Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-19T22:17:43.596Z Has data issue: false hasContentIssue false

Estimates of parental-dominance and full-sib permanent environment variances in laying hens

Published online by Cambridge University Press:  18 August 2016

I. Misztal
Affiliation:
Animal and Dairy Science Department, University of Georgia, Athens, GA 30605, USA
B. Besbes
Affiliation:
Hubbard-ISA, BP 27, 35220 Châteaubourg, France
Get access

Abstract

Estimates of variance components for five egg traits on 26265 laying hens were obtained by restricted maximum likelihood (REML) using several models. In the DOMFS model, the effects included hatch group, additive genetic, full-sib, parental dominance and inbreeding depression. In the DOM model, the full-sib effect was eliminated. In the FS model, the parental dominance effect was eliminated. In the ADD model, both the full-sib and the dominance effects were eliminated. In the DOMFS model, the estimates of the full-sib variance were generally higher for egg production traits and lower for egg characteristics than those of the parental dominance variance. However, this model has partially failed in separating these two components. When the full-sib effect was removed from the model, almost all of its estimated variance moved to the estimated parental dominance variance. When the parental dominance effect was removed from the model, almost all of its estimated variance moved to the estimated full-sib variance. The estimates obtained with REML and the DOM model were compared with those obtained by method R and tilde-hat methodologies. The d2 (ratio of dominance variance to total variance) differed by up to 86% for method R and up to 225% for tilde-hat. The h2 differed by up to 26 and 28%, respectively. For data sets that are too large to be analysed with REML, method R is a feasible alternative. A model for estimation of dominance variance should also include the full-sib or a similar effect, provided the data set is large. Similarly, to analyse egg production traits, the model should include at least the full-sib effect.

Type
Research Article
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.)

References

Bernon, D. E. and Chambers, J. R. 1985. Maternal and sex-linked genetic effects in broiler parent stocks. Poultry Science 64: 2938.Google Scholar
Besbes, B. and Gibson, J. P. 1999. Genetic variation of egg production traits in purebred and crossbred laying hens. Animal Science 68: 433439.Google Scholar
Brade, W. and Groeneveld, E. 1996. Importance of special combining ability in dairy breeding. Proceedings of the 47th annual meeting of the European Association for Animal Production, Lillehammer, Norway, p. 13.Google Scholar
Cantet, R. J. C. and Birchmeier, A. N. 1998. The effects of sampling selected data on method R estimates of h2. Proceedings of the sixth world congress on genetics applied to livestock production, Armidale, NSW, Australia, vol. 25, pp. 529532.Google Scholar
Chang, H. A. 1988. Studies on estimation of genetic variances under non-additive gene action. >Ph.D. dissertation, University of Illinois, Urbana, USA.Ph.D.+dissertation,+University+of+Illinois,+Urbana,+USA.>Google Scholar
Culbertson, M. S., Mabry, J. W., Misztal, I. and Bertrand, J. K. 1997. Effects of inbreeding and outbreeding in purebred Hampshire and Duroc swine. Professional Animal Scientist 13: 194197.Google Scholar
Dempster, A. P., Laird, N. M. and Rubin, D. B. 1977. Maximum likelihood from incomplete data via the EM algorithm. Journal of Royal Statistics Society B 39: 138.Google Scholar
Fairfull, R. W. 1990. Heterosis. In Poultry breeding and genetics (ed. Crawford, R. D.), pp. 913933. Elsevier, Amsterdam.Google Scholar
Fairfull, R. W. and Gowe, R. S. 1986. Use of breed resources for poultry egg and meat production. Proceedings of the third world congress on genetics applied to livestock production, Lincoln, vol. X, pp. 242256.Google Scholar
Fairfull, R. W., Gowe, R. S. and Nagai, J. 1987. Dominance and epistasis in heterosis of White Leghorn strain crosses. Canadian Journal of Animal Science 67: 663680.Google Scholar
Falconer, D. S. 1981. Introduction to quantitative genetics, second edition. Longman, New York.Google Scholar
Gengler, N., Misztal, I., Bertrand, J. K. and Culbertson, M. S. 1998. Estimation of dominance variance for post weaning gain in the US Limousin population. Journal of Animal Science 76: 25152520.Google Scholar
Henderson, C. R. 1989. Prediction of merits of potential matings from sire-maternal grandsire models with nonadditive genetic effects. Journal of Dairy Science 72: 25922605.CrossRefGoogle Scholar
Hill, G. H. 1999. Advances in quantitative genetics theory. Proceedings of the meeting ‘From Jay Lush to genomics: visions for animal breeding and genetics’, pp. 3546. Iowa State University, Ames, IA.Google Scholar
Höeschele, I. and VanRaden, P. M. 1991. Rapid inversion of dominance relationship matrices for noninbred populations by including sire by dam subclass effects. Journal of Dairy Science 74: 557569.Google Scholar
Misztal, I. 1997. Estimation of variance components with large-scale dominance models. Journal of Dairy Science 80: 965974.Google Scholar
Misztal, I. 1998. REMLF90 manual. Web site at http://num.ads.uga.edu/blupf90. Google Scholar
Misztal, I., Fernando, R. L., Grossman, M., Lawlor, T. J. and Lukaszewicz, M. 1995. Dominance and epistatic effects in genetic evaluation of farm animals. Animal Science Papers and Reports 13: 251266.Google Scholar
Reverter, A., Golden, B. L., Bourdon, R. M. and Brinks, J. S. 1994. Method R variance components procedure: application on the simple breeding value model. Journal of Animal Science 72: 22472253.Google Scholar
Rye, M. and Mao, I. L. 1998. Nonadditive genetic effects and inbreeding depression for body weight in Atlantic salmon (Salmo salar L.). Livestock Production Science 57: 1522.Google Scholar
Sheridan, A. K. and Randall, M. C. 1977. Heterosis for egg production in White Leghorn Australorp crosses. British Poultry Science 18: 6977.Google Scholar
VanRaden, P. M. and Jung, Y. C. 1988. A general purpose approximation to restricted maximum likelihood: the tilde-hat approach. Journal of Dairy Science 71: 187194.Google Scholar
VanRaden, P. M., Lawlor, T. J., Short, T. H. and Höschele, I. 1992. Use of reproductive technology to estimate variances and predict effects of gene interactions. Journal of Dairy Science 75: 28922901.Google Scholar
Wei, M. and Werf, J. H. J. van der. 1993. Animal model estimation of additive and dominance variances in egg production traits of poultry. Journal of Animal Science 71: 5765.Google Scholar