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Estimation of genetic variation in residual variance in female and male broiler chickens

Published online by Cambridge University Press:  11 August 2009

H. A. Mulder*
Affiliation:
Animal Breeding and Genomics Centre, Animal Sciences Group, PO Box 65, 8200 AB Lelystad, The Netherlands
W. G. Hill
Affiliation:
Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JT, UK
A. Vereijken
Affiliation:
Hendrix Genetics B.V., Breeding Research and Technology Centre, Spoorstraat 49, PO Box 114, 5830 AC Boxmeer, The Netherlands
R. F. Veerkamp
Affiliation:
Animal Breeding and Genomics Centre, Animal Sciences Group, PO Box 65, 8200 AB Lelystad, The Netherlands
*
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Abstract

In breeding programs, robustness of animals and uniformity of end product can be improved by exploiting genetic variation in residual variance. Residual variance can be defined as environmental variance after accounting for all identifiable effects. The aims of this study were to estimate genetic variance in residual variance of body weight, and to estimate genetic correlations between body weight itself and its residual variance and between female and male residual variance for broilers. The data sets comprised 26 972 female and 24 407 male body weight records. Variance components were estimated with ASREML. Estimates of the heritability of residual variance were in the range 0.029 (s.e. = 0.003) to 0.047 (s.e. = 0.004). The genetic coefficients of variation were high, between 0.35 and 0.57. Heritabilities were higher in females than in males. Accounting for heterogeneous residual variance increased the heritabilities for body weight as well. Genetic correlations between body weight and its residual variance were −0.41 (s.e. = 0.032) and −0.45 (s.e. = 0.040), respectively, in females and males. The genetic correlation between female and male residual variance was 0.11 (s.e. = 0.089), indicating that female and male residual variance are different traits. Results indicate good opportunities to simultaneously increase the mean and improve uniformity of body weight of broilers by selection.

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Full Paper
Copyright
Copyright © The Animal Consortium 2009

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References

Akaike, H 1973. Information theory and an extension of the maximum likelihood principle. In Proceedings of the 2nd International Symposium on Information Theory (ed. BN Petrov and F Csaki), pp. 267281. Akademiai Kiado, Budapest, Hungary.Google Scholar
Bolet, G, Garreau, H, Joly, T, Theau-Clement, M, Falieres, J, Hurtaud, J, Bodin, L 2007. Genetic homogenisation of birth weight in rabbits: indirect selection response for uterine horn characteristics. Livestock Science 111, 2832.CrossRefGoogle Scholar
Cardin, S, Minvielle, F 1986. Selection on phenotypic variation of pupa weight in Tribolium castaneum. Canadian Journal of Genetics and Cytology 28, 856861.CrossRefGoogle Scholar
Falconer, DS, Robertson, A 1956. Selection for environmental variability of body size in mice. Zeitschrift fur Inductive Abstammungs- und Vererbungslehre 87, 385391.Google ScholarPubMed
Garreau, H, Bolet, G, Larzul, C, Robert-Granie, C, Saleil, G, SanCristobal, M, Bodin, L 2008. Results of four generations of a canalizing selection for rabbit birth weight. Livestock Science 119, 5562.CrossRefGoogle Scholar
Gilmour, AR, Gogel, BJ, Cullis, BR, Thompson, R 2006. ASREML User Guide Release 2.0. VSN International Ltd, Hemel Hempstead, UK.Google Scholar
Gutierrez, JP, Nieto, B, Piqueras, P, Ibanez, N, Salgado, C 2006. Genetic parameters for canalisation analysis of litter size and litter weight traits at birth in mice. Genetics Selection Evolution 38, 445462.CrossRefGoogle ScholarPubMed
Hill, WG, Zhang, X-S 2004. Effects of phenotypic variability of directional selection arising through genetic differences in residual variability. Genetical Research, Cambridge 83, 121132.CrossRefGoogle ScholarPubMed
Hohenboken, WD 1985. The manipulation of variation in quantitative traits: a review of possible genetic strategies. Journal of Animal Science 60, 101110.CrossRefGoogle Scholar
Ibanez-Escriche, N, Moreno, A, Nieto, B, Piqueras, P, Salgado, C, Gutierrez, JP 2008a. Genetic parameters related to environmental variability of weight traits in a selection experiment for weight gain in mice; signs of correlated canalised response. Genetics Selection Evolution 40, 279293.Google Scholar
Ibanez-Escriche, N, Varona, L, Sorensen, D, Noguera, JL 2008b. A study of heterogeneity of environmental variance for slaughter weight in pigs. Animal 2, 1926.CrossRefGoogle ScholarPubMed
Kaufman, PK, Enfield, FD, Comstock, RE 1977. Stabilizing selection for pupa weight in Tribolium castaneum. Genetics 87, 327341.CrossRefGoogle ScholarPubMed
Larzul, C, Le Roy, P, Tribout, T, Gogue, J, SanCristobal, M 2006. Canalizing selection on ultimate pH in pigs: consequences on meat quality. In Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, Communication 13-09, Belo Horizonte, Brazil.Google Scholar
Lidauer, M, Stranden, I 1999. Fast and flexible program for genetic evaluation in dairy cattle. Interbull Bulletin 20, 2025.Google Scholar
Mackay, TFC, Lyman, RF 2005. Drosophila bristles and the nature of quantitative genetic variation. Philosophical Transactions of the Royal Society B: Biological Sciences 360, 15131527.Google Scholar
Mulder, HA, Bijma, P, Hill, WG 2007. Prediction of breeding values and selection responses with genetic heterogeneity of environmental variance. Genetics 175, 18951910.Google Scholar
Mulder, HA, Bijma, P, Hill, WG 2008. Selection for uniformity in livestock by exploiting genetic heterogeneity of residual variance. Genetics Selection Evolution 40, 3759.Google ScholarPubMed
Odegard, J, Madsen, P, Gianola, D, Klemetsdal, G, Jensen, J, Heringstad, B, Korsgaard, IR 2005. A Bayesian threshold-normal mixture model for analysis of a continuous mastitis-related trait. Journal of Dairy Science 88, 26522659.Google Scholar
Rendel, JM, Sheldon, BL, Finlay, DE 1966. Selection for canalization of the scute phenotype. II. American Naturalist 100, 1331.CrossRefGoogle Scholar
Ros, M, Sorensen, D, Waagepetersen, R, Dupont-Nivet, M, SanCristobal, M, Bonnett, JC, Mallard, J 2004. Evidence for genetic control of adult weight plasticity in the snail Helix aspersa. Genetics 168, 20892097.CrossRefGoogle ScholarPubMed
Rowe, SJ, White, IMS, Avendano, S, Hill, WG 2006. Genetic heterogeneity of residual variance in broiler chickens. Genetics Selection Evolution 38, 617635.CrossRefGoogle ScholarPubMed
SanCristobal-Gaudy, M, Bodin, L, Elsen, JM, Chevalet, C 2001. Genetic components of litter size variability in sheep. Genetics Selection Evolution 33, 249271.Google Scholar
SanCristobal-Gaudy, M, Elsen, JM, Bodin, L, Chevalet, C 1998. Prediction of the response to a selection for canalisation of a continuous trait in animal breeding. Genetics Selection Evolution 30, 423451.CrossRefGoogle Scholar
Sorensen, D, Waagepetersen, R 2003. Normal linear models with genetically structured residual variance heterogeneity: a case study. Genetical Research, Cambridge 82, 207222.CrossRefGoogle ScholarPubMed
Schwarz, G 1978. Estimating the dimension of a model. Annals of Statistics 6, 461464.CrossRefGoogle Scholar
Wilks, SS 1938. The large-sample distribution of the likelihood ratio for testing composite hypotheses. Annals of Mathematical Statistics 9, 6062.CrossRefGoogle Scholar
Wolc, A, White, IMS, Avendano, S, Hill, WG 2009. Genetic variability in residual variation of body weight and conformation scores in broiler chickens. Poultry Science 88, 11561161.CrossRefGoogle ScholarPubMed