Database Commons

a catalog of worldwide biological databases

ODB (Operon DataBase) aims to collect data of all known and conserved operons in completely sequenced genomes. Three newly updated features of this database have been added as follows: (i) Data from included operons were updated. The genome-wide analysis of transcription and transcriptional units has become popular recently and ODB successfully integrates these high-throughput operon data, including genome-wide transcriptional units of five prokaryotes and two eukaryotes. The current version of our database contains information from about 10,000 known operons in more than 50 genomes, and more than 400,000 conserved operons obtained from more than 1000 bacterial genomes. (ii) ODB proposes the idea of reference operons as a new operon prediction tool. A reference operon, a set of possible orthologous genes that organize operons, is defined by clustering all known operons. A large number of known operons, including the recently added genome-wide analysis of operons, allowed us to define more reliable reference operons. (iii) ODB also provides new graphical interfaces. One is for comparative analyses of operon structures in multiple genomes. The other is for visualization of possible operons in multiple genomes obtained from the reference operons. The 2011 updated version of ODB is now available at http://operondb.jp/.

Operon structures play an important role in co-regulation in prokaryotes. Although over 200 complete genome sequences are now available, databases providing genome-wide operon information have been limited to certain specific genomes. Thus, we have developed an ODB (Operon DataBase), which provides a data retrieval system of known operons among the many complete genomes. Additionally, putative operons that are conserved in terms of known operons are also provided. The current version of our database contains about 2000 known operon information in more than 50 genomes and about 13 000 putative operons in more than 200 genomes. This system integrates four types of associations: genome context, gene co-expression obtained from microarray data, functional links in biological pathways and the conservation of gene order across the genomes. These associations are indicators of the genes that organize an operon, and the combination of these indicators allows us to predict more reliable operons. Furthermore, our system validates these predictions using known operon information obtained from the literature. This database integrates known literature-based information and genomic data. In addition, it provides an operon prediction tool, which make the system useful for both bioinformatics researchers and experimental biologists. Our database is accessible at http://odb.kuicr.kyoto-u.ac.jp/.