Email updates

Keep up to date with the latest news and content from Genome Biology and BioMed Central.

Open Access Research

Prediction of co-regulated genes in Bacillus subtilis on the basis of upstream elements conserved across three closely related species

Goro Terai12, Toshihisa Takagi1 and Kenta Nakai1*

Author Affiliations

1 Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan

2 INTEC Web and Genome Informatics Corp., 1-3-3 Shinsuna, Koto-ku, Tokyo 136-8637, Japan

For all author emails, please log on.

Genome Biology 2001, 2:research0048-research0048.12  doi:10.1186/gb-2001-2-11-research0048

Published: 15 October 2001

Abstract

Background

Identification of co-regulated genes is essential for elucidating transcriptional regulatory networks and the function of uncharacterized genes. Although co-regulated genes should have at least one common sequence element, it is generally difficult to identify these genes from the presence of this element because it is very easily obscured by noise. To overcome this problem, we used conserved information from three closely related species: Bacillus subtilis, B. halodurans and B. stearothermophilus.

Results

Even though such species have a limited number of clearly orthologous genes, we obtained 1,884 phylogenetically conserved elements from the upstream intergenic regions of 1,568 B. subtilis genes. Similarity between these elements was used to cluster these genes. No other a priori knowledge on genes and elements was used. We could identify some genes known or suggested to be regulated by a common transcription factor as well as genes regulated by a common attenuation effector.

Conclusions

We confirmed that our method generates relatively few false positives in clusters with higher scores and that general elements such as -35/-10 boxes and Shine-Dalgarno sequence are not major obstacles. Moreover, we identified some plausible additional members of groups of known co-regulated genes. Thus, our approach is promising for exploring potentially co-regulated genes.