Issue |
Genet. Sel. Evol.
Volume 35, Number 5, September-October 2003
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|
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Page(s) | 469 - 487 | |
DOI | https://doi.org/10.1051/gse:2003035 |
DOI: 10.1051/gse:2003035
Bayesian inference on genetic merit under uncertain paternity
Fernando F. Cardoso and Robert J. TempelmanDepartment of Animal Science, Michigan State University, East Lansing, MI 48824, USA
(Received 3 October 2002; accepted 3 April 2003)
Abstract
A hierarchical animal model was developed for inference on genetic
merit of livestock with uncertain paternity. Fully conditional
posterior distributions for fixed and genetic effects, variance
components, sire assignments and their probabilities are derived to
facilitate a Bayesian inference strategy using MCMC methods. We
compared this model to a model based on the Henderson average
numerator relationship (ANRM) in a simulation study with 10 replicated
datasets generated for each of two traits. Trait 1 had a medium
heritability (
h2) for each of direct and maternal genetic effects
whereas Trait 2 had a high
h2 attributable only to direct
effects. The average posterior probabilities inferred on the true sire
were between 1 and 10% larger than the corresponding priors (the
inverse of the number of candidate sires in a mating pasture) for
Trait 1 and between 4 and 13% larger than the corresponding priors
for Trait 2. The predicted additive and maternal genetic effects were
very similar using both models; however, model choice criteria (Pseudo
Bayes Factor and Deviance Information Criterion) decisively favored
the proposed hierarchical model over the ANRM model.
Key words: uncertain paternity / multiple-sire / genetic merit / Bayesian inference / reduced animal model
Correspondence and reprints: Fernando F. Cardoso
e-mail: cardosof@msu.edu
© INRA, EDP Sciences 2003