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

Abstract

Abstract

Heterosis is critical to high maize (Zea mays L.) yields; however, its genetic mechanism remains poorly understood because different molecular markers reflect distinct genetic components. This study uses a North Carolina II mating design to evaluate grain yield per plant of 87 hybrids derived from 29 recombinant inbred lines and three testers from different heterotic groups across two environments. The correlations between heterosis, combining ability, and heterozygous functional variant sites located in upstream regions, exons, and splice sites (HEUES-single nucleotide polymorphism [SNPs] and HEUES-insertion and deletions [InDels]) were analyzed. Results showed that the heterotic group-specific and general combining ability had the strongest correlation with heterosis (r = 0.560, p < 0.001). Functional HEUES markers correlated more closely with heterosis than genome-wide genetic distance. HEUES-SNPs and HEUES-InDels showed similar associations (r = 0.469 and 0.455, respectively) with better-parent heterosis. The two marker types presented high collinearity (r = 0.987), indicating overlapping genetic information and indistinguishable independent genetic mechanisms. Residual analysis further confirmed no significant difference of performance between the two markers in different environments. Accordingly, a conceptual weighted multi-kernel genomic prediction framework integrating marker types, functional contexts and genetic architecture were proposed. This framework innovates the traditional single-marker method and provides a theoretical reference for developing advanced genomic prediction models to improve parental selection efficiency in maize breeding.