Evidence map›Paper›PMID 25673498›Full record

ArticleScientific reports2015

Chromatin modifications and genomic contexts linked to dynamic DNA methylation patterns across human cell types.

Haidan Yan, Dongwei Zhang, Hongbo Liu, Yanjun Wei, Jie Lv, Fang Wang, Chunlong Zhang, Qiong Wu, Jianzhong Su, Yan Zhang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

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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

10 authors at 3 institutions in 1 country.

Haidan YanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Dongwei ZhangThe Department of General Surgery, The Second Affiliated Hospital, Harbin Medical University, Harbin 150086, China.
Hongbo LiuSchool of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150001, China.
Yanjun WeiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Jie LvSchool of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150001, China.
Fang WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Chunlong ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Qiong WuSchool of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150001, China.
Jianzhong SuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yan ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Harbin Medical University · CNHarbin Institute of Technology · CNFujian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA methylation is related closely to sequence contexts and chromatin modifications; however, their potential differences in different genomic regions across cell types remain largely unexplored. We used publicly available genome-scale DNA methylation and histone modification profiles to study their relationships among different genomic regions in human embryonic stem cells (H1), H1-derived neuronal progenitor cultured cells (NPC), and foetal fibroblasts (IMR90) using the Random forests classifier. Histone modifications achieved high accuracy in modelling DNA methylation patterns on a genome scale in the three cell types. The inclusion of sequence features helped improve accuracy only in non-promoter regions of IMR90. Furthermore, the top six feature combinations obtained by mean decrease Gini were important indicators of different DNA methylation patterns, suggesting that H3K4me2 and H3K4me3 are important indicators that are independent of genomic regions and cell types. H3K9me3 was IMR90-specific and exhibited a genomic region-specific correlation with DNA methylation. Variations of essential chromatin modification signals may effectively discriminate changes of DNA methylation between H1 and IMR90. Genes with different co-variations of epigenetic marks exhibited genomic region-specific biological relevance. This study provides an integrated strategy to identify systematically essential epigenetic and genetic elements of genomic region-specific and cell type-specific DNA methylation patterns.

Indexed as

DNA MethylationEpigenesis, GeneticEpigenomicsCell LineChromatinCpG IslandsEmbryonic Stem CellsGenetic VariationGenomeHistonesHumansMolecular Sequence AnnotationOrgan SpecificityChromatinHistones

Identifiers

PMID25673498
PMCPMC4325317
OpenAlexW2055195009

What OpenQuestion holds

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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.