Literature DB >> 26411866

Identification of coupling DNA motif pairs on long-range chromatin interactions in human K562 cells.

Ka-Chun Wong1, Yue Li2, Chengbin Peng3.   

Abstract

MOTIVATION: The protein-DNA interactions between transcription factors (TFs) and transcription factor binding sites (TFBSs, also known as DNA motifs) are critical activities in gene transcription. The identification of the DNA motifs is a vital task for downstream analysis. Unfortunately, the long-range coupling information between different DNA motifs is still lacking. To fill the void, as the first-of-its-kind study, we have identified the coupling DNA motif pairs on long-range chromatin interactions in human.
RESULTS: The coupling DNA motif pairs exhibit substantially higher DNase accessibility than the background sequences. Half of the DNA motifs involved are matched to the existing motif databases, although nearly all of them are enriched with at least one gene ontology term. Their motif instances are also found statistically enriched on the promoter and enhancer regions. Especially, we introduce a novel measurement called motif pairing multiplicity which is defined as the number of motifs that are paired with a given motif on chromatin interactions. Interestingly, we observe that motif pairing multiplicity is linked to several characteristics such as regulatory region type, motif sequence degeneracy, DNase accessibility and pairing genomic distance. Taken into account together, we believe the coupling DNA motif pairs identified in this study can shed lights on the gene transcription mechanism under long-range chromatin interactions.
AVAILABILITY AND IMPLEMENTATION: The identified motif pair data is compressed and available in the supplementary materials associated with this manuscript. CONTACT: kc.w@cityu.edu.hk SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2015        PMID: 26411866     DOI: 10.1093/bioinformatics/btv555

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  5 in total

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2.  A systematic study of motif pairs that may facilitate enhancer-promoter interactions.

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Journal:  J Integr Bioinform       Date:  2022-02-07

3.  A Novel Approach to Predict Core Residues on Cancer-Related DNA-Binding Domains.

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Journal:  Cancer Inform       Date:  2016-06-02

4.  Uncovering direct and indirect molecular determinants of chromatin loops using a computational integrative approach.

Authors:  Raphaël Mourad; Lang Li; Olivier Cuvier
Journal:  PLoS Comput Biol       Date:  2017-05-23       Impact factor: 4.475

5.  Computational Detection of Stage-Specific Transcription Factor Clusters during Heart Development.

Authors:  Sebastian Zeidler; Cornelia Meckbach; Rebecca Tacke; Farah S Raad; Angelica Roa; Shizuka Uchida; Wolfram-Hubertus Zimmermann; Edgar Wingender; Mehmet Gültas
Journal:  Front Genet       Date:  2016-03-23       Impact factor: 4.599

  5 in total

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