Genomic Prediction Accuracies for Growth and Carcass Traits in a Brangus Heifer Population

Simple Summary The genomic estimated breeding value (GEBV) using data from Brangus heifers were obtained from genomic selection (GS) methods associating the single nucleotide polymorphisms (SNP) marker genotypes with phenotypic data for economically important growth (birth, weaning, and yearling weights) and carcass (depth of rib fat, and percent intramuscular fat and longissimus muscle area) traits using the linkage disequilibrium (LD) between SNP markers and quantitative trait loci (QTL) and/or the genomic relationship between animals. The heritability estimates were found similar across genomic best linear unbiased prediction (the GBLUP), and the Bayesian (BayesA, BayesB, BayesC and Lasso) GS methods for k-means and random cluster. The Bayesian methods resulted in underestimates of heritabilities and overestimates of accuracy of GEBV. However, the GBLUP method resulted in more reasonable estimates of heritabilities and accuracies of GEBV for growth and carcass traits of heifers from a composite population. Abstract The predictive abilities and accuracies of genomic best linear unbiased prediction (GBLUP) and the Bayesian (BayesA, BayesB, BayesC and Lasso) genomic selection (GS) methods for economically important growth (birth, weaning, and yearling weights) and carcass (depth of rib fat, apercent intramuscular fat and longissimus muscle area) traits were characterized by estimating the linkage disequilibrium (LD) structure in Brangus heifers using single nucleotide polymorphisms (SNP) markers. Sharp declines in LD were observed as distance among SNP markers increased. The application of the GBLUP and the Bayesian methods to obtain the GEBV for growth and carcass traits within k-means and random clusters showed that k-means and random clustering had quite similar heritability estimates, but the Bayesian methods resulted in the lower estimates of heritability between 0.06 and 0.21 for growth and carcass traits compared with those between 0.21 and 0.35 from the GBLUP methodologies. Although the prediction ability of the GBLUP and the Bayesian methods were quite similar for growth and carcass traits, the Bayesian methods overestimated the accuracies of GEBV because of the lower estimates of heritability of growth and carcass traits. However, GBLUP resulted in accuracy of GEBV for growth and carcass traits that parallels previous reports.

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