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Poultry Science, Vol 83, Issue 12, 1932-1939
Copyright © 2004 by Poultry Science Association


Articles

Bayesian inference on major loci in related multigeneration selection lines of laying hens

C Hagger, LL Janss, HN Kadarmideen, and G Stranzinger

Breeding Biology Group, Institute of Animal Science, Swiss Federal Institute of Technology, ETH-Zentrum, CH-8092 Zurich, Switzerland. hagger@inw.agrl.ethz.ch

A mixed inheritance model, postulating a polygenic effect and differences between the 3 genotypes of a biallelic locus, was fitted separately to the data of 2 multigeneration selection lines and a control evolving from a common base population. Inferences about the model were drawn from the application of the Gibbs sampler. Body weight at 20 and 40 wk (BW20, BW40) and average egg weight to 40 wk (EW40) were included in the analyses. Significance of differences between posterior means of parameters was established by comparing their 95% highest probability density regions. Significant (P < 0.05) additive and dominance effects due to the genotypes at the major locus were found for all traits. The allele causing a lower trait value was the (partial) dominant one in all traits, leading to a negative dominance effect. The additive variance due to the major locus was also significant, i.e., greater than zero (P < 0.05) in all traits, whereas the dominance variance was only important for EW40. With the exception of the residual variances of one selection and the control line, no (P > 0.05) differences of posterior means of any parameter could be observed between lines. No significant genotypic or polygenic selection response was found for BW40. On the contrary, both genetic responses were found significant for EW40 in the selected lines, but not in the control. No differences (P > 0.05) between lines could be observed for the derived frequencies of the allele causing the higher trait value and the frequencies of one homozygote and the heterozygote genotypes at the major locus. The detection of a major locus with relatively modest effect confirmed that this type of analysis with data from selected lines was indeed powerful.


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