Computational Genomics Approaches for Livestock Improvement and Management

Abstract

Livestock (domesticated animals such as cattle, buffalo) are important economic and genetic resources used in agriculture to provide labour, and commodities such as meat, eggs, milk, fur, leather, and wool. Due to their commercial importance, continuous efforts have been made by breeders and research community worldwide to increase resistance and reproductive potential for their improvement and better management. The advancement in next-generation sequencing approaches made it is possible to conduct various genome-wide studies at a lower cost with faster, efficient, and higher depth to analyse various diseases, diversity, breeds, resistance, reproduction, and developmental stages in livestock. In this chapter, we are providing a summary of various computational approaches utilized at the various level of study of genomics such as the genome assembly, molecular markers, epigenetics, and transcriptome. This chapter covers various computational approaches for genome assembly along with approaches related to genome assessment, structural annotations (localization of transposable elements, non-coding RNAs, RNAs, etc.), and functional annotation (identification and characterization of genes) post-assembly. Next, it covers computational approaches for identification and characterization of molecular markers (SNP, SSRs). This chapter also includes computational approaches for epigenomics to study DNA methylation (MeDIP-seq, BS-seq analyses) and histone modifications (ChIP-seq, ATAC-seq, DNase-seq analyses) along with the approaches for transcriptome (RNA-seq, sRNA-seq, Degradome-seq analyses). This chapter could be helpful to introduce students and researchers with various computational genomics approaches available for the improvement and management of livestock.