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Integrating GWAS and Transcriptome Analysis Identifies Candidate Genes for Kernel Starch Quality Traits in Maize
Wenye Rui1,2, Yimei Tian1,2, Dan Sun1,2
1Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Key Laboratory of Plant Functional Genomics of the Ministry of Education, Agriculture College of Yangzhou University, Yangzhou225009, China.
Abstract:
Maize (Zea mays L.) starch quality is a complex trait with significant implications for grain processing and industrial applications. However, the genetic basis underlying starch quality, particularly for gelatinization and thermodynamic properties, remains poorly understood. In this study, we evaluated 12 starch quality traits, including seven gelatinization characteristics, four thermodynamic traits, and kernel starch content (KSC) in a diverse panel of 335 maize inbred lines. Considerable phenotypic variation was observed for all traits. A total of 228 quantitative trait loci (QTLs) were significantly associated with 12 starch quality traits through genome-wide association studies (GWAS). By integrating a dynamic transcriptome analysis of two maize inbred lines with contrasting starch quality, we identified 60 candidate genes. One gene, waxy1, encoding a starch synthase, was found to be associated with enthalpy of gelatinization (ΔHgel) and pasting temperature (Ptemp). Six variants in waxy1 contributed to natural variation in ΔHgel and Ptemp, and a cost-effective InDel and two PARMS-based molecular markers were developed and validated in 144 maize inbred lines, enabling efficient marker-assisted selection. Our findings provide key genes and molecular markers for high-quality maize breeding with improved starch properties.