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Since the completion of genome sequences of model organisms, functional identification of unknown genes has become a principal challenge in biology. Postgenomics sciences such as transcriptomics, proteomics, and metabolomics are expected to discover gene functions. This report outlines the elucidation of gene-togene 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.In the era of post-genomics, a systematic and comprehensive understanding of the complex events of life is a great concern in biology. The first step in this process is to identify all gene functions and gene-to-gene networks as the components of the system, the whole events of life. The metabolome is the final product of a series of gene actions. Hence, metabolomics has a potential to elucidate gene functions and networks, especially when integrated with transcriptomics. A promising approach is pair-wise transcript-metabolite correlation analysis, which can reveal unexpected correlations and bring to light candidate genes for modifying the metabolite content (1). Gene functions involved in the specific pathway of interest have been identified by the integration of transcript and targeted metabolic profiling in experimental systems where the pathway was activated (2-6). However, up to now, no gene function has been identified by non-targeted analyses of the transcriptome and metabolome. In this report, we analyzed the non-targeted metabolome and transcriptome of a model plant Arabidopsis under sulfur (S) 1 deficiency whose genome sequencing has been completed. Our strategy for integrated analyses using batch-learning-selforganizing mapping (BL-SOM) (7-9) enabled the identification of gene-to-gene and metabolite-to-gene networks and new gene fun...

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Glucosinolates are sulfur-rich plant metabolites of the order Brassicales that function in the defense of plants against pests and pathogens. They are also important in human society as flavor components, cancer-prevention agents, and crop biofumigants. Since glucosinolates may represent up to 30 % of the total sulfur content of plant organs, their accumulation should depend intimately on the sulfur status of the entire plant. Here we review the literature on how sulfur supply affects glucosinolate content. In field and greenhouse experiments involving soil, hydroponic and tissue culture media, sulfur fertilisation usually led to an increase in glucosinolate content ranging from 25 % to more than 50-fold, depending on the plant species, amount of sulfur applied, and type of treatment. The effect was greater on glucosinolates derived from the sulfur amino acid, methionine, than on glucosinolates derived from tryptophan. These changes are regulated not by simple mass action effects, but by extensive changes in gene transcription. In sulfur-deficient plants, there is a general down-regulation of glucosinolate biosynthetic genes which accompanies an up-regulation of genes controlling sulfur uptake and assimilation. Glucosinolates may be considered a potential source of sulfur for other metabolic processes under low-sulfur conditions, since increased breakdown of glucosinolates has been reported under sulfur deficiency. However, the pathway for sulfur mobilisation from glucosinolates has not been determined. The breakdown of indolic glucosinolates to form auxin in roots under sulfur-deficient conditions may help stimulate root formation for sulfur uptake.