title: Elucidation of gene-to-gene and metabolite-to-gene networks in arabidopsis by integration of metabolomics and transcriptomics.
abstract: Since the completion of genome sequences of model organisms, functional identification of unknown genes has become a principal challenge in biology. Post-genomics sciences such as transcriptomics, proteomics, and metabolomics are expected to discover gene functions. This report outlines the elucidation of gene-to-gene and metabolite-to-gene networks via integration of metabolomics with transcriptomics and presents a strategy for the identification of novel gene functions. Metabolomics and transcriptomics data of Arabidopsis grown under sulfur deficiency were combined and analyzed by batch-learning self-organizing mapping. A group of metabolites/genes regulated by the same mechanism clustered together. The metabolism of glucosinolates was shown to be coordinately regulated. Three uncharacterized putative sulfotransferase genes clustering together with known glucosinolate biosynthesis genes were candidates for involvement in biosynthesis. In vitro enzymatic assays of the recombinant gene products confirmed their functions as desulfoglucosinolate sulfotransferases. Several genes involved in sulfur assimilation clustered with O-acetylserine, which is considered a positive regulator of these genes. The genes involved in anthocyanin biosynthesis clustered with the gene encoding a transcriptional factor that up-regulates specifically anthocyanin biosynthesis genes. These results suggested that regulatory metabolites and transcriptional factor genes can be identified by this approach, based on the assumption that they cluster with the downstream genes they regulate. This strategy is applicable not only to plant but also to other organisms for functional elucidation of unknown genes.
authors.affiliation: Department of Molecular Biology and Biotechnology, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba 263-8522, Japan.
authors.forename: Masami Yokota
authors.initials: MY
authors.lastname: Hirai
authors.forename: Marion
authors.initials: M
authors.lastname: Klein
authors.forename: Yuuta
authors.initials: Y
authors.lastname: Fujikawa
authors.forename: Mitsuru
authors.initials: M
authors.lastname: Yano
authors.forename: Dayan B
authors.initials: DB
authors.lastname: Goodenowe
authors.forename: Yasuyo
authors.initials: Y
authors.lastname: Yamazaki
authors.forename: Shigehiko
authors.initials: S
authors.lastname: Kanaya
authors.forename: Yukiko
authors.initials: Y
authors.lastname: Nakamura
authors.forename: Masahiko
authors.initials: M
authors.lastname: Kitayama
authors.forename: Hideyuki
authors.initials: H
authors.lastname: Suzuki
authors.forename: Nozomu
authors.initials: N
authors.lastname: Sakurai
authors.forename: Daisuke
authors.initials: D
authors.lastname: Shibata
authors.forename: Jim
authors.initials: J
authors.lastname: Tokuhisa
authors.forename: Michael
authors.initials: M
authors.lastname: Reichelt
authors.forename: Jonathan
authors.initials: J
authors.lastname: Gershenzon
authors.forename: Jutta
authors.initials: J
authors.lastname: Papenbrock
authors.forename: Kazuki
authors.initials: K
authors.lastname: Saito
mesh_terms: D017360:Arabidopsis / Q000235:genetics* / Q000378:metabolism*; D004734:Energy Metabolism / Q000502:physiology*; D018506:Gene Expression Regulation, Plant / Q000502:physiology*; D023281:Genomics / Q000379:methods*; D005961:Glucosinolates / Q000235:genetics; D012694:Serine / Q000031:analogs & derivatives* / Q000378:metabolism; D015238:Sulfotransferases / Q000235:genetics; D013455:Sulfur / Q000378:metabolism; D014157:Transcription Factors / Q000378:metabolism; D014158:Transcription, Genetic / Q000502:physiology
chemical_list: D005961:Glucosinolates; D014157:Transcription Factors; D012694:Serine; D013455:Sulfur; D015238:Sulfotransferases; C043943:O-acetylserine