ArticleBMC plant biology2026
Integrating GWAS and gene expression to decipher genetic components of pericarp thickness and soluble sugars in sweet corn.
Article in BMC plant biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundGrain quality in sweet corn (Zea mays L.) is primarily determined by pericarp thickness and soluble sugar composition, which influence consumer preference and processing suitability. Despite their importance, the genetic basis of these traits remains insufficiently understood. Elucidating the underlying genetic architecture is essential for developing sweet corn varieties with improved kernel texture and sweetness.
resultsA panel of 240 sweet corn inbred lines was evaluated across two seasons in Guangzhou, China, using an alpha-lattice design with two replications to enhance phenotypic precision. Phenotypic data for pericarp thickness and sugar-related traits were adjusted using best linear unbiased predictions (BLUPs), and genotyping was performed with a 60 K SNP array. Genome-wide association study (GWAS) identified 174 loci significantly associated with the target traits, of which 84 were consistently detected across both seasons. Candidate genes within these loci were enriched in biological pathways related to cell wall biosynthesis and sugar metabolism. Notable gene families included cellulose synthase, pectin methylesterase, peroxidase, sucrose synthase, sucrose phosphate synthase, and SWEET transporters, all of which are known to contribute to pericarp development or sugar accumulation. Expression profiling of 12 representative candidate genes in contrasting inbred lines revealed consistent differential expression patterns aligned with phenotypic variation, further supporting their role in regulating pericarp thickness and sweetness.
conclusionsThis study provides a comprehensive analysis of the genetic determinants of grain quality traits in sweet corn. The discovery of stable loci and functionally relevant candidate genes offers new insights into the molecular mechanisms governing kernel texture and sugar accumulation. These findings supply valuable markers and genomic resources for marker-assisted selection and genomic prediction, facilitating the development of improved sweet corn varieties with enhanced quality attributes.
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