The Solanaceae family includes several economically important vegetable crops. The tomato (Solanum lycopersicum) is regarded as a model plant of the Solanaceae family. Recently, a number of tomato resources have been developed in parallel with the ongoing tomato genome sequencing project. In particular, a miniature cultivar, Micro-Tom, is regarded as a model system in tomato genomics, and a number of genomics resources in the Micro-Tom-background, such as ESTs and mutagenized lines, have been established by an international alliance. To accelerate the progress in tomato genomics, we developed a collection of fully-sequenced 13,227 Micro-Tom full-length cDNAs. By checking redundant sequences, coding sequences, and chimeric sequences, a set of 11,502 non-redundant full-length cDNAs (nrFLcDNAs) was generated. Analysis of untranslated regions demonstrated that tomato has longer 5'- and 3'-untranslated regions than most other plants but rice. Classification of functions of proteins predicted from the coding sequences demonstrated that nrFLcDNAs covered a broad range of functions. A comparison of nrFLcDNAs with genes of sixteen plants facilitated the identification of tomato genes that are not found in other plants, most of which did not have known protein domains. Mapping of the nrFLcDNAs onto currently available tomato genome sequences facilitated prediction of exon-intron structure. Introns of tomato genes were longer than those of Arabidopsis and rice. According to a comparison of exon sequences between the nrFLcDNAs and the tomato genome sequences, the frequency of nucleotide mismatch in exons between Micro-Tom and the genome-sequencing cultivar (Heinz 1706) was estimated to be 0.061%. The collection of Micro-Tom nrFLcDNAs generated in this study will serve as a valuable genomic tool for plant biologists to bridge the gap between basic and applied studies. The nrFLcDNA sequences will help annotation of the tomato whole-genome sequence and aid in tomato functional genomics and molecular breeding. Full-length cDNA sequences and their annotations are provided in the database KaFTom http://www.pgb.kazusa.or.jp/kaftom/ via the website of the National Bioresource Project Tomato http://tomato.nbrp.jp .

Background: Rhizotoxic ions in problem soils inhibit nutrient and water acquisition by roots, which in turn leads to reduced crop yields. Previous studies on the effects of rhizotoxic ions on root growth and physiological functions suggested that some mechanisms were common to all rhizotoxins, while others were more specific. To understand this complex system, we performed comparative transcriptomic analysis with various rhizotoxic ions, followed by bioinformatics analysis, in the model plant Arabidopsis thaliana. Results: Roots of Arabidopsis were treated with the major rhizotoxic stressors, aluminum (Al) ions, cadmium (Cd) ions, copper (Cu) ions and sodium (NaCl) chloride, and the gene expression responses were analyzed by DNA array technology. The top 2.5% of genes whose expression was most increased by each stressor were compared with identify common and specific gene expression responses induced by these stressors. A number of genes encoding glutathione-S-transferases, peroxidases, Ca-binding proteins and a trehalose-synthesizing enzyme were induced by all stressors. In contrast, gene ontological categorization identified sets of genes uniquely induced by each stressor, with distinct patterns of biological processes and molecular function. These contained known resistance genes for each stressor, such as AtALMT1 (encoding Al-activated malate transporter) in the Al-specific group and DREB (encoding dehydration responsive element binding protein) in the NaCl-specific group. These gene groups are likely to reflect the common and differential cellular responses and the induction of defense systems in response to each ion. We also identified co-expressed gene groups specific to rhizotoxic ions, which might aid further detailed investigation of the response mechanisms. Conclusion: In order to understand the complex responses of roots to rhizotoxic ions, we performed comparative transcriptomic analysis followed by bioinformatics characterization. Our analyses revealed that both general and specific genes were induced in Arabidopsis roots exposed to various rhizotoxic ions. Several defense systems, such as the production of reactive oxygen species and disturbance of Ca homeostasis, were triggered by all stressors, while specific defense genes were also induced by individual stressors. Similar studies in different plant species could help to clarify the resistance mechanisms at the molecular level to provide information that can be utilized for marker-assisted selection.

Correlations of gene-to-gene co-expression and metabolite-to-metabolite co-accumulation calculated from large amounts of transcriptome and metabolome data are useful for uncovering unknown functions of genes, functional diversities of gene family members and regulatory mechanisms of metabolic pathway flows. Many databases and tools are available to interpret quantitative transcriptome and metabolome data, but there are only limited ones that connect correlation data to biological knowledge and can be utilized to find biological significance of it. We report here a new metabolic pathway database, KaPPA-View4 ( http://kpv.kazusa.or.jp/kpv4/ ), which is able to overlay gene-to-gene and/or metabolite-to-metabolite relationships as curves on a metabolic pathway map, or on a combination of up to four maps. This representation would help to discover, for example, novel functions of a transcription factor that regulates genes on a metabolic pathway. Pathway maps of the Kyoto Encyclopedia of Genes and Genomes (KEGG) and maps generated from their gene classifications are available at KaPPA-View4 KEGG version ( http://kpv.kazusa.or.jp/kpv4-kegg/ ). At present, gene co-expression data from the databases ATTED-II, COXPRESdb, CoP and MiBASE for human, mouse, rat, Arabidopsis , rice, tomato and other plants are available.

Currently, in mass spectrometry-based metabolomics, limited reference mass spectra are available for flavonoid identification. In the present study, a database of probable mass fragments for 6,867 known flavonoids (FsDatabase) was manually constructed based on new structure- and fragmentation-related rules using new heuristics to overcome flavonoid complexity. We developed the FlavonoidSearch system for flavonoid annotation, which consists of the FsDatabase and a computational tool (FsTool) to automatically search the FsDatabase using the mass spectra of metabolite peaks as queries. This system showed the highest identification accuracy for the flavonoid aglycone when compared to existing tools and revealed accurate discrimination between the flavonoid aglycone and other compounds. Sixteen new flavonoids were found from parsley, and the diversity of the flavonoid aglycone among different fruits and vegetables was investigated.

A unique cytosol-localized geranyl diphosphate synthase supporting a large production of shikonin has evolved from farnesyl diphosphate synthase in Lithospermum

Jatropha curcas is an important biofuel crop due to the presence of high amount of oil in its seeds suitable for biodiesel production. Triacylglycerols (TAGs) are the most abundant form of storage oil in plants. Diacylglycerol O-acyltransferase (DGAT1) enzyme is responsible for the last and only committed step in seed TAG biosynthesis. Direct upregulation of TAG biosynthesis in seeds and vegetative tissues through overexpression of the DGAT1 could enhance the energy density of the biomass, making significant impact on biofuel production. The enzyme diacylglycerol O-acyltransferase is the rate-limiting enzyme responsible for the TAG biosynthesis in seeds. We generated transgenic Jatropha ectopically expressing an Arabidopsis DGAT1 gene through Agrobacterium-mediated transformation. The resulting AtDGAT1 transgenic plants showed a dramatic increase in lipid content by 1.5- to 2 fold in leaves and 20–30 % in seeds, and an overall increase in TAG and DAG, and lower free fatty acid (FFA) levels compared to the wild-type plants. The increase in oil content in transgenic plants is accompanied with increase in average plant height, seeds per tree, average 100-seed weight, and seed length and breadth. The enhanced TAG accumulation in transgenic plants had no penalty on the growth rates, growth patterns, leaf number, and leaf size of plants. In this study, we produced transgenic Jatropha ectopically expressing AtDGAT1. We successfully increased the oil content by 20–30 % in seeds and 1.5- to 2.0-fold in leaves of Jatropha through genetic engineering. Transgenic plants had reduced FFA content compared with control plants. Our strategy of increasing energy density by enhancing oil accumulation in both seeds and leaves in Jatropha would make it economically more sustainable for biofuel production.