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Influences of genetic variance in phenotypic variability on response to artificial selection

Published online by Cambridge University Press:  20 November 2017

W. G. Hill
W. G. Hill*
Affiliation:
Institute of Cell, Animal and Population Biology, School of Biological Sciences, University of Edinburgh, West Mains Road, Edinburgh EH9 3JT, UK.
*
E-mail: [email protected]
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Extract

In standard models of the genetic basis of quantitative traits such as growth rate and milk yield, it is assumed that genotypes differ in their effect on the mean but not on the variance. There is much evidence of differences in variability among environments, and more limited but quite conclusive evidence of differences in residual variability among genotypes (e.g. CanCristobal-Gaudy et al, 1998; Sorensen and Waagepetersen, 2003). Differences among genotypes at an individual locus in their residual phenotypic variation or in the environmental variation among whole genotypes may influence rates of genetic progress and rates of change in variability. We propose models and quantify such changes for directional selection (see also Hill, 2002; Hill and Zhang, 2004).

Type
Theatre Presentations
Information
Proceedings of the British Society of Animal Science , Volume 2004 , 2004 , pp. 30
Copyright
Copyright © The British Society of Animal Science 2004

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References

Hill, ill.G. 2002. Direct effects of selection on phenotypic variability of quantitative traits. Proceedings of the 7th World Congress on Genetics Applied to Livestock Production. CD-ROM comm. n° 19–02.Google Scholar
Hill, ill.G. and Zhang, X.-S. 2004. Effects on phenotypic variability of directional selection arising through genetic differences in residual variability. Genetical Research 83: (in press).Google Scholar
SanCristobal–Gaudy, M., Elsen, J.-M., Bodin, L. and Chevalet, C. 1998. Prediction of the response to a selection for canalisation of a continuous trait in animal breeding. Genetics Selection Evolution 30: 423–451.CrossRefGoogle Scholar
Sorensen, D. and Waagepetersen, R. 2003. Normal linear models with genetically structured residual variance heterogeneity: A case study. Genetical Research 82: 209–224.Google Scholar