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Comparison of the transcriptome and metabolome of wheat (Triticum aestivum L.) proteins content during grain formation provides insight

文献类型： 外文期刊

作者： Shi, Jia 1 ; Wang, Lihong 1 ; Wang, Zhong 1 ; Li, Jianfeng 1 ; Zhang, Hongzhi 1 ; Gao, Xin 1 ; Wang, Chunsheng 1 ; Xia, Jianqiang 1 ; Zhao, Zhun 1 ; Wang, Zhenlong 1 ; Yang, Zhenyu 1 ; Xu, Zihan 1 ; Zhang, Yueqiang 1 ; Fan, Zheru 1 ;

作者机构： 1.Inst Nucl & Biol Technol, Xinjiang Acad Agr Sci, Crop Chem Regulat Engn Technol Res Ctr Xinjiang, Xinjiang Key Lab Crop Biotechnol, Urumqi, Peoples R China

关键词： wheat; transcriptome; metabolome; glutenin content; WGCNA

期刊名称：FRONTIERS IN PLANT SCIENCE （ 影响因子：5.6； 五年影响因子：6.8 ）

ISSN： 1664-462X

年卷期： 2024 年 14 卷

页码：

收录情况： SCI

摘要： Introduction: Wheat is a food crop with a large global cultivation area, and the content and quality of wheat glutenin accumulation are important indicators of the quality of wheat flour. Methods: To elucidate the gene expression regulation and metabolic characteristics related to the gluten content during wheat grain formation, transcriptomic and metabolomic analyses were performed for the high gluten content of the Xinchun 26 cultivar and the low proteins content of the Xinchun 34 cultivar at three periods (7 d, 14 d and 21 d) after flowering. Results: Transcriptomic analysis revealed that 5573 unique differentially expressed genes (DEGs) were divided into two categories according to their expression patterns during the three periods. The metabolites detected were mainly divided into 12 classes. Lipid and lipid-like molecule levels and phenylpropanoid and polyketide levels were the highest, and the difference analysis revealed a total of 10 differentially regulated metabolites (DRMs) over the three periods. Joint analysis revealed that the DEGs and DRMs were significantly enriched in starch and sucrose metabolism; the citrate cycle; carbon fixation in photosynthetic organisms; and alanine, aspartate and glutamate metabolism pathways. The genes and contents of the sucrose and gluten synthesis pathways were analysed, and the correlation between gluten content and its related genes was calculated. Based on weighted correlation network analysis (WGCNA), by constructing a coexpression network, a total of 5 specific modules and 8 candidate genes that were strongly correlated with the three developmental stages of wheat grain were identified. Discussion: This study provides new insights into the role of glutenin content in wheat grain formation and reveals potential regulatory pathways and candidate genes involved in this developmental process.

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