Preface

**Section 2 Omics: From Bioeconomy to Human Health 171**

Chapter 8 **Transcriptome Analysis and Genetic Engineering 213**

Chapter 10 **Transcriptome Analysis in Chickpea (Cicer arietinum L.):**

Chapter 11 **Comprehensive Network Analysis of Cancer Stem Cell**

Hiroko Kozuka‐Hata and Masaaki Oyama

Chapter 13 **Application of Next-Generation Sequencing in the Era of**

Menezes Freire and Patrícia Gonçalves Pereira Couto

Chapter 12 **Epitranscriptomics for Biomedical Discovery 279**

Zhang, Ding‐You Li and Shui Q. Ye

**Precision Medicine 293**

Tikhonovich and Vladimir A. Zhukov

Santosh Kumar and Sabhyata Bhatia

**Modification Dynamics 265**

Chapter 9 **Transcriptomic Studies in Non-Model Plants: Case of Pisum sativum L. and Medicago lupulina L. 227**

Asima Tayyeb

**VI** Contents

Chapter 7 **Current Advances in Functional Genomics in Aquaculture 173** Hetron M. Munang'andu and Øystein Evensen

Uzma Qaisar, Samina Yousaf, Tanzeela Rehman, Anila Zainab and

Olga A. Kulaeva, Alexey M. Afonin, Aleksandr I. Zhernakov, Igor A.

**Applications in Study of Gene Expression, Non-Coding RNA Prediction, and Molecular Marker Development 245** Chandra Kant, Vimal Pandey, Subodh Verma, Manish Tiwari,

**Signalling through Systematic Integration of Post-Translational**

Min Xiong, Daniel P. Heruth, Xun Jiang, Shamima Islam, Li Qin

Michele Araújo Pereira, Frederico Scott Varella Malta, Maíra Cristina

This book is an overview about transcriptome analysis and how other "omics" could be ap‐ plied in different fields, from microorganisms to precision medicine. The content of each chapter was designed to encourage three types of readers. First, this book will benefit those interested in learning about the most powerful and cost-efficient methods applied for a broad analysis of gene expression regulation of a single cell, a tissue, or the whole living organisms. We aim to offer a wide view of these applications in distinct areas, from agricul‐ ture to human diseases, introducing and revising advanced concepts of RNA-Seq technolo‐ gy. In addition, some particularities of the vast world of RNAs were investigated. Most researchers would agree that the memorable event in the RNA area over the last 20 years has been the discovery of the driver functions of noncoding RNAs, such as siRNA and miR‐ NA. These new findings allowed new extensive researches on the control of RNA levels. Besides the contribution to uncover the multitude of small RNAs regulating gene expres‐ sion, the development of high-throughput sequencing technologies also allowed the investi‐ gation of mechanisms related to RNA modifications. Unlike the well-established role of DNA modifications in gene regulation, little is known about modifications in RNA and their influence on gene expression. Mechanisms of RNA modification were addressed here, dis‐ cussing future challenges and perspectives of studies that attempt to unravel the processes related to the regulation of several stages of the biological system. In spite of the numerous initiatives with animal model investigation, the study of gene expression in plants was also assessed in this book. We point out tools and methodologies for those who are interested in transcriptome analysis in this area, considering the most diverse aspects involved in this challenge. Some points discussed were the influence of transcriptome regulation and mecha‐ nisms associated to the responses of environmental stresses, plant-pathogen interactions, and resistance, which in many aspects are closely related to studies performed in the agri‐ culture field to improve, for example, the productivity.

Second, this book will also benefit those who are interested in developing an RNA-Seq study, from the experimental design to the exploration of the most varied algorithms availa‐ ble, following the best practices currently recommended. We present an overview of stateof-the-art methods including experimental design, library preparation, quality check, and preprocessing of raw reads. The particularities involved in differential expression analysis and an accurate investigation of data for specific biological questions aims to show the dif‐ ferent approaches that could be found by researchers during the development of the most varied experiments using this technology. Besides presenting a description of concepts and tools, the chapters also offer *in silico* mechanisms to initiate an experiment and to perform a good quality data analysis. Numerous options of bioinformatics tools were presented con‐ sidering users with limited access for computational resources or little experience with com‐

mand-line execution. Also, free online and commercial platforms that can be very helpful and intuitive were discussed, once as important as having the methods available is to fully understand each step in which this method could be used. A good prior planning to choose the correct algorithms and statistical criteria that best fit the different conditions and types of data results in a pleased journey toward success.

Third, it is also for those who are interested in an idea about other omics and the different areas where the big data could be applied. Widely known for having a crucial role in biolog‐ ical systems, post-translational modifications contributed to the recent explosion of proteo‐ mic data. Remarkable technological advances in mass spectrometry-based proteomics have resulted in a large quantity of information obtained with great sensitivity in different as‐ pects. We also introduce high-resolution shotgun proteomics technology in combination with bioinformatics platforms to better understand the crucial network structures based on phosphorylation dynamics, as well as global protein expression profiles. Another powerful tool to study the hidden microbial treasure, the metagenomics field, has accelerated the in‐ vestigation of emerging pathogens, thereby contributing to the design of disease control strategies. Here, we also present the most current knowledge about this technology in scien‐ tific studies and commercial application in aquaculture. Regardless of the omics investigat‐ ed, the large amount of data generated requires the development of new and efficient tools to deal with such information and then to contribute to several studies worldwide. Regard‐ ing genomics field, we discuss many molecular tools that have been developed to allow a better understanding of the biology of some diseases, their particularities and variabilities concerning the sequencing of genomes of different species. These tools allow medical and scientific groups to improve patient management, providing personalized prevention and treatment of diseases with more specific and accurate approaches. The potential use of nextgeneration sequencing in personalized medicine is enormous and the comprehension of this technique is necessary for an effective implementation in the clinical workplace.

In general, there are a great number of books dealing with transcriptomics or other omics in several areas, but our intention was to offer the readers the opportunity to have all this con‐ tent in one book. Here, the readers can find an overview of different areas of knowledge and take advantage of such knowledges to develop their own pipelines and be in touch with the most current algorithms and platforms used for the scientific community.

> **Fabio A. Marchi** A.C.Camargo Cancer Center São Paulo, Brazil

**Section 1**

**Getting Started with RNA-Seq Data Analysis**

**Priscila D.R. Cirillo** Hermes Pardini Institute Belo Horizonte, Brazil

**Elvis C. Mateo** Hermes Pardini Institute Belo Horizonte, Brazil **Getting Started with RNA-Seq Data Analysis**

mand-line execution. Also, free online and commercial platforms that can be very helpful and intuitive were discussed, once as important as having the methods available is to fully understand each step in which this method could be used. A good prior planning to choose the correct algorithms and statistical criteria that best fit the different conditions and types

Third, it is also for those who are interested in an idea about other omics and the different areas where the big data could be applied. Widely known for having a crucial role in biolog‐ ical systems, post-translational modifications contributed to the recent explosion of proteo‐ mic data. Remarkable technological advances in mass spectrometry-based proteomics have resulted in a large quantity of information obtained with great sensitivity in different as‐ pects. We also introduce high-resolution shotgun proteomics technology in combination with bioinformatics platforms to better understand the crucial network structures based on phosphorylation dynamics, as well as global protein expression profiles. Another powerful tool to study the hidden microbial treasure, the metagenomics field, has accelerated the in‐ vestigation of emerging pathogens, thereby contributing to the design of disease control strategies. Here, we also present the most current knowledge about this technology in scien‐ tific studies and commercial application in aquaculture. Regardless of the omics investigat‐ ed, the large amount of data generated requires the development of new and efficient tools to deal with such information and then to contribute to several studies worldwide. Regard‐ ing genomics field, we discuss many molecular tools that have been developed to allow a better understanding of the biology of some diseases, their particularities and variabilities concerning the sequencing of genomes of different species. These tools allow medical and scientific groups to improve patient management, providing personalized prevention and treatment of diseases with more specific and accurate approaches. The potential use of nextgeneration sequencing in personalized medicine is enormous and the comprehension of this

technique is necessary for an effective implementation in the clinical workplace.

most current algorithms and platforms used for the scientific community.

In general, there are a great number of books dealing with transcriptomics or other omics in several areas, but our intention was to offer the readers the opportunity to have all this con‐ tent in one book. Here, the readers can find an overview of different areas of knowledge and take advantage of such knowledges to develop their own pipelines and be in touch with the

**Fabio A. Marchi**

São Paulo, Brazil

**Elvis C. Mateo**

**Priscila D.R. Cirillo** Hermes Pardini Institute Belo Horizonte, Brazil

Hermes Pardini Institute Belo Horizonte, Brazil

A.C.Camargo Cancer Center

of data results in a pleased journey toward success.

VIII Preface

**Chapter 1**

**Provisional chapter**

**RNA‐seq: Applications and Best Practices**

**RNA**‐**seq: Applications and Best Practices**

DOI: 10.5772/intechopen.69250

RNA‐sequencing (RNA‐seq) is the state‐of‐the‐art technique for transcriptome analysis that takes advantage of high‐throughput next‐generation sequencing. Although being a powerful approach, RNA‐seq imposes major challenges throughout its steps with numerous caveats. There are currently many experimental options available, and a com‐ plete comprehension of each step is critical to make right decisions and avoid getting into inconclusive results. A complete workflow consists of: (1) experimental design; (2) sample and library preparation; (3) sequencing; and (4) data analysis. RNA‐seq enables a wide range of applications such as the discovery of novel genes, gene/transcript quan‐ tification, and differential expression and functional analysis. This chapter will encom‐ pass the main aspects from sample preparation to downstream data analysis. It will be discussed how to obtain high‐quality samples, replicates amount, library preparation, sequencing platforms and coverage, focusing on best recommended practices based on specialized literature. Basic techniques and well‐known algorithms are presented and discussed, guiding both beginners and experienced users in the implementation of reli‐

**Keywords:** RNA‐seq, next‐generation sequencing, transcriptome, data analysis, best

A transcriptome represents the entire repertoire of RNA content from an organism, a tis‐ sue or a cell and it is dynamic, changing in response to genetic and environmental factors. Several approaches have been developed for transcriptome analysis: hybridization‐based (DNA microarray [1]) or sequence‐based (ESTs—Expressed Sequence Tags [2], SAGE—Serial Analysis of Gene Expression [3], CAGE—Cap Analysis of Gene Expression [4] and MPSS— Massively Parallel Signature Sequencing [5]). The first sequence‐based methods relied on

> © 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,

© 2017 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.

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

Michele Araújo Pereira, Eddie Luidy Imada and

Michele Araújo Pereira, Eddie Luidy Imada

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

Rafael Lucas Muniz Guedes

**Abstract**

able experiments.

practices

**1. Introduction**

and Rafael Lucas Muniz Guedes

http://dx.doi.org/10.5772/intechopen.69250

**Provisional chapter**
