Mixed linear model approaches in mapping QTLs with epistatic effects by a simulation study

Abstract

AbstractEpistasis refers to the phenotypic effects of interactions between alleles of different loci. Statistical detection of such interactions remains to be the subject of presented studies. A method based on mixed linear model was developed for mapping QTLs with digenic epistasis. Reliable estimates of QTL additive and epistasis effects can be obtained by the maximum-likelihood estimate methods. Likelihood ratio and t statistics were combined for testing hypotheses about QTL effects (additive and epistasis effects). Monte Carlo simulations were conducted for evaluating the unbiasedness, accuracy and power for parameter estimation in QTL mapping. The results indicated that the mixed-model approaches could provide unbiased estimates for effects of QTLs. Additionally, the mixed-model approaches also showed high accuracy in mapping QTLs with epistasis effects. The information obtained in this study will be useful for manipulating the QTLs for plant breeding by marker assisted selection.