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Updated: Aug 16, 2025

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
Published on: May 21, 2020
Genome-Wide Transcriptome Analysis Revealing the Genes Related to Sugar Metabolism in Kernels of Sweet Corn
Bin Chen1, Shouli Feng2, Junfeng Hou1
1Institute of Maize and Featured Dryland Crops, Zhejiang Academy of Agriculture Sciences, Dongyang 322100, China.
Abstract:
Sugar metabolism influences the quality of sweet corn (Zea mays var. saccharate Sturt) kernels, which is a major goal for maize breeding. In this study, the genome-wide transcriptomes from two supersweet corn cultivars (cv. Xuetian 7401 and Zhetian 11) with a nearly two-fold difference in kernel sugar content were carried out to explore the genes related to kernel sugar metabolism. In total, 45,748 differentially expressed genes (DEGs) in kernels and 596 DEGs in leaves were identified. PsbS, photosynthetic system II subunit S, showed two isoforms with different expression levels in leaf tissue between two cultivars, indicating that this gene might influence sugar accumulation in the kernel. On the other hand, hexokinases and beta-glucosidase genes involved in glycolysis, starch and sucrose metabolism were found in developing kernels with a genome-wide transcriptome analysis of developing kernels, which might contribute to the overaccumulation of water-soluble polysaccharides and an increase in the sweetness in the kernels of Xuetian 7401. These results indicated that kernel sugar accumulation in sweet corn might be influenced by both photosynthesis efficiency and the sugar metabolism rate. Our study supplied a new insight for breeding new cultivars with high sugar content and laid the foundation for exploring the regulatory mechanisms of kernel sugar content in corn.
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