Modeling QTL-by-environment interactions for multi-parent populations

Area of Science:

• Quantitative genetics
• Plant and animal breeding
• Statistical genomics

Background:

• Multi-parent populations (MPPs) offer genetic diversity and controlled structures for genetic studies.
• Existing quantitative trait loci (QTL) mapping methods primarily focus on single environments, neglecting QTL-by-environment interactions (QEIs).
• There is a need for robust methods to analyze QTLs in multi-environment trials (METs) and model QEIs.

Purpose of the Study:

• To develop and present mixed-model approaches for detecting and modeling consistent versus environment-dependent QTLs (QEIs) in MPPs.
• To provide a flexible framework applicable to various MPP designs and MET data.
• To improve the accuracy and scope of QTL mapping in complex breeding programs.

Main Methods:

• Utilized mixed models with normally distributed QTL effects, incorporating variances for consistency and environment/family dependence.
• Employed identity-by-descent (IBD) probabilities derived from parental origins in design matrices.
• Integrated polygenic effects to account for background genetic variation.

Main Results:

• Successfully detected and modeled both consistent and environment-dependent QTLs across diverse MPP datasets (diallel, NAM, MAGIC) from METs.
• Demonstrated the method's ability to handle complex genetic architectures and environmental influences.
• Achieved favorable comparisons with existing, specialized QTL mapping methods.

Conclusions:

• The proposed mixed-model approach offers a powerful and versatile tool for QTL and QEI analysis in MPPs under MET conditions.
• This method enhances the understanding of genotype-by-environment interactions, crucial for developing robust crop varieties and livestock.
• The approach is broadly applicable and provides a significant advancement over single-environment QTL mapping.