Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học quốc tế đề tài: International genomic evaluation methods for dairy cattle | VanRaden and Sullivan Genetics Selection Evolution 2010 42 7 http content 42 1 7 Ge n et i cs Selection Evolution RESEARCH Open Access International genomic evaluation methods for dairy cattle Paul M VanRaden1 Peter G Sullivan2 Abstract Background Genomic evaluations are rapidly replacing traditional evaluation systems used for dairy cattle selection. Higher reliabilities from larger genotype files promote cooperation across country borders. Genomic information can be exchanged across countries using simple conversion equations by modifying multi-trait across-country evaluation MACE to account for correlated residuals originating from the use of foreign evaluations or by multi-trait analysis of genotypes for countries that use the same reference animals. 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 genomic data as a fraction of the total in each country and proportions of bulls shared. MACE methods developed to combine separate within-country genomic evaluations were compared to direct multi-country analysis of combined genotypes using simulated genomic and phenotypic data for 8 193 bulls in nine countries. Results 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. Gains in reliability from genomic MACE were similar to those of multi-trait evaluation of genotypes but required less computation. Sharing of reference genotypes among countries created large residual correlations especially for young bulls that are accounted for in genomic MACE. 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
