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Pure Appl. Chem., 2007, Vol. 79, No. 4, pp. 811-823

http://dx.doi.org/10.1351/pac200779040811

Phytochemical genomics in Arabidopsis thaliana: A case study for functional identification of flavonoid biosynthesis genes

Takayuki Tohge1, Keiko Yonekura-Sakakibara1, Rie Niida1, Akiko Watanabe-Takahashi1 and Kazuki Saito1,2

1 RIKEN Plant Science Center, 1-7-22, Suehiro-cho, Tsurumi-ku, Yokohama-shi, Kanagawa 230-0045, Japan
2 Graduate School of Pharmaceutical Sciences,Chiba University, Yayoi-cho 1-33, Inage-ku, Chiba-shi, Chiba 263-8522, Japan

Abstract: The completion of the whole genome sequence of Arabidopsis thaliana has made it possible to explore the phytochemical genomics in this species by determining gene-to-metabolite correlation through the comprehensive analysis of metabolite accumulation and gene expression. In this study, flavonoid profiling of wild-type plants and T-DNA insertion mutants was analyzed using ultra-performance liquid chromatography (UPLC)/photodiode array detection (PDA)/electrospray ionization (ESI)/multiple-stage mass spectrometry (MSn). Detailed analysis of the metabolite changes in the mutants suggested the functions of genes that have been mutated. In silico coexpression analysis of genes involved in flavonoid metabolism in Arabidopsis was performed using a publicly available transcriptome database of DNA microarrays. We inferred a coexpression framework model of the genes involved in the pathways of flavonol, anthocyanin, and proanthocyanidin synthesis, suggesting specific functions and coregulation of the genes of pathway enzymes and transcription factors. The metabolic profiling of the omt1 mutant lacking a methyltransferase gene narrowed down by the coexpression analysis showed that AtOMT1 (At5g54160) is involved not only in the production of lignins and sinapoyl esters but also in the methylation of flavonols forming isorhamnetin. These results suggest that the functional genomics approach by detailed target-metabolite profiling with transcriptome coexpression analysis provides an efficient way of identifying novel gene functions involved in plant metabolism.