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BIOINFORMATICS

EGENES: Transcriptome-Based Plant Database of Genes with Metabolic Pathway Information and Expressed Sequence Tag Indices in KEGG^{1,[C],[W],[OA]}

Laboratory of Bioknowledge Systems, Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho Uji, Kyoto 611–0011, Japan (A.M.-N., S.G., R.J., M.I., Y.M., M.K.); Laboratory of Bioinformatics and Bioknowledge Systems, Institute of Biochemistry and Biophysics, and Center of Excellence for BioMathematics, School of Computer Science, University of Tehran, Tehran, Iran (A.M.-N.); Laboratory of Genome Database, Human Genome Center, University of Tokyo, Tokyo 108–8639, Japan (S.K., M.K.); and Laboratory of Plant Genetics, Division of Applied Bioscience, Kyoto University, Kyoto 606–8502, Japan (T.R.E.)

EGENES is a knowledge-based database for efficient analysis of plant expressed sequence tags (ESTs) that was recently added to the KEGG suite of databases. It links plant genomic information with higher order functional information in a single database. It also provides gene indices for each genome. The genomic information in EGENES is a collection of EST contigs constructed from assembly of ESTs. Due to the extremely large genomes of plant species, the bulk collection of data such as ESTs is a quick way to capture a complete repertoire of genes expressed in an organism. Using ESTs for reconstructing metabolic pathways is a new expansion in KEGG and provides researchers with a new resource for species in which only EST sequences are available. Functional annotation in EGENES is a process of linking a set of genes/transcripts in each genome with a network of interacting molecules in the cell. EGENES is a multispecies, integrated resource consisting of genomic, chemical, and network information containing a complete set of building blocks (genes and molecules) and wiring diagrams (biological pathways) to represent cellular functions. Using EGENES, genome-based pathway annotation and EST-based annotation can now be compared and mutually validated. The ultimate goals of EGENES will be to: bring new plant species into KEGG by clustering and annotating ESTs; abstract knowledge and principles from large-scale plant EST data; and improve computational prediction of systems of higher complexity. EGENES will be updated at least once a year. EGENES is publicly available and is accessible by the following link or by KEGG's navigation system (http://www.genome.jp/kegg-bin/create_kegg_menu?category=plants_egenes).

² Present address: BIOBASE GmbH, Haltchersche Str. 33, D–38304 Wolfenbüttel, Germany.

The author responsible for distribution of materials integral to the findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is: Ali Masoudi-Nejad (amasoudin{at}ibb.ut.ac.ir).

^[C] Some figures in this article are displayed in color online but in black and white in the print edition.

^[W] The online version of this article contains Web-only data.

^[OA] Open Access articles can be viewed online without a subscription.

www.plantphysiol.org/cgi/doi/10.1104/pp.106.095059

^* Corresponding author; e-mail amasoudin{at}ibb.ut.ac.ir; fax 98–(0)21–6640–4680.

Received December 19, 2006; accepted April 18, 2007; published April 27, 2007.

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