QTLxQTLxQTL Interaction Effects for Total Phenolic Content of Wheat Mapping Population of CSDH Lines under Drought Stress by Weighted Multiple Linear Regression

This paper proposes the use of weighted multiple linear regression to estimate the triple3interaction (additivexadditivexadditive) of quantitative trait loci (QTLs) effects. The use of unweighted regression yielded an improvement (in absolute value) in the QTLxQTLxQTL interaction effects compared to assessment based on phenotypes alone in three cases (severe drought in 2010, control in 2012 and severe drought in 2012). In contrast, weighted regression yielded an improvement (in absolute value) in the evaluation of the aaa(gw) parameter compared to aaa(p) in five cases, with the exception of severe drought in 2012. The results show that by using weighted regression on marker observations, the obtained estimates are closer to the ones obtained by the phenotypic method. The coefficients of determination for the weighted regression model were significantly higher than for the unweighted regression and ranged from 46.2% (control in 2010) to 95.0% (control in 2011). Considering this, it is clear that a three-way interaction had a significant effect on the expression of quantitative traits.

Automated summary

This paper suggests using weighted multiple linear regression to estimate the triple interaction of quantitative trait loci (QTLs) effects. The results showed that weighted regression improved the evaluation of the aaa(gw) parameter compared to aaa(p) in most cases, while unweighted regression improved the QTLxQTLxQTL interaction effects. The coefficients of determination for the weighted regression model were significantly higher, indicating the significant effect of the three-way interaction on quantitative traits expression.