VARIANCE DECOMPOSITION IN THE ESTIMATION OF GENETIC VARIANCE WITH SELECTED DATA

Estimation of genetic variance in populations under selection involves assumptions on base animals. Base animals are often considered unselected and it also has been proposed to treat selected base animals as fixed. The consequences of assumptions on base animals in the estimation of genetic variance in selected populations axe not fully understood. Variance decompositions are introduced for simple designs to quantify the differences between models that treat base animals in different ways. Independent contrasts were constructed and REML estimates of variance components were compared for different designs and selection rules. The method shows how selection is accounted for in a complete model and why estimation of variance components can become biased when base animals are treated as fixed.