Selection for uniformity in livestock by exploiting genetic heterogeneity of environmental variance

H.A. Mulder, P. Bijma, W.G. Hill

Research output: Contribution to journalArticleAcademicpeer-review

67 Citations (Scopus)

Abstract

In some situations, it is worthwhile to change not only the mean, but also the variability of traits by selection. Genetic variation in residual variance may be utilised to improve uniformity in livestock populations by selection. The objective was to investigate the effects of genetic parameters, breeding goal, number of progeny per sire and breeding scheme on selection responses in mean and variance when applying index selection. Genetic parameters were obtained from the literature. Economic values for the mean and variance were derived for some standard non-linear profit equations, e.g. for traits with an intermediate optimum. The economic value of variance was in most situations negative, indicating that selection for reduced variance increases profit. Predicted responses in residual variance after one generation of selection were large, in some cases when the number of progeny per sire was at least 50, by more than 10% of the current residual variance. Progeny testing schemes were more efficient than sib-testing schemes in decreasing residual variance. With optimum traits, selection pressure shifts gradually from the mean to the variance when approaching the optimum. Genetic improvement of uniformity is particularly interesting for traits where the current population mean is near an intermediate optimum.
Original languageEnglish
Pages (from-to)37-59
JournalGenetics, Selection, Evolution
Volume40
Issue number1
DOIs
Publication statusPublished - 2008

Keywords

  • economic values
  • breeding values
  • environment interaction
  • tribolium-castaneum
  • order statistics
  • nonlinear profit
  • milk-production
  • meat quality
  • pupa weight
  • traits

Fingerprint

Dive into the research topics of 'Selection for uniformity in livestock by exploiting genetic heterogeneity of environmental variance'. Together they form a unique fingerprint.

Cite this