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Motif oriented high-resolution analysis of ChIP-seq data reveals the topological order of CTCF and cohesin proteins on DNA.

ABSTRACT: ChIP-seq provides a wealth of information on the approximate location of DNA-binding proteins genome-wide. It is known that the targeted motifs in most cases can be found at the peak centers. A high resolution mapping of ChIP-seq peaks could in principle allow the fine mapping of the protein constituents within protein complexes, but the current ChIP-seq analysis pipelines do not target the basepair resolution strand specific mapping of peak summits.The approach proposed here is based on i) locating regions that are bound by a sufficient number of proteins constituting a complex; ii) determining the position of the underlying motif using either a direct or a de novo motif search approach; and iii) determining the exact location of the peak summits with respect to the binding motif in a strand specific manner. We applied this method for analyzing the CTCF/cohesin complex, which holds together DNA loops. The relative positions of the constituents of the complex were determined with one-basepair estimated accuracy. Mapping the positions on a 3D model of DNA made it possible to deduce the approximate local topology of the complex that allowed us to predict how the CTCF/cohesin complex locks the DNA loops. As the positioning of the proteins was not compatible with previous models of loop closure, we proposed a plausible "double embrace" model in which the DNA loop is held together by two adjacent cohesin rings in such a way that the ring anchored by CTCF to one DNA duplex encircles the other DNA double helix and vice versa.A motif-centered, strand specific analysis of ChIP-seq data improves the accuracy of determining peak positions. If a genome contains a large number of binding sites for a given protein complex, such as transcription factor heterodimers or transcription factor/cofactor complexes, the relative position of the constituent proteins on the DNA can be established with an accuracy that allow one to deduce the local topology of the protein complex. The proposed high resolution mapping approach of ChIP-seq data is applicable for detecting the contact topology of DNA-binding protein complexes.

SUBMITTER: Nagy G

PROVIDER: S-EPMC4986361 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Motif oriented high-resolution analysis of ChIP-seq data reveals the topological order of CTCF and cohesin proteins on DNA.

Nagy Gergely G Czipa Erik E Steiner László L Nagy Tibor T Pongor Sándor S Nagy László L Barta Endre E

BMC genomics 20160815 1

<h4>Background</h4>ChIP-seq provides a wealth of information on the approximate location of DNA-binding proteins genome-wide. It is known that the targeted motifs in most cases can be found at the peak centers. A high resolution mapping of ChIP-seq peaks could in principle allow the fine mapping of the protein constituents within protein complexes, but the current ChIP-seq analysis pipelines do not target the basepair resolution strand specific mapping of peak summits.<h4>Results</h4>The approac ...[more]

PMID: 27526722

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Project description:BackgroundMotif enrichment analysis of transcription factor ChIP-seq data can help identify transcription factors that cooperate or compete. Previously, little attention has been given to comparative motif enrichment analysis of pairs of ChIP-seq experiments, where the binding of the same transcription factor is assayed under different conditions. Such comparative analysis could potentially identify the distinct regulatory partners/competitors of the assayed transcription factor under different conditions or at different stages of development.ResultsWe describe a new methodology for identifying sequence motifs that are differentially enriched in one set of DNA or RNA sequences relative to another set, and apply it to paired ChIP-seq experiments. We show that, using paired ChIP-seq data for a single transcription factor, differential motif enrichment analysis identifies all the known key transcription factors involved in the transformation of non-cancerous immortalized breast cells (MCF10A-ER-Src cells) into cancer stem cells whereas non-differential motif enrichment analysis does not. We also show that differential motif enrichment analysis identifies regulatory motifs that are significantly enriched at constrained locations within the bound promoters, and that these motifs are not identified by non-differential motif enrichment analysis. Our methodology differs from other approaches in that it leverages both comparative enrichment and positional enrichment of motifs in ChIP-seq peak regions or in the promoters of genes bound by the transcription factor.ConclusionsWe show that differential motif enrichment analysis of paired ChIP-seq experiments offers biological insights not available from non-differential analysis. In contrast to previous approaches, our method detects motifs that are enriched in a constrained region in one set of sequences, but not enriched in the same region in the comparative set. We have enhanced the web-based CentriMo algorithm to allow it to perform the constrained differential motif enrichment analysis described in this paper, and CentriMo's on-line interface (http://meme.ebi.edu.au) provides dozens of databases of DNA- and RNA-binding motifs from a full range of organisms. All data and output files presented here are available at http://research.imb.uq.edu.au/t.bailey/supplementary\_data/Lesluyes2014.

Dataset Information

Motif oriented high-resolution analysis of ChIP-seq data reveals the topological order of CTCF and cohesin proteins on DNA.

Publications

Motif oriented high-resolution analysis of ChIP-seq data reveals the topological order of CTCF and cohesin proteins on DNA.

Similar Datasets

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