Single-step genomic predictions for crossbred Holstein and Jersey cattle in the United States

Abstract

In the dairy cattle sector, the number of crossbred genotypes increased in the last years, and therefore, the need for accurate genomic evaluations for crossbred animals has also increased. Thus, this study aimed to investigate the feasibility of including crossbred genotypes in multibreed, single-step genomic BLUP (ssGBLUP) evaluations. The Council of Dairy Cattle Breeding provided more than 47 million lactation records registered between 2000 and 2021 in purebred Holstein and Jersey and their crosses. A total of 27 million animals were included in the analysis, of which 1.4 million were genotyped. Milk, fat, and protein yields were analyzed in a 3-trait repeatability model using BLUP or ssGBLUP. The 2 models were validated using prediction bias and accuracy computed for genotyped cows with no records in the truncated dataset and at least one lactation in the complete dataset. Bias and accuracy were better in the genomic model than in the pedigree-based one, with accuracies for crossbred cows higher than those of purebreds, except for fat yield in Holstein. Our study shows that genotypes for crossbred animals can be included in a ssGBLUP analysis with their purebred ancestors to estimate genomic estimated breeding values in a single run.