Hostname: page-component-7dd5485656-7jgsp Total loading time: 0 Render date: 2025-10-29T18:35:39.921Z Has data issue: false hasContentIssue false
  • English
  • Français

Dynamic selection for maximizing response with constrained inbreeding in schemes with overlapping generations

Published online by Cambridge University Press:  18 August 2016

B. Grundy ,
B. Villanueva  and
J. A. Woolliams
B. Grundy
Affiliation:
Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG
B. Villanueva
Affiliation:
Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG
J. A. Woolliams
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS
Get access

Abstract

A dynamic selection algorithm for maximizing annual genetic response while constraining the rate of inbreeding per generation in populations with overlapping generations is presented. The procedure gives the optimum number of individuals to be selected and the progeny they each produce. The solution to the problem was obtained by using BLUP estimated breeding values, the augmented numerator relationship matrix and lifetime breeding profiles. The procedure was able to constrain the rate of inbreeding per generation to a predefined level across generations of selection by considering all gene flow pathways. The optimization procedure represents an improvement on standard truncation BLUP selection, as it yielded substantially more genetic response (up to 35%) at the same rate of inbreeding.

Keywords

best linear unbiased predictionbreeding programmesinbreeding

Information

Type
Breeding and genetics
Information
Animal Science , Volume 70 , Issue 3 , June 2000 , pp. 373 - 382
Copyright
Copyright © British Society of Animal Science 2000

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.)

Article purchase

Temporarily unavailable

References

Bijma, P. and Woolliams, J. A. 1999. Prediction of genetic contributions and generation intervals in populations with overlapping generations under selection. Genetics 151: 1197–1210.Google Scholar
Brisbane, J. R. and Gibson, J. P. 1995. Balancing selection response and rate of inbreeding by including genetic relationships in selection decisions. Theoretical and Applied Genetics 91: 421–431.CrossRefGoogle ScholarPubMed
Bulmer, M. G. 1971. The effect of selection on genetic variability. The American Naturalist 105: 201–211.Google Scholar
Grundy, B., Caballero, A., Santiago, E. and Hill, W. G. 1994. A note on using biased parameter values and non-random mating to reduce rates of inbreeding in selection programmes. Animal Production 59: 465–468.Google Scholar
Grundy, B., Villanueva, B. and Woolliams, J. A. 1997. Maximizing response with a predefined rate of inbreeding for overlapping generation structure. Proceedings of the British Society of Animal Science, 1997, p. 27.Google Scholar
Grundy, B., Villanueva, B. and Woolliams, J. A. 1998. Dynamic selection procedures for constrained inbreeding and their consequences for pedigree development. Genetical Research, Cambridge 72: 159–168.Google Scholar
Hill, W. G. 1974. Prediction and evaluation of response to selection with overlapping generations. Animal Production 18: 117–139.Google Scholar
Luo, Z. W., Woolliams, J. A. and Thompson, R. 1995. Controlling inbreeding in dairy MOET nucleus schemes. Animal Science 60: 379–387.CrossRefGoogle Scholar
Meuwissen, T. H. E. 1997. Maximizing the response of selection with a predefined rate of inbreeding. Journal of Animal Science 75: 934–940.Google Scholar
Meuwissen, T.H.E. and Sonesson, A.K. 1998. Maximizing the response of selection with a predefined rate of inbreeding: overlapping generations. Journal of Animal Science 76: 2575–2583.CrossRefGoogle ScholarPubMed
Meuwissen, T. H. E. and Woolliams, J. A. 1994. Maximizing genetic response in breeding schemes of dairy cattle with constraints on variance of response. Journal of Dairy Science 77: 1905–1916.Google Scholar
Press, W. H., Teukolsky, S. A., Vetterling, W. T. and Flannery, B. P. 1992. Numerical recipes in FORTRAN: the art of scientific computing, second edition. Cambridge University Press.Google Scholar
Sonesson, A. K., Grundy, B., Woolliams, J. A. and Meuwissen, T. H. E. 2000. Selection with control of inbreeding in populations with overlapping generations: a comparison of methods. Animal Science 70: 1–8.CrossRefGoogle Scholar
Thompson, R. 1977. The estimation of heritability with unbalanced data. II. Data available on more than two generations. Biometrics 33: 497–504.CrossRefGoogle Scholar
Villanueva, B., Woolliams, J. A. and Simm, G. 1994. Strategies for controlling rates of inbreeding in MOET nucleus schemes for beef cattle. Genetics, Selection, Evolution 26: 517–535.Google Scholar
Woolliams, J. A. and Mäntysaari, E. A. 1995. Genetic contributions of Finnish Ayrshire bulls over four generations. Animal Production 61: 177–187.Google Scholar
Woolliams, J. A. and Thompson, R. 1994. A theory of genetic contributions. Proceedings of the 5th world congress on genetics applied to livestock production, Guelph, vol. 19, pp. 127–134.Google Scholar
Woolliams, J. A., Bijma, P. and Villanueva, B. 1999. Expected genetic contributions and their impact on gene flow and genetic gain. Genetics 153: 1009–1020.CrossRefGoogle ScholarPubMed
Wray, N. R. and Goddard, M. E. 1994a. Increasing long-term response to selection. Genetics, Selection, Evolution 26: 431–451.Google Scholar
Wray, N. R. and Goddard, M. E. 1994b. MOET breeding schemes for wool sheep. 1. Design alternatives. Animal Production 59: 71–86.Google Scholar