HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by van Kaam, J. B. C. H. M. Articles by Quaas, R. L. Search for Related Content PubMed PubMed Citation Articles by van Kaam, J. B. C. H. M. Articles by Quaas, R. L.

Bayesian reanalysis of a quantitative trait locus accounting for multiple environments by scaling in broilers¹

J. B. C. H. M. van Kaam^*,2, M. C. A. M. Bink, D. O. Maizon, J. A. M. van Arendonk and R. L. Quaas^#

^* Istituto Zooprofilattico Sperimentale della Sicilia "A. Mirri," Via G. Marinuzzi 3, 90129 Palermo, Italy; and Biometris, Wageningen-UR, P.O. Box 16, 6700 AA, Wageningen, The Netherlands; and Department S.En.Fi.Mi.Zo.-Animal Production Section, University of Palermo, Viale delle Scienze-Parco d’Orleans, 90128 Palermo, Italy; and Animal Breeding and Genetics Group, Wageningen Institute of Animal Sciences, Wageningen University, P.O. Box 338, 6700 AH, Wageningen, The Netherlands; and ^# Department of Animal Science, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY 14853

² Corresponding author: jtkaam{at}unipa.it

A Bayesian method was developed to handle QTL analyses of multiple experimental data of outbred populations with heterogeneity of variance between sexes for all random effects. The method employed a scaled reduced animal model with random polygenic and QTL allelic effects. A parsimonious model specification was applied by choosing assumptions regarding the covariance structure to limit the number of parameters to estimate. Markov chain Monte Carlo algorithms were applied to obtain marginal posterior densities. Simulation demonstrated that joint analysis of multiple environments is more powerful than separate single trait analyses of each environment. Measurements on broiler BW obtained from 2 experiments concerning growth efficiency and carcass traits were used to illustrate the method. The population consisted of 10 full-sib families from a cross between 2 broiler lines. Microsatellite genotypes were determined on generations 1 and 2, and phenotypes were collected on groups of generation 3 animals. The model included a polygenic correlation, which had a posterior mean of 0.70 in the analyses. The reanalysis agreed on the presence of a QTL in marker bracket MCW0058-LEI0071 accounting for 34% of the genetic variation in males and 24% in females in the growth efficiency experiment. In the carcass experiment, this QTL accounted for 19% of the genetic variation in males and 6% in females.

Key Words: Bayesian theory • chicken • genetic marker • Monte Carlo method • multiple environment • quantitative trait locus