Simulation analysis to test the influence of model adequacy and data structure on the estimation of genetic parameters for traits with direct and maternal effects

Simulations were used to study the influence of model adequacy and data str ucture on the estimation of genetic parameters for traits governed by direc t and maternal effects. To test model adequacy, several data sets were simu lated according to different underlying genetic assumptions and analysed by comparing the correct and incorrect models. Results showed that omission o f one of the random effects leads to an incorrect decomposition of the othe r components. If maternal genetic effects exist but are neglected, direct h eritability is overestimated, and sometimes more than double. The bias depe nds on the value of the genetic correlation between direct and maternal eff ects. To study the influence of data structure on the estimation of genetic parameters, several populations were simulated, with different degrees of known paternity and different levels of genetic connectedness between flock s. Results showed that the lack of connectedness affects estimates when flo cks have different genetic means because no distinction can be made between genetic and environmental differences between flocks. In this case, direct and maternal heritabilities are under-estimated, whereas maternal environm ental effects are overestimated. The insufficiency of pedigree leads to bia sed estimates of genetic parameters.