Indirect Genomic Predictions for Indicine Cattle Breeds With SNP Effects From a Multi-Breed Genomic Evaluation.

Abstract

Indirect predictions (IP) are used for young genotyped animals that lack phenotypes (of their own or from progeny) or are from commercial herds. The former can be left behind because they do not contribute to the official genomic evaluations. The latter are often excluded from the evaluations because they are not registered and may not have pedigree information. Including such animals could result in inflated and biased genomic breeding values (GEBV). In Brazil, pedigree, phenotype and genotype information is scarce for important breeds like Brahman, Guzerat, and Tabapua, while the Nellore breed has a substantial amount of information. IP for young animals of these breeds based on a larger reference population could enhance genomic selection accuracy. Our objective in this study was to compute IP for young genotyped Nellore, Brahman, Guzerat, and Tabapua animals using single- and multi-breed analyses, with or without metafounders (MF) to model genetic differences across breeds. Records from the four breeding programs of the National Association of Breeders and Researchers (ANCP-Ribeirão Preto, SP, Brazil) were used. Data included pedigree (4.2 M), phenotypes (329 K), and genotypes (63.5 K) across all breeds. The number of genotyped animals within each breed was 58,574 for Nellore, 3102 for Brahman, 1389 for Guzerat, and 427 for Tabapua. The analysed traits were adjusted weight at 210 (W210) and 450 (W450) days of age and the scrotal circumference at 365 (SC365) days of age. IP were derived as the sum of the SNP effects weighted by the gene content using different reference populations: multi-breed with or without MF, Nellore, or within-breed. Scenarios were compared using the linear regression (LR) method for bias, dispersion, and accuracy. Adding MF decreased bias and under- or overdispersion and slightly increased the accuracy of IP. Combining breeds increased the accuracy of IP, mainly benefiting breeds with a small number of genotypes. These findings suggest that when young genotyped animals are not included in an official multi-breed evaluation in zebuine cattle from Brazil, robust IP can be obtained with proper modelling, regardless of the breed. This helps obtain fast genomic predictions for young animals without overwhelming the evaluation system with too many animals.