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Nucleic Acids Research 2006 34(9):2791-2802; doi:10.1093/nar/gkl356
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Published online 22 May 2006

© The Author 2006. Published by Oxford University Press. All rights reserved
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

Article

Target prediction for small, noncoding RNAs in bacteria

Brian Tjaden*, Sarah S. Goodwin1, Jason A. Opdyke1, Maude Guillier2, Daniel X. Fu1, Susan Gottesman2 and Gisela Storz1

Computer Science Department, Wellesley College Wellesley, MA 02481, USA 1 Cell Biology and Metabolism Branch, National Institute of Child Health and Human Development Bethesda, MD 208902-5430, USA 2 Laboratory of Molecular Biology, National Cancer Institute Bethesda, MD 20892, USA

*To whom correspondence should be addressed. Tel: +1 781 283 3354; Fax: +1 781 283 3642; Email: btjaden{at}wellesley.edu

Received February 2, 2006. Revised April 5, 2006. Accepted April 20, 2006.

Many small, noncoding RNAs in bacteria act as post-transcriptional regulators by basepairing with target mRNAs. While the number of characterized small RNAs (sRNAs) has steadily increased, only a limited number of the corresponding mRNA targets have been identified. Here we present a program, TargetRNA, that predicts the targets of these bacterial RNA regulators. The program was evaluated by assessing whether previously known targets could be identified. The program was then used to predict targets for the Escherichia coli RNAs RyhB, OmrA, OmrB and OxyS, and the predictions were compared with changes in whole genome expression patterns observed upon expression of the sRNAs. Our results show that TargetRNA is a useful tool for finding mRNA targets of sRNAs, although its rate of success varies between sRNAs.

Present addresses: Sarah S. Goodwin, University of California, San Francisco, CA 94143, USA

Daniel X. Fu, California Institute of Technology, Pasadena, CA 91126, USA


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