Genomic regions associated with principal components for growth, visual score and reproductive traits in Nellore cattle

The search for candidate genes underlying the expression of principal components (PCs) for different traits is a useful tool that allows exploring biological mechanisms associated with the traits of interest. The aim of this study was to identify genomic regions associated with PCs for growth, visual score and reproductive traits in Nellore cattle by performing a genome-wide association study (GWAS). Phenotypic and pedigree data from 355,524 animals and genotypes from 3,519 animals, were used in this investigation. The estimated breeding values (EBV) were obtained from a multi-trait analysis using a mixed linear animal model. The eigen-decomposition of the additive genetic (co)variance matrix among traits was used to calculate the EBVs for the main PCs. The SNP effects were estimated using the weighted single-step GBLUP and the BayesC method. The top-10 ranking windows that explained the highest proportion of variance were identified for further functional analyses. The most important genomic regions were identified on BTA7 and BTA24 for PC1, BTA8 for PC2, and BTA3 and BTA10 for PC3. The functional analyses contributed to unravel biological interpretation of PCs by identifying genes potentially associated with growth, carcass traits, conformation, and fatty acid composition traits. These findings are of relevance to the biological understanding of the PCs and their related biotypes in Nellore cattle, potentially allowing for genetic selection for more specific breeding goals.