title: Prior (co)variances can improve multiple-trait across-country evaluations of weakly linked bull populations.
abstract: National genetic evaluation results for fore udder attachment from 9 Ayrshire populations were used to assess the impact of different uses of prior genetic correlations in multiple-trait across-country evaluations (MACE) on predicted international genetic merit. These Ayrshire populations were poorly connected; that is, 2% of the bulls had evaluations in 2 or more countries. Genetic correlations from the Holstein populations in the same countries were used as prior information to improve inferences of location parameters and international genetic merits. Fully Bayesian analyses using Gibbs sampling and computationally less demanding traditional MACE assuming a weighted average of prior and estimated Ayrshire genetic correlations were compared for 3 different prior degrees of belief and for different groups of bulls. Posterior means of genetic correlations estimated by Gibbs sampling were on average higher (+0.2) than those estimated by REML. Posterior heritabilities differed up to 0.2 units from those assumed in national genetic evaluations. Predicted genetic merit and international sire rankings of bulls with daughter information in the country of interest were not affected substantially by method of analysis and even less by varying prior degree of belief. Method of analysis had a larger impact on predicted genetic merit for bulls without daughter information in the country of interest. Here the average correlation between predicted genetic merit in different analyses ranged from 0.62 to 0.99. The predictive ability for young and randomly chosen bulls favored Bayesian MACE. The prior degree of belief did not have much impact on sire rankings and predictive ability, but intermediate prior degree of belief tended to perform best. All MACE analyses yielded nearly unbiased predictions. Traditional MACE assuming a simple weighted average of prior and estimated Ayrshire genetic correlations has been implemented by Interbull for routine international genetic evaluations.
authors.affiliation: Interbull Centre, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, P.O. Box 7023, 750 07 Uppsala, Sweden. Thomas.Mark@hgen.slu.se
authors.forename: T
authors.initials: T
authors.lastname: Mark
authors.forename: P
authors.initials: P
authors.lastname: Madsen
authors.forename: J
authors.initials: J
authors.lastname: Jensen
authors.forename: W F
authors.initials: WF
authors.lastname: Fikse
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D001499:Bayes Theorem; D001947:Breeding; D002417:Cattle / Q000235:genetics*; D005260:Female; D007315:Insemination, Artificial / Q000662:veterinary; D007391:International Cooperation; D008297:Male; D008321:Mammary Glands, Animal; D010375:Pedigree; D019655:Quantitative Trait, Heritable; D012641:Selection, Genetic