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Depicting the genetic and metabolic panorama of chemical diversity in the tea plant

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Zhang,  YJ
Central Metabolism, Department Gutjahr, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Fernie,  A. R.       
Central Metabolism, Department Gutjahr, Max Planck Institute of Molecular Plant Physiology, Max Planck Society;

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Citation

Qiu, H., Zhang, X., Zhang, Y., Jiang, X., Ren, Y., Gao, D., et al. (2024). Depicting the genetic and metabolic panorama of chemical diversity in the tea plant. Plant Biotechnology Journal, 22, 1001-1016. doi:10.1111/pbi.14241.


Cite as: https://hdl.handle.net/21.11116/0000-000E-0491-9
Abstract
Summary As a frequently consumed beverage worldwide, tea is rich in naturally important bioactive metabolites. Combining genetic, metabolomic and biochemical methodologies, here, we present a comprehensive study to dissect the chemical diversity in tea plant. A total of 2837 metabolites were identified at high-resolution with 1098 of them being structurally annotated and 63 of them were structurally identified. Metabolite-based genome-wide association mapping identified 6199 and 7823 metabolic quantitative trait loci (mQTL) for 971 and 1254 compounds in young leaves (YL) and the third leaves (TL), respectively. The major mQTL (i.e., P?<?1.05???10?5, and phenotypic variation explained (PVE)?>?25%) were further interrogated. Through extensive annotation of the tea metabolome as well as network-based analysis, this study broadens the understanding of tea metabolism and lays a solid foundation for revealing the natural variations in the chemical composition of the tea plant. Interestingly, we found that galloylations, rather than hydroxylations or glycosylations, were the largest class of conversions within the tea metabolome. The prevalence of galloylations in tea is unusual, as hydroxylations and glycosylations are typically the most prominent conversions of plant specialized metabolism. The biosynthetic pathway of flavonoids, which are one of the most featured metabolites in tea plant, was further refined with the identified metabolites. And we demonstrated the further mining and interpretation of our GWAS results by verifying two identified mQTL (including functional candidate genes CsUGTa, CsUGTb, and CsCCoAOMT) and completing the flavonoid biosynthetic pathway of the tea plant.