Abstract
Ongoing advances in genome sequencing technologies have enabled the identification of numerous structural variants (SVs) in livestock genomes, which are the main determinants of complex traits due to their impact on gene expression. Thus, this study aimed to detect structural variants using whole genome re-sequencing (WGS) data and identify positional candidate genes and quantitative trait loci (QTL) overlapping the most frequent SV regions in Nellore cattle. The WGS from 151 representative Nellore bulls were analyzed to conduct genome-wide structural variation calling and to identify common SV regions. Gene and QTL information surrounding the most frequent SV regions was identified using the Ensembl Genes and Cattle QTL database. The identified genes were functionally classified for biological mechanisms and pathways (Gene Ontology - GO) using the panther database. A total of 215,031 SVs were identified, with most of them being copy number variants (CNV) (183,032 deletions and 14,013 duplications) and 17,986 inversions (INV). These SVs cover, on average, 4.81% of the autosomal genome. Furthermore, we found 3,752 non-redundant SV regions that are frequent in at least 5% of the bulls. These SV regions mainly correspond to CNV regions (97%) and inversion regions (3%). In total, all SV regions cover 13.13% of the total autosomal genome, with 11.4% attributed to CNV regions and 1.7% to inversion regions. Moreover, we found that 532 SV regions were common in more than 50% of the bulls evaluated and overlapped 130 QTL previously associated with economically important traits related to exterior, health, meat and carcass, milk, production, and reproduction. A total of 1,164 positional candidate genes were identified, with 204 SVRs overlapping these genes. These genes are significantly overrepresented in GO terms related to biological processes (BP), molecular functions (MF), and biochemical pathways, playing an essential role in environmental adaptation mechanisms and feed efficiency indicator traits. Our results suggest that genes surrounding SV regions play key biological functions essential to thermotolerance, immunity, metabolism, tissue integrity, and environmental adaptation in tropical regions.