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Cumulative selection differentials and realized heritabilities with overlapping generations

Published online by Cambridge University Press:  02 September 2010

J. W. James
Affiliation:
Institute of Animal Genetics, West Mains Road, Edinburgh EH9 3JN
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Abstract

It is shown that a commonly used method of calculating cumulative selection differentials in experiments where generations overlap is biased, and consequently leads to biased estimates of realized heritability. In one example, the heritability was underestimated by about one-fifth. Since genetic variation in a given progeny crop may be increased by genetic differences between parental age groups, realized heritability estimated by regression may not agree with base population estimates. An alternative form of analysis is proposed to allow for this effect.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1986

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References

REFERENCES

Bichard, M., Pease, A. H. R., Swales, P. H. and Ozkotuk, K. 1973. Selection in a population with overlapping generations. Anim. Prod. 17: 215227.Google Scholar
Blair, H. T. and Pollak, E. J. 1984. Estimation of genetic trend in a selected population with and without the use of a control population. J. Anim. Sci. 58: 878886.CrossRefGoogle Scholar
Bulmer, M. G. 1971. The effect of selection on genetic variability. Am. Nat. 105: 201211.CrossRefGoogle Scholar
Bulmer, M. G. 1980. The Mathematical Theory of Quantitative Genetics, p. 148. Oxford University Press.Google Scholar
Falconer, D. S. 1981. Introduction to Quantitative Genetics. 2nd ed. Longman, London.Google Scholar
Hill, W. G. 1972. Estimation of realised heritabilities from selection experiments. 1. Divergent selection. Biometrics 28: 747765.CrossRefGoogle Scholar
Hill, W. G. 1977. Variation in response to selection. In Proc. int. Conf. Quantitative Genetics (ed. Pollak, E., Kempthorne, O. and Bailey, T. B.), pp. 343365. Iowa State University Press, Ames, la.Google Scholar
James, J. W. 1972. Computation of genetic contributions from pedigrees. Theor. appl. Genet. 42: 272273.CrossRefGoogle ScholarPubMed
James, J. W. and McBride, G. 1958. The spread of genes by natural and artificial selection in closed poultry flock. J. Genet. 56: 5562.CrossRefGoogle Scholar
Mueller, J. P. and James, J. W. 1983. Effects of reduced variance due to selection in open nucleus breeding systems. Aust. J. agric. Res. 34: 5362.CrossRefGoogle Scholar
Newman, J. A., Rahnefeld, G. W. and Fredef, N. H. T. 1973. Selection intensity and response to selection for yearling weight in beef cattle. Can. J. Anim. Sci. 53: 112.CrossRefGoogle Scholar
Pattie, W. A. 1965. Selection for weaning weight in Merino sheep. 1. Direct response to selection. Aust. J. exp. Agric. Anim. Husb. 5: 353360.CrossRefGoogle Scholar
Robertson, A. 1961. Inbreeding in artificial selection programmes. Genet. Res. 2: 189194.CrossRefGoogle Scholar
Turner, H. N. and Young, S. S. Y. 1969. Quantitative Genetics in Sheep Breeding, p. 159. Macmillan. Melbourne.Google Scholar