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Across-country genomic prediction of bull fertility in Jersey dairy cattle.

F. M. Rezende




Across-country genomic prediction of bull fertility in Jersey dairy cattle.
F. M. Rezende*1, M. Haile-Mariam2, J. E. Pryce2, F. Pe�agaricano1. 1University of Florida Gainesville, FL, 2Agriculture Victoria Research Bundoora, VIC, Australia.

The use of information across populations is an attractive approach to increase the accuracy of genomic predictions for numerically small breeds and traits that are time-consuming and difficult to measure, such as male fertility in cattle. This study was conducted to evaluate genomic prediction of Jersey bull fertility using an across-country reference population combining records from United States (US) and Australia (AU). Data set consisted of 1.5k US Jersey bulls with sire conception rate (SCR) records, 603 AU Jersey bulls with semen fertility value (SFV) records and roughly 90k SNP genotypes. Both SCR and SFV are evaluations of service sire fertility based on cow field data, and both are intended as phenotypic evaluations because the estimates include genetic and non-genetic effects. Within and across-country genomic predictions were evaluated using univariate and bivariate GBLUP models. Predictive ability was assessed in 5-fold cross-validation using the correlation between observed and predicted fertility values. Genomic predictions within-country exhibited predictive correlations around 0.30 and 0.02 for US and AU, respectively. The AU Jersey population is genetically diverse, so careful selection of the reference population by including only closely related animals (e.g., excluding New Zealand bulls) allowed to increase the predictive correlations up to 0.20. Notably, the use of bivariate models fitting all US Jersey records and the optimized AU population allowed to achieve predictive correlations around 0.24 for SFV values, which is a gaining in predictive ability of 20%. Conversely, for predicting SCR values, the use of an across-country reference population did not outperform the standard approach using a pure US Jersey reference data set. Overall, our findings indicate that genomic prediction of male fertility in cattle is feasible, and the use of an across-country reference population would be beneficial when local populations are small and genetically diverse.

Keywords: multi-country reference population, semen fertility value, sire conception rate.