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This Article Free Via Open Access Full Text Full Text (PDF) All Versions of this Article: jas.2008-1586v1 87/8/2510    most recent 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 Google Scholar Articles by David, I. Articles by Robert-Granié, C. PubMed PubMed Citation Articles by David, I. Articles by Robert-Granié, C.

Product versus additive threshold models for analysis of reproduction outcomes in animal genetics¹

I. David^*,2, L. Bodin^*, D. Gianola, A. Legarra^*, E. Manfredi^* and C. Robert-Granié^*

^* Institut National de la Recherche Agronomique UR 631, Station d’Amélioration Génétique des Animaux, 31320 Castanet-Tolosan, France; and Department of Animal Sciences, University of Wisconsin, Madison 53706

² Corresponding author: Ingrid.David{at}toulouse.inra.fr

The phenotypic observation of some reproduction traits (e.g., insemination success, interval from lambing to insemination) is the result of environmental and genetic factors acting on 2 individuals: the male and female involved in a mating couple. In animal genetics, the main approach (called additive model) proposed for studying such traits assumes that the phenotype is linked to a purely additive combination, either on the observed scale for continuous traits or on some underlying scale for discrete traits, of environmental and genetic effects affecting the 2 individuals. Statistical models proposed for studying human fecundability generally consider reproduction outcomes as the product of hypothetical unobservable variables. Taking inspiration from these works, we propose a model (product threshold model) for studying a binary reproduction trait that supposes that the observed phenotype is the product of 2 unobserved phenotypes, 1 for each individual. We developed a Gibbs sampling algorithm for fitting a Bayesian product threshold model including additive genetic effects and showed by simulation that it is feasible and that it provides good estimates of the parameters. We showed that fitting an additive threshold model to data that are simulated under a product threshold model provides biased estimates, especially for individuals with high breeding values. A main advantage of the product threshold model is that, in contrast to the additive model, it provides distinct estimates of fixed effects affecting each of the 2 unobserved phenotypes.

Key Words: additive model • Gibbs sampling • product model • reproduction traits