A new approach to dissecting complex traits by combining quantitative trait transcript (QTT) mapping and diallel cross analysis

A promising way to uncover the genetic architectures underlying complex traits may lie in the ability to recognize the genetic variants and expression transcripts that are responsible for the traits’ inheritance. However, statistical methods capable of investigating the association between the inheritance of a quantitative trait and expression transcripts are still limited. In this study, we described a two-step approach that we developed to evaluate the contribution of expression transcripts to the inheritance of a complex trait. First, a mixed linear model approach was applied to detect significant trait-associated differentially expressed transcripts. Then, conditional analysis were used to predict the contribution of the differentially expressed genes to a target trait. Diallel cross data of cotton was used to test the application of the approach. We proposed that the detected differentially expressed transcripts with a strong impact on the target trait could be used as intermediates for screening lines to improve the traits in plant and animal breeding programs. It can benefit the discovery of the genetic mechanisms underlying complex traits.