Mapping QTLs with digenic epistasis under multiple environments and predicting heterosis based on QTL effects

Area of Science:

• Quantitative genetics
• Statistical genomics
• Plant breeding

Background:

• Mapping quantitative trait loci (QTLs) is crucial for understanding complex traits.
• Existing methods may not fully capture digenic epistasis or QTL by environment (QE) interactions.
• Accurate prediction of heterosis requires robust QTL analysis.

Purpose of the Study:

• To propose a mixed linear model approach for QTL mapping that incorporates digenic epistasis and QE interactions.
• To develop a method for predicting heterosis based on individual QTL effects.
• To introduce updated QTL mapping software, QTLMapper 2.0.

Main Methods:

• A mixed linear model was developed to analyze additive, dominant, digenic epistasis, and QE interaction effects.
• Monte Carlo simulations were used to validate the accuracy and unbiasedness of the proposed method.
• An immortalized F(2) (IF(2)) population was utilized for its suitability in mapping complex genetic interactions.

Main Results:

• The proposed method provides unbiased estimations for QTL positions and genetic main effects.
• QE interaction effects can be predicted without bias.
• A novel method for predicting heterosis based on individual QTL effects was established.

Conclusions:

• The developed mixed linear model effectively addresses epistasis and QE interactions in QTL mapping.
• QTLMapper 2.0 software is a valuable tool for analyzing various populations (DH, RIL, F(2), IF(2)).
• The approach facilitates improved breeding strategies through accurate genetic analysis and heterosis prediction.