Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-10T10:58:40.407Z Has data issue: false hasContentIssue false
  • English
  • Français

Individual animal model estimates of genetic parameters for performance test traits of male and female landrace pigs tested in a commercial nucleus herd

Published online by Cambridge University Press:  02 September 2010

R. E. Crump ,
C. S. Haley ,
R. Thompson  and
J. Mercer
R. E. Crump
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS
C. S. Haley
Affiliation:
Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS
R. Thompson
Affiliation:
Institute of Cell, Animal and Population Biology, University of Edinburgh, West Mains Road, Edinburgh EH9 3JT
J. Mercer
Affiliation:
Institute of Cell, Animal and Population Biology, University of Edinburgh, West Mains Road, Edinburgh EH9 3JT
Get access

Abstract

Estimates of heritabilities, common litter of birth effects and additive maternal genetic effects were produced for ultrasonic backfat depth, average daily food intake, average daily gain and food conversion ratio of Landrace boars and gilts. Boars and gilts were performance tested under different regimes. A bivariate derivative-free restricted maximum likelihood procedure was used to estimate genetic correlations between the performance test traits as recorded in the two sexes.

Heritability estimates from the analysis including the common litter of birth effect tended to be towards the low end of the range of recently published estimates. This may reflect either population specific effects, such as effects of long-term selection, or the use of an individual animal model.

Estimates of the common litter of birth effect were around 0·05, and generally had a significant effect upon the fit of the model, while additive maternal genetic effect estimates were negligible. Therefore, it is expected that omission of maternal effects from models for evaluation by best linear unbiased prediction will not hinder genetic progress. Inclusion of common litter of birth effects would be recommended, although this result may not hold for populations given food ad libitum.

The estimates of genetic correlations between performance test traits of boars and gilts indicate that the levels of genotype-environment interaction (G × E) and genotype-sex interaction were low across most traits and data sets, with all genetic correlation estimates lying between 0·8 and 1·0. The lowest estimates of the genetic correlations, which were observed in data sets where the environments appeared to differ most, indicate that G × E interactions may be a problem in populations where males and females are subject to test regimes with greater differences than those seen here.

Keywords

animal modelsgenetic parametersgenotype environment interactionpigs
Type
Research Article
Information
Animal Science , Volume 65 , Issue 2 , October 1997 , pp. 275 - 283
Copyright
Copyright © British Society of Animal Science 1997

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

Brascamp, E. W., Merks, J. W. M. and Wilmink, J. B. M. 1985. Genotype environment interaction in pig breeding programmes: methods of estimation and relevance of the estimates. Livestock Production Science 13:135–146.CrossRefGoogle Scholar
Cameron, N. D. 1991. Problems associated with estimation of genotype with environment interaction (and their solutions). Forty-second annual meeting of the European Association of Animal Production, Berlin, Germany.Google Scholar
Cameron, N. D., Curran, M. K. and Thompson, R. 1988. Estimation of sire with feeding regime interaction in pigs. Animal Production 46: 87–95.Google Scholar
Crump, R. E., Thompson, R., Haley, C. S. and Mercer, J. 1997. Individual animal model estimates of genetic correlations between performance test and reproduction traits of Landrace pigs performance tested in a commercial nucleus herd. Animal Science 65:291–298.CrossRefGoogle Scholar
Falconer, D. S. 1952. The problem of environment and selection. American Naturalist 86:293–298.CrossRefGoogle Scholar
Graser, H.-U., Smith, S. P. and Tier, B. 1987. A derivative-free approach for estimating variance components in animal models by restricted maximum likelihood. Journal of Animal Science 64:1362–1370.CrossRefGoogle Scholar
Kennedy, B. W., Schaeffer, L. R. and Sorenson, D. A. 1988. Genetic properties of animal models. Journal of Dairy Science 71: (suppl. 2) 17–26.CrossRefGoogle Scholar
Merks, J. W. M. 1986. Genotype environment interaction in pigs. 1. Central test station. Livestock Production Science 14: 365–381.CrossRefGoogle Scholar
Meyer, K. 1989. Restricted maximum likelihood to estimate variance components for animal models with several random effects using a derivative-free algorithm. Genetics, Selection, Evolution 21:317–340.CrossRefGoogle Scholar
Ollivier, L. 1983. Dix ans d'une experience de selection individuelle sur les verrats utilises en insemination artificielle. II. Parametres genetiques estimes. Genetique, Selection, Evolution 15:99–118.CrossRefGoogle Scholar
Roberts, D. J. and Curran, M. K. 1981. A comparison of ‘on-farm’ and station testing in pigs. Animal Production 33: 291–298.Google Scholar
Smith, C. and Ross, G. J. S. 1965. Genetic parameters of British Landrace bacon pigs. Animal Production 7: 291–301.Google Scholar
Smith, S. P. and Graser, H.-U. 1986. Estimating variance components in a class of mixed models by restricted maximum likelihood. Journal of Dairy Science 69:1156–1165.CrossRefGoogle Scholar
Standal, N. 1973. Studies on breeding and selection schemes in pigs. III. The effect of parity and litter size on the "on-the-farm" results. Ada Agrkulturae Scandinavica 29: 139–144.CrossRefGoogle Scholar
Thompson, R., Crump, R. E., Juga, J. and Visscher, P. 1995. Estimating variances and covariances for bivariate animal models using scaling and transformation. Genetics, Selection, Evolution 27: 33–42.CrossRefGoogle Scholar
Van Diepen, T. A. and Kennedy, B. W. 1989. Genetic correlations between test station and on-farm performance for growth rate and backfat in pigs. Journal of Animal Science 67:1425–1431.CrossRefGoogle ScholarPubMed
Vries, A. G. de and Sorenson, D. A. 1990. Optimization of present pig breeding programmes. Proceedings of the fourth world congress on genetics applied to livestock production, vol. XV, pp. 395–404.Google Scholar
Webb, A. J. and Curran, M. K. 1986. Selection regime by production system interaction in pig improvement: a review of possible causes and solutions. Livestock Production Science 14: 41–54.CrossRefGoogle Scholar
Werf, J. H. J. van der and de Boer, I. J. M. 1990. Estimation of additive genetic variance when base populations are selected. Journal of Animal Science 68: 3124–3132.CrossRefGoogle ScholarPubMed
Willeke, H. and Richter, L. 1979. The effect of parity and litter size on the "on-the-farm" performance tested gilts. Zeitschrift fur Tierziichtung und Zuchtungsbiologie 96: 38–43.CrossRefGoogle Scholar
Willham, R. L. 1963. The covariance between relatives for characters composed of components contributed by related individuals. Biometrics 19:18–27.CrossRefGoogle Scholar