IXED LINEAR MODE APPROACHES FOR ANAYZING GENETIC MODELS OF COMPLEX QUANTITATIVE TRAITS

摘要

New approaches based on genera mixed linear models were presentedfor annexing complex quantitative traits in animal models, seedmodels and QTL (quantitative trait locus) mapping models. Variancesand conversances can be appropriately estimated by MINQUE (minimumnorm quadratic unbiased estimation) approaches. Random geneticeffects can be produced without bias by LUP (linear unbiasedprediction) or AUP (adjusted unbiased prediction) methods.Mixed-model based composite innerve mapping (MCIM) methods aresuitable for efficiently searching QTLs along the whole genome.Bayesian methods and Markov Chain Monte Carlo (MCMC) methods can beapplied in analyzing parameters of random effects as well as theirvariances.