Hostname: page-component-586b7cd67f-vdxz6 Total loading time: 0 Render date: 2024-11-30T14:36:09.134Z Has data issue: false hasContentIssue false
  • English
  • Français

Asymptotic rates of response from index selection

Published online by Cambridge University Press:  02 September 2010

Naomi R. Wray  and
W. G. Hill
Naomi R. Wray
Affiliation:
Institute of Animal Genetics, University of Edinburgh, King's Buildings, West Mains Road, Edinburgh EH9 3JN
W. G. Hill
Affiliation:
Institute of Animal Genetics, University of Edinburgh, King's Buildings, West Mains Road, Edinburgh EH9 3JN
Get access

Abstract

The reduction in additive genetic variance due to selection is investigated when index selection using family records is practised. A population of infinite size with no accumulation of inbreeding, an infinitesimal model and discrete generations are assumed. After several generations of selection, the additive genetic variance and the rate of response to selection reach an asymptote. A prediction of the asymptotic rate of response is considered to be more appropriate for comparing response from alternative breeding programmes and for comparing predicted and realized response than the response following the first generation of selection that is classically used. Algorithms to calculate asymptotic response rate are presented for selection based on indices which include some or all of the records of an individual, its full- and half-sibs and its parental estimated breeding values. An index using all this information is used to predict response when selection is based on breeding values estimated by using a Best Linear Unbiased Prediction (BLUP) animal model, and predictions agree well with simulation results. The predictions are extended to multiple trait selection.

Asymptotic responses are compared with one-generation responses for a variety of alternative breeding schemes differing in population structure, selection intensity and heritability of the trait. Asymptotic responses can be up to one-quarter less than one-generation responses, the difference increasing with selection intensity and accuracy of the index. Between family variance is reduced considerably by selection, perhaps to less than half its original value, so selection indices which do not account for this tend to place too much emphasis on family information. Asymptotic rates of response to selection, using indices including family information for traits not measurable on the individuals available for selection, such as sex limited or post-slaughter traits, are found to be as much as two-fifths less than their expected one-generation responses. Despite this, the ranking of the breeding schemes is not greatly altered when compared by one-generation rather than asymptotic responses, so the one-generation prediction is usually likely to be adequate for determining optimum breeding structure.

Type
Papers
Information
Animal Production , Volume 49 , Issue 2 , October 1989 , pp. 217 - 227
Copyright
Copyright © British Society of Animal Science 1989

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

Avalos, E. and Smith, C. 1987. Genetic improvement of litter size in pigs. Animal Production 44: 153–163.Google Scholar
Bulmhr, M. G. 1971. The effect of selection on genetic variability. American Naturalist 105: 201–211.CrossRefGoogle Scholar
Dempfle, L. 1975. A note on increasing the limit of selection through selection within families. Genetical Research 24: 127–135.CrossRefGoogle Scholar
Falconer, D. S. 1981. Introduction to Quantitative Genetics. 2nd ed. Longman, London.Google Scholar
Henderson, C. R. 1975. Best linear unbiased estimation and prediction under a selection model. Biometrics 31: 423–447.CrossRefGoogle Scholar
Henderson, C. R. and Quaas, R. L. 1976. Multiple trait evaluation using relatives' records. Journal of Animal Science 43: 1188–1197.CrossRefGoogle Scholar
Hill, W. G. 1976. Order statistics of correlated variables and implications in genetic selection programmes. Biometrics 32: 889–902.CrossRefGoogle ScholarPubMed
Hill, W. G. 1977. Order statistics of correlated variables and implications in genetic selection programmes. 2. Response to selection. Biometrics 33: 703–712.CrossRefGoogle Scholar
Land, R. B. and Hill, W. G. 1975. The possible use of superovulation and embryo transfer in cattle to increase response to selection. Animal Production 21: 1–12.Google Scholar
Nicholas, F. W. and Smith, C. 1983. Increase rates of genetic change in dairy cattle by embryo transfer and splitting. Animal Production 36: 341–353.Google Scholar
Pearson, K. 1903. Mathematical contributions to the theory of evolution. XI. On the influence of natural selection on the variability and correlation of organs. Philosophical Transactions of the Royal Society London Series A 200: 1–66.Google Scholar
Quaas, R. L. and Pollak, E. J. 1980. Mixed model methodology for farm and ranch beef cattle testing programs. Journal of Animal Science 51: 1277–1287.CrossRefGoogle Scholar
Robertson, A. 1961. Inbreeding in artificial selection programmes. Genetical Research 2: 189–194.CrossRefGoogle Scholar
Robertson, A. 1977. The effect of selection on the estimation of genetic parameters. Zeitschrift für Tierzüchtung und Züchtungsbiologie 94: 131–135.CrossRefGoogle Scholar
Sales, J. and Hill, W. G. 1976. Effect of sampling errors on efficiency of selection indices. 1. Use of information from relatives for single trait improvement. Animal Production 22: 1–17.Google Scholar
Toro, M. A., Silio, L., Rodriganfz, J. and Dobao, M. T. 1988. Inbreeding and family index selection for prolificacy in pigs. Animal Production 46: 79–85.Google Scholar
Wray, N. R. and Thompson, R. 1989. Prediction of rate of inbreeding in selected populations. Genetical Research In press.Google Scholar