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Published on: July 21, 2014
Identification of context-dependent motifs by contrasting ChIP binding data.
Mike J Mason1, Kathrin Plath, Qing Zhou
1Department of Statistics, University of California, Los Angeles, CA 90095, USA.
Bioinformatics (Oxford, England)
|September 28, 2010
Summary
A new motif finding method, Contrast Motif Finder (CMF), accurately identifies transcription factor (TF) binding motifs. CMF reveals context-dependent TF binding and competitive interactions, advancing gene regulation studies.
Area of Science:
- Genomics and Molecular Biology
- Bioinformatics and Computational Biology
Background:
- DNA-binding proteins, including transcription factors (TFs), are critical regulators of gene expression.
- TF binding sites share sequence patterns (motifs), but one TF can recognize multiple motifs, and vice versa, influenced by co-regulators.
- Detecting context-dependent TF binding motifs is challenging due to the complexity of TF-DNA interactions.
Purpose of the Study:
- To develop a computational method for de novo identification of differentially enriched motifs.
- To analyze TF binding data and uncover context-specific TF-motif relationships.
- To identify novel binding motifs and understand TF competition in gene regulation.
Main Methods:
- Developed Contrast Motif Finder (CMF), a novel algorithm for identifying motifs differentially enriched in two sequence sets.
- Applied CMF to genome-wide transcription factor binding datasets from mouse embryonic stem cells.
- Compared CMF performance against established motif-finding methodologies.
Main Results:
- CMF demonstrated significantly higher accuracy in motif identification compared to existing methods.
- Identified distinct motifs potentially recognized by Oct4, dependent on co-regulator presence.
- Detected subtle motif signals indicative of competitive binding between Sox2 and Tcf3.
Conclusions:
- CMF is an effective tool for discovering context-dependent transcription factor binding motifs.
- The findings provide new insights into the nuanced regulation of gene expression by TFs.
- The CMF software is publicly available for academic research.
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