Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-11-26T23:53:51.316Z Has data issue: false hasContentIssue false

Predicted and realized responses to selection for an index of bone length and body weight in Scottish Blackface sheep 1. Responses in the index and component traits

Published online by Cambridge University Press:  02 September 2010

K. D. Atkins
Affiliation:
AFRC Animal Breeding Research Organisation, West Mains Road, Edinburgh EH9 3JQ
R. Thompson
Affiliation:
AFRC Animal Breeding Research Organisation, West Mains Road, Edinburgh EH9 3JQ
Get access

Abstract

A selection experiment with Scottish Blackface sheep was used to compare predicted and realized responses to selection. Three closed lines, of approximate annual size of 270 ewes and 10 rams, were maintained between 1956 and 1974, in which selection was at random, or for high and low values of an index of cannon-bone length at 8 weeks of age adjusted for body weight at the same age. An unselected base flock (1954-55) and the randomly selected line were used to estimate base population parameters, while the selected lines were used to estimate realized responses to selection.

Heritabilities and genetic correlations were obtained in the unselected lines from a variety of collateral and ancestral relationships. The important components of phenotypic variance were estimated and likely responses to selection predicted for the index and its two component traits. Realized responses to selection were estimated from the regression of response on selection differential. The expected variance-covariance matrix of observed responses was included in generalized least-squares estimates of these regressions.

The realized heritability of the index under selection, estimated from the divergence of selected lines, was 0·52 (s.e. 0·02). After allowing for the expected reduction in heritability arising from linkage disequilibrium, this was very similar to the base population estimate of 0·56 (s.e. 0·04). The responses in the component traits of the index were also very close to those expected from base population parameters

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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Atkins, K. D. 1984. The estimation of responses to selection in hill sheep. Ph.D. Thesis, University of Edinburgh.CrossRefGoogle Scholar
Atkins, K. D. 1986. A genetic analysis of the components of lifetime productivity in Scottish Blackface sheep. Animal Production 43: 405419.Google Scholar
Baker, R. J. and Nelder, J. A. 1978. The GUM System, Release 3. Numerical Algorithms Group, Oxford.Google Scholar
Becker, W. A. 1975. Manual of Quantitative Genetics. 3rd ed. Pullman, Washington State University.Google Scholar
Bulmer, M. G. 1976. The effect of selection on genetic variability: a simulation study. Genetical Research 28: 101117.CrossRefGoogle ScholarPubMed
Bulmer, M. G. 1980. The Mathematical Theory of Quantitative Genetics. Clarendon Press, Oxford.Google Scholar
Dalton, D. C. and Baker, R. L. 1980. Selection experiments with beef cattle and sheep. In Selection Experiments in Laboratory and Domestic Animals (ed. Robertson, A.), pp. 131143. Commonwealth Agricultural Bureaux, Slough.Google Scholar
Eisen, E. J. 1967. Mating designs for estimating direct and maternal genetic variances and direct-maternal genetic covariances. Canadian Journal of Genetics and Cytology 9: 1322.CrossRefGoogle ScholarPubMed
Falconer, D. S. 1981. Introduction to Quantitative Genetics. 2nd ed. Longman, London.Google Scholar
Hanrahan, J. P. 1976. Maternal effects and selection response with an application to sheep data. Animal Production 22: 359369.Google Scholar
Harvey, W. R. 1977. User's guide for LSML76. Mixed model least-squares and maximum likelihood computer program. Ohio State University, Columbus.(Mimeograph).Google Scholar
Hill, W. G. 1971. Design and efficiency of selection experiments for estimating genetic parameters. Biometrics 27: 293311.CrossRefGoogle ScholarPubMed
Hill, W. G. 1972a. Estimation of realised heritabilities from selection experiments. I. Divergent selection. Biometrics 28: 747765.CrossRefGoogle ScholarPubMed
Hill, W. G. 1972b. Estimation of realised heritabilities from selection experiments. II. Selection in one direction. Biometrics 28: 767780.CrossRefGoogle ScholarPubMed
Hill, W. G. 1974. Prediction and evaluation of response to selection with overlapping generations. Animal Production 18: 117139.Google Scholar
Hill, W. G. 1980. Design of quantitative genetic selection experiments. In Selection Experiments in Laboratory and Domestic Animals (ed. Robertson, A.), pp. 113. Commonwealth Agricultural Bureaux, Slough.Google Scholar
Hohenboken, W. D. and Brinks, J. S. 1971. Relationships between direct and maternal effects on growth in Herefords. II. Partitioning of covariance between relatives. Journal of Animal Science 32: 2634.CrossRefGoogle Scholar
Johnson, D. L. 1977. Variance-covariance structure of group means with overlapping generations. Proceedings of the International Conference on Quantitative Genetics, Iowa, 1976 (ed. Pollak, E., Kempthorne, O. and Bailey, T. B.), pp. 851858. Iowa State University Press, Ames, la.Google Scholar
Koch, R. M. 1972. The role of maternal effects in animal breeding. VI. Maternal effects in beef cattle. Journal of Animal Science 35: 13161323.CrossRefGoogle ScholarPubMed
Koch, R. M. and Clark, R. T. 1955. Genetic and environmental relationships among economic characters in beef cattle. III. Evaluating maternal environment. Journal of Animal Science 14: 979996.CrossRefGoogle Scholar
Latter, B. D. H. and Robertson, A. 1960. Experimental design in the estimation of heritability by regression methods. Biometrics 16: 348353.CrossRefGoogle Scholar
Pattie, W. A. 1965. Selection for weaning weight in Merino sheep. 1. Direct response to selection. Australian Journal of Experimental Agriculture and Animal Husbandry 5: 353360.CrossRefGoogle Scholar
Pattie, W. A. and Trimmer, B. 1964. The milk production of Merino ewes from flocks selected for high and low weaning weight. Proceedings of the Australian Society of Animal Production 5: 156159.Google Scholar
Purser, A. F. 1960. The use of correction for regression on a second character to increase the efficiency of selection. In Biometrical Genetics (ed. Kempthorne, O.), pp. 210214. Pergamon Press, London.Google Scholar
Purser, A. F. 1980. Comparison of expected and realised responses in three sheep selection experiments. In Selection Experiments in Laboratory and Domestic Animals (ed. Robertson, A.), pp. 2130. Commonwealth Agricultural Bureaux, Slough.Google Scholar
Purser, A. F., Wiener, G. and West, D. M. 1982. Causes of variation in dental characters of Scottish Blackface sheep in a hill flock, and relations to ewe performance. Journal of Agricultural Science, Cambridge 99: 287294.CrossRefGoogle Scholar
Thompson, R. 1976. The estimation of maternal genetic variances. Biometrics 32: 903917.CrossRefGoogle ScholarPubMed
Tsiatis, A. A. 1980. A note on a gdodness-of-fit test for the logistic regression model. Biometrika 67: 250251.CrossRefGoogle Scholar
Turner, H. N. and Young, S. S. Y. 1969. Quantitative Genetics in Sheep Breeding. MacMillan, Australia.Google Scholar
Willham, R. L. 1963. The covariance between relatives for characters composed of components contributed by related individuals. Biometrics 19: 1827.CrossRefGoogle Scholar