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Mating animals by minimising the covariance between ancestral contributions generates less inbreeding without compromising genetic gain in breeding schemes with truncation selection

Published online by Cambridge University Press:  01 October 2009

M. Henryon*
Affiliation:
Department of Genetics and Biotechnology, Faculty of Agricultural Sciences, Aarhus University, P.O. Box 50, 8830 Tjele, Denmark
A. C. Sørensen
Affiliation:
Department of Genetics and Biotechnology, Faculty of Agricultural Sciences, Aarhus University, P.O. Box 50, 8830 Tjele, Denmark
P. Berg
Affiliation:
Department of Genetics and Biotechnology, Faculty of Agricultural Sciences, Aarhus University, P.O. Box 50, 8830 Tjele, Denmark
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Abstract

We reasoned that mating animals by minimising the covariance between ancestral contributions (MCAC mating) will generate less inbreeding and at least as much genetic gain as minimum-coancestry mating in breeding schemes where the animals are truncation-selected. We tested this hypothesis by stochastic simulation and compared the mating criteria in hierarchical and factorial breeding schemes, where the animals were selected based on breeding values predicted by animal-model BLUP. Random mating was included as a reference-mating criterion. We found that MCAC mating generated 4% to 8% less inbreeding than minimum-coancestry mating in the hierarchical and factorial breeding schemes without any loss in genetic gain. Moreover, it generated upto 28% less inbreeding and about 3% more genetic gain than random mating. The benefits of MCAC mating over minimum-coancestry mating are worthwhile because they can be achieved without extra costs or practical constraints. MCAC mating merely uses pedigree information to pair the animals more appropriately and is clearly a worthy alternative to minimum-coancestry mating and probably any other mating criterion. We believe, therefore, that MCAC mating should be used in breeding schemes where pedigree information is available.

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Full Paper
Copyright
Copyright © The Animal Consortium 2009

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References

Berg, P, Nielsen, J, Sørensen, MK 2006. EVA: realized and predicted optimal genetic contributions. Proceedings of the 8th World Congress on Genetics Applied to Livestock Production. Communications No. 27-09.Google Scholar
Brisbane, JR, Gibson, JP 1994. Balancing selection response and rate of inbreeding by including genetic relationships in selection decisions. Theoretical and Applied Genetics 91, 421431.CrossRefGoogle Scholar
Caballero, A, Santiago, E, Toro, MA 1996. Systems of mating to reduce inbreeding in selected populations. Animal Science 62, 431442.CrossRefGoogle Scholar
Falconer, DS, McKay, TFC 1996. Introduction to quantitative genetics, 4th edition. Longmann, England.Google Scholar
Grundy, B, Villanueva, B, Woolliams, JA 1998. Dynamic selection procedures for constrained inbreeding and their consequences for pedigree development. Genetical Research 72, 159168.CrossRefGoogle Scholar
James, JW, McBride, G 1958. The spread of genes by natural and artificial selection in a closed poultry flock. Journal of Genetics 56, 5562.CrossRefGoogle Scholar
Lindgren, D, Matheson, AC 1986. An algorithm for increasing the genetic quality of seed from orchards by using the better clones in higher proportions. Silvae Genetica 35, 173177.Google Scholar
Madsen, P, Sørensen, P, Su, G, Damgaard, LH, Thomsen, H, Labouriau, R 2006. DMU – a package for analyzing multivariate mixed models. Proceedings of the 8th World Congress on Genetics Applied to Livestock Production. Communications No. 27-11.Google Scholar
Meuwissen, THE 1997. Maximising the response of selection with a pre-defined rate of inbreeding. Journal of Animal Science 75, 934940.CrossRefGoogle Scholar
Meuwissen, THE 2007. Operation of conservation schemes. In Utilisation and conservation of farm animals genetic resources (ed. H Oldenbroek), pp. 167193. Wageningen Academic, The Netherlands.CrossRefGoogle Scholar
Meuwissen, THE, Luo, Z 1992. Computing inbreeding coefficients in large populations. Genetics Selection Evolution 24, 305313.CrossRefGoogle Scholar
Pedersen, LD, Sørensen, AC, Henryon, M, Ansari-Mahyari, S, Berg, P 2009. ADAM: a computer program to simulate selective-breeding schemes for animals. Livestock Science 121, 343344.CrossRefGoogle Scholar
Quaas, RL 1976. Computing the diagonal elements and inverse of a large numerator relationship matrix. Biometrics 32, 949953.CrossRefGoogle Scholar
Sánchez, L, Bijma, P, Woolliams, JA 2003. Minimising inbreeding by managing genetic contributions across generations. Genetics 164, 15891595.CrossRefGoogle Scholar
Sonesson, AK, Meuwissen, THE 2000. Mating schemes for optimum contribution selection with constrained rates of inbreeding. Genetics Selection Evolution 32, 231248.CrossRefGoogle ScholarPubMed
Toro, MA, Pérez-Enciso, M 1990. Optimization of selection response under restricted inbreeding. Genetics Selection Evolution 22, 93107.CrossRefGoogle Scholar
Woolliams, JA, Thompson, R 1994. A theory of genetic contributions. Proceedings of the 5th World Congress on Genetics Applied to Livestock Production 19, 127134.Google Scholar
Woolliams, JA, Pong-Wong, R, Villanueva, B 2002. Strategic optimisation of short- and long-term gain and inbreeding in MAS and non-MAS schemes. Proceedings of the 7th World Congress on Genetics Applied to Livestock Production. Communications No. 23-02.Google Scholar
Wray, NR, Goddard, ME 1994. Increasing long-term response to selection. Genetics Selection Evolution 26, 431451.CrossRefGoogle Scholar
Wray, NR, Thompson, R 1990. Prediction of rates of inbreeding in selected populations. Genetical Research 55, 4154.CrossRefGoogle ScholarPubMed
Wright, S 1921. Systems of mating. Genetics 6, 111178.CrossRefGoogle ScholarPubMed