A Bayesian multilevel whole-genome regression model is disclosed and its prediction performance compared to that of the popular BayesA model applied to each population separately (no pooling) and to the joined data set (complete pooling). For small population sizes (e.g., < 50), partial pooling increased prediction accuracy over no or complete pooling for populations represented in the estimation set. Partial pooling with multilevel models can make optimal use of information in multi-population estimation sets.
