Cited by 680Epigenetics and DNA MethylationGenomics and Chromatin DynamicsCancer-related gene regulation

The DOI matches its Crossref record; 146 of the 146 references it cites were found in a registry or an index; none of the 134 sources its claims cite is checked for support yet.

Transcription factors as readers and effectors of DNA methylation

Open access
Zhu, Heng, Wang, Guohua, Qian, Jiang·2016·Nature Reviews Genetics

Abstract

Recent technological advances have made it possible to decode DNA methylomes at single-base-pair resolution under various physiological conditions. Many aberrant or differentially methylated sites have been discovered, but the mechanisms by which changes in DNA methylation lead to observed phenotypes, such as cancer, remain elusive. The classical view of methylation-mediated protein–DNA interactions is that only proteins with a methyl-CpG binding domain (MBD) can interact with methylated DNA. However, evidence is emerging to suggest that transcription factors lacking a MBD can also interact with methylated DNA. The identification of these proteins and the elucidation of their characteristics and the biological consequences of methylation-dependent transcription factor–DNA interactions are important stepping stones towards a mechanistic understanding of methylation-mediated biological processes, which have crucial implications for human development and disease.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This review/analysis argues that transcription factors lacking methyl-CpG binding domains can act as sequence-specific readers and effectors of methylated DNA, extending the classical MBD-only model. It combines in vitro discovery screens with in vivo ENCODE-based integration to show that many TF binding sites overlap highly methylated CpGs, while stressing unresolved causality and physiological relevance.

Key findings

  • Classical MBD proteins bind methylated DNA without strong sequence specificity, but emerging evidence shows TFs such as Kaiso, CEBPα, ZFP57/KAP1, KLF4 and others can recognize methylated motifs in a sequence-dependent manner.
  • A protein microarray probing 1,321 human TFs and 210 cofactors with 154 methylated motifs found that 150 motifs bound at least one protein; 41 TFs and 6 cofactors bound at least one methylated sequence, with binding spread across families such as zf-C2H2, homeobox, bHLH, forkhead, bZIP and HMG.
  • An MS/MS pulldown from mouse ES nuclear extracts identified 19 proteins preferring methylated over unmethylated probes, including known MBD proteins and TFs; a distinct set was found in neuronal progenitor cells.
  • In H1 human ES cells, 77,124 of 258,188 DNase I hypersensitive sites (29.9%) had average CpG methylation above 80%; for CEBPβ, 6,675 of 15,557 ChIP–seq peaks (42.9%) exceeded 80% methylation, and motif analysis found 3,894 of 15,557 CEBPβ sites (25.0%) carried a highly methylated CpG in the enriched motif, compared with 7.7% for E2F6, 5.2% for RFX5, 3.0% for KLF4 and 1.6% for BACH1.

Methods

  • This is a review/Analysis article synthesizing literature on DNA methylation readers and effectors, focused mainly on mammalian methylated CpG sites.
  • It describes high-throughput discovery approaches including tandem mass spectrometry pulldown, functional protein microarrays, DNA microarrays and ChIP–BS-seq.
  • It also reports an integrative in vivo analysis: ENCODE H1 hESC DNase I hypersensitivity peaks and whole-genome bisulfite methylome data were overlaid; TF ChIP–seq peaks were called with IDR and compared with methylation levels; MEME was used for motif discovery, with NRF1 and TAF1 as negative controls.

Limitations

  • The authors state that causality between DNA methylation and TF binding remains unclear, that a more comprehensive catalogue of readers/effectors is needed, and that in vivo validation and physiological relevance are still major challenges; many interactions rest mainly on in vitro evidence.
  • Method-specific limitations stated include: MS/MS probes are often generic, so sequence specificity is elusive; DNA microarrays require prior knowledge of a candidate TF; ChIP–BS-seq requires prior knowledge and suitable antibodies; and Kaiso in vivo results conflict across cell types, suggesting cell-type specificity.
  • Evident from the text: the in vivo integration is constrained by limited available ChIP–seq data (only six TFs in H1 cells) and uses a stringent >80% methylation cutoff, making the reported overlap estimates conservative; as a review, it does not present a single new experimental cohort.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1038/nrg.2016.83

Cites

146 of 146 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 of 134 cited sources checked · 0 supported · 0 flagged

  • It may state two separate claims as one. 38
  • Probably not a substantial claim. 7
42 of 42
  • The paper relies on this without support.

    NRF1 and TAF1 do not interact with methylated DNA.

    “we selected two TFs (nuclear respiratory factor 1 (NRF1) and transcription initiation factor TFIID subunit 1 (TAF1)), which are known not to interact with methylated DNA (based on our current knowledge), as negative controls”
  • The paper relies on this without support.

    DNA in heterochromatin is often methylated and tightly wrapped around nucleosomes, making it inaccessible to most transcription factors.

    “As DNA in heterochromatin is wrapped tightly around the nucleosomes and is often methylated, it is inaccessible to most TFs; pioneer TFs must possess special features to enable protein–DNA interactions.”
  • The paper relies on this without support.

    Splicing occurs co-transcriptionally.

    “However, it is now well-established that splicing occurs co-transcriptionally, which means that DNA modification could influence RNA splicing.”
  • The paper relies on this without support.

    The role of MBD proteins as non-sequence-specific methylation readers has been fairly well studied.

    “Although the role of MBD proteins, as non-sequence-specific methylation readers, has been fairly well-studied, the biological functions of an emerging class of sequence-specific methylation readers and/or effectors remain elusive.”
  • The paper relies on this without support.

    The biological functions of sequence-specific methylation readers and/or effectors remain elusive.

    “Although the role of MBD proteins, as non-sequence-specific methylation readers, has been fairly well-studied, the biological functions of an emerging class of sequence-specific methylation readers and/or effectors remain elusive.”
  • The paper relies on this without support.

    Methylation readers typically bind both methylated and unmethylated sites.

    “A methylation reader usually interacts with both methylated sites and unmethylated sites.”
  • The paper relies on this without support.

    Most transcription factors do not interact with methylated DNA.

    “Of note, this new concept does not refute the conventional view that most TFs do not interact with methylated DNA.”
  • The paper relies on this without support.

    The mechanism by which altered epigenetic state causes disease remains elusive.

    “However, the mechanism by which the altered epigenetic state causes disease remains elusive.”
8 of 8

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Kaiso studies are cited with the wrong reference numbers

    Minor

    The later passage assigns Kaiso's in-vivo binding studies to references 58-60, whereas the earlier passage identifies those studies as references 61-63.

  • The cited IDR reference describes a different method

    Minor

    The paper cites reference 66 for the Irreproducible Discovery Rate method, but its reference list identifies 66 as a paper on RNA-seq isoform modeling.

2 of 2

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Metadata

Authors
Zhu, H., Wang, G., & Qian, J.
Affiliations
Johns Hopkins University (US)
Corresponding author
  • Zhu, Heng
  • Qian, Jiang
Venue
Nature Reviews Genetics
Published
2016-08-01
Volume
17
Issue
9
Pages
551-565
ISSN
  • 1471-0056 (ISSN-L)
  • 1471-0064
OpenAlex
W2494121918
Cited by
649
References
146
Citations by year
2026: 35 · 2025: 46 · 2024: 81 · 2023: 53 · 2022: 107 · 2021: 102 · 2020: 74 · 2019: 62 · 2018: 44 · 2017: 38 · 2016: 7
FWCI
4.55
Type
journal article
Language
en
Open access
Locations
  • Nature Reviews Genetics (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Eye Institute (R01EY024580, R01EY023188)
  • National Institute of General Medical Sciences (R01GM111514)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Cancer-related gene regulation
Keywords
DNA methylation, transcription factors, methyl-CpG binding domain, protein-DNA interactions, methylated DNA, differentially methylated sites, aberrant DNA methylation, epigenetic regulation, cancer epigenetics, human development
MeSH terms
DNA, DNA-Binding Proteins, Humans, Transcription Factors, Transcription, Genetic, DNA Methylation

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