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Prediction of asymptotic rates of response from selection on multiple traits using univariate and multivariate best linear unbiased predictors

Published online by Cambridge University Press:  02 September 2010

B. Villanueva ,
N. R. Wray  and
R. Thompson
B. Villanueva
Affiliation:
Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG
N. R. Wray
Affiliation:
Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG
R. Thompson
Affiliation:
AFRC Roslin Institute(Edinburgh), Research Station, Roslin, Midlothian EH25 9PS‡
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Abstract

Predicted rate of genetic response for multiple trait breeding objectives from multivariate analyses is compared with that from univariate analyses for a range of breeding schemes, A selection index that approximates a multipl trait best linear unbiased prediction (BLUP) animal model is utilized. Changes in genetic parameters due to linkage disequilibrium generated by selection are accounted for. This study shows that asymptotic response in the aggregate breeding value, and its component traits, to selection on multivariate predictions, can easily be calculated from first generation responses, which use ancestral information. For two-path breeding schemes with equal accuracy for males and females, proportional reductions in responses depend only on selection intensity. In general, benefit from multivariate over univariate analyses is slightly smaller at the asymptote than in the first generation. Multivariate analyses give substantially more response than univariate analyses on untransformed data, when correlations between traits are high and when genetic and phenotypic correlations have opposite signs. The advantage of multivariate analyses decreases with increasing family size. When three random factors (additive genetic, common and individual environmental effects) are included in the model, the benefit of multivariate analysis is negligible if univariate analyses are performed on canonical traits. In this case, the advantage of multivariate analyses is never higher than 1% for all cases studied. These results are of particular relevance to the design of genetic evaluation programmes.

Keywords

best linear unbaised predictioncanonical analysislinkage disequilibriummultivariate analysisselection responses
Type
Research Article
Information
Animal Production , Volume 57 , Issue 1 , August 1993 , pp. 1 - 13
Copyright
Copyright © British Society of Animal Science 1993

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