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  A computational evaluation of over-representation of regulatory motifs in the promoter regions of differentially expressed genes

Meng, G., Mosig, A., & Vingron, M. (2010). A computational evaluation of over-representation of regulatory motifs in the promoter regions of differentially expressed genes. BMC Bioinformatics, 11, 11:267-11:267. doi:10.1186/1471-2105-11-267.

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Meng, G.1, Author           
Mosig, A., Author
Vingron, M.2, Author           
Affiliations:
1Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              
2Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479639              

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Free keywords: Animals; Computational Biology/*methods; *Gene Expression Regulation; Humans; Mice; Promoter Regions, Genetic/*genetics
 Abstract: BACKGROUND: Observed co-expression of a group of genes is frequently attributed to co-regulation by shared transcription factors. This assumption has led to the hypothesis that promoters of co-expressed genes should share common regulatory motifs, which forms the basis for numerous computational tools that search for these motifs. While frequently explored for yeast, the validity of the underlying hypothesis has not been assessed systematically in mammals. This demonstrates the need for a systematic and quantitative evaluation to what degree co-expressed genes share over-represented motifs for mammals. RESULTS: We identified 33 experiments for human and mouse in the ArrayExpress Database where transcription factors were manipulated and which exhibited a significant number of differentially expressed genes. We checked for over-representation of transcription factor binding sites in up- or down-regulated genes using the over-representation analysis tool oPOSSUM. In 25 out of 33 experiments, this procedure identified the binding matrices of the affected transcription factors. We also carried out de novo prediction of regulatory motifs shared by differentially expressed genes. Again, the detected motifs shared significant similarity with the matrices of the affected transcription factors. CONCLUSIONS: Our results support the claim that functional regulatory motifs are over-represented in sets of differentially expressed genes and that they can be detected with computational methods.

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Language(s): eng - English
 Dates: 2010
 Publication Status: Issued
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 Identifiers: eDoc: 539709
DOI: 10.1186/1471-2105-11-267
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Title: BMC Bioinformatics
Source Genre: Journal
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Pages: - Volume / Issue: 11 Sequence Number: - Start / End Page: 11:267 - 11:267 Identifier: ISSN: 1471-2105 (Electronic)