Publication

An all-to-all approach to the identification of sequence-specific readers for epigenetic DNA modifications on cytosine

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Last modified
  • 05/21/2025
Type of Material
Authors
    Guang Song, Johns Hopkins UniversityGouhua Wang, Harbin Institute of TechnologyXimei Luo, Harbin Institute of TechnologyYing Cheng, Emory UniversityQifeng Song, Johns Hopkins UniversityJun Wan, Johns Hopkins UniversityCedric Moore, Johns Hopkins UniversityHongjun Song, University of PennsylvaniaPeng Jin, Emory UniversityJiang Qian, Johns Hopkins UniversityHeng Zhu, Johns Hopkins University
Language
  • English
Date
  • 2021-02-04
Publisher
  • NATURE RESEARCH
Publication Version
Copyright Statement
  • © The Author(s) 2021
License
Final Published Version (URL)
Title of Journal or Parent Work
Volume
  • 12
Issue
  • 1
Start Page
  • 795
End Page
  • 795
Abstract
  • Epigenetic modifications of DNA play important roles in many biological processes. Identifying readers of these epigenetic marks is a critical step towards understanding the underlying mechanisms. Here, we present an all-to-all approach, dubbed digital affinity profiling via proximity ligation (DAPPL), to simultaneously profile human TF-DNA interactions using mixtures of random DNA libraries carrying different epigenetic modifications (i.e., 5-methylcytosine, 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxylcytosine) on CpG dinucleotides. Many proteins that recognize consensus sequences carrying these modifications in symmetric and/or hemi-modified forms are identified. We further demonstrate that the modifications in different sequence contexts could either enhance or suppress TF binding activity. Moreover, many modifications can affect TF binding specificity. Furthermore, symmetric modifications show a stronger effect in either enhancing or suppressing TF-DNA interactions than hemi-modifications. Finally, in vivo evidence suggests that USF1 and USF2 might regulate transcription via hydroxymethylcytosine-binding activity in weak enhancers in human embryonic stem cells.
Author Notes
Keywords
Research Categories
  • Health Sciences, Pharmacology
  • Biology, Neuroscience
  • Computer Science

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