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

UBC Faculty Research and Publications

Improving analysis of transcription factor binding sites within ChIP-Seq data based on topological motif enrichment Worsley Hunt, Rebecca; Mathelier, Anthony; del Peso, Luis; Wasserman, Wyeth W.

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.

Item Metadata

Title	Improving analysis of transcription factor binding sites within ChIP-Seq data based on topological motif enrichment
Creator	Worsley Hunt, Rebecca; Mathelier, Anthony; del Peso, Luis; Wasserman, Wyeth W.
Contributor	Child and Family Research Institute
Publisher	BioMed Central
Date Issued	2014-06-13
Description	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.
Subject	Chromatin immunoprecipitation; ChIP-Seq; Motif prediction; Over-representation analysis; Regulation; Sequence analysis; Transcription factor; Transcription factor binding site; Visualization
Genre	Article
Type	Text
Language	eng
Date Available	2015-11-15
Provider	Vancouver : University of British Columbia Library
Rights	Attribution 4.0 International (CC BY 4.0)
DOI	10.14288/1.0228397
URI	http://hdl.handle.net/2429/55331
Affiliation	Medical Genetics, Department of; Medicine, Faculty of; Molecular Medicine and Therapeutics, Centre for; Science, Faculty of; Non UBC
Citation	BMC Genomics. 2014 Jun 13;15(1):472
Publisher DOI	10.1186/1471-2164-15-472
Peer Review Status	Reviewed
Scholarly Level	Faculty
Copyright Holder	Worsley Hunt et al.; licensee BioMed Central Ltd.
Rights URI	http://creativecommons.org/licenses/by/4.0/
Aggregated Source Repository	DSpace

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