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Partition of the genetic trend to validate multiple selection decisions

Published online by Cambridge University Press:  13 May 2008

L. A. García-Cortés ,
J. C. Martínez-Ávila  and
M. A. Toro
L. A. García-Cortés*
Affiliation:
Departamento de Mejora Genética, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Ctra de La Coruña Km 7.5, 28040, Madrid, Spain
J. C. Martínez-Ávila
Affiliation:
Departamento de Mejora Genética, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Ctra de La Coruña Km 7.5, 28040, Madrid, Spain
M. A. Toro
Affiliation:
Departamento de Mejora Genética, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Ctra de La Coruña Km 7.5, 28040, Madrid, Spain
*
E-mail: [email protected]
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Abstract

In this note, a procedure to partition the genetic trend of a selected population is presented. Each part of the genetic gain accounts for the Mendelian sampling terms of different groups of animals, which can be sometimes assigned to different selection policies. The method is based on a simple transformation of the predicted breeding values. The procedure was illustrated with two simulated examples. In the first example, the genetic trend is partitioned into two pieces, one coming from the selection on sires and the other coming from the selection on dams. The second example shows how the impact of an artificial insemination center in the genetic gain of the whole population can be evaluated.

Keywords

selection responsegenetic trendbest linear unbiased predictionnumerator relationship matrix
Type
Full Paper
Information
animal , Volume 2 , Issue 6 , June 2008 , pp. 821 - 824
Copyright
Copyright © The Animal Consortium 2008

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References

Blair, HT, Pollak, EJ 1984. Estimation of genetic trend in a selected population with and without the use of a control population. Journal of Animal Science 58, 878–886.CrossRefGoogle Scholar
Burnside, EB, Jansen, GB, Civati, G, Dadati, E 1992. Observed and theoretical genetic trends in a large dairy population under intensive selection. Journal of Dairy Science 75, 2242–2253.CrossRefGoogle Scholar
Henderson CR 1973. Sire evaluation and genetic trends. Proceedings of the Animal Breeding and Genetics Symposium in honor of Dr. Jay L. Lush, ASAS and ADSA, Champaign, IL, USA, pp. 10–41.CrossRefGoogle Scholar
Im, S, Fernando, RL, Gianola, D 1989. Likelihood inferences in animal breeding under selection: a missing-data theory viewpoint. Genetics Selection Evolution 21, 399–414.CrossRefGoogle Scholar
Quaas, RL 1976. Computing the diagonal elements and inverse of a large numerator relationship matrix. Biometrics 32, 949–953.CrossRefGoogle Scholar
Sorensen, DA, Kennedy, BW 1984. Estimation of response to selection using least-squares and mixed model methodology. Journal of Animal Science 58, 1097–1106.CrossRefGoogle Scholar
Sorensen, DA, Wang, CS, Jensen, J, Gianola, D 1994. Bayesian analysis of genetic change due to selection using Gibbs sampling. Genetics Selection Evolution 26, 333–360.CrossRefGoogle Scholar
Thompson, R 1986. Estimation of realized heritability in a selected population using mixed-model methods. Genetics Selection Evolution 18, 475–483.CrossRefGoogle Scholar
Van Tassell, CP, Van Vleck, LD 1990. Estimates of genetic selection differentials and generation intervals for four paths of selection. Journal of Dairy Science 74, 1078–1086.CrossRefGoogle Scholar
Woolliams, JA, Bijma, P, Villanueva, B 1999. Expected genetic contributions and their impact on gene flow and genetic gain. Genetics 153, 1009–1020.CrossRefGoogle ScholarPubMed