About 10,000 non-redundant Arabidopsis full length cDNA (fl-cDNA) clones (RAFL cDNA) were mixed to make a normalized fl-cDNA over-expression T-DNA library. Agrobacterium was transformed with the normalized T-DNA library to give the corresponding Agrobacterium library. A. thaliana Col-0 WT plants were dipped with the Agrobacteria library. About 15,000 transformed plants were grown in green house to isolate plants that showed obvious phenotypes such as morphological abnormality, greening and pigmentation. Among them four lines showed phenotype similar to plant over-expressing tryptophan 2-monooxigenase gene (auxin synthesis gene from bacteria). PCR was performed to amplify four different fl-cDNAs from these lines. These cDNAs were reintroduced into wild type plant to confirm recapitulation of the original phenotype. We designated this activation tagging-like system as Fox Hunting System (full-length cDNA over-expressor gene hunting system) to develop it as a novel technology for the functional genomics of agronomically important genomic materials.

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For investigating the global metabolic changes in ilent phenotypes we introduced metabolomics concept using OX (Full-length cDNA Over-expressor gene) hunting system of model plants, Arabidopsis thaliana. Using the system we are trying to make a rapid and useful method to find the silent phenotypes by GC-TOF/MS.
Five seeds from every FOX hunting lines were grown on the MS agar medium for screening. The aerial part of each 25 days-old FOX line was harvested. Samples were extracted and analysed by GC-TOF/MS, and thereafter the non-processed GC-MS files were subjected to multivariate analysis. The PLS-DA results indicated that several lines had metabolic differences compared with those of other lines. The compounds which made differences contained both primary and secondary metabolites. In the poster, we will present the method of sample cultivation, extraction and the result of multivariate analysis using chemometrics.

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To study function of nuclear genes involved in chloroplast development and photosynthesis, we have started to collect Ds-tagged knock-out lines that 2090 plastid proteins with a cTP predicted to be encoded by nuclear genomes in Arabidopsis thaliana.
To understand regulatory-networks of metabolite, we obtained metabolic profiles of apg1 (the 37 kDa inner envelope membrane polypeptide related plastoquinone biosynthesis), apg2 (TatC homologue of a ΔpH-dependent protein transporter in thylakoid membrane) and apg3 (translation system in chloroplast) using integration of metabolomics.
FT-ICRMS (Fourier Transform-Ion cyclotron Resonance-Mass spectrometry) is a nontargeted, high-throughput analytical system for metabolomics analysis in which crude by means of direct injection without prior separation metabolites by chromatography. We observed about 500 m/z values (mass peaks) from each analysis of 100% methanol extracts in 3-week-old apg mutants and the results were subjected to PCA. We will discuss roles of metabolites with significant profiles.

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Our objective of this study is to elucidate a whole response of plants to sulfur starvation by integrating metabolomics with transcriptomics. To elucidate gene-to-metabolite and gene-to-gene networks, the time-course data of metabolome and transcriptome of sulfur-starved Arabidopsis were combined into a single data set and analyzed by batch-learning-self-organizing mapping (BL-SOM), a sophisticated form of cluster analyses. BL-SOM can cluster the metabolites and genes showing similar accumulation and expression patterns. By this analysis, a known gene-to-metabolite network, that is, correlation between the sulfur assimilation genes and O-acetylserine, a positive regulator of them, was shown. Moreover, an unknown gene-to-gene network, that is, correlation of the glucosinolate-biosynthesis genes was shown. Based on this finding, three previously unknown sulfotransferase genes involved in glucosinolate biosynthesis were identified. This strategy is useful for functional identification of unknown genes, especially when the genes of interest are involved in metabolism and the knock-out mutants don't show apparent phenotypes.

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This work is a metabolomics-based approach that helps to reveal dynamics of metabolites in cells, and thus to comprehensively understand the whole cellular process of metabolism. We have developed metabolome informatics tools for the purpose of analysis of metabolic profiling data that are obtained from mass spectrometry (MS), such as FT-MS, GC-MS and LC-MS. In addition, we also have designed a database system for searching relationships between metabolites and plant species. This database system is also useful for obtaining information on metabolites and their corresponding species, chemical structure and biological activity. Here, we introduce the present system and database by using a model case of analysis of metabolome data that were obtained from Arabidopsis thaliana.

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NMR might play a comprehensive methodology in the metabolomics studies due to its excellent reproductively, and availability of in vivo measurement. Therefore, we are currently focusing to develop novel methodologies for an NMR-based metabolomics. Especially, we are trying to apply the uniform stable isotope labeling of higher plants for the hetero-nuclear NMR experiments previously used in protein NMR. Use of stable isotope labeling methods has enormous advantage for discrimination of incorporated or de novo synthesized compounds. First, the NMR-based metabolomics revealed that the higher plants can uptake not only inorganic nitrogen sources, but also nitrogen-containing organic compounds. Since the plant uptake of organic compounds is also extremely important issues in applied sciences, we are currently investigating two types of plant culture; Oryza sativa grown in hydroponics and Arabidopsis thaliana grown with soil. Furthermore, potentiality of in vivo NMR metabolomics will be discussed in the conference.

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In the RIKEN Genomic Sciences Center, more than 60,000 activation tagged mutant lines of Arabidopsis have been produced for the saturated mutagenesis of the genome. To find the function of a gene, systematic analysis of phenotypes is vital. However, conventional phenotypic analysis of mutant screens depends mainly on qualitative descriptions after visual observation of morphological traits. We have proposed a new methodology of phenotypic analysis based on precise three-dimensional (3D) measurement by a laser range finder and automatic data processing. In this report, we introduce the methods of shape modeling and data processing with the micro X-ray computed tomography (μCT) as a new 3D measurement device. Moreover, on the computationally phenotypic analysis, advantage or disadvantage by using μCT is described with comparing to the laser surface scanner.
In addition, dry seeds of a wild-type and several mutants are analyzed as an example of morphological trait extraction.

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