Preface

Techniques involved in animal genetics and breeding are the most important factors affecting genetic improvement and production efficiency of livestock. It is due to the continuous development and extensive application of techniques, such as performance testing, estimation of breeding value, analysis of the genetic mechanism of complex traits, sex control, and so on, that we can meet the needs for more high-quality livestock products to meet the needs of the world's increasing population. With the advent of the post-genome era, multiomics and bioengineering technologies are being combined with computer-based statistical analysis methods, resulting in new approaches to improving techniques used in animal genetics and breeding, and thus, promoting the development of animal husbandry. This book provides a comprehensive overview of the traditional and current state-of-the-art techniques in animal genetics and breeding, from both theoretical and practical viewpoints. The introductory chapter describes applications of omics techniques in livestock genetics and breeding. Subsequent chapters address such topics as techniques for genetically selecting highly productive animals while producing less greenhouse gas (GHG) emissions, breeding soundness (BSE) of rams and bucks using community-based breeding programs (CBBPs), how bovine species respond to in vitro thermal stress stimulation using peripheral blood monoclonal cells as the cellular system, and semen characteristics of wool-breed ram lambs raised in high altitudes. These techniques are important for the healthy and sustainable development of animal husbandry, especially for animals living under specific climatic and geographical environmental conditions.

> **Prof. Xiaojun Liu and Dr. Hong Li** College of Animal Science and Technology, Henan Agricultural University, Henan Province, Zhengzhou, China

Section 1 Introduction

#### **Chapter 1**

## Introductory Chapter: Applications of Omics Techniques on Livestock Genetics and Breeding

*Hong Li and Xiaojun Liu*

#### **1. Introduction**

Livestock has been domesticated for thousands of years, and generated into various breeds under a long artificial selection. They provide economic and high quality animal-derived proteins to meet the human nutrition requirement. The process of artificial selection has significantly enhanced crucial traits in agricultural animals [1, 2]. However, the genetic potential of farm animals has not yet been fully exploited. The quantitative trait is determined by multiple genes and regulated by the interplay of genetics, environment and their interaction [3]. The underlying biological mechanisms governing these phenotypic characteristics remain poorly understood. Therefore, the investigation into the formation mechanism of such intricate traits has consistently garnered significant attention within the realm of animal genetics and breeding.

Due to the limited number of molecular markers available for gene mapping, few breakthroughs have been made in the fine mapping of quantitative traits. Although quantitative genetics has been applied in animal breeding, leading to a technological revolution in the past century, selecting certain complex traits based solely on pedigreederived breeding remains challenging due to the intricate nature of animal genetics and developmental mechanisms. The related concept and technology completion of the Human Genome Project has greatly promoted farm animal genomic research. With the completion of major livestock and poultry breed genome sequencing projects, coupled with the continuous emergence of high-throughput sequencing technologies (omics), agricultural animal genetic breeding research methods and means have gradually evolved from traditional conventional breeding to the integration of various omics technologies. The integration of diverse omics data for analyzing important economic traits aids in accurately and comprehensively revealing the formation mechanism.

#### **2. Application of omics enhances the progress of animal selection and breeding**

The omics mainly includes genomics, transcriptomics, proteomics, epigenomics and metabolomics. The application of them in livestock can improve the detection efficiency in the subtle changes of phenotypic [4, 5]. In animal genetics and breeding, integrative analysis of omics data can promise to deliver comprehensive insights into the biological systems under study, and contribute to the identification of causal mutations, thereby enhancing the accuracy of genetic selection [6]. Additionally, it has contributed to the estimation of more accurate breeding values (BVs) and facilitated the selection of genetically superior animals at an early stage, thereby enhancing genetic gain [7, 8]. This, in turn, leads to improved animal productivity and profitability.

*Genomics* Deciphers the origin of agricultural animal domestication has been paid much attention by researchers. Understanding the origin of modern domestic animals helps us understand the history of breed and population formation, animal adaptability to the environment, the basic characteristics of genetic background shaping, and the molecular mechanism of the formation of main traits, which can provide basic information for the rational development of molecular breeding. Whole genome resequencing (WGS) has been widely used in detecting the molecular signatures, origin of domestication, and genetic variation of economic traits of agricultural animals [9, 10]. The genome-wide association studies (GWAS) was a kind of method, that firstly genome-wide genotyping through high-throughput sequencing technology, and then the phenotype and genotype of each marker were sequentially regressed to determine whether each marker was significant. With the development of sequencing technology and the reduction of cost, GWAS has become a new strategy and mainstream method to identify complex (quantitative) traits in the world [11].

*Transcriptomics* Transcriptome sequencing (RNA-seq) is widely recognized as the predominant method for investigating RNA functions. It can help the researchers to deepen the elucidation of the gene function, and analyze the possible intrinsic connections between gene expression alteration and animals' phenotype [12]. The integrated analysis between the RNA-seq and GWAS can reveal the key genes and their complex interactions mechanism involved in the concerned phenomenon [13]. In addition, the early selection of individuals based on multi-omics data obtained during early sexual maturity may contribute to an increased genetic gain by effectively reducing the generation intervals [14].

*Proteomics* Proteomics essentially refers to the study of protein characteristics at a large-scale level, including protein expression levels, post-translational modifications, protein-protein interactions, etc. It could decrease the sample analysis time while increasing the depth of proteome coverage when proteomics combined with advanced bioinformatic tools [15]. Proteomic studies primarily focus on characterizing the proteome of a specific organ, tissue, cell type, or organism under particular conditions or by comparing differential protein expression across two or more selected scenarios [16]. It has been commonly used to identify the candidate protein markers of fertility and reproductive problems [17], early growth and development [18], and meat quality [19] for molecular breeding in animal science. To identify the genetic variants with desirable traits for selection and breeding, proteomics has been used in different animal products such as meat, milk and cheese [20].

*Metabolomics* The field of metabolomics offers valuable insights into the intricate biochemical pathways underlying diverse physiological processes. It can identify metabolic pathways that play important roles in life processes, such as growth and development. For example, metabolomics approach was employed to investigate the impact of bone quality on productivity in chickens [21].

*Epigenomics* Epigenetic mechanisms encompass post-translational modifications of histones, DNA methylation, chromatin conformation and non-coding RNAs, and mainly participate in the processes of DNA repair, regulating gene expression and

#### *Introductory Chapter: Applications of Omics Techniques on Livestock Genetics and Breeding DOI: http://dx.doi.org/10.5772/intechopen.113934*

homologous recombination [22]. Epigenetic changes are important for understanding complex trait variation and inheritance. Revealing the epigenomic constituents across diverse cell types facilitates the identification of numerous potential regulatory elements [23]. The methylation level of *SLCO1B3* gene identified through the wholegenomic bisulfate sequencing was associated with the changes in eggshell color in Lushi blue-eggshell chickens [24]. Candidate epigenetic regions or biomarkers for pig fertility were also identified by using the genome-wide DNA methylation method [25]. A new insight into the molecular mechanism of adaptation to physiological changes in liver of hens at the pre-laying and peak-laying stage was revealed by liver proteome and acetyl-proteome [26].

#### **3. Conclusion**

With the fast development of modern technology, modern animal breeding programs are constantly evolving with advances in breeding theory, biotechnology, and genetics. The application of the omics approach has the potential to revolutionize animal breeding practice, shifting it from a simplistic "black box" methodology to one that incorporates an understanding of regulatory networks and pathways that underlie the expression of crucial phenotypes. It establishes the groundwork for further investigations into the molecular mechanisms governing quantitative trait regulation and the development of molecular markers applicable to breeding practices. Therefore, the integration of Omics data to enhance livestock production is promising.

#### **Author details**

Hong Li1,2,3 and Xiaojun Liu1,2,3\*

1 College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China

2 International Joint Research Laboratory for Poultry Breeding of Henan, Zhengzhou, China

3 Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou, China

\*Address all correspondence to: xjliu2008@hotmail.com

© 2023 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.

#### **References**

[1] Rexroad C, Vallet J, Matukumalli LK, Reecy J, Bickhart D, Blackburn H, et al. Genome to phenome: Improving animal health, production, and well-being - a new USDA blueprint for animal genome research 2018-2027. Frontiers in Genetics. 2019;**10**:327

[2] Erasmus LM, van Marle-Köster E. Moving towards sustainable breeding objectives and cow welfare in dairy production: A south African perspective. Tropical Animal Health and Production. 2021;**53**(5):470

[3] Womack JE, Jang HJ, Lee MO. Genomics of complex traits. Annals of the New York Academy of Sciences. 2012;**1271**(1):33-36

[4] Mu Y, Qi W, Zhang T, Zhang J, Mao S. Multi-omics analysis revealed coordinated responses of rumen microbiome and epithelium to highgrain-induced subacute rumen acidosis in lactating dairy cows. mSystems. 2022;**7**(1):e0149021

[5] Wang Y, Li J, Lu D, Meng Q, Song N, Zhou H, et al. Integrated proteome and phosphoproteome analysis of interscapular brown adipose and subcutaneous white adipose tissues upon high fat diet feeding in mouse. Journal of Proteomics. 2022;**255**:104500

[6] Chang LY, Toghiani S, Aggrey SE, Rekaya R. Increasing accuracy of genomic selection in presence of high density marker panels through the prioritization of relevant polymorphisms. BMC Genetics. 2019;**20**(1):21

[7] Pedrosa VB, Schenkel FS, Chen SY, Oliveira HR, Casey TM, Melka MG, et al. Genomewide association analyses of lactation persistency and milk production traits in Holstein cattle based on imputed whole-genome sequence data. Genes (Basel). 2021;**12**(11):1830

[8] Peng C, Wang J, Asante I, Louie S, Jin R, Chatzi L, et al. A latent unknown clustering integrating multi-omics data (LUCID) with phenotypic traits. Bioinformatics. 2020;**36**(3):842-850

[9] Bovo S, Ribani A, Muñoz M, Alves E, Araujo JP, Bozzi R, et al. Whole-genome sequencing of European autochthonous and commercial pig breeds allows the detection of signatures of selection for adaptation of genetic resources to different breeding and production systems. Genetics, Selection, Evolution. 2020;**52**(1):33

[10] Elsik CG, Tellam RL, Worley KC, Gibbs RA, Muzny DM, Weinstock GM, et al. The genome sequence of taurine cattle: A window to ruminant biology and evolution. Science. 2009;**324**(5926):522-528

[11] McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JP, et al. Genomewide association studies for complex traits: Consensus, uncertainty and challenges. Nature Reviews. Genetics. 2008;**9**(5):356-369

[12] Shi TP, Zhang L. Application of whole transcriptomics in animal husbandry. Yi Chuan. 2019;**41**(3):193-205

[13] Cánovas A, Reverter A, DeAtley KL, Ashley RL, Colgrave ML, Fortes MR, et al. Multi-tissue omics analyses reveal molecular regulatory networks for puberty in composite beef cattle. PLoS One. 2014;**9**(7):e102551

*Introductory Chapter: Applications of Omics Techniques on Livestock Genetics and Breeding DOI: http://dx.doi.org/10.5772/intechopen.113934*

[14] Chakraborty D, Sharma N, Kour S, Sodhi SS, Gupta MK, Lee SJ, et al. Applications of omics Technology for Livestock Selection and Improvement. Frontiers in Genetics. 2022;**13**:774113

[15] Zhang Z, Wu S, Stenoien DL, Paša-Tolić L. High-throughput proteomics. Annual Review of Analytical Chemistry (Palo Alto, Calif.). 2014;**7**:427-454

[16] Soares R, Franco C, Pires E, Ventosa M, Palhinhas R, Koci K, et al. Mass spectrometry and animal science: Protein identification strategies and particularities of farm animal species. Journal of Proteomics. 2012;**75**(14):4190-4206

[17] Peddinti D, Memili E, Burgess SC. Proteomics in animal reproduction and breeding. In: Eckersall PD, Whitfield PD, editors. Methods in Animal Proteomics. New Jersey, USA: Wiley-Blackwell; 2011. pp. 369-396

[18] Yarmush ML, Jayaraman A. Advances in proteomic technologies. Annual Review of Biomedical Engineering. 2002;**4**:349-373

[19] Bendixen E. The use of proteomics in meat science. Meat Science. 2005;**71**(1):138-149

[20] Almeida AM, Bassols A, Bendixen E, Bhide M, Ceciliani F, Cristobal S, et al. Animal board invited review: Advances in proteomics for animal and food sciences. Animal. 2015;**9**(1):1-17

[21] Li D, Wu Y, Shi K, Shao M, Duan Y, Yu M, et al. Untargeted metabolomics reveals the effect of rearing systems on bone quality parameters in chickens. Frontiers in Genetics. 2022;**13**:1071562

[22] Fingerman IM, McDaniel L, Zhang X, Ratzat W, Hassan T, Jiang Z, et al. NCBI Epigenomics: A new public resource for exploring epigenomic data sets. Nucleic Acids Research. 2011;**39**(Database issue):D908-D912

[23] Zentner GE, Henikoff S. Epigenome editing made easy. Nature Biotechnology. 2015;**33**(6):606-607

[24] Li Z, Ren T, Li W, Zhou Y, Han R, Li H, et al. Association between the methylation statuses at CpG sites in the promoter region of the SLCO1B3, RNA expression and color change in blue eggshells in Lushi chickens. Frontiers in Genetics. 2019;**10**:161

[25] Wang X, Kadarmideen HN. An epigenome-wide DNA methylation map of testis in pigs for study of complex traits. Frontiers in Genetics. 2019;**10**:405

[26] Wang Z, Wang D, Jiang K, Guo Y, Li Z, Jiang R, et al. A comprehensive proteome and acetyl-proteome atlas reveals molecular mechanisms adapting to the physiological changes from pre-laying to peak-laying stage in liver of hens (Gallus gallus). Frontiers in Veterinary Science. 2021;**8**:700669

Section 2
