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基因共表达网络分析揭示了茶树(Camellia sinensis)中三个特征次生生物合成途径的协调调控。

Gene co-expression network analysis reveals coordinated regulation of three characteristic secondary biosynthetic pathways in tea plant (Camellia sinensis).

机构信息

School of Life Science, Anhui Agricultural University, Hefei, 230036, China.

State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China.

出版信息

BMC Genomics. 2018 Aug 15;19(1):616. doi: 10.1186/s12864-018-4999-9.

Abstract

BACKGROUND

The leaves of tea plants (Camellia sinensis) are used to produce tea, which is one of the most popular beverages consumed worldwide. The nutritional value and health benefits of tea are mainly related to three abundant characteristic metabolites; catechins, theanine and caffeine. Weighted gene co-expression network analysis (WGCNA) is a powerful system for investigating correlations between genes, identifying modules among highly correlated genes, and relating modules to phenotypic traits based on gene expression profiling. Currently, relatively little is known about the regulatory mechanisms and correlations between these three secondary metabolic pathways at the omics level in tea.

RESULTS

In this study, levels of the three secondary metabolites in ten different tissues of tea plants were determined, 87,319 high-quality unigenes were assembled, and 55,607 differentially expressed genes (DEGs) were identified by pairwise comparison. The resultant co-expression network included 35 co-expression modules, of which 20 modules were significantly associated with the biosynthesis of catechins, theanine and caffeine. Furthermore, we identified several hub genes related to these three metabolic pathways, and analysed their regulatory relationships using RNA-Seq data. The results showed that these hub genes are regulated by genes involved in all three metabolic pathways, and they regulate the biosynthesis of all three metabolites. It is notable that light was identified as an important regulator for the biosynthesis of catechins.

CONCLUSION

Our integrated omics-level WGCNA analysis provides novel insights into the potential regulatory mechanisms of catechins, theanine and caffeine metabolism, and the identified hub genes provide an important reference for further research on the molecular biology of tea plants.

摘要

背景

茶树的叶子被用来制作茶叶,茶叶是全球最受欢迎的饮品之一。茶的营养价值和健康益处主要与三种丰富的特征代谢物有关:儿茶素、茶氨酸和咖啡因。加权基因共表达网络分析(WGCNA)是一种强大的系统,可以研究基因之间的相关性,识别高度相关基因之间的模块,并根据基因表达谱将模块与表型特征相关联。目前,对于这三种次生代谢途径在组学水平上的调控机制和相关性,人们知之甚少。

结果

在这项研究中,测定了茶树十种不同组织中三种次生代谢物的水平,组装了 87319 个高质量的 unigenes,并通过两两比较鉴定了 55607 个差异表达基因(DEGs)。所得的共表达网络包括 35 个共表达模块,其中 20 个模块与儿茶素、茶氨酸和咖啡因的生物合成显著相关。此外,我们还鉴定了几个与这三种代谢途径相关的枢纽基因,并使用 RNA-Seq 数据分析了它们的调控关系。结果表明,这些枢纽基因受涉及这三种代谢途径的基因调控,它们调节这三种代谢物的生物合成。值得注意的是,光照被鉴定为儿茶素生物合成的重要调控因子。

结论

我们的综合组学水平 WGCNA 分析为儿茶素、茶氨酸和咖啡因代谢的潜在调控机制提供了新的见解,鉴定的枢纽基因为茶树的分子生物学进一步研究提供了重要参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c3d/6094456/07c01e8c3ceb/12864_2018_4999_Fig1_HTML.jpg

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