Estimation of genomic breed composition of individual animals in composite beef cattle

Summary Three statistical models (an admixture model, linear regression, and ridge‐regression BLUP) and two strategies for selecting SNP panels (uniformly spaced vs. maximum Euclidean distance of SNP allele frequencies between ancestral breeds) were compared for estimating genomic‐estimated breed composition (GBC) in Brangus and Santa Gertrudis cattle, respectively. Animals were genotyped with a GeneSeek Genomic Profiler bovine low‐density version 4 SNP chip. The estimated GBC was consistent among the uniformly spaced SNP panels, and values were similar between the three models. However, estimated GBC varied considerably between the three methods when using fewer than 10 000 SNPs that maximized the Euclidean distance of allele frequencies between the ancestral breeds. The admixture model performed most consistently across various SNP panel sizes. For the other two models, stabilized estimates were obtained with an SNP panel size of 20 000 SNPs or more. Based on the uniformly spaced 20K SNP panel, the estimated GBC was 69.8–70.5% Angus and 29.5–30.2% Brahman for Brangus, and 63.9–65.3% Shorthorn and 34.7–36.1% Brahman in Santa Gertrudis. The estimated GBC of ancestries for Santa Gertrudis roughly agreed with the pedigree‐expected values. However, the estimated GBC in Brangus showed a considerably larger Angus composition than the pedigree‐expected value (62.5%). The elevated Angus composition in the Brangus could be due to the mixture of some 1/2 Ultrablack animals (Brangus × Angus). Another reason could be the consequences of selection in Brangus cattle for phenotypes where the Angus breed has advantages.