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Optimum designs for breeding programmes under mass selection with an application in fish breeding

Published online by Cambridge University Press:  02 September 2010

B. Villanueva
Affiliation:
Scottish Agricultural College, West Mains Road, Edinburgh EH9 3JG
J. A. Woolliams
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS
B. Gjerde
Affiliation:
AKVAFORSK, PO Box 5010, N-1432 Ås, Norway
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Abstract

A procedure for maximizing genetic gain (after a number of generations of selection) for a given rate of inbreeding or for a given coefficient of variation of response is presented. An infinitesimal genetic model is assumed. Mass selection is practised for a number of discrete generations. With constraints on inbreeding, expected rates of genetic progress (ΔG) are combined with expeced rates of inbreeding (ΔF) in a linear objective function (Ω = ΔG - μΔF). In addition, an expression to approximate the rate of gain at any generation accounting for changes in genetic parameters due to linkage disequilibrium and due to inbreeding is derived. Predicted gain is in general within 5% of that obtained from simulation. Thus, both ΔG and ΔF are obtained from simple analytical formulae. An equivalent function is used when the coefficient of variation of response (CV) is the parameter restricted (Ω = ΔG -μCV). Maximization of the objective function Ω for appropriate values of μ gives the optimum number of sires and dams selected when specific constraints on the level of inbreeding or the coefficient of variation of response are imposed. The method is applied to a practical situation in fish breeding. Optimum mating ratios and optimum numbers of sires selected are obtained for different scored population sizes and heritabilities. Results obtained with this procedure agree very well with results from simulation studies. The optimum number of sires increases with the size of the scheme and with more severe restrictions on risk. In the schemes considered, the optimum mating ratio is equal to 2 unless the constraint on the rate of inbreeding is severe, the size of the scheme is small and the heritability is low. In these situations the optimum mating ratio is equal to 1. The procedure is general in terms of generations of selection considered and in terms of parameters to be constrained. A large amount of computer processor unit time is saved with this method in comparison with simulation procedures.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1996

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References

Bentsen, H. B. and Gjerde, B. 1994. Design of fish breeding programs. Proceedings of the fifth world congress on applied to livestock production, Guelph, vol. 19, pp. 353359.Google Scholar
Brisbane, J. R. and Gibson, J. P. 1994. Balancing selection response and rate of inbreeding by including genetic relationships in selection decisions. Proceedings of the fifth world congress on genetics applied to livestock production, Guelph, vol. 19, pp. 135138.Google Scholar
Bulmer, M. G. 1971. The effect of selection on genetic variability. American Naturalist. 105: 201211.CrossRefGoogle Scholar
Caballero, A., Santiago, E. and Toro, M. 1996a. Systems of mating to reduce inbreeding in selected populations. Animal Science 62: 431442.CrossRefGoogle Scholar
Caballero, A., Wei, M. and Hill, W. G. 1996b. Survival rates of mutant genes under artificial selection using individual and family information. Journal of Genetics In press.Google Scholar
Gjerde, B., Gjoen, H. M. and Villanueva, B. 1996. Optimum designs for fish breeding programmes with constrained inbreeding. I. Mass selection for a normally distributed trait. Livestock Production Science In press.Google Scholar
Goddard, M. E. 1987. Policy of selecting bulls to breed bulls. Animal Production. 44: 2938.Google Scholar
Gomez-Raya, L. and Burnside, E. B. 1990. The effect of repeated cycles of selection on genetic variance, heritability and response. Theoretical and Applied Genetics. 79: 568574.CrossRefGoogle ScholarPubMed
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: 465468.Google Scholar
Hill, W. G. 1976. Order statistics of correlated variables and implications in genetic selection programmes. Biometrics. 32: 889902.CrossRefGoogle ScholarPubMed
Jodar, B. and Lopez-Fanjul, C. 1977. Optimum proportions selected with unequal sex numbers. Theoretical and Applied Genetics. 50: 5761.CrossRefGoogle ScholarPubMed
Meuwissen, T. H. E. and Luo, Z. 1992. Computing inbreeding coefficients in large populations. Genetics Selection Evolution. 24: 305313.CrossRefGoogle Scholar
Meuwissen, T. H. E. and Woolliams, J. A. 1994a. Maximising genetic response in breeding schemes of dairy cattle with constraints on variance of response. Journal of Dairy Science. 77: 19051916.CrossRefGoogle Scholar
Meuwissen, T. H. E. and Woolliams, J. A. 1994b. Response versus risk in breeding schemes. Proceedings of thefifth congress on genetics applied to livestock production, 18, pp. 236243.Google Scholar
Meuwissen, T. H. E. and Woolliams, J. A. 1994c. Effective sizes of livestock populations to prevent a decline in fitness. Theoretical and Applied Genetics 89: 10191026.CrossRefGoogle ScholarPubMed
Nicholas, F. W. 1989. Incorporation of new reproductive technology in genetic improvement programmes. In Evolution and animal breeding (ed. W., G. and MacKay, F. C.), pp. 203209. CAB International, Wallingford.Google Scholar
Press, W. H., Teukolsky, S. A., Vetterling, W. T. and Flannery, B. P. 1992. Numerical recipes in FORTRAN: the art scentific computing. Second edition, pp. 390395. Cambridge University Press.Google Scholar
Santiago, E. and Caballero, A. 1995. Effective size of populations under selection. Genetics. 139: 10131030.CrossRefGoogle ScholarPubMed
Stam, P. 1980. The distribution of the fraction of the genome identical by descendant in finite random mating populations. Genetical Research. 35: 131155.CrossRefGoogle Scholar
Toro, M. and Nieto, B. 1984. A simple method for increasing the response to artificial selection. Genetical Research. 44: 347349.CrossRefGoogle ScholarPubMed
Toro, M. and Perez-Enciso, M. 1990. Optimization of selection response under restricted inbreeding. Genetics Selection Evolution. 22: 93107.CrossRefGoogle Scholar
Verrier, E., Colleau, J. J. and Foulley, J. L. 1990. Predicting cumulated response to directional selection in finite panmictic populations. Theoretical and Applied Genetics 78: 833840.CrossRefGoogle Scholar
Verrier, E., Colleau, J. J. and Foulley, J. L. 1993. Long-term effects of selection based on animal model BLUP in a finite population. Theoretical and Applied Genetics. 87: 446454.CrossRefGoogle Scholar
Villanueva, B. and Kennedy, B. W. 1990. Effect of selection on genetic parameters of correlated traits. Theoretical and Applied Genetics. 80: 746752.CrossRefGoogle ScholarPubMed
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: 517535.CrossRefGoogle Scholar
Villanueva, B., Wray, N. R. and Thompson. R. 1993. Prediction of asymptotic rates of response from selection on multiple traits using univariate and multivariate best linear unbiased predictors. Animal Production. 57: 113.Google Scholar
Woolliams, J. A. 1989. Modifications to MOET nucleus breeding schemes to improve rates of genetic progress and decrease rates of inbreeding in dairy cattle. Animal Production. 49: 114.Google Scholar
Woolliams, J. A. and Thompson, R. 1994. A theory of genetic contributions. Proceedings of the fifth world congress genetics applied to livestock production, Guelph, vol. 19, pp. 134.Google Scholar
Woolliams, J. A., Wray, N. R. and Thompson, R. 1993. Prediction of long-term contributions and inbreeding in populations undergoing mass selection. Genetical Research. 62: 231242.CrossRefGoogle Scholar
Wray, N. R. and Goddard, M. E. 1994. Increasing long term response to selection. Genetics Selection Evolution. 26: 431451.CrossRefGoogle Scholar
Wray, N. R. and Hill, W. G. 1989. Asymptotic rates of response from index selection. Animal Production. 49: 217227.Google Scholar
Wray, N. R., Woolliams, J. A. and Thompson, R. 1994. Prediction of rates of inbreeding in populations undergoing index selection. Theoretical and Applied Genetics. 87: 878892.CrossRefGoogle ScholarPubMed