On the use of animal models in the analysis of selection experiments

The use of an animal model in the analysis of selection experiments offers the theoretical advantage of accounting for changes occurring in the genetic parameters in the course of the experiments. Explicit estimators of realized heritability (h(r)(2)) are derived in this paper for balanced one-generation selection designs. Expressions are given for the expectations and variances of the estimators in relation to the true heritability and for the sensitivity of the estimators to the prior value of heritability. Sensitivity is generally high, except for high values of the true heritability and/or extremely large family sizes. The uncertainty on heritability may, however, be taken into account in a context of Bayesian inference, which allows a simultaneous estimation of the initial heritability and of the response. On the other hand, animal model estimators, being dependent on the genetic model assumed, may not provide adequate measures of the actual responses. They also tend to overestimate the accuracy of genetic trend evaluations, since genetic drift is not properly accounted for. Animal models, however, provide a way of evaluating the effects of selection and limited population size in long-term selection experiments, and thus permit a check on the validity of the underlying infinitesimal additive genetic model. Some examples based on published results of long-term selection experiments on mice are discussed. (C) Inra/Elsevier, Paris.