Genomic prediction of breed composition and heterosis effects in Angus, Charolais, and Hereford crosses using 50K genotypes

This study examined the feasibility and accuracy of using Illumina BovineSNP50 genotypes to estimate individual cattle breed composition and heterosis relative to estimate from pedigree. First, pedigree was used to compute breed fractions for 1124 crossbred cattle. Given the breed composition of sires and dams, retained heterosis and retained heterozygosity were computed for all individuals. Second, all animals' genotypes were used to compute individual's genomic breed fractions by applying a cross-validation method. Average genome-wide heterozygosity and retained heterozygosity based on genomic breed fraction were computed. Lastly, accuracies of breed composition, retained heterozygosity and retained heterosis were assessed as Pearson's correlation between pedigree- and genome-based predictions. The average breed compositions observed were 0.52 Angus, 0.23 Charolais, and 0.25 Hereford for pedigree-based prediction and 0.46, 0.26, and 0.28 for genome-based prediction, respectively. Correlations of predicted breed composition ranged from 0.94 to 0.96. Genome-based retained heterozygosity and retained heterosis from pedigree were also highly correlated (0.96). A positive association of nonadditive genetic effects was observed for growth traits reflecting the importance of heterosis for these traits. Genomic prediction can aid analyses that depend on knowledge of breed composition and serve as a reliable method to predict heterosis to improve the efficiency of commercial crossbreeding schemes.