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Functional inference from non-random distributions of conserved predicted transcription factor binding sites

Item Type:Article
Title:Functional inference from non-random distributions of conserved predicted transcription factor binding sites
Creators Name:Dieterich, C. and Rahmann, S. and Vingron, M.
Abstract:Our understanding of how genes are regulated in a concerted fashion is still limited. Especially, complex phenomena like cell cycle regulation in multicellular organisms are poorly understood. Therefore, we investigated conserved predicted transcription factor binding sites (TFBSs) in man-mouse upstream regions of genes that can be associated to a particular cell cycle phase in HeLa cells. TFBSs were predicted from selected binding site motifs (represented by position weight matrices, PWMs) based on a statistical approach. A regulatory role for a transcription factor is more probable if its predicted TFBSs are enriched in upstream regions of genes, that are associated with a subset of cell cycle phases. We tested for this association by computing exact P-values for the observed phase distributions under the null distribution defined by the relative amount of conserved upstream sequence of genes per cell cycle phase. We considered non-exonic and 5'-untranslated region (5'-UTR) binding sites separately and corrected for multiple testing by taking the false discovery rate into account. RESULTS: We identified 22 non-exonic and 11 5'-UTR significant PWM phase distributions although expecting one false discovery. Many of the corresponding transcription factors (e.g. members of the thyroid hormone/retinoid receptor subfamily) have already been associated with cell cycle regulation, proliferation and development. It appears that our method is a suitable tool for detecting putative cell cycle regulators in the realm of known human transcription factors.
Keywords:Binding Sites, Computer Simulation, Conserved Sequence, Molecular Evolution, Hela Cells, Genetic Models, Statistical Models, Protein Binding, Nucleic Acid Regulatory Sequences, DNA Sequence Analysis, Statistical Distributions, Transcription Factors, Animals, Mice
Publisher:Oxford University Press
Number:Suppl 1
Page Range:i109-i115
Date:4 August 2004
Official Publication:https://doi.org/10.1093/bioinformatics/bth908
PubMed:View item in PubMed

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