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Identification of Candidate Gene Networks Controlling Soluble Sugar Metabolism During Brassica napus L. Development by Integrated Analysis of Metabolic and Transcriptomic Analyses
Identification of Candidate Gene Networks Controlling Soluble Sugar Metabolism During Brassica napus L. Development by Integrated Analysis of Metabolic and Transcriptomic Analyses
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Identification of Candidate Gene Networks Controlling Soluble Sugar Metabolism During Brassica napus L. Development by Integrated Analysis of Metabolic and Transcriptomic Analyses
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Identification of Candidate Gene Networks Controlling Soluble Sugar Metabolism During Brassica napus L. Development by Integrated Analysis of Metabolic and Transcriptomic Analyses
Identification of Candidate Gene Networks Controlling Soluble Sugar Metabolism During Brassica napus L. Development by Integrated Analysis of Metabolic and Transcriptomic Analyses

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Identification of Candidate Gene Networks Controlling Soluble Sugar Metabolism During Brassica napus L. Development by Integrated Analysis of Metabolic and Transcriptomic Analyses
Identification of Candidate Gene Networks Controlling Soluble Sugar Metabolism During Brassica napus L. Development by Integrated Analysis of Metabolic and Transcriptomic Analyses
Journal Article

Identification of Candidate Gene Networks Controlling Soluble Sugar Metabolism During Brassica napus L. Development by Integrated Analysis of Metabolic and Transcriptomic Analyses

2025
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Overview
Soluble sugars are among the key components determining the flavor quality of rapeseed bolting. However, the potential regulatory network governing the biosynthesis of soluble sugars during the growth and development of rapeseed bolting remains largely unknown. In this study, the total soluble sugar and starch contents were measured at the seedling and bolting stages in 203 Brassica napus germplasms. Among them, the inbred lines No51 and No106 were identified as high- and low-sugar materials, respectively. A comparative analysis of the soluble sugar composition between these two extreme lines revealed that sucrose and glucose are the key metabolites contributing to differences in the soluble sugar content. A total of 36,893 differentially expressed genes (DEGs) were identified by transcriptomics, including 19,031 significantly upregulated genes and 17,862 downregulated genes. Metabolomics has identified 25 common and unique metabolites. The combined analysis of transcriptomics and metabolomics showed that differentially expressed genes and metabolites were mainly concentrated in starch and sucrose metabolism, galactose metabolism, and the interconversion of pentose and glucuronic acid. The expression patterns obtained by RNA seq and qRT PCR are highly consistent. A regulatory network related to soluble sugar synthesis and metabolism was constructed, leading to the identification of BnaC02G0100500ZS, BnaC02G0100700ZS, and BnaC02G0092700ZS as potential key genes involved in the regulation of soluble sugar biosynthesis.