A composite model of maize heterosis based on structural complementation and functional variants

Area of Science:

• Plant Genetics
• Agricultural Science
• Maize Breeding

Background:

• Heterosis is crucial for high maize yields but its genetic basis is not fully understood.
• Existing molecular markers provide incomplete insights into the genetic components of heterosis.

Purpose of the Study:

• To investigate the genetic mechanisms underlying heterosis in maize.
• To analyze the correlation between heterosis, combining ability, and functional genetic variants.
• To propose an advanced genomic prediction framework for maize breeding.

Main Methods:

• Utilized a North Carolina II mating design with 87 maize hybrids from 29 recombinant inbred lines and three testers.
• Analyzed correlations between grain yield, heterosis, combining ability, and heterozygous functional variant sites (HEUES-SNPs and HEUES-InDels).
• Developed a weighted multi-kernel genomic prediction framework.

Main Results:

• Heterotic group-specific and general combining ability showed the strongest correlation with heterosis (r=0.560).
• Functional HEUES markers (SNPs and InDels) correlated more strongly with heterosis than genome-wide genetic distance.
• HEUES-SNPs and HEUES-InDels exhibited similar associations with better-parent heterosis and high collinearity.

Conclusions:

• Functional genetic variants in upstream regions, exons, and splice sites are closely associated with maize heterosis.
• A novel genomic prediction framework integrating multiple marker types and functional contexts enhances parental selection efficiency.
• This study provides a theoretical basis for developing improved genomic prediction models in maize breeding.