Hostname: page-component-76fb5796d-25wd4 Total loading time: 0 Render date: 2024-04-25T10:42:03.848Z Has data issue: false hasContentIssue false

Sources of information for estimating heritability from selection experiments

Published online by Cambridge University Press:  14 April 2009

R. Thompson*
Affiliation:
A.F.R.C. Roslin Institute (Edinburgh), Roslin, Midlothian, EH25 9PS, Scotland
K. D. Atkins
Affiliation:
NSW Agriculture, Agricultural Research & Veterinary Centre, Orange, Australia
*
Corresponding author.
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Maximum likelihood estimation methods with an individual animal model were used to analyse a bi-directional selection experiment, with control, for cannon bone length in Scottish Blackface sheep. A method is described for partitioning the likelihood to allow within- and between-line estimates of genetic variance. It is concluded that both sources of information made substantial contributions to the precision of the base population heritability estimate. The implications for different experimental designs and varying heritability are discussed.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1994

References

Atkins, K. D. & Thompson, R. (1986). 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. Animal Production 43, 421435.Google Scholar
Blair, H. T. & Pollak, E. J. (1984). Estimation of genetic trend in a selected population with and without the use of a control population. Journal of Animal Science 58, 878886.CrossRefGoogle Scholar
Graser, H.-U., Smith, S. P. & Tier, B. (1987). A derivative-free approach for estimating variance components in animal models by restricted maximum likelihood. Journal of Animal Science 64, 13621370.CrossRefGoogle Scholar
Henderson, C. R. (1976). A simple model for computing the inverse of a numerator relationship matrix used in prediction of breeding values. Biometrics 32, 6983.CrossRefGoogle Scholar
Hill, W. G. (1972). Estimation of realised heritabilities from selection experiments. I. Divergent selection. Biometrics 28, 747765.CrossRefGoogle ScholarPubMed
James, J. W. (1990). Selection theory versus selection results-A comparison. Proceedings of the 4th World Congress on Genetics Applied to Livestock Production, Edinburgh, Vol. XIII: 195204.Google Scholar
Meyer, K. (1989). Restricted maximum likelihood to estimate variance components for animal models with several random effects using a derivative-free algorithm. Genetics, Selection, Evolution 21, 317340.CrossRefGoogle Scholar
Patterson, D. D. & Thompson, R. (1971). Recovery of inter-block information when block sizes are unequal. Biometrika 58, 545554.CrossRefGoogle Scholar
Robertson, A. (1977). The effect of selection on the estimation of genetic parameters. Journal of Animal Breeding and Genetics 94, 131135.Google Scholar
Sheridan, A. K. (1988). Agreement between estimated and realised genetic parameters. Animal Breeding Abstracts 56, 877889.Google Scholar
Sorenson, D. A. & Kennedy, B. W. (1984). Estimation of response to selection using least-squares and mixed model methodology. Journal of Animal Science 58, 10971106.CrossRefGoogle Scholar
Visscher, P. M. & Thompson, R. (1992). Comparisons between genetic variances estimated from different types of relatives in dairy cattle. Animal Production 55, 315320.Google Scholar