EGENES: Transcriptome-based plant metabolic pathway database in KEGG

EGENES is a knowledge-based database for efficient analysis of plant 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 expressed sequence tags (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; to abstract knowledge and principles from large-scale plant EST data; and to 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 following link or by KEGG's navigation system