Comparison of combined, crossbred, and purebred reference populations for genomic selection in small populations

Abstract The main purpose of the present study was to evaluate the accuracy of genomic predictions in two purebreds using three different ways for the reference population formation: (1) a separate purebred reference population (SI), (2) a combined reference population from two breeds (CO), and (3) use of crossbred data (CR). The effects of different reference population structure were compared under different marker densities, reference population sizes, divergence between breeds, and methods used for estimating marker effects. The results showed that at lower marker densities, the SI had the highest accuracy of breeding values. With the increase in the marker density, the use of the CO increased the accuracy relative to the SI in scenarios were generations since divergence was low. In the CO and CR, the BayesB method was more accurate than the rrBLUP, and decreasing the generations since divergence increased the accuracy of predictions at higher marker density. Increased population size, marker density, and genetic relationship between breeds and using the BayesB method retained accuracies higher after five generations. Interestingly, the CR had the lowest accuracy drop after five generations.