pmc logo image
Logo of narJournal URL: http://nar.oupjournals.org
Journal List > Nucleic Acids Res > v.34(8); 2006

Formats:
Nucleic Acids Res. 2006; 34(8): 2418–2427.
Published online 2006 May 8. doi: 10.1093/nar/gkl294.
PMCID: PMC1458513
Copyright © The Author 2006. Published by Oxford University Press. All rights reserved
Detecting uber-operons in prokaryotic genomes
Dongsheng Che,2 Guojun Li,1,3 Fenglou Mao,1 Hongwei Wu,1 and Ying Xu1,2*
1Department of Biochemistry and Molecular Biology, University of Georgia, USA
2Department of Computer Science, University of Georgia, USA
3School of Mathematics and System Sciences, Shandong University, China
*To whom correspondence should be addressed. Tel: 1 706 542 9779; Fax: 1 706 542 9751; Email: Ying Xu xyn/at/bmb.uga.edu
The authors wish it to be known that, in their opinion, the first three authors should be regarded as joint First Authors
Received January 6, 2006; Revised February 15, 2006; Accepted April 6, 2006.
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org
Small right arrow pointing to: This article has been cited by other articles in PMC.
Abstract
We present a study on computational identification of uber-operons in a prokaryotic genome, each of which represents a group of operons that are evolutionarily or functionally associated through operons in other (reference) genomes. Uber-operons represent a rich set of footprints of operon evolution, whose full utilization could lead to new and more powerful tools for elucidation of biological pathways and networks than what operons have provided, and a better understanding of prokaryotic genome structures and evolution. Our prediction algorithm predicts uber-operons through identifying groups of functionally or transcriptionally related operons, whose gene sets are conserved across the target and multiple reference genomes. Using this algorithm, we have predicted uber-operons for each of a group of 91 genomes, using the other 90 genomes as references. In particular, we predicted 158 uber-operons in Escherichia coli K12 covering 1830 genes, and found that many of the uber-operons correspond to parts of known regulons or biological pathways or are involved in highly related biological processes based on their Gene Ontology (GO) assignments. For some of the predicted uber-operons that are not parts of known regulons or pathways, our analyses indicate that their genes are highly likely to work together in the same biological processes, suggesting the possibility of new regulons and pathways. We believe that our uber-operon prediction provides a highly useful capability and a rich information source for elucidation of complex biological processes, such as pathways in microbes. All the prediction results are available at our Uber-Operon Database: http://csbl.bmb.uga.edu/uber, the first of its kind.
Articles from Nucleic Acids Research are provided here courtesy of
Oxford University Press

PubMed articles by these authors