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


BACKGROUND
Further details and supplementary data can be obtained from http://corg.molgen.mpg.de/cellcycle
Dieterich
Christoph
C
Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany. christoph.dieterich@molgen.mpg.de
Rahmann
Sven
S
Vingron
Martin
M
D000818:Animals; D001665:Binding Sites; D003198:Computer Simulation; D017124:Conserved Sequence / Q000235:genetics*; D019143:Evolution, Molecular; D006367:HeLa Cells; D006801:Humans; D051379:Mice; D008957:Models, Genetic; D015233:Models, Statistical; D011485:Protein Binding; D012045:Regulatory Sequences, Nucleic Acid / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D016008:Statistical Distributions; D014157:Transcription Factors / Q000235:genetics*
D014157:Transcription Factors