Data Subsetting Strategies for Estimation of Across-Country Genetic Correlations

International genetic evaluation of dairy cattle requires estimation of genetic correlations among populations to account for genotype-environment interaction. Simultaneous estimation of across-country genetic correlations among all populations of a widespread breed, such as the Holstein breed is, however, hampered by connectedness problems and computational challenges. The purpose of this study was to examine the effects of using bulls with across-country, balanced distribution of daughters on estimates of genetic correlations. For this purpose, dairy cattle populations undergoing selection in 6 countries were simulated. Two population-size settings were used. In the small population-size setting (S-populations), the 6 simulated countries had 2000 cows and 20 young progeny testing bulls per generation. In the larger population-size setting (L-populations), the 6 simulated countries had between 2000 and 64,000 cows and 20 to 640 young progeny testing bulls per generation. The simulated (true) across-country genetic correlations, depending on the country combination, varied between 0.5 and 0.9. Simulations comprised a base population and 10 generations and were replicated 16 times. Results for the S-populations were not conclusive. For the L-populations, results indicated that by use of data from a relatively small subset of bulls with distribution of daughters balanced across countries, genetic correlations could be estimated with very small bias (overall average of absolute value of bias across replicates was 0.03 for the L-populations). The suggested bull subsetting strategy would allow simultaneous estimation of across-country genetic correlations to be computed for a larger number of countries and in a shorter window of time than was possible previously.