Open Access Research article

Improving analysis of transcription factor binding sites within ChIP-Seq data based on topological motif enrichment

Rebecca Worsley Hunt12, Anthony Mathelier2, Luis del Peso3 and Wyeth W Wasserman24*

Author Affiliations

1 Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada

2 Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada

3 Universidad Autónoma de Madrid, Biochemistry, Madrid 28029, Spain

4 Centre for Molecular Medicine and Therapeutics, 950 W.28th Avenue, Vancouver, BC V5Z 4H4, Canada

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BMC Genomics 2014, 15:472  doi:10.1186/1471-2164-15-472

Published: 13 June 2014

Abstract

Background

Chromatin immunoprecipitation (ChIP) coupled to high-throughput sequencing (ChIP-Seq) techniques can reveal DNA regions bound by transcription factors (TF). Analysis of the ChIP-Seq regions is now a central component in gene regulation studies. The need remains strong for methods to improve the interpretation of ChIP-Seq data and the study of specific TF binding sites (TFBS).

Results

We introduce a set of methods to improve the interpretation of ChIP-Seq data, including the inference of mediating TFs based on TFBS motif over-representation analysis and the subsequent study of spatial distribution of TFBSs. TFBS over-representation analysis applied to ChIP-Seq data is used to detect which TFBSs arise more frequently than expected by chance. Visualization of over-representation analysis results with new composition-bias plots reveals systematic bias in over-representation scores. We introduce the BiasAway background generating software to resolve the problem. A heuristic procedure based on topological motif enrichment relative to the ChIP-Seq peaks’ local maximums highlights peaks likely to be directly bound by a TF of interest. The results suggest that on average two-thirds of a ChIP-Seq dataset’s peaks are bound by the ChIP’d TF; the origin of the remaining peaks remaining undetermined. Additional visualization methods allow for the study of both inter-TFBS spatial relationships and motif-flanking sequence properties, as demonstrated in case studies for TBP and ZNF143/THAP11.

Conclusions

Topological properties of TFBS within ChIP-Seq datasets can be harnessed to better interpret regulatory sequences. Using GC content corrected TFBS over-representation analysis, combined with visualization techniques and analysis of the topological distribution of TFBS, we can distinguish peaks likely to be directly bound by a TF. The new methods will empower researchers for exploration of gene regulation and TF binding.

Keywords:
Chromatin immunoprecipitation; ChIP-Seq; Motif prediction; Over-representation analysis; Regulation; Sequence analysis; Transcription factor; Transcription factor binding site; Visualization