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Open Access Highly Accessed Database

sRNAdb: A small non-coding RNA database for gram-positive bacteria

Jordan Pischimarov1, Carsten Kuenne1, André Billion1, Jüergen Hemberger2, Franz Cemič2, Trinad Chakraborty1 and Torsten Hain1*

Author Affiliations

1 Institute of Medical Microbiology, Justus-Liebig-University, Schubertstrasse 81, Giessen, D-35392, Germany

2 Institute for Biochemical Engineering and Analytics, University of Applied Sciences Giessen-Friedberg, Wiesenstrasse 14, Giessen, D-35390, Germany

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BMC Genomics 2012, 13:384  doi:10.1186/1471-2164-13-384

Published: 10 August 2012

Abstract

Background

The class of small non-coding RNA molecules (sRNA) regulates gene expression by different mechanisms and enables bacteria to mount a physiological response due to adaptation to the environment or infection. Over the last decades the number of sRNAs has been increasing rapidly. Several databases like Rfam or fRNAdb were extended to include sRNAs as a class of its own. Furthermore new specialized databases like sRNAMap (gram-negative bacteria only) and sRNATarBase (target prediction) were established. To the best of the authors’ knowledge no database focusing on sRNAs from gram-positive bacteria is publicly available so far.

Description

In order to understand sRNA’s functional and phylogenetic relationships we have developed sRNAdb and provide tools for data analysis and visualization. The data compiled in our database is assembled from experiments as well as from bioinformatics analyses. The software enables comparison and visualization of gene loci surrounding the sRNAs of interest. To accomplish this, we use a client–server based approach. Offline versions of the database including analyses and visualization tools can easily be installed locally on the user’s computer. This feature facilitates customized local addition of unpublished sRNA candidates and related information such as promoters or terminators using tab-delimited files.

Conclusion

sRNAdb allows a user-friendly and comprehensive comparative analysis of sRNAs from available sequenced gram-positive prokaryotic replicons. Offline versions including analysis and visualization tools facilitate complex user specific bioinformatics analyses.