Time-series transcriptomic analysis reveals novel gene modules that control theanine biosynthesis in tea plant (Camellia sinensis)

• Main Authors: Haisheng Cao, Xiaolong He, Jinke Du, Rui Zhang, Ying Chen, Yong Ma, Qi Chen, Congbing Fang, Chi-Tang Ho, Shihua Zhang, Xiaochun Wan, Tapan Kumar Mondal
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2020-01-01
• Series: PLoS ONE
• Online Access: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482930/?tool=EBI

Theanine (thea) is a unique non-protein amino acid in tea plant (Camellia sinensis) and one of the most important small molecular compounds for tea quality and health effects. The molecular mechanism that maintains thea biosynthesis is not clear but may be reflected in complicated biological networks as other secondary metabolites in plants. We performed an integrative transcriptomic analysis of tea seedlings bud and leave over the time-course of ethylamine (EA) treatment that activated thea pathway. We identified 54 consistent differentially expressed genes (cDEGs, 25 upregulated and 29 downregulated) during thea activation. Gene Ontology (GO) functional enrichment analysis of upregulated genes and downregulated genes showed that they may function as a cascade of biological events during their cooperative contribution to thea biosynthesis. Among the total cDEGs, a diversity of functional genes (e.g., enzymes, transcription factors, transport and binding proteins) were identified, indicating a hierarchy of gene control network underlying thea biosynthesis. A gene network associated with thea biosynthesis was modeled and three interconnected gene functional modules were identified. Among the gene modules, several topologically important genes (e.g., CsBCS-1, CsRP, CsABC2) were experimentally validated using a combined thea content and gene expression analysis. Collectively, we presented here for the first time a comprehensive landscape of the biosynthetic mechanism of thea controlled by a underling gene network, which might provide a theoretical basis for the identification of key genes that contribute to thea biosynthesis.