Abstract
Behaviour of the additive finite locus model
Highlights
Genetic evaluation in livestock has traditionally been carried out using an infinitesimal genetic model, where the trait is assumed to be influenced by an infinite number of genes, each with an infinitesimally small effect
In this paper a genetic model assuming a finite number of loci affecting a quantitative trait was implemented using Gibbs sampling
The behaviour of the results when changing the number of loci and the distribution of the gene effects assumed on the model of analysis were studied using stochastic simulation
Summary
Genetic evaluation in livestock has traditionally been carried out using an infinitesimal genetic model, where the trait is assumed to be influenced by an infinite number of genes, each with an infinitesimally small effect Such a model is biologically incorrect, its use has been justified because it allows the handling of the total additive genetic effect as a normally distributed variable so that standard statistical mixed model techniques can be applied. Single genes that have a relatively large effect on quantitative traits (e.g. Booroola gene, double muscle gene, Callipyge gene) are expected to have a rapid change in allele frequency due to selection Under these circumstances, the infinitesimal model would wrongly predict the evolution of the genetic variance even when the selected trait is affected by a large number of loci with small effects [8]. The assumptions required to describe dominance with the infinitesimal model are unclear [25]
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