Genomic prediction for carcass traits in Japanese Black cattle using single nucleotide polymorphism markers of different densities

Genomic prediction (GP) of breeding values using single nucleotide polymorphism (SNP) markers can be conducted even when pedigree information is unavailable, providing phenotypes are known and marker data are provided. While use of high-density SNP markers is desirable for accurate GP, lower-density SNPs can perform well in some situations. In the present study, GP was performed for carcass weight and marbling score in Japanese Black cattle using SNP markers of varying densities. The 1791 fattened steers with phenotypic data and 189 having predicted breeding values provided by the official genetic evaluation using pedigree data were treated as the training and validation populations respectively. Genotype data on 565837 autosomal SNPs were available and SNPs were selected to provide different equally spaced SNP subsets of lower densities. Genomic estimated breeding values (GEBVs) were obtained using genomic best linear unbiased prediction incorporating one of two types of genomic relationship matrices (G matrices). The GP accuracy assessed as the correlation between the GEBVs and the corrected records divided by the square root of estimated heritability was around 0.85 for carcass weight and 0.60 for marbling score when using 565837 SNPs. The type of G matrix used gave no substantial difference in the results at a given SNP density for traits examined. Around 80% of the GP accuracy was retained when the SNP density was decreased to 1/1000 of that of all available SNPs. These results indicate that even when a SNP panel of a lower density is used, GP may be beneficial to the pre-selection for the carcass traits in Japanese Black young breeding animals.