that ABA-mediated gene regulation is suppressed by AP2 [44]. Overexpression of *Nicotiana tabacum Tsi1* gene encoding an EREBP/AP2 TF in tobacco enhances resistance against osmotic stress and pathogen attack [45]. Overexpression of *WXP1,* an AP2 domain-containing TF gene of *Medicago truncatula*, enhances wax accumulation and drought tolerance in transgenic alfalfa [46]. Overexpression of *ORA59*, an AP2/ERF transcription factor domain, results in enhanced resistance against fungus *Botrytis cinerea* [47]. WIND1 and AP2/ERF TFs regulate cell differentiation in Arabidopsis [48]. WRINKLED1 (WRI1), an AP2-type transcription factor, was found to be associated with

TCF transcription factors comprise a domain, called TCP domain, which shares a motif that forms a basic helix-loop-helix (bHLH) structure that has DNA-binding properties [50]. The name TCP came from TEOSINTE BRANCHED1, CYCLOIDEA (CYC) and PROLIFERATING CELL NUCLEAR ANTIGEN FACTOR1 (PCF1) and PCF2, first four members of the TCP family derived from maize, snapdragon and rice, respectively [51]. Earlier studies have shown that TCP has been involved in the regulation of leaf formation by regulating cell cycle [52]. TCP transcription factors are also involved in flower development [53], leaf senescence [54], shoot development [55], jasmonic acid and auxin signaling [56], cell proliferation [57], leaf shape regulation [58], development of macro and micro [50], mitochondrial biogenesis [59]

One of the largest and diverse families of plant regulators is WRKY transcription factors, with nearly 74 members in Arabidopsis, over 100 in rice, soybean and poplar [61]. There is at least one conserved DNA-binding domain called WRKY domain, which comprises a preserved protein

factor genes are also involved in combating salt stress [41].

triacylglycerol (TAGs) accumulation in Arabidopsis [49].

and regulating circadian cycle [60].

**Table 1.** Plant transcription factors database.

various biotic and abiotic stresses and will help in developing high yielding and stress tolerant varieties, which is the ultimate aim of the agricultural scientists.

## **2. Regulatory roles of transcription factors in plants**

TFs genes are regulated at both transcriptional and post-transcriptional level in plants [14]. Therefore, to build regulatory networks, understanding the expression of TFs is of great importance. Mainly, TFs act by binding the *cis* element present inside the transcription initiation (promoter) region of their target gene [15]. Recent studies have shown that changes in gene expression are closely related with changes in expression of TFs [16] affecting growth and development in plants [17]. Manipulation of desired traits in plants by engineering TF genes is considered as a major future outlook [18].

Nuclear factor Y (NF-Y) is a class of transcription factor that has three subunits and all are vital for DNA-binding ability (NF-YA, NF-YB and NF-YC) [19]. The function of these TFs varies with the type of subunit. For example, NF-YA and NF-YB are involved in plant responses to drought stress, whereas NF-YC is involved in the regulation of flower development and light-mediated plant growth and development (photomorphogenesis) [20]. NF-Y transcription factors are also involved in plant-microbe interaction, root development and responses to stress [21]. Dark-grown phenotype was exhibited by *NF-Y* mutant plants even in the presence of light; this indicates that NFY TF is a positive regulator of photomorphogenesis [20]. In combination with NF-YB/NF-YC, NF-YA was found to be involved in flowering by triggering *FLOWERING LOCUS T* (FT) gene [22]. Overexpression of NF-YA5 in Arabidopsis resulted in tolerance to drought stress [23]. ABA disruptive phenotype was exhibited by *NF-YC* mutant Arabidopsis plants [24]. Nuclear factor Y complex binds with a unique *cis*-element within the SOC1 promoter region of Arabidopsis and regulates flowering time [25]. In Arabidopsis, leaf development is regulated by NF-YA2 and NF-YA10 via auxin signaling [26]. Arabidopsis nuclear transcription factor genes NF-YA1, 5, 6 and 9 play an important role in the regulation of male gametogenesis, embryogenesis and seed germination [27]. NF-YB confers drought tolerance and leads to improved yield in maize under water-limited conditions [28]. In Arabidopsis, NF-YC3, 4 and 9 are required for regulation of CONSTANTS (CO)-mediated photoperiod-independent flowering [29]. During the early seedling stage in Arabidopsis, under photomorphogenesis, hypocotyl elongation is suppressed by NF-YC1, 3, 4 and 9 [30]. Wheat *TaNF-YB3* gene imparts drought tolerance by regulating ABA-associated signaling pathway [31]. Overexpression of NF-YC9 confers ABA hypersensitivity in Arabidopsis [32].

MYB (myeloblastosis), a huge family protein, is characteristic of all eukaryotes and plays a diverse role in gene networking. Generally, MYB functions as transcription factor and their DNA-binding ability varies with the number of MYB domains [33]. In plants, MYB proteins are classified in four different classes depending upon the number of DNA-binding MYB domains: MYB-related, R2R3-MYBs, R1R2R3-MYBs and atypical MYBs [34]. The first plant MYB gene C1 was identified from maize [35]. Since their identification, they have been found to be extensively dispersed in plants and communicate with additional transcription factors [36]. MYB transcription factors are involved in the regulation of plant growth and development in various species like in soybean, they are involved in regulation of flower color [37] and regulation of signal transduction pathways in Arabidopsis, rice and cassava [38]. Biosynthesis of secondary metabolites is regulated in Arabidopsis and Medicago [36]. In Arabidopsis, sugarcane, potato, cotton, wheat, rice and *Camelina sativa*, they are involved in drought tolerance [39]. Chilling tolerance is imparted in Arabidopsis, wheat and rice [40]. MYB transcription factor genes are also involved in combating salt stress [41].

various biotic and abiotic stresses and will help in developing high yielding and stress toler-

transcriptionfactor.org/ index.cgi?Home

DBD is a database of predicted TFs in completely sequenced genomes

Provides information about function of TFs

TFs genes are regulated at both transcriptional and post-transcriptional level in plants [14]. Therefore, to build regulatory networks, understanding the expression of TFs is of great importance. Mainly, TFs act by binding the *cis* element present inside the transcription initiation (promoter) region of their target gene [15]. Recent studies have shown that changes in gene expression are closely related with changes in expression of TFs [16] affecting growth and development in plants [17]. Manipulation of desired traits in plants by engineering TF

Nuclear factor Y (NF-Y) is a class of transcription factor that has three subunits and all are vital for DNA-binding ability (NF-YA, NF-YB and NF-YC) [19]. The function of these TFs varies with the type of subunit. For example, NF-YA and NF-YB are involved in plant responses to drought stress, whereas NF-YC is involved in the regulation of flower development and light-mediated plant growth and development (photomorphogenesis) [20]. NF-Y transcription factors are also involved in plant-microbe interaction, root development and responses to stress [21]. Dark-grown phenotype was exhibited by *NF-Y* mutant plants even in the presence of light; this indicates that NFY TF is a positive regulator of photomorphogenesis [20]. In combination with NF-YB/NF-YC, NF-YA was found to be involved in flowering by triggering *FLOWERING LOCUS T* (FT) gene [22]. Overexpression of NF-YA5 in Arabidopsis resulted in tolerance to drought stress [23]. ABA disruptive phenotype was exhibited by *NF-YC* mutant Arabidopsis plants [24]. Nuclear factor Y complex binds with a unique *cis*-element within the SOC1 promoter region of Arabidopsis and regulates flowering time [25]. In Arabidopsis, leaf development is regulated by NF-YA2 and NF-YA10 via auxin signaling [26]. Arabidopsis nuclear transcription factor genes NF-YA1, 5, 6 and 9 play an important role in the regulation of male gametogenesis, embryogenesis and seed germination [27]. NF-YB confers drought tolerance and leads to improved yield in maize under water-limited conditions [28]. In Arabidopsis, NF-YC3, 4 and 9 are required for regulation of CONSTANTS (CO)-mediated photoperiod-independent flowering [29]. During the early seedling stage in Arabidopsis, under photomorphogenesis, hypocotyl elongation is suppressed by NF-YC1, 3, 4 and 9 [30]. Wheat *TaNF-YB3* gene imparts drought tolerance by regulating ABA-associated signaling pathway [31]. Overexpression of NF-YC9 confers ABA

ant varieties, which is the ultimate aim of the agricultural scientists.

**Database Acronym Public URL Description**

DBD http://www.

IT3F http://jicbio.nbi.ac.uk/ IT3F/

Transcription factor prediction database

Interspecies TF function finder for plants

**Table 1.** Plant transcription factors database.

106 Transcriptional and Post-transcriptional Regulation

**2. Regulatory roles of transcription factors in plants**

genes is considered as a major future outlook [18].

hypersensitivity in Arabidopsis [32].

Arabidopsis transcription factor APETALA2 (AP2) is involved in the regulation of complicated processes of plant growth and development, which includes seed development, maintenance of stem cells and flower development [42]. APETALA2 family, also known as "A" class, acts together with B and C class to determine the final floral organ development, and this interaction of transcription factors forms the well-known ABC model of flower development [43]. Pandey et al. identified an APETALA2 (AP2) domain TF in Arabidopsis that suppresses ABA response during seed germination and ABA and stress-induced gene expression. They also observed that *abr1* mutant plants were hypersensitive to osmotic stress and higher level of ABA was found in mutant plants; this supports that ABA-mediated gene regulation is suppressed by AP2 [44]. Overexpression of *Nicotiana tabacum Tsi1* gene encoding an EREBP/AP2 TF in tobacco enhances resistance against osmotic stress and pathogen attack [45]. Overexpression of *WXP1,* an AP2 domain-containing TF gene of *Medicago truncatula*, enhances wax accumulation and drought tolerance in transgenic alfalfa [46]. Overexpression of *ORA59*, an AP2/ERF transcription factor domain, results in enhanced resistance against fungus *Botrytis cinerea* [47]. WIND1 and AP2/ERF TFs regulate cell differentiation in Arabidopsis [48]. WRINKLED1 (WRI1), an AP2-type transcription factor, was found to be associated with triacylglycerol (TAGs) accumulation in Arabidopsis [49].

TCF transcription factors comprise a domain, called TCP domain, which shares a motif that forms a basic helix-loop-helix (bHLH) structure that has DNA-binding properties [50]. The name TCP came from TEOSINTE BRANCHED1, CYCLOIDEA (CYC) and PROLIFERATING CELL NUCLEAR ANTIGEN FACTOR1 (PCF1) and PCF2, first four members of the TCP family derived from maize, snapdragon and rice, respectively [51]. Earlier studies have shown that TCP has been involved in the regulation of leaf formation by regulating cell cycle [52]. TCP transcription factors are also involved in flower development [53], leaf senescence [54], shoot development [55], jasmonic acid and auxin signaling [56], cell proliferation [57], leaf shape regulation [58], development of macro and micro [50], mitochondrial biogenesis [59] and regulating circadian cycle [60].

One of the largest and diverse families of plant regulators is WRKY transcription factors, with nearly 74 members in Arabidopsis, over 100 in rice, soybean and poplar [61]. There is at least one conserved DNA-binding domain called WRKY domain, which comprises a preserved protein sequence (WRKYGQK) and a zinc-finger domain. Both of these sequences (hexapeptide and zinc finger domain) are required for binding to *cis* element known as W box (TTGACT/C) [62]. WRKY transcription factors are involved in several molecular and genetic pathways to regulate multiple responses simultaneously, whether it is abiotic or biotic stress [63]. Production of few secondary metabolites like lignin, flavanols and tannins is also regulated by WRKY TFs [64].

NAC transcription factors are one of the major class of plant regulators, engaged in stress responses. The name NAC is derived from three genes initially having the NAC domain; no apical meristem (NAM), Arabidopsis transcription activation factor (ATAF1/2) and cup-shaped cotyledon (CUC2) [65]. The availability of genome sequencing technology has led to the identification of several NAC TFs genes in various species like 117 in Arabidopsis, 151 in rice, 79 in grape, 26 in citrus, 163 in poplar, 152 each in soybean and tobacco, 145 in cotton, 45 in tea plant, 172 in radish, 152 in maize and 110 in potato [66]. In Arabidopsis, of 10 NAC domains 9 domains bind to a conserved DNA target with a GGT[GA] core [67]. NAC TFs are mainly involved in the regulation of plant growth and development under biotic and abiotic stress [68].

Another important class of TFs that belong to plant kingdom is homeodomain-leucine zippers (HD-Zip). In Arabidopsis, there are more than 25 genes that encode these TFs. The HD-Zip protein is characterized by the presence of two important domains: a homeodomain (HD) involved in DNA binding and leucine zipper domain (Zip) responsible for protein-protein interactions [69]. On the basis of earlier sequence similarity findings, HD-Zip class of TFs has been grouped into four different classes (HD-Zip I, II, III and IV). Class I TFs (HD-Zip I) are engaged in ABA (abscisic acid) signaling, embryo development and responses to abiotic stress. Class II (HD-Zip II) TFs are involved hormone signaling (auxin), responses to light and shade. Likewise, class III (HD-Zip III) regulate embryo development, initiation of lateral organs, leaf polarity and meristem functioning, whereas class IV (HD-Zip IV) governs trichome development, root development, epidermal cell differentiation and accumulation of anthocyanin [69].

## **3. Interplay between transcription factors and miRNA**

Plant miRNAs are involved in regulatory networks, which control differential gene expression at tissue and developmental levels. MiRNAs and TFs provide combinatorial gene regulation involving diverse functions which can further be exploited in crop improvement. Combination of microRNA and their targets, which are mainly transcription factors that depict an integrated image for designing regulatory relationship but it could be very difficult at times to develop a clear cut relationship as interaction could take place with each other leading to some novel regulatory pathway. With the advancement in bioinformatic softwares and use of advanced techniques, it is comparatively easy to develop an interaction. MiRNA and TFs are among the primary regulators of gene expression, thus affect plant phenotype in relation to growth and development (**Table 2**).

by negatively regulating AUXIN RESPONSE FACTORs (ARF 10, 16 and 17) and resulted into shorter roots with tumor like puffed-up apex, if overexpression of miRNA160 occurs [70]. Apart from this, another miR164 targets transcription factors of the NAC (NAMATAF-CUC) family and regulates lateral root initiation by limiting NAC1expression [71]. Similarly, in legumes such as *M. truncatula*, miR166 and HD-Zip regulate cell-to-cell communication in root vascular and meristematic tissues [72]. In *A. thaliana*, miR169 isoforms are engaged in targeting NF-YA TF and control primary root growth. The prevention of miR169 expression affects lateral root initiation led to altered dimensions in root meristem [73]. The cross talk between miR166/165 and their target HD-Zip III ensures root development in *Arabidopsis thaliana* as well as in Maize.

169 NY-FA *A. thaliana* Root architecture, nodule formation, drought and salinity stress, abscisic acid response

Lateral root development

Leaf and grain development

Lateral root development Drought tolerance 166 HD-Zip III *A. thaliana* Shoot apical meristem, organ polarity and vascular development

Floral development

Nodule formation

*T. aestivum* Contribute resistance against *P. striiformis f. sp. Tritici (Pst*)

828 and 858 MYB *G. hirsutum* Fiber development, response to high temperature

*O. sativa* Response to arsenic treatment

319 TCP *A. thaliana* Leaf and floral development, jasmonic acid biosynthesis

WRKY *H. annuus* L. Response to high temperature

Seed germination, senescence, ABA hypersensitivity

Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement

http://dx.doi.org/10.5772/intechopen.75942

109

Phosphorus is essential nutrient for plants and can be acquired by plants only as inorganic phosphate. Certain transcription factors, such as AtPHR1, AtWRKY75, AtZAT6 and

**3.2. Phosphate content**

**miRNA TF family Plant Role**

*O. sativa*

*Z. mays*

*Z. mays*

*A. thaliana Z. mays*

*Z. mays O. sativa S. lycopersicum*

*P. vulgaris*

**Table 2.** Differential role of TF-MiRNA interaction in plants.

447 and 5255 MYB *G. hirsutum* Root and fiber development

159 MYB *A. thaliana*

164 NAC1 *A. thaliana*

396 GRF *A. thaliana*

NAC1

156 SPL *A. thaliana*

172 AP2 *Glycine max,*

164 NAC

#### **3.1. Root architecture**

MiRNAs and TFs together govern the regulatory network involved in the development of root architecture in various species. In *A. thaliana*, miR160 is known to play key role in root growth


**Table 2.** Differential role of TF-MiRNA interaction in plants.

by negatively regulating AUXIN RESPONSE FACTORs (ARF 10, 16 and 17) and resulted into shorter roots with tumor like puffed-up apex, if overexpression of miRNA160 occurs [70]. Apart from this, another miR164 targets transcription factors of the NAC (NAMATAF-CUC) family and regulates lateral root initiation by limiting NAC1expression [71]. Similarly, in legumes such as *M. truncatula*, miR166 and HD-Zip regulate cell-to-cell communication in root vascular and meristematic tissues [72]. In *A. thaliana*, miR169 isoforms are engaged in targeting NF-YA TF and control primary root growth. The prevention of miR169 expression affects lateral root initiation led to altered dimensions in root meristem [73]. The cross talk between miR166/165 and their target HD-Zip III ensures root development in *Arabidopsis thaliana* as well as in Maize.

#### **3.2. Phosphate content**

sequence (WRKYGQK) and a zinc-finger domain. Both of these sequences (hexapeptide and zinc finger domain) are required for binding to *cis* element known as W box (TTGACT/C) [62]. WRKY transcription factors are involved in several molecular and genetic pathways to regulate multiple responses simultaneously, whether it is abiotic or biotic stress [63]. Production of few secondary metabolites like lignin, flavanols and tannins is also regulated by WRKY TFs [64].

108 Transcriptional and Post-transcriptional Regulation

NAC transcription factors are one of the major class of plant regulators, engaged in stress responses. The name NAC is derived from three genes initially having the NAC domain; no apical meristem (NAM), Arabidopsis transcription activation factor (ATAF1/2) and cup-shaped cotyledon (CUC2) [65]. The availability of genome sequencing technology has led to the identification of several NAC TFs genes in various species like 117 in Arabidopsis, 151 in rice, 79 in grape, 26 in citrus, 163 in poplar, 152 each in soybean and tobacco, 145 in cotton, 45 in tea plant, 172 in radish, 152 in maize and 110 in potato [66]. In Arabidopsis, of 10 NAC domains 9 domains bind to a conserved DNA target with a GGT[GA] core [67]. NAC TFs are mainly involved in the regulation of plant growth and development under biotic and abiotic stress [68]. Another important class of TFs that belong to plant kingdom is homeodomain-leucine zippers (HD-Zip). In Arabidopsis, there are more than 25 genes that encode these TFs. The HD-Zip protein is characterized by the presence of two important domains: a homeodomain (HD) involved in DNA binding and leucine zipper domain (Zip) responsible for protein-protein interactions [69]. On the basis of earlier sequence similarity findings, HD-Zip class of TFs has been grouped into four different classes (HD-Zip I, II, III and IV). Class I TFs (HD-Zip I) are engaged in ABA (abscisic acid) signaling, embryo development and responses to abiotic stress. Class II (HD-Zip II) TFs are involved hormone signaling (auxin), responses to light and shade. Likewise, class III (HD-Zip III) regulate embryo development, initiation of lateral organs, leaf polarity and meristem functioning, whereas class IV (HD-Zip IV) governs trichome development, root development, epidermal cell differentiation and accumulation of anthocyanin [69].

**3. Interplay between transcription factors and miRNA**

relation to growth and development (**Table 2**).

**3.1. Root architecture**

Plant miRNAs are involved in regulatory networks, which control differential gene expression at tissue and developmental levels. MiRNAs and TFs provide combinatorial gene regulation involving diverse functions which can further be exploited in crop improvement. Combination of microRNA and their targets, which are mainly transcription factors that depict an integrated image for designing regulatory relationship but it could be very difficult at times to develop a clear cut relationship as interaction could take place with each other leading to some novel regulatory pathway. With the advancement in bioinformatic softwares and use of advanced techniques, it is comparatively easy to develop an interaction. MiRNA and TFs are among the primary regulators of gene expression, thus affect plant phenotype in

MiRNAs and TFs together govern the regulatory network involved in the development of root architecture in various species. In *A. thaliana*, miR160 is known to play key role in root growth Phosphorus is essential nutrient for plants and can be acquired by plants only as inorganic phosphate. Certain transcription factors, such as AtPHR1, AtWRKY75, AtZAT6 and AtBHLH32, regulate phosphate starvation responsive genes in plants. The interplay between miR399 and transcription factor AtMYB2 is known to function in abiotic stress signaling in Arabidopsis, and overexpression of AtMYB2 results into increased phosphorous uptake and changes in root architecture [39].

development in *M. truncatula* [76]. In legumes, such as soybean and common beans, miR172

Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement

http://dx.doi.org/10.5772/intechopen.75942

111

MicroRNA and TFs play a vital role in leaf morphogenesis such as miR319 and TCP are involved in regulation of leaf size. Increase in leaf size was observed with loss of function of miR319 [81]. Similarly, miR319 overexpression resulted in enlarged leaf formation in tomato [82]. Another miRNA family (miR396) targets GRF (GROWTH-REGULATING FACTOR) TF family and regulates leaf morphogenesis [83]. Cell division in leaves is enhanced by suppression of six GRF genes and GIF1 by overexpression of miR396 [83]. MiR396 and GRF TFs are found to be associated with effective grain filling in maize [84]. Similar findings were observed in rice where LOC\_Os02g47280 was downregulated by miR396 and was found to be responsible for grain shape [85]. These studies approved the networking between miR396 and GRF transcription factor and suggested the strong role in leaf development and

Plants exhibit a long period of organogenesis and give rise to new leaves throughout their life cycle depending upon the activity of shoot meristems. The transcripts of miR165 and miR166 are detected in shoot apical meristem, leaf primordial and vascular tissues in Arabidopsis. The interaction of HD-Zip III with miR165 and miR166 is well known [86]. It regulates diverse functions including plant development, apical and lateral meristem formation, vascular growth and leaf polarity. Downregulation of three HD-Zip genes (ATHB-9/PHV, ATHB-14/ PHB and ATHB-15) resulted into recapitulate phenotype upon overexpression of miR166. Similarly, downregulation of five HD-Zip genes by overexpression of miR165 resulted in loss of SAM (shoot apical meristem), changed organ polarity and defected vascular development [87]. MiR165 and miR166 are involved in the regulation of leaf asymmetry patterning in maize and Arabidopsis. The suppression of HD-Zip by miRNA is responsible for vascular pattern-

In Arabidopsis, miR858a is supposed to target R2R3-MYB transcription factor. Genomic analysis suggested that miR858a targets various regulatory factors involved in plant growth and development. Overexpression of miR858a led to downregulation of several MYB transcription factors, which in turn regulates and redirects the metabolic flux towards flavonoid bio-

Jasmonic acid (JA) acts as systemic signaling molecule, which is effective against tomato root knot disease (RKN). This can reduce the number of root knots from nematode invasion resulting into JA-mediated RKN resistance in roots. Several miRNAs are found responsive

interacts with AP2 TFs to regulate nodule organogenesis [80].

**3.7. Leaf morphogenesis and grain filling**

**3.8. Shoot apical meristem and vascular patterning**

ing in leaves and stem in both monocots and dicots [86].

**3.9. Flavonoid biosynthesis pathway**

**3.10. Jasmonic acid biosynthesis**

grain filling.

synthesis [88].

#### **3.3. Leaf senescence**

Leaf senescence is a physiological process, which affects vegetative and productive developmental processes in plants. Increased seed yield and prolonged life span are observed during delayed. The conversion, which occurs from leaf maturation to senescence, is complex and is associated with several genes and transcription factors such as MYB, SQUAMOSA PRMOTER BINDING-LIKE (SPL), WRKY, etc. [74]. Transcription factor MYB was targeted by zms-miR 159d and was downregulated in maize inbred line ELS-1, whereas in Yu87-1inbreed line, zms-miR 159d was found to be upregulated [75].

### **3.4. Fiber development**

Various studies have reported that different transcription factors play an important role in fiber initiation. For example, MYB transcription factors are involved in fiber trichome development in cotton. TFs are predicted to be targeted by certain miRNAs such as MYB3 and MYB88 are targeted by miR447, which is significantly expressed during different fiber initiation, elongation and secondary wall synthesis and play important role in fiber development under salinity and drought stress [76]. In a recent study, MYB genes, including MYB2, MYB3 and MYB12, are targeted by miR828 and are known to play negative role in fiber elongation [77].

#### **3.5. Floral development**

Different microRNAs function and play role throughout flower development from early stages to late stages. These microRNAs target various transcription factors by targeting and downregulation and affect floral timing [78]. There are around 11 different miRNA families (miR156, miR159, miR160, miR164, miR165/miR166, miR167, miR169, miR172, miR319, miR390 and miR399) that regulate flower development at several stages. MiR156, miR172 and miR399 mediate plant changes from juvenile to adult, whereas mR159, miR169, miR172 and miR399 mediate transition from vegetative to adult. MiR156 controls flower development in rice, tomato and maize, and its role is found to be conserved [78]. The targets of miR156 are SPL (SQUAMOSA PROMOTER BINDING-LIKE) TFs, which are being downregulated in Arabidopsis, and miR172 targets expression of APETELA2, which resulted in delayed flowering by inhibiting translation [79].

#### **3.6. Nodule formation**

Nodule formation and establishment of symbiotic relationship are complex processes. Various miRNA and transcription factors are associated with nodule development. It was suggested that miR169-mediated repression of MtHAP2, a transcription factor, was required for nodule development in *M. truncatula* [76]. In legumes, such as soybean and common beans, miR172 interacts with AP2 TFs to regulate nodule organogenesis [80].

#### **3.7. Leaf morphogenesis and grain filling**

AtBHLH32, regulate phosphate starvation responsive genes in plants. The interplay between miR399 and transcription factor AtMYB2 is known to function in abiotic stress signaling in Arabidopsis, and overexpression of AtMYB2 results into increased phosphorous uptake and

Leaf senescence is a physiological process, which affects vegetative and productive developmental processes in plants. Increased seed yield and prolonged life span are observed during delayed. The conversion, which occurs from leaf maturation to senescence, is complex and is associated with several genes and transcription factors such as MYB, SQUAMOSA PRMOTER BINDING-LIKE (SPL), WRKY, etc. [74]. Transcription factor MYB was targeted by zms-miR 159d and was downregulated in maize inbred line ELS-1, whereas in Yu87-1inbreed

Various studies have reported that different transcription factors play an important role in fiber initiation. For example, MYB transcription factors are involved in fiber trichome development in cotton. TFs are predicted to be targeted by certain miRNAs such as MYB3 and MYB88 are targeted by miR447, which is significantly expressed during different fiber initiation, elongation and secondary wall synthesis and play important role in fiber development under salinity and drought stress [76]. In a recent study, MYB genes, including MYB2, MYB3 and MYB12, are targeted by miR828 and are known to play negative role in fiber

Different microRNAs function and play role throughout flower development from early stages to late stages. These microRNAs target various transcription factors by targeting and downregulation and affect floral timing [78]. There are around 11 different miRNA families (miR156, miR159, miR160, miR164, miR165/miR166, miR167, miR169, miR172, miR319, miR390 and miR399) that regulate flower development at several stages. MiR156, miR172 and miR399 mediate plant changes from juvenile to adult, whereas mR159, miR169, miR172 and miR399 mediate transition from vegetative to adult. MiR156 controls flower development in rice, tomato and maize, and its role is found to be conserved [78]. The targets of miR156 are SPL (SQUAMOSA PROMOTER BINDING-LIKE) TFs, which are being downregulated in Arabidopsis, and miR172 targets expression of APETELA2, which resulted in delayed flower-

Nodule formation and establishment of symbiotic relationship are complex processes. Various miRNA and transcription factors are associated with nodule development. It was suggested that miR169-mediated repression of MtHAP2, a transcription factor, was required for nodule

changes in root architecture [39].

110 Transcriptional and Post-transcriptional Regulation

line, zms-miR 159d was found to be upregulated [75].

**3.3. Leaf senescence**

**3.4. Fiber development**

elongation [77].

**3.5. Floral development**

ing by inhibiting translation [79].

**3.6. Nodule formation**

MicroRNA and TFs play a vital role in leaf morphogenesis such as miR319 and TCP are involved in regulation of leaf size. Increase in leaf size was observed with loss of function of miR319 [81]. Similarly, miR319 overexpression resulted in enlarged leaf formation in tomato [82]. Another miRNA family (miR396) targets GRF (GROWTH-REGULATING FACTOR) TF family and regulates leaf morphogenesis [83]. Cell division in leaves is enhanced by suppression of six GRF genes and GIF1 by overexpression of miR396 [83]. MiR396 and GRF TFs are found to be associated with effective grain filling in maize [84]. Similar findings were observed in rice where LOC\_Os02g47280 was downregulated by miR396 and was found to be responsible for grain shape [85]. These studies approved the networking between miR396 and GRF transcription factor and suggested the strong role in leaf development and grain filling.

#### **3.8. Shoot apical meristem and vascular patterning**

Plants exhibit a long period of organogenesis and give rise to new leaves throughout their life cycle depending upon the activity of shoot meristems. The transcripts of miR165 and miR166 are detected in shoot apical meristem, leaf primordial and vascular tissues in Arabidopsis. The interaction of HD-Zip III with miR165 and miR166 is well known [86]. It regulates diverse functions including plant development, apical and lateral meristem formation, vascular growth and leaf polarity. Downregulation of three HD-Zip genes (ATHB-9/PHV, ATHB-14/ PHB and ATHB-15) resulted into recapitulate phenotype upon overexpression of miR166. Similarly, downregulation of five HD-Zip genes by overexpression of miR165 resulted in loss of SAM (shoot apical meristem), changed organ polarity and defected vascular development [87]. MiR165 and miR166 are involved in the regulation of leaf asymmetry patterning in maize and Arabidopsis. The suppression of HD-Zip by miRNA is responsible for vascular patterning in leaves and stem in both monocots and dicots [86].

#### **3.9. Flavonoid biosynthesis pathway**

In Arabidopsis, miR858a is supposed to target R2R3-MYB transcription factor. Genomic analysis suggested that miR858a targets various regulatory factors involved in plant growth and development. Overexpression of miR858a led to downregulation of several MYB transcription factors, which in turn regulates and redirects the metabolic flux towards flavonoid biosynthesis [88].

#### **3.10. Jasmonic acid biosynthesis**

Jasmonic acid (JA) acts as systemic signaling molecule, which is effective against tomato root knot disease (RKN). This can reduce the number of root knots from nematode invasion resulting into JA-mediated RKN resistance in roots. Several miRNAs are found responsive to jasmonic acid against pathogen infection. Recent study demonstrated negative correlation between miR319 and its target TCP4 in tomato using reverse genetic approaches. This interaction leads to change in levels of jasmonic acid in leaves. The potential cross talk between miR319 and TCP4 modulates systemic defensive response [89].

**3.12. Drought tolerance**

**3.13. Fungal pathogen resistance**

**3.14. Juvenile to adult plant development**

bility of juvenile and adult phases (**Figure 1**) [79].

**4. Conclusion**

Communication between miR164 and NAC TF genes confer negative regulatory role in drought resistance in rice in addition to developmental roles. In transgenic Arabidopsis plants, overexpression of miR169a in NF-YA5 mutants resulted in increased susceptibility towards water stress in comparison to wild-type plants. Enhanced drought tolerance was observed in plants overexpressing NF-YA5. In addition to drought tolerance, miR169 is also

Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement

http://dx.doi.org/10.5772/intechopen.75942

113

The molecular crosstalk between miRNA and transcription factor is necessary to better understand the disease development. In wheat, stripe rust caused by Puccinia is a serious disease occurring during growing season. Crosstalk between miR164 and NAC21/22 TF resulted into reduced stripe rust resistance. These results conclude that mir164 and novel transcription fac-

The conversion from juvenile to adult is accompanied by changes in vegetative morphology and increase in reproductive potential. The regulatory mechanism of this transition involves miR156, miR172 and SPL gene family in case of Arabidopsis. SQUAMOSA PROMOTER BINDING-LIKE (SPL) TF family is a major target of miR156, and 11 SPL genes are repressed through translational inhibition and mRNA cleavage [95]. MiR156 and miR172 are positively regulated by transcription factors they target, and negative feedback loops contribute to sta-

Regulatory network involving TFs and miRNA provides deep insight in understanding the complexity of gene regulation in plants. Till date, the computationally and experimentally mapped networks portray considerable information on gene regulation. The complete spectrum of miRNA and their interactions with transcription factors need to be considered in order to study regulatory interactions at particular developmental times or in a tissue specific manner. However, it will be imperative to incorporate all accessible miRNA, TF and target expression blueprint to confine the network to just those communications that can happen and to extend the studies in different set of conditions. For the computational researchers, the particular issues will be to gather and analyze the accessible information, make predictions and to approve the speculations in view of literature or wet lab experiments for set up of regulatory network. In near future, better understanding of regulatory networks is expected, which will enable us for manipulating gene expression for crop improvement and industrial applications. At present, it is, by all accounts, a difficult work to build complete real-time networks

related with salt stress [92]. This phenomenon was also observed with miR393 [93].

tor are imperative in the development of stripe rust resistance in wheat [94].

#### **3.11. High temperature tolerance**

An environmental fluctuation such as high temperature imparts detrimental effect on plants. Some plants show tolerance to these stresses than others and are regulated by a wide network of transcriptional cross talk between transcription factors such as WRKY, ERF, NAC, MADS and miRNA. WRKY TFs found most exclusively in plants and are involved in various developmental and physiological processes. When plants are exposed to high temperature or salicylic acid in case of sunflower, opposite expression of HaWRKY6 and miR396 was observed [90]. In case of cotton, MYB transcription factor is known to be upregulated against high temperature and was targeted by miR828a and miR858 [91].

**Figure 1.** Interaction between miRNAs and TFs for gene regulation in plants.

#### **3.12. Drought tolerance**

to jasmonic acid against pathogen infection. Recent study demonstrated negative correlation between miR319 and its target TCP4 in tomato using reverse genetic approaches. This interaction leads to change in levels of jasmonic acid in leaves. The potential cross talk between

An environmental fluctuation such as high temperature imparts detrimental effect on plants. Some plants show tolerance to these stresses than others and are regulated by a wide network of transcriptional cross talk between transcription factors such as WRKY, ERF, NAC, MADS and miRNA. WRKY TFs found most exclusively in plants and are involved in various developmental and physiological processes. When plants are exposed to high temperature or salicylic acid in case of sunflower, opposite expression of HaWRKY6 and miR396 was observed [90]. In case of cotton, MYB transcription factor is known to be upregulated against high

miR319 and TCP4 modulates systemic defensive response [89].

temperature and was targeted by miR828a and miR858 [91].

**Figure 1.** Interaction between miRNAs and TFs for gene regulation in plants.

**3.11. High temperature tolerance**

112 Transcriptional and Post-transcriptional Regulation

Communication between miR164 and NAC TF genes confer negative regulatory role in drought resistance in rice in addition to developmental roles. In transgenic Arabidopsis plants, overexpression of miR169a in NF-YA5 mutants resulted in increased susceptibility towards water stress in comparison to wild-type plants. Enhanced drought tolerance was observed in plants overexpressing NF-YA5. In addition to drought tolerance, miR169 is also related with salt stress [92]. This phenomenon was also observed with miR393 [93].

#### **3.13. Fungal pathogen resistance**

The molecular crosstalk between miRNA and transcription factor is necessary to better understand the disease development. In wheat, stripe rust caused by Puccinia is a serious disease occurring during growing season. Crosstalk between miR164 and NAC21/22 TF resulted into reduced stripe rust resistance. These results conclude that mir164 and novel transcription factor are imperative in the development of stripe rust resistance in wheat [94].

#### **3.14. Juvenile to adult plant development**

The conversion from juvenile to adult is accompanied by changes in vegetative morphology and increase in reproductive potential. The regulatory mechanism of this transition involves miR156, miR172 and SPL gene family in case of Arabidopsis. SQUAMOSA PROMOTER BINDING-LIKE (SPL) TF family is a major target of miR156, and 11 SPL genes are repressed through translational inhibition and mRNA cleavage [95]. MiR156 and miR172 are positively regulated by transcription factors they target, and negative feedback loops contribute to stability of juvenile and adult phases (**Figure 1**) [79].

## **4. Conclusion**

Regulatory network involving TFs and miRNA provides deep insight in understanding the complexity of gene regulation in plants. Till date, the computationally and experimentally mapped networks portray considerable information on gene regulation. The complete spectrum of miRNA and their interactions with transcription factors need to be considered in order to study regulatory interactions at particular developmental times or in a tissue specific manner. However, it will be imperative to incorporate all accessible miRNA, TF and target expression blueprint to confine the network to just those communications that can happen and to extend the studies in different set of conditions. For the computational researchers, the particular issues will be to gather and analyze the accessible information, make predictions and to approve the speculations in view of literature or wet lab experiments for set up of regulatory network. In near future, better understanding of regulatory networks is expected, which will enable us for manipulating gene expression for crop improvement and industrial applications. At present, it is, by all accounts, a difficult work to build complete real-time networks for more experimental information. Still, it is a long way to establish complete miRNA-mediated regulatory network in plants.

[8] Nazarov P V, Reinsbach SE, Muller A, Nicot N, Philippidou D, Vallar L, et al. Interplay of microRNAs, transcription factors and target genes: Linking dynamic expression changes to function. Nucleic Acids Research [Internet]. Mar 1, 2013;**41**(5):2817-2831. Available

Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement

http://dx.doi.org/10.5772/intechopen.75942

115

[9] Cammaerts S, Strazisar M, De Rijk P, Del Favero J. Genetic variants in microRNA genes: Impact on microRNA expression, function, and disease. Frontiers in Genetics [Internet]. 2015;**6**:186. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26052338 [Accessed:

[10] Akhtar MM, Micolucci L, Islam MS, Olivieri F, Procopio AD. Bioinformatic tools for microRNA dissection. Nucleic Acids Research [Internet]. Jan 8, 2016;**44**(1):24-44. DOI:

[11] Jin J, Tian F, Yang D-C, Meng Y-Q, Kong L, Luo J, et al. PlantTFDB 4.0: Toward a central hub for transcription factors and regulatory interactions in plants. Nucleic Acids Research [Internet]. Jan 4, 2017;**45**(D1):D1040-D10405. Available from: http://www.ncbi.

[12] Chow C-N, Zheng H-Q, Wu N-Y, Chien C-H, Huang H-D, Lee T-Y, et al. PlantPAN 2.0: An update of plant promoter analysis navigator for reconstructing transcriptional regulatory networks in plants. Nucleic Acids Research [Internet]. Jan 4, 2016;**44**(D1):D1154-D1160. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26476450 [Accessed: Jan 20, 2018]

[13] Mitsuda N, Ohme-Takagi M. Functional analysis of transcription factors in arabidopsis. Plant and Cell Physiology [Internet]. Jul 2009;**50**(7):1232-1248. Available from: http://

[14] Payne JL, Wagner A. Mechanisms of mutational robustness in transcriptional regulation. Frontiers in Genetics [Internet]. Oct 27, 2015;**6**(Oct):322. Available from: http://www.

[15] Biłas R, Szafran K, Hnatuszko-Konka K, Kononowicz AK. Cis-regulatory elements used to control gene expression in plants. Plant Cell, Tissue and Organ Culture [Internet]. Nov 10, 2016;**127**(2):269-287. Available from: http://link.springer.com/10.1007/s11240-

[16] Yan X, Dong C, Yu J, Liu W, Jiang C, Liu J, et al. Transcriptome profile analysis of young floral buds of fertile and sterile plants from the self-pollinated offspring of the hybrid between novel restorer line NR1 and Nsa CMS line in *Brassica napus*. BMC Genomics [Internet]. Jan 16, 2013;**14**(1):26. Available from: http://www.ncbi.nlm.nih.gov/pubmed/

[17] Li J, Han S, Ding X, He T, Dai J, Yang S, et al. Comparative transcriptome analysis between the cytoplasmic male sterile line NJCMS1A and its maintainer NJCMS1B in soybean (*Glycine max* (L.) Merr.). Tian Z, editor. PLoS One [Internet]. May 18, 2015;**10**(5):e0126771. Available from: http://dx.plos.org/10.1371/journal.pone.0126771 [Accessed: Jan 21, 2018]

[18] Weng L, Bai X, Zhao F, Li R, Xiao H. Manipulation of flowering time and branching by overexpression of the tomato transcription factor SlZFP2. Plant Biotechnology Journal

www.ncbi.nlm.nih.gov/pubmed/19478073 [Accessed: Jan 20, 2018]

ncbi.nlm.nih.gov/pubmed/26579194 [Accessed: Jan 20, 2018]

016-1057-7 [Accessed: Jan 20, 2018]

23324545 [Accessed: Jan 21, 2018]

from: http://www.ncbi.nlm.nih.gov/pubmed/23335783 [Accessed: Jan 19, 2008]

Jan 19, 2018]

10.1093/nar/gkv1221 [Accessed: Jan 19, 2018]

nlm.nih.gov/pubmed/27924042 [Accessed: Jan 20, 2018]

## **Author details**

Sumit Jangra, Vrantika Chaudhary and Neelam R. Yadav\*

\*Address all correspondence to: nryadav58@gmail.com

Department of Molecular Biology, Biotechnology and Bioinformatics, CCS Haryana Agricultural University, Hisar, India

## **References**


[8] Nazarov P V, Reinsbach SE, Muller A, Nicot N, Philippidou D, Vallar L, et al. Interplay of microRNAs, transcription factors and target genes: Linking dynamic expression changes to function. Nucleic Acids Research [Internet]. Mar 1, 2013;**41**(5):2817-2831. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23335783 [Accessed: Jan 19, 2008]

for more experimental information. Still, it is a long way to establish complete miRNA-medi-

Department of Molecular Biology, Biotechnology and Bioinformatics, CCS Haryana

[1] Morris KV, Mattick JS. The rise of regulatory RNA. Nature Reviews Genetics [Internet]. Jun 29, 2014;**15**(6):423-437. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24776770

[2] Osório J. Landscape and mechanisms of transcription factor cooperativity. Nature Reviews Genetics [Internet]. Jan 23, 2016;**17**(1):5-5. Available from: http://www.ncbi.nlm.

[3] Duval I, Lachance D, Giguère I, Bomal C, Morency M-J, Pelletier G, etal. Large-scale screening of transcription factor-promoter interactions in spruce reveals a transcriptional network involved in vascular development. Journal of Experimental Botany [Internet]. Jun 2014;**65**(9):2319-2333. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24713992

[4] Bartel DP. MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell. 2004;**116**:

[5] Lee RC, Feinbaum RL, Ambros V. The *C. elegans* heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell [Internet]. Dec 1993;**75**(5):843-854. Available from: http://www.cell.com/cell/pdf/0092-8674(93)90529-Y.pdf?\_returnURL=h ttps%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2F009286749390529Y%3F

[6] Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, Bettinger JC, Rougvie AE, et al. The 21-nucleotide let-7 RNA regulates developmental timing in *Caenorhabditis elegans*. Nature [Internet]. Feb 24, 2000;**403**(6772):901-906. Available from: http://www.nature.com/articles/

[7] Wang Y, Lan Q, Zhao X, Xu W, Li F, Wang Q, et al. Comparative profiling of microRNA expression in soybean seeds from genetically modified plants and their near-isogenic parental lines (Xue Y, editor). PLoS One [Internet]. May 23, 2016;**11**(5):e0155896. Available from: http://dx.plos.org/10.1371/journal.pone.0155896 [Accessed: Jan 19, 2018]

ated regulatory network in plants.

114 Transcriptional and Post-transcriptional Regulation

Agricultural University, Hisar, India

[Accessed: Jan 19, 2018]

[Accessed: Jan 19, 2018]

281-297

Sumit Jangra, Vrantika Chaudhary and Neelam R. Yadav\*

nih.gov/pubmed/26593418 [Accessed: Jan 19, 2008]

showall%3Dtrue [Accessed: Feb 17, 2018]

35002607 [Accessed: Feb 17, 2008]

\*Address all correspondence to: nryadav58@gmail.com

**Author details**

**References**


[Internet]. Dec 2016;**14**(12):2310-2321. Available from: http://www.ncbi.nlm.nih.gov/ pubmed/27214796 [Accessed: Jan 21, 2018]

on water-limited acres. Proceedings of the National Academy of Sciences of the United States of America [Internet]. Oct 16, 2007;**104**(42):16450-16455. Available from: http://

Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement

http://dx.doi.org/10.5772/intechopen.75942

117

[29] Kumimoto RW, Zhang Y, Siefers N, Holt BF. NF-YC3, NF-YC4 and NF-YC9 are required for CONSTANS-mediated, photoperiod-dependent flowering in *Arabidopsis thaliana*. Plant Journal [Internet]. 2010 Aug 1, 2010;**63**(3):379-391. DOI: 10.1111/j.1365-

[30] Tang Y, Liu X, Liu X, Li Y, Wu K, Hou X.Arabidopsis NF-YCs mediate the light-controlled hypocotyl elongation via modulating histone acetylation. Molecular Plant [Internet]. Feb 13, 2017;**10**(2):260-273. Available from: http://www.sciencedirect.com/science/article/pii/

[31] Yang M, Zhao Y, Shi S, Du X, Gu J, Xiao K. Wheat nuclear factor Y (NF-Y) B subfamily gene TaNF-YB3;l confers critical drought tolerance through modulation of the ABAassociated signaling pathway. Plant Cell, Tissue and Organ Culture [Internet]. Jan 19, 2017;**128**(1):97-111. Available from: http://link.springer.com/10.1007/s11240-016-1088-0

[32] Bi C, Ma Y, Wang X-F, Zhang D-P. Overexpression of the transcription factor NF-YC9 confers abscisic acid hypersensitivity in Arabidopsis. Plant Molecular Biology [Internet]. Nov 18, 2017;**95**(4-5):425-439. Available from: http://link.springer.com/10.1007/s11103-

[33] Ambawat S, Sharma P, Yadav NR, Yadav RC. MYB transcription factor genes as regulators for plant responses: an overview. Physiology and Molecular Biology of Plants [Internet]. Jul 2013;**19**(3):307-321. Available from: http://www.ncbi.nlm.nih.gov/pubmed/

[34] Dubos C, Stracke R, Grotewold E, Weisshaar B, Martin C, Lepiniec L. MYB transcription factors in Arabidopsis. Trends in Plant Sciences [Internet]. Oct 2010;**15**(10):573-581. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20674465 [Accessed: Jan 22, 2018]

[35] Paz-Ares J, Ghosal D, Wienand U, Peterson PA, Saedler H. The regulatory c1 locus of *Zea mays* encodes a protein with homology to myb proto-oncogene products and with structural similarities to transcriptional activators. EMBO Journal [Internet]. Dec 1, 1987;**6**(12):3553-3558. Available from: http://www.ncbi.nlm.nih.gov/pubmed/3428265

[36] Nguyen NH, Lee H. MYB-related transcription factors function as regulators of the circadian clock and anthocyanin biosynthesis in Arabidopsis. Plant Signaling & Behavior [Internet]. Mar 3, 2016;**11**(3):e1139278. Available from: http://www.ncbi.nlm.nih.gov/

[37] Takahashi R, Yamagishi N, Yoshikawa N. A MYB transcription factor controls flower color in soybean. Journal of Heredity [Internet]. Jan 1, 2013;**104**(1):149-153. Available

[38] Liao W, Yang Y, Li Y, Wang G, Peng M. Genome-wide identification of cassava R2R3 MYB family genes related to abscission zone separation after environmental-stress-induced

from: http://www.ncbi.nlm.nih.gov/pubmed/23048163 [Accessed: Jan 22, 2018]

www.ncbi.nlm.nih.gov/pubmed/17923671 [Accessed: Jan 22, 2018]

313X.2010.04247.x [Accessed: Jan 22, 2018]

S1674205216302775 [Accessed: Jan 22, 2018]

[Accessed: Jan 22, 2018]

017-0661-1 [Accessed: 2018 Jan 22]

24431500 [Accessed: Jan 22, 2018]

[Accessed: Jan 22, 2018]

pubmed/26905954 [Accessed: Jan 22, 2018]


on water-limited acres. Proceedings of the National Academy of Sciences of the United States of America [Internet]. Oct 16, 2007;**104**(42):16450-16455. Available from: http:// www.ncbi.nlm.nih.gov/pubmed/17923671 [Accessed: Jan 22, 2018]

[29] Kumimoto RW, Zhang Y, Siefers N, Holt BF. NF-YC3, NF-YC4 and NF-YC9 are required for CONSTANS-mediated, photoperiod-dependent flowering in *Arabidopsis thaliana*. Plant Journal [Internet]. 2010 Aug 1, 2010;**63**(3):379-391. DOI: 10.1111/j.1365- 313X.2010.04247.x [Accessed: Jan 22, 2018]

[Internet]. Dec 2016;**14**(12):2310-2321. Available from: http://www.ncbi.nlm.nih.gov/

[19] Ren C, Zhang Z, Wang Y, Li S, Liang Z. Genome-wide identification and characterization of the NF-Y gene family in grape (*Vitis vinifera* L.). BMC Genomics [Internet]. 2016;**17**(1):605. Available from: http://www.ncbi.nlm.nih.gov/pubmed/27516172 [Accessed: Jan 21, 2018]

[20] Myers ZA, Kumimoto RW, Siriwardana CL, Gayler KK, Risinger JR, Pezzetta D, et al. Nuclear factor Y, subunit C (NF-YC) transcription factors are positive regulators of photomorphogenesis in *Arabidopsis thaliana*. Hake S, editor. PLoS Genet [Internet]. Sep 29, 2016;**12**(9):e1006333. Available from: http://dx.plos.org/10.1371/journal.pgen.1006333

[21] Zanetti ME, Rípodas C, Niebel A. Plant NF-Y transcription factors: Key players in plant-microbe interactions, root development and adaptation to stress. Biochimica et Biophysica Acta [Internet]. May 2017;**1860**(5):645-654. Available from: http://www.ncbi.

[22] Siriwardana CL, Gnesutta N, Kumimoto RW, Jones DS, Myers ZA, Mantovani R, et al. Nuclear factor Y, subunit A (NF-YA) proteins positively regulate flowering and act through *FLOWERING LOCUS T*. Muday GK, editor. PLOS Genetics [Internet]. Dec 15, 2016;**12**(12):e1006496. Available from: http://dx.plos.org/10.1371/journal.pgen.1006496

[23] Petroni K, Kumimoto RW, Gnesutta N, Calvenzani V, Fornari M, Tonelli C, et al. The promiscuous life of plant nuclear factor Y transcription factors. Plant Cell [Internet]. Dec 1, 2012;**24**(12):4777-4792. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23275578

[24] Kumimoto RW, Siriwardana CL, Gayler KK, Risinger JR, Siefers N, Holt BF. Nuclear factor Y transcription factors have both opposing and additive roles in ABA-mediated seed germination. Huq E, editor. PLoS One [Internet]. Mar 19, 2013;**8**(3):e59481. Available

[25] Hou X, Zhou J, Liu C, Liu L, Shen L, Yu H. Nuclear factor Y-mediated H3K27me3 demethylation of the SOC1 locus orchestrates flowering responses of Arabidopsis. Nature Communications [Internet]. Aug 8, 2014;**5**:4601. DOI: 10.1038/ncomms5601

[26] Zhang M, Hu X, Zhu M, Xu M, Wang L. Transcription factors NF-YA2 and NF-YA10 regulate leaf growth via auxin signaling in Arabidopsis. Scientific Reports [Internet]. May 3, 2017;**7**(1):1395. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28469131

[27] Mu J, Tan H, Hong S, Liang Y, Zuo J. Arabidopsis transcription factor genes NF-YA1, 5, 6, and 9 play redundant roles in male gametogenesis, embryogenesis, and seed development. Molecular Plant [Internet]. 2013;**6**(1):188-201. Available from: http://www.cell.

[28] Nelson DE, Repetti PP, Adams TR, Creelman RA, Wu J, Warner DC, et al. Plant nuclear factor Y (NF-Y) B subunits confer drought tolerance and lead to improved corn yields

com/molecular-plant/pdf/S1674-2052(14)60890-X.pdf [Accessed: Jan 22, 2018]

from: http://dx.plos.org/10.1371/journal.pone.0059481 [Accessed: Jan 22, 2018]

pubmed/27214796 [Accessed: Jan 21, 2018]

nlm.nih.gov/pubmed/27939756 [Accessed: Jan 22, 2018]

[Accessed: Jan 21, 2018]

116 Transcriptional and Post-transcriptional Regulation

[Accessed: Jan 21, 2018]

[Accessed: Jan 21, 2018]

[Accessed: Jan 21, 2018]

[Accessed: Jan 22, 2018]


abscission. Scientific Reports [Internet]. Oct 30, 2016;**6**(1):32006. Available from: http:// www.ncbi.nlm.nih.gov/pubmed/27573926 [Accessed: Jan 22, 2018]

[48] Iwase A, Mitsuda N, Koyama T, Hiratsu K, Kojima M, Arai T, et al. The AP2/ERF transcription factor WIND1 controls cell dedifferentiation in arabidopsis. Current Biology [Internet]. Mar 22, 2011;**21**(6):508-514. Available from: http://www.sciencedirect.com/sci-

Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement

http://dx.doi.org/10.5772/intechopen.75942

119

[49] Maeo K, Tokuda T, Ayame A, Mitsui N, Kawai T, Tsukagoshi H, et al. An AP2-type transcription factor, WRINKLED1, of *Arabidopsis thaliana* binds to the AW-box sequence conserved among proximal upstream regions of genes involved in fatty acid synthesis. Plant Journal [Internet]. Nov 1, 2009;**60**(3):476-487. DOI: 10.1111/j.1365-313X.2009.03967.x

[50] Li S. The *Arabidopsis thaliana* TCP transcription factors: A broadening horizon beyond development. Plant Signaling & Behavior [Internet]. Jun 3, 2015;**10**(7):1-12. Available

[51] Danisman S. TCP transcription factors at the interface between environmental challenges and the plant's growth responses. Frontiers in Plant Science [Internet]. Dec 21, 2016;**7**:1930. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28066483 [Accessed:

[52] Bresso EG, Chorostecki U, Rodriguez RE, Palatnik JF, Schommer C. Spatial control of gene expression by miR319-regulated TCP transcription factors in leaf development. Plant Physiology [Internet]. Nov 13, 2017;**176**(2):1694-1708. Available from: http://www.

[53] Chai W, Jiang P, Huang G, Jiang H, Li X. Identification and expression profiling analysis of TCP family genes involved in growth and development in maize. Physiology and Molecular Biology of Plants [Internet]. Oct 11, 2017;**23**(4):779-791. Available from: http://

[54] Schommer C, Palatnik JF, Aggarwal P, Chételat A, Cubas P, Farmer EE, et al. Control of jasmonate biosynthesis and senescence by miR319 targets. Carrington JC, editor. PLoS Biology [Internet]. Sep 23, 2008;**6**(9):e230. Available from: http://dx.plos.org/10.1371/

[55] Koyama T, Furutani M, Tasaka M, Ohme-Takagi M. TCP transcription factors control the morphology of shoot lateral organs via negative regulation of the expression of boundary-specific genes in Arabidopsis. Plant Cell [Internet]. Feb 9, 2007;**19**(2):473-484. Available from: http://www.ncbi.nlm.nih.gov/pubmed/17307931 [Accessed: Jan 22, 2018]

[56] Danisman S, van der Wal F, Dhondt S, Waites R, de Folter S, Bimbo A, et al. Arabidopsis class I and class II TCP transcription factors regulate jasmonic acid metabolism and leaf development antagonistically. Plant Physiology [Internet]. Aug 1, 2012;**159**(4):1511-1523. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22718775 [Accessed: Jan 22, 2018]

[57] Davière J-M, Wild M, Regnault T, Baumberger N, Eisler H, Genschik P, et al. Class I TCP-DELLA interactions in inflorescence shoot apex determine plant height. Current Biology [Internet]. Aug 18, 2014;**24**(16):1923-1928. Available from: http://www.ncbi.nlm.

from: http://www.ncbi.nlm.nih.gov/pubmed/26039357 [Accessed: Jan 22, 2018]

ence/article/pii/S0960982211002119 [Accessed: Jan 22, 2018]

ncbi.nlm.nih.gov/pubmed/29133375 [Accessed: Jan 22, 2018]

journal.pbio.0060230 [Accessed: Jan 22, 2018]

nih.gov/pubmed/25127215 [Accessed: Jan 22, 2018]

www.ncbi.nlm.nih.gov/pubmed/29158628 [Accessed: Jan 22, 2018]

[Accessed: Jan 22, 2018]

Jan 22, 2018]


[48] Iwase A, Mitsuda N, Koyama T, Hiratsu K, Kojima M, Arai T, et al. The AP2/ERF transcription factor WIND1 controls cell dedifferentiation in arabidopsis. Current Biology [Internet]. Mar 22, 2011;**21**(6):508-514. Available from: http://www.sciencedirect.com/science/article/pii/S0960982211002119 [Accessed: Jan 22, 2018]

abscission. Scientific Reports [Internet]. Oct 30, 2016;**6**(1):32006. Available from: http://

[39] Baldoni E, Genga A, Cominelli E. Plant MYB transcription factors: Their role in drought response mechanisms. International Journal of Molecular Sciences [Internet]. Jul 13, 2015;**16**(7):15811-15851. Available from: http://www.ncbi.nlm.nih.gov/pubmed/26184177

[40] Yang A, Dai X, Zhang W-H. A R2R3-type MYB gene, OsMYB2, is involved in salt, cold, and dehydration tolerance in rice. Journal of Experimental Botany [Internet]. Apr 1,

[41] Kim JH, Nguyen NH, Jeong CY, Nguyen NT, Hong S-W, Lee H. Loss of the R2R3 MYB, AtMyb73, causes hyper-induction of the SOS1 and SOS3 genes in response to high salinity in Arabidopsis. Journal of Plant Physiology [Internet]. Nov 1, 2013;**170**(16):1461-1465. Available from: http://www.sciencedirect.com/science/article/pii/S0176161713002241

[42] Liu Z, Gu C, Chen F, Jiang J, Yang Y, Li P, et al. Identification and expression of an APETALA2-like gene from *Nelumbo nucifera*. Applied Biochemistry and Biotechnology [Internet]. Sep 22, 2012;**168**(2):383-391. Available from: http://link.springer.com/10.1007/

[43] Xie W, Huang J, Liu Y, Rao J, Luo D, He M. Exploring potential new floral organ morphogenesis genes of *Arabidopsis thaliana* using systems biology approach. Frontiers in Plant Science [Internet]. Oct 13, 2015;**6**:829. Available from: http://www.ncbi.nlm.nih.

[44] Pandey GK, Grant JJ, Cheong YH, Kim BG, Li L, Luan S. ABR1, an APETALA2-domain transcription factor that functions as a repressor of ABA response in Arabidopsis. Plant Physiology [Internet]. Nov 1, 2005;**139**(3):1185-1193. Available from: http://www.ncbi.

[45] Park JM, Park CJ, Lee SB, Ham BK, Shin R, Paek KH. Overexpression of the tobacco Tsi1 gene encoding an EREBP/AP2-type transcription factor enhances resistance against pathogen attack and osmotic stress in tobacco. Plant Cell [Internet]. May 1, 2001;**13**(5):1035-1046. Available from: http://www.ncbi.nlm.nih.gov/pubmed/11340180

[46] Zhang J-Y, Broeckling CD, Blancaflor EB, Sledge MK, Sumner LW, Wang Z-Y. Overexpression of WXP1, a putative *Medicago truncatula* AP2 domain-containing transcription factor gene, increases cuticular wax accumulation and enhances drought tolerance in transgenic alfalfa (*Medicago sativa*). Plant Journal [Internet]. Apr 21, 2005;**42**(5):

[47] Pré M, Atallah M, Champion A, De Vos M, Pieterse CMJ, Memelink J. The AP2/ERF domain transcription factor ORA59 integrates jasmonic acid and ethylene signals in plant defense. Plant Physiol [Internet]. Jul 1, 2008;**147**(3):1347-1357. Available from:

689-707. DOI: 10.1111/j.1365-313X.2005.02405.x [Accessed: Jan 22, 2018]

http://www.ncbi.nlm.nih.gov/pubmed/18467450 [Accessed: Jan 22, 2018]

2012;**63**(7):2541-2556. Available from: 10.1093/jxb/err431 [Accessed: Jan 22, 2018]

www.ncbi.nlm.nih.gov/pubmed/27573926 [Accessed: Jan 22, 2018]

[Accessed: Jan 22, 2018]

118 Transcriptional and Post-transcriptional Regulation

[Accessed: Jan 22, 2018]

[Accessed: Jan 22, 2018]

s12010-012-9782-9 [Accessed: Jan 22, 2018]

gov/pubmed/26528302 [Accessed: Jan 22, 2018]

nlm.nih.gov/pubmed/16227468 [Accessed: Jan 22, 2018]


[58] Ma X, Ma J, Fan D, Li C, Jiang Y, Luo K. Genome-wide identification of TCP family transcription factors from populus euphratica and their involvement in leaf shape regulation. Scientific Reports [Internet]. Dec 8, 2016;**6**(1):32795. Available from: http://www. ncbi.nlm.nih.gov/pubmed/27605130 [Accessed: Jan 22, 2018]

[68] Nuruzzaman M, Sharoni AM, Kikuchi S. Roles of NAC transcription factors in the regulation of biotic and abiotic stress responses in plants. Frontiers in Microbiology [Internet]. Sep 3, 2013;**4**:248. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24058359 [Accessed:

Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement

http://dx.doi.org/10.5772/intechopen.75942

121

[69] Mao H, Yu L, Li Z, Liu H, Han R. Molecular evolution and gene expression differences within the HD-Zip transcription factor family of *Zea mays* L. Genetica [Internet]. Apr 15, 2016;**144**(2):243-257. Available from: http://link.springer.com/10.1007/s10709-016-9896-z

[70] Wang J-W, Wang L-J, Mao Y-B, Cai W-J, Xue H-W, Chen X-Y. control of root cap formation by MicroRNA-targeted auxin response factors in arabidopsis. Plant Cell Online [Internet]. Aug 1, 2005;**17**(8):2204-2216. Available from: http://www.ncbi.nlm.nih.gov/

[71] Guo H-S, Xie Q, Fei J-F, Chua N-H. MicroRNA directs mRNA cleavage of the transcription factor NAC1 to downregulate auxin signals for arabidopsis lateral root development. Plant Cell Online [Internet]. May 1, 2005;**17**(5):1376-1386. Available from: http://

[72] Boualem A, Laporte P, Jovanovic M, Laffont C, Plet J, Combier J-P, et al. MicroRNA166 controls root and nodule development in Medicago truncatula. Plant Journal [Internet]. Jun 2008;**54**(5):876-887. Available from: http://www.ncbi.nlm.nih.gov/pubmed/18298674

[73] Sorin C, Declerck M, Christ A, Blein T, Ma L, Lelandais-Brière C, et al. A miR169 isoform regulates specific NF-YA targets and root architecture in Arabidopsis. New Phytologist [Internet]. Jun 2014;**202**(4):1197-1211. Available from: http://www.ncbi.nlm.nih.gov/

[74] Balazadeh S, Riaño-Pachón DM, Mueller-Roeber B. Transcription factors regulating leaf senescence in *Arabidopsis thaliana*. Plant Biology [Internet]. Sep 1, 2008;**10**(s1):63-75. DOI:

[75] Wu X, Ding D, Shi C, Xue Y, Zhang Z, Tang G, et al. microRNA-dependent gene regulatory networks in maize leaf senescence. BMC Plant Biology [Internet]. Dec 22, 2016;**16**(1):73. Available from: http://www.biomedcentral.com/1471-2229/16/73 [Accessed: Feb 11, 2018]

[76] Xie F, Wang Q, Sun R, Zhang B. Deep sequencing reveals important roles of microR-NAs in response to drought and salinity stress in cotton. Journal of Experimental Botany [Internet]. Feb 1, 2015;**66**(3):789-804. DOI: 10.1093/jxb/eru437 [Accessed: Feb 18, 2018] [77] Wang M, Sun R, Li C, Wang Q, Zhang B. MicroRNA expression profiles during cotton (*Gossypium hirsutum* L) fiber early development. Scientific Reports [Internet]. Mar 22, 2017;**7**:44454. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28327647 [Accessed:

[78] Hong Y, Jackson S. Floral induction and flower formation-the role and potential applications of miRNAs. Plant Biotechnology Journal [Internet]. Apr 1, 2015;**13**(3):282-292. DOI:

www.ncbi.nlm.nih.gov/pubmed/15829603 [Accessed: Feb 18, 2018]

Jan 25, 2018]

[Accessed: Jan 25, 2018]

[Accessed: Feb 18, 2018]

Feb 16, 2018]

pubmed/16006581 [Accessed: Feb 18, 2018]

pubmed/24533947 [Accessed: Feb 11, 2018]

10.1111/pbi.12340 [Accessed: Feb 11, 2018]

10.1111/j.1438-8677.2008.00088.x [Accessed: Feb 16, 2018]


[68] Nuruzzaman M, Sharoni AM, Kikuchi S. Roles of NAC transcription factors in the regulation of biotic and abiotic stress responses in plants. Frontiers in Microbiology [Internet]. Sep 3, 2013;**4**:248. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24058359 [Accessed: Jan 25, 2018]

[58] Ma X, Ma J, Fan D, Li C, Jiang Y, Luo K. Genome-wide identification of TCP family transcription factors from populus euphratica and their involvement in leaf shape regulation. Scientific Reports [Internet]. Dec 8, 2016;**6**(1):32795. Available from: http://www.

[59] Welchen E, García L, Mansilla N, Gonzalez DH. Coordination of plant mitochondrial biogenesis: Keeping pace with cellular requirements. Frontiers in Plant Science [Internet]. Jan 8, 2014;**4**:551. Available from: http://journal.frontiersin.org/article/10.3389/

[60] Giraud E, Ng S, Carrie C, Duncan O, Low J, Lee CP, et al. TCP transcription factors link the regulation of genes encoding mitochondrial proteins with the circadian clock in *Arabidopsis thaliana*. Plant Cell [Internet]. Dec 2010;**22**(12):3921-3934. DOI: 10.1105/

[61] Bakshi M, Oelmüller R. WRKY transcription factors: Jack of many trades in plants. Plant Signaling & Behavior [Internet]. 2014;**9**(2):e27700. Available from: http://www.ncbi.nlm.

[62] Samad AFA, Sajad M, Nazaruddin N, Fauzi IA, Murad AMA, Zainal Z, et al. MicroRNA and transcription factor: Key players in plant regulatory network. Frontiers in Plant Science [Internet]. Apr 12, 2017;**8**:565. Available from: http://journal.frontiersin.org/arti-

[63] Hichri I, Muhovski Y, Žižková E, Dobrev PI, Gharbi E, Franco-Zorrilla JM, et al. The *Solanum lycopersicum* WRKY3 transcription factor SlWRKY3 is involved in salt stress tolerance in tomato. Frontiers in Plant Science [Internet]. Jul 31, 2017;**8**:1343. Available from:

[64] Amato A, Cavallini E, Zenoni S, Finezzo L, Begheldo M, Ruperti B, et al. A grapevine TTG2-like WRKY transcription factor is involved in regulating vacuolar transport and flavonoid biosynthesis. Frontiers in Plant Science [Internet]. Jan 5, 2017;**7**:1979. Available

[65] Aida M, Ishida T, Fukaki H, Fujisawa H, Tasaka M. Genes involved in organ separation in arabidopsis: an analysis of the cup-shaped cotyledon mutant. Plant Cell Online [Internet]. Jun 1, 1997;**9**(6):841-857. Available from: http://www.ncbi.nlm.nih.gov/pubmed/9212461

[66] Singh AK, Sharma V, Pal AK, Acharya V, Ahuja PS.Genome-wide organization and expression profiling of the NAC transcription factor family in potato (*Solanum tuberosum* L.). DNA Research [Internet]. Aug 1, 2013;**20**(4):403-423. Available from: http://www.ncbi.

[67] Lindemose S, Jensen MK, Van de Velde J, O'Shea C, Heyndrickx KS, Workman CT, et al. A DNA-binding-site landscape and regulatory network analysis for NAC transcription factors in Arabidopsis thaliana. Nucleic Acids Research [Internet]. Jul 2014;**42**(12):7681- 7693. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24914054 [Accessed: Jan

from: http://www.ncbi.nlm.nih.gov/pubmed/28105033 [Accessed: Jan 25, 2018]

http://www.ncbi.nlm.nih.gov/pubmed/28824679 [Accessed: Jan 25, 2018]

ncbi.nlm.nih.gov/pubmed/27605130 [Accessed: Jan 22, 2018]

fpls.2013.00551/abstract [Accessed: Jan 22, 2018]

nih.gov/pubmed/24492469 [Accessed: Jan 23, 2018]

cle/10.3389/fpls.2017.00565/full [Accessed: Jan 23, 2018]

nlm.nih.gov/pubmed/23649897 [Accessed: Jan 25, 2018]

tpc.110.074518 [Accessed: Jan 22, 2018]

120 Transcriptional and Post-transcriptional Regulation

[Accessed: Jan 25, 2018]

25, 2018]


[79] Wu G, Park MY, Conway SR, Wang J-W, Weigel D, Poethig RS. The sequential action of miR156 and miR172 regulates developmental timing in arabidopsis. Cell [Internet]. Aug 21, 2009;**138**(4):750-759. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19703400 [Accessed: Feb 11, 2018]

Plant Physiology [Internet]. Apr 27, 2016;**171**(2):01831.2015. Available from: http://www.

Transcription Factors and MicroRNA Interplay: A New Strategy for Crop Improvement

http://dx.doi.org/10.5772/intechopen.75942

123

[89] Zhao W, Li Z, Fan J, Hu C, Yang R, Qi X, et al. Identification of jasmonic acid-associated microRNAs and characterization of the regulatory roles of the miR319/TCP4 module under root-knot nematode stress in tomato. Journal of Experimental Botany [Internet]. Aug 2015;**66**(15):4653-4667. Available from: http://www.ncbi.nlm.nih.gov/

[90] Giacomelli JI, Weigel D, Chan RL, Manavella PA. Role of recently evolved miRNA regulation of sunflower *HaWRKY6* in response to temperature damage. New Phytologist [Internet]. Sep 1, 2012;**195**(4):766-773. DOI: 10.1111/j.1469-8137.2012.04259.x [Accessed:

[91] Wang H, Wang H, Shao H, Tang X. Recent advances in utilizing transcription factors to improve plant abiotic stress tolerance by transgenic technology. Frontiers in Plant Science [Internet]. Feb 9, 2016;**7**:67. Available from: http://www.ncbi.nlm.nih.gov/pubmed/

[92] Zhao B, Ge L, Liang R, Li W, Ruan K, Lin H, et al. Members of miR-169 family are induced by high salinity and transiently inhibit the NF-YA transcription factor. BMC Molecular Biology [Internet]. Apr 8, 2009;**10**(1):29. Available from: http://www.ncbi.nlm.

[93] Xia K, Wang R, Ou X, Fang Z, Tian C, Duan J, et al. OsTIR1 and OsAFB2 downregulation via OsmiR393 overexpression leads to more tillers, early flowering and less tolerance to salt and drought in rice. Zhang B, editor. PLoS One [Internet]. Jan 10, 2012;**7**(1):e30039. Available from: http://dx.plos.org/10.1371/journal.pone.0030039 [Accessed: Feb 18, 2018]

[94] Feng H, Duan X, Zhang Q, Li X, Wang B, Huang L, et al. The target gene of tae-miR164, a novel NAC transcription factor from the NAM subfamily, negatively regulates resistance of wheat to stripe rust. Molecular Plant Pathology [Internet]. Apr 2014;**15**(3):284-296. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24128392 [Accessed: Jan 25, 2018]

[95] Teotia S, Tang G. To bloom or not to bloom: Role of MicroRNAs in plant flowering. Molecular Plant [Internet]. Mar 2015;**8**(3):359-377. Available from: http://www.ncbi.nlm.

ncbi.nlm.nih.gov/pubmed/27208307 [Accessed: Feb 11, 2018]

pubmed/26002970 [Accessed: Feb 11, 2018]

26904044 [Accessed: Jan 20, 2018]

nih.gov/pubmed/19351418 [Accessed: Jan 26, 2018]

nih.gov/pubmed/25737467 [Accessed: Feb 11, 2018]

Feb 11, 2018]


Plant Physiology [Internet]. Apr 27, 2016;**171**(2):01831.2015. Available from: http://www. ncbi.nlm.nih.gov/pubmed/27208307 [Accessed: Feb 11, 2018]

[79] Wu G, Park MY, Conway SR, Wang J-W, Weigel D, Poethig RS. The sequential action of miR156 and miR172 regulates developmental timing in arabidopsis. Cell [Internet]. Aug 21, 2009;**138**(4):750-759. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19703400

[80] Nova-Franco B, Íñiguez LP, Valdés-López O, Alvarado-Affantranger X, Leija A, Fuentes SI, et al. The Micro-RNA172c-APETALA2-1 node as a key regulator of the common bean – *Rhizobium etli* nitrogen fixation symbiosis. Plant Physiol [Internet]. May 2015;**168**(1):273-291. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25739700 [Accessed: Feb 11, 2018]

[81] Schommer C, Palatnik JF, Aggarwal P, Chételat A, Cubas P, Farmer EE, et al. Control of jasmonate biosynthesis and senescence by miR319 targets. Carrington JC, editor. PLoS Biology [Internet]. Sep 23, 2008;**6**(9):e230. Available from: http://dx.plos.org/10.1371/

[82] Parapunova V, Busscher M, Busscher-Lange J, Lammers M, Karlova R, Bovy AG, et al. Identification, cloning and characterization of the tomato TCP transcription factor family. BMC Plant Biology [Internet]. Jun 6, 2014;**14**(1):157. Available from: http://www.ncbi.

[83] Baucher M, Moussawi J, Vandeputte OM, Monteyne D, Mol A, Pérez-Morga D, et al. A role for the miR396/GRF network in specification of organ type during flower development, as supported by ectopic expression of *Populus trichocarpa* miR396c in transgenic tobacco. Piechulla B, editor. Plant Biology [Internet]. Sep 2013;**15**(5):892-898. Available

from: http://www.ncbi.nlm.nih.gov/pubmed/23173976 [Accessed: Feb 11, 2018]

[84] Zhang K, Shi X, Zhao X, Ding D, Tang J, Niu J. Investigation of miR396 and growthregulating factor regulatory network in maize grain filling. Acta Physiologiae Plantarum [Internet]. Feb 21, 2015;**37**(2):28. Available from: http://link.springer.com/10.1007/s11738-

[85] Zhang W, Sun P, He Q, Shu F, Wang J, Deng H. Fine mapping of GS2, a dominant gene for big grain rice. Crop Journal [Internet]. Dec 1, 2013;**1**(2):160-165. Available from: https://www.sciencedirect.com/science/article/pii/S2214514113000238 [Accessed: Feb

[86] Ramachandran P, Carlsbecker A, Etchells JP, Turner S. Class III HD-ZIPs govern vascular cell fate: An HD view on patterning and differentiation. Journal of Experimental Botany [Internet]. 2016;**68**:55-69. Available from: http://www.ncbi.nlm.nih.gov/pubmed/27794018

[87] Zhou G-K, Kubo M, Zhong R, Demura T, Ye Z-H. Overexpression of miR165 affects apical meristem formation, organ polarity establishment and vascular development in arabidopsis. Plant and Cell Physiology [Internet]. Mar 2007;**48**(3):391-404. Available from:

[88] Sharma D, Tiwari M, Pandey A, Bhatia C, Sharma A, Trivedi PK. MicroRNA858 is a potential regulator of phenylpropanoid pathway and plant development in Arabidopsis.

http://www.ncbi.nlm.nih.gov/pubmed/17237362 [Accessed: Feb 11, 2018]

[Accessed: Feb 11, 2018]

122 Transcriptional and Post-transcriptional Regulation

journal.pbio.0060230 [Accessed: Feb 11, 2018]

014-1767-6 [Accessed: Feb 11, 2018]

11, 2018]

[Accessed: Feb 11, 2018]

nlm.nih.gov/pubmed/24903607 [Accessed: Feb 11, 2018]


## *Edited by Kais Ghedira*

This book focuses on the transcriptional and post-transcriptional gene regulations and presents a detailed portrait of many novel aspects related to highlighting the importance of key TFs in some vital biological processes, the role of certain TFs to control some infectious diseases, the role of non-coding RNAs in controlling mRNA expression, the involvement of these non-coding RNAs in diseases, and the interplay between TFs and microRNAs as key players for gene expression regulation giving a complete picture of how genes are regulated at the cellular level.

The editor embarked upon this writing project entitled "Transcriptional and Posttranscriptional Regulation" to make pertinent contributions accessible to the scientific community. Hopefully, a large audience will enjoy reading and benefit from the chapters of this book.

Published in London, UK © 2018 IntechOpen © Rost-9D / iStock

Transcriptional and Post-transcriptional Regulation

Transcriptional and Post-

transcriptional Regulation