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Bioinformatics Advance Access published online on November 15, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti780
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received June 29, 2005
Revised October 6, 2005
Accepted November 11, 2005

Article

Elucidation of directionality for co-expressed genes: predicting intra-operon termination sites

Anshuman Gupta 1, Costas D. Maranas 2, and Réka Albert 3 *

1 Academic Services and Emerging Technologies, The Pennsylvania State University, University Park, PA, USA
2 Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA
3 Department of Physics, The Pennsylvania State University, University Park, PA, USA

* To whom correspondence should be addressed.
Réka Albert, E-mail: ralbert{at}phys.psu.edu


  Abstract

Motivation: In this paper, we present a novel framework for inferring regulatory and sequence-level information from gene co-expression networks. The key idea of our methodology is the systematic integration of network inference and network topological analysis approaches for uncovering biological insights.

Results: We determine the gene co-expression network of Bacillus subtilis using Affymetrix GeneChip® time series data and show how the inferred network topology can be linked to sequence-level information hard-wired in the organism's genome. We propose a systematic way for determining the correlation threshold at which two genes are assessed to be co-expressed by using the clustering coefficient and we expand the scope of the gene co-expression network by proposing the slope ratio metric as a means for incorporating directionality on the edges. We show through specific examples for B. subtilis that by incorporating expression level information in addition to the temporal expression patterns, we can uncover sequence-level biological insights. In particular, we are able to identify a number of cases where (i) the co-expressed genes are part of a single transcriptional unit or operon and (ii) the inferred directionality arises due to the presence of intra-operon transcription termination sites.

Availability: Provided on request.


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