Exploring the size of reference population for expected accuracy of genomic prediction using simulated and real data in Japanese Black cattle.

BACKGROUND: Size of reference population is a crucial factor affecting the accuracy of prediction of the genomic estimated breeding value (GEBV). There are few studies in beef cattle that have compared accuracies achieved using real data to that achieved with simulated data and deterministic predictions. Thus, extent to which traits of interest affect accuracy of genomic prediction in Japanese Black cattle remains obscure. This study aimed to explore the size of reference population for expected accuracy of genomic prediction for simulated and carcass traits in Japanese Black cattle using a large amount of samples. RESULTS: A simulation analysis showed that heritability and size of reference population substantially impacted the accuracy of GEBV, whereas the number of quantitative trait loci did not. The estimated numbers of independent chromosome segments (Me) and the related weighting factor (w) derived from simulation results and a maximum likelihood (ML) approach were 1900-3900 and 1, respectively. The expected accuracy for trait with heritability of 0.1-0.5 fitted well with empirical values when the reference population comprised > 5000 animals. The heritability for carcass traits was estimated to be 0.29-0.41 and the accuracy of GEBVs was relatively consistent with simulation results. When the reference population comprised 7000-11,000 animals, the accuracy of GEBV for carcass traits can range 0.73-0.79, which is comparable to estimated breeding value obtained in the progeny test. CONCLUSION: Our simulation analysis demonstrated that the expected accuracy of GEBV for a polygenic trait with low-to-moderate heritability could be practical in Japanese Black cattle population. For carcass traits, a total of 7000-11,000 animals can be a sufficient size of reference population for genomic prediction.

Genotypes and allele frequencies of buried SNPs in a bovine single-nucleotide polymorphism array in Japanese Black cattle.

Single nucleotide polymorphism (SNP) arrays are widely used for genetic and genomic analyses in cattle breeding; thus, data derived from SNP arrays have accumulated on a large scale nationwide. Commercial SNP arrays contain a considerable number of unassigned SNPs on the chromosome/position on the genome; these SNPs are excluded in subsequent analyses. Notably, the position-unassigned SNPs, or "buried SNPs" include some of the markers associated with genetic disease. In this study, we identified the position of buried SNPs using the Basic Local Alignment Search Tool against the surrounding sequences and characterized the relationship between SNPs and genetic diseases in Online Mendelian Inheritance in Animals based on the genomic position. We determined the position of 285 buried SNPs on the genome and surveyed the genotype and allele frequencies of these SNPs in 5,955 individual Japanese Black cattle. Eleven SNPs associated with genetic disease, which contained five buried SNPs, were found in the population with the risk allele frequency ranging from 0.00008396 to 0.46. These results indicate that buried SNPs in the bovine SNP array can be utilized to identify associations with genetic disorders from large scale accumulated SNP genotype data in Japanese Black cattle.