Evidence map›Paper›PMID 33008446›Full record

ArticleEpigenetics & chromatin2020

Characterization of universal features of partially methylated domains across tissues and species.

Benjamin E Decato, Jianghan Qu, Xiaojing Ji, Elvin Wagenblast, Simon R V Knott, Gregory J Hannon, Andrew D Smith

Open access · goldAbstract read
In one paragraph

Article in Epigenetics & chromatin, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

16 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
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  6. Epigenomic insights into common human disease pathology.Cellular and molecular life sciences : CMLS · 2024
    Review
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  8. Review
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  13. Review
  14. The Role of DNA Methylation and DNA Methyltransferases in Cancer.Advances in experimental medicine and biology · 2022
    Article
  15. Article
  16. 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

7 authors at 4 institutions in 3 countries.

Benjamin E DecatoQuantitative and Computational Biology Section, University of Southern California, Childs Way, Los Angeles, California, USA. decato@alumni.usc.edu.ORCID 0000-0003-3092-1102
Jianghan QuQuantitative and Computational Biology Section, University of Southern California, Childs Way, Los Angeles, California, USA.
Xiaojing JiQuantitative and Computational Biology Section, University of Southern California, Childs Way, Los Angeles, California, USA.
Elvin WagenblastWatson School of Biological Sciences, Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York, 11724, USA.
Simon R V KnottWatson School of Biological Sciences, Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York, 11724, USA.
Gregory J HannonWatson School of Biological Sciences, Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York, 11724, USA.
Andrew D SmithQuantitative and Computational Biology Section, University of Southern California, Childs Way, Los Angeles, California, USA. andrewds@usc.edu.
University of Southern California · USHoward Hughes Medical Institute · USCedars-Sinai Medical Center · USQB3 · US

Funding

Analytic tools to examine high-resolution and genome-scale DNA methylation dataR01HG005238 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI SMITH, ANDREW DAVID · 2010 to 2013
$1.5M
Cancer Research UK 21143NHGRI NIH HHS R01 HG005238NIH HHS HG005238
6 · The paper itself

Abstract

backgroundPartially methylated domains (PMDs) are a hallmark of epigenomes in reproducible and specific biological contexts, including cancer cells, the placenta, and cultured cell lines. Existing methods for deciding whether PMDs exist in a sample, as well as their identification, are few, often tailored to specific biological questions, and require high coverage samples for accurate identification.

resultsIn this study, we outline a set of axioms that take a step towards a functional definition for PMDs, describe an improved method for comparable PMD detection across samples with substantially differing sequencing depths, and refine the decision criteria for whether a sample contains PMDs using a data-driven approach. Applying our method to 267 methylomes from 7 species, we corroborated recent results regarding the general association between replication timing and PMD state, and report identification of several reproducibly "escapee" genes within late-replicating domains that escape the reduced expression and hypomethylation of their immediate genomic neighborhood. We also explored the discordant PMD state of orthologous genes between human and mouse, and observed a directional association of PMD state with gene expression and local gene density.

conclusionsOur improved method makes low sequencing depth, population-level studies of PMD variation possible and our results further refine the model of PMD formation as one where sequence context and regional epigenomic features both play a role in gradual genome-wide hypomethylation.

Indexed as

DNA MethylationEpigenomeAnimalsCell Line, TumorCells, CulturedFemaleGene Expression Regulation, NeoplasticHumansLungMammary Glands, HumanMiceMice, Inbred C57BLOrgan SpecificityPlacentaPregnancySpecies SpecificityCancerDNA methylationHidden Markov modelsPartially methylated domains

Identifiers

PMID33008446
PMCPMC7532633
OpenAlexW3091750472

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.