Connected populations for detecting quantitative trait loci and testing for epistasis: an application in maize

Area of Science:

• Plant Genetics and Breeding
• Quantitative Genetics
• Genomic Analysis

Background:

• Traditional quantitative trait loci (QTL) detection is limited by biallelic populations, restricting genetic variability and epistasis analysis.
• Connected multiparental crosses offer a strategy to expand genetic diversity and investigate complex genetic interactions.

Purpose of the Study:

• To detect QTL for three agronomic traits in maize using connected F2 populations.
• To evaluate the impact of connected designs on QTL detection accuracy and epistasis analysis.
• To assess the contribution of allelic relationships and epistasis to QTL position consistency.

Main Methods:

• Utilized six connected F2 maize populations (150 F2:3 families each) derived from four inbred lines.
• Employed composite interval mapping (CIM) for QTL detection on individual populations and the global design.
• Analyzed QTL detection with and without accounting for population connections, including epistasis testing.

Main Results:

• Incorporating population connections significantly increased the number of detected QTL and refined QTL position estimates.
• Numerous epistatic interactions were identified, notably for grain yield QTL, increasing R2 by 9.6%.
• Connected designs enabled global allele ranking at each QTL, highlighting the interplay of allelic relationships and epistasis.

Conclusions:

• Connected multiparental crosses enhance QTL detection power and accuracy in maize.
• Epistasis plays a substantial role in trait variation and contributes to inconsistencies in QTL mapping across populations.
• This approach facilitates efficient allele stacking for marker-assisted selection to improve desirable agronomic traits.