Evidence map›Paper›PMID 29409522›Full record

ArticleEpigenetics & chromatin2018

Systematic prediction of DNA shape changes due to CpG methylation explains epigenetic effects on protein-DNA binding.

Satyanarayan Rao, Tsu-Pei Chiu, Judith F Kribelbauer, Richard S Mann, Harmen J Bussemaker, Remo Rohs

Open access · goldAbstract read
In one paragraph

Article in Epigenetics & chromatin, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
3.5field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed, 96 citations in OpenAlex.

  1. Article
  2. Article
  3. Structural and cellular insights into DCTPP1 antagonists and their synergistic action with DNMT inhibitors.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  4. Epigenetic Modulation of the ACE System Underlies the Slow Aerobic Muscle Phenotype and Metabolic Exercise Response.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026
    Article
  5. Article
  6. Review
  7. DNA methylation shapes transcription factor binding beyond canonical CpG contexts.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. Article
  9. Epigenetic networks coordinate DNA methylation across the genome.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Review
  10. Article
  11. Review
  12. Article
  13. Modeling DNA methyltransferase function to predict epigenetic correlation patterns in healthy and cancer cells.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. DNA Hyperstructure.ACS omega · 2024
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Satyanarayan RaoComputational Biology and Bioinformatics Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA, 90089, USA.
Tsu-Pei ChiuComputational Biology and Bioinformatics Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA, 90089, USA.
Judith F KribelbauerDepartment of Biological Sciences, Columbia University, New York, NY, 10027, USA.
Richard S MannDepartment of Systems Biology, Columbia University, New York, NY, 10032, USA.
Harmen J BussemakerDepartment of Biological Sciences, Columbia University, New York, NY, 10027, USA. hjb2004@columbia.edu.
Remo RohsComputational Biology and Bioinformatics Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA, 90089, USA. rohs@usc.edu.ORCID 0000-0003-1752-1884
Columbia University · USUniversity of Southern California · US

Funding

TRAINING IN CELLULAR, MOLECULAR AND BIOPHYSICAL STUDIEST32GM008224 · NIGMS · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI LIEM, RONALD K. · 1987 to 2021
$9.9M
Inferring regulatory circuitry from microarray dataR01HG003008 · NHGRI · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI BUSSEMAKER, HARMEN J · 2004 to 2020
$7.0M
Interpreting and Deploying Genomic Information During Animal DevelopmentR35GM118336 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI RICHARD S MANN · 2016 to 2026
$6.9M
Genome analysis based on the integration of DNA sequence and shapeR01GM106056 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ROHS, REMO · 2014 to 2017
$1.3M
Alfred P. Sloan Foundation BR2013-082Howard Hughes Medical InstituteNHGRI NIH HHS R01 HG003008NHGRI NIH HHS R01HG003008NIGMS NIH HHS R01 GM106056NIGMS NIH HHS R01GM106056NIGMS NIH HHS R35 GM118336NIGMS NIH HHS R35GM118336NIGMS NIH HHS T32 GM008224
6 · The paper itself

Abstract

backgroundDNA shape analysis has demonstrated the potential to reveal structure-based mechanisms of protein-DNA binding. However, information about the influence of chemical modification of DNA is limited. Cytosine methylation, the most frequent modification, represents the addition of a methyl group at the major groove edge of the cytosine base. In mammalian genomes, cytosine methylation most frequently occurs at CpG dinucleotides. In addition to changing the chemical signature of C/G base pairs, cytosine methylation can affect DNA structure. Since the original discovery of DNA methylation, major efforts have been made to understand its effect from a sequence perspective. Compared to unmethylated DNA, however, little structural information is available for methylated DNA, due to the limited number of experimentally determined structures. To achieve a better mechanistic understanding of the effect of CpG methylation on local DNA structure, we developed a high-throughput method, methyl-DNAshape, for predicting the effect of cytosine methylation on DNA shape.

resultsUsing our new method, we found that CpG methylation significantly altered local DNA shape. Four DNA shape features-helix twist, minor groove width, propeller twist, and roll-were considered in this analysis. Distinct distributions of effect size were observed for different features. Roll and propeller twist were the DNA shape features most strongly affected by CpG methylation with an effect size depending on the local sequence context. Methylation-induced changes in DNA shape were predictive of the measured rate of cleavage by DNase I and suggest a possible mechanism for some of the methylation sensitivities that were recently observed for human Pbx-Hox complexes.

conclusionsCpG methylation is an important epigenetic mark in the mammalian genome. Understanding its role in protein-DNA recognition can further our knowledge of gene regulation. Our high-throughput methyl-DNAshape method can be used to predict the effect of cytosine methylation on DNA shape and its subsequent influence on protein-DNA interactions. This approach overcomes the limited availability of experimental DNA structures that contain 5-methylcytosine.

Indexed as

DNA MethylationAnimalsBase SequenceCpG IslandsCytosineDNADNA-Binding ProteinsEpigenesis, GeneticHumansMammalsModels, MolecularNucleic Acid ConformationCytosineDNADNA-Binding Proteins5-methylcytosineDNA methylationDNase I cleavage sensitivityDNA structureEpigeneticsHuman Hox protein binding specificitymethyl-DNAshape

Identifiers

PMID29409522
PMCPMC5800008
OpenAlexW2792170325

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.