Research article
Predictive screening for regulators of conserved functional gene modules (gene batteries) in mammals
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* Corresponding author: Per Lindahl per.lindahl@wlab.gu.se
1 Sahlgrenska Academy, Department of medical and physiological biochemistry Box 440, SE-405 30 Göteborg, Sweden
2 Chalmers Technical University, Department of mathematical statistics, Eklandagatan 76, SE-412 96 Göteborg, Sweden
3 Lund Strategic Research Center for Stem Cell Biology and Cell Therapy, BMC B10, Klinikgatan 26, SE-221 48 Lund, Sweden
BMC Genomics 2005, 6:68 doi:10.1186/1471-2164-6-68
Published: 9 May 2005Abstract
Background
The expression of gene batteries, genomic units of functionally linked genes which are activated by similar sets of cis- and trans-acting regulators, has been proposed as a major determinant of cell specialization in metazoans. We developed a predictive procedure to screen the mouse and human genomes and transcriptomes for cases of gene-battery-like regulation.
Results
In a screen that covered ~40 per cent of all annotated protein-coding genes, we identified 21 co-expressed gene clusters with statistically supported sharing of cis-regulatory sequence elements. 66 predicted cases of over-represented transcription factor binding motifs were validated against the literature and fell into three categories: (i) previously described cases of gene battery-like regulation, (ii) previously unreported cases of gene battery-like regulation with some support in a limited number of genes, and (iii) predicted cases that currently lack experimental support. The novel predictions include for example Sox 17 and RFX transcription factor binding sites that were detected in ~10% of all testis specific genes, and HNF-1 and 4 binding sites that were detected in ~30% of all kidney specific genes respectively. The results are publicly available at http://www.wlab.gu.se/lindahl/genebatteries webcite.
Conclusion
21 co-expressed gene clusters were enriched for a total of 66 shared cis-regulatory sequence elements. A majority of these predictions represent novel cases of potential co-regulation of functionally coupled proteins. Critical technical parameters were evaluated, and the results and the methods provide a valuable resource for future experimental design.