Location: Location not imported yet.Title: International genomic evaluation methods for dairy cattle) Author
Submitted to: Genetics Selection Evolution
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/1/2010
Publication Date: 3/1/2010
Publication URL: hdl.handle.net/10113/40259
Citation: Van Raden, P.M., Sullivan, P. 2010. International genomic evaluation methods for dairy cattle. Genetics Selection Evolution. 42:7. Interpretive Summary: Genomic evaluations are rapidly replacing traditional evaluation systems used for dairy cattle selection. Economies of scale in genomics promote cooperation across country borders because additional information increases the reliability of evaluations in each country. Methods were derived to exchange genomic information using modified multi-trait across-country evaluations or combined genotype files. Simulated Brown Swiss data revealed large gains in reliability for young bulls from merging data across countries. Gains for old bulls were smaller because traditional reliability was already high. International genomic evaluations should benefit all breeders by improving genetic progress.
Technical Abstract: Background Genomic evaluations are rapidly replacing traditional evaluation systems used for dairy cattle selection. Economies of scale in genomics promote cooperation across country borders. Genomic information can be transferred across countries using simple conversion equations, by modifying multi-trait across-country evaluation (MACE) to account for increased reliability of evaluations and correlated residuals from use of foreign evaluations, or by direct multi-trait analysis for countries that share genotypes. Methods Traditional MACE assumes independent residuals because each daughter is measured in only one country. Genomic MACE could account for residual correlations using daughter equivalents from genomics as a fraction of the total in each country and proportions of common bulls shared. MACE methods to combine separate within-country genomic evaluations were compared to multi-country, direct analysis of combined genotypes. Results Highest residual correlations in genomic MACE are expected for young bulls in countries that share genotypes. MACE gains in reliability were similar to those of direct multi-trait evaluation but required less computation when tested using simulated genotypes for 8,193 Brown Swiss bulls in 9 countries. Reliabilities for young bulls were much higher for across-country than within-country genomic evaluations as measured by squared correlations of estimated with true breeding values. Conclusions International genomic evaluations can be computed either by modifying MACE to account for residual correlations across countries or by multi-trait evaluation of combined genotype files. The gains in reliability justify the increased computation but require more cooperation than in previous breeding programs.