Genomic prediction in Merino sheep for varying reference population size and marker density

Incorporation of genomic information in genetic evaluation of farm animals can considerably enhance the rate of genetic improvement by increasing the accuracy of selection and decreasing the generation interval. The aim of this study was to determine the accuracy of genomic prediction for yearling greasy fleece weight (YGFW), early breech wrinkle (EBRWR) and post weaning weight (PWW) in Australian Merino sheep, depending on the size of the reference population (Nref) and the number of SNP markers genome wide (Nmark = 5k, 10k and 50k SNPs). The marker subsets were chosen at random, and always evenly distributed across the genome. Genomic prediction of breeding value (GEBV) was obtained via the GBLUP method, using genomic relationships between a reference population of merino sheep and 150 to 184 merino industry sires with progeny and the GEBV accuracy was calculated from its correlation with the Australian Sheep Breeding Value (ASBVs) on those sires. For Nref = 4000 and Nmark = 50k, the GEBV accuracy was 0.64, 0.31 and 0.56 for YGFW, EBRWR and PWW, respectively. With Nref = 1000, the accuracy decreased between 11% and 13.8%. When Nmark decreased to 10k, the accuracies decreased between 9 and 10.5% and for Nmark = 5k accuracy decreased between 11.1% and 13.2%, on average. The decline in accuracy was higher in low heritable traits. We suspect that a fair part of the prediction accuracy is due to the degree of genetic relationships and population substructure.