Molecular breeding approaches for the improvement of oil content and fatty acid composition in exotic-derived maize germplasm

Abstract

Molecular breeding strategies such as genome-wide association studies (GWAS) and genomic prediction have revolutionized crop improvement by enhancing selection accuracy and genetic gains. Through a comprehensive evaluation of a large set of maize lines from Germplasm Enhancement of Maize (BGEM) and their testcross hybrids, we aimed to characterize the genetic basis of oil content and fatty acid composition and predict superior hybrids and breeding populations. We evaluated 241 BGEM lines and 187 testcross hybrids derived from exotic maize landraces crossed with elite lines (PHB47 and PHZ51), across multiple environments, for oil content and 10 fatty acid traits using GWAS and genomic prediction with GBLUP and simulated RILs. Our study revealed wide phenotypic variation among BGEM lines and testcrosses for tested traits, with promising genotype mean values. Leveraging GWAS, we identified significant genomic regions associated with oil content and fatty acids, unveiling useful candidate genes. Incorporating both additive and nonadditive genomic prediction models did not enhance the predictive ability. Furthermore, our predictive modeling facilitated the identification of breeding populations with increased oil-related traits compared to the original BGEM lines. These findings highlight how BGEM germplasm can be more effectively utilized through molecular breeding approaches to enhance oil-related traits in maize.