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Nucleic Acids Research, 2004, Vol. 32, Database issue D273-D276
© 2004 Oxford University Press

FusionDB: a database for in-depth analysis of prokaryotic gene fusion events

Karsten Suhre* and Jean-Michel Claverie

Information Génomique and Structurale, CNRS-UPR 2589, 31 chemin Joseph Aiguier, 13402 Marseille Cedex 20, France

*To whom correspondence should be addressed. Tel: +33 4 91 16 46 04; Fax: +33 4 91 16 45 49; Email: karsten.suhre{at}igs.cnrs-mrs.fr

FusionDB (http://igs-server.cnrs-mrs.fr/FusionDB/) constitutes a resource dedicated to in-depth analysis of bacterial and archaeal gene fusion events. Such events can provide the ‘Rosetta stone’ in the search for potential protein–protein interactions, as well as metabolic and regulatory networks. However, the false positive rate of this approach may be quite high, prompting a detailed scrutiny of putative gene fusion events. FusionDB readily provides much of the information required for that task. Moreover, FusionDB extends the notion of gene fusion from that of a single gene to that of a family of genes by assembling pairs of genes from different genomes that belong to the same Cluster of Orthogonal Groups (COG). Multiple sequence alignments and phylogenetic tree reconstruction for the N- and C-terminal parts of these ‘COG fusion’ events are provided to distinguish single and multiple fusion events from cases of gene fission, pseudogenes and other false positives. Finally, gene fusion events with matches to known structures of heterodimers in the Protein Data Bank (PDB) are identified and may be visualized. FusionDB is fully searchable with access to sequence and alignment data at all levels. A number of different scores are provided to easily differentiate ‘real’ from ‘questionable’ cases, especially when larger database searches are performed. FusionDB is cross-linked with the ‘Phylogenomic Display of Bacterial Genes’ (PhydBac) online web server. Together, these servers provide the complete set of information required for in-depth analysis of non-homology-based gene function attribution.


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