Evidence map›Paper›PMID 26169043›Full record

ArticleScientific reports2015

Chromatin states modify network motifs contributing to cell-specific functions.

Hongying Zhao, Tingting Liu, Ling Liu, Guanxiong Zhang, Lin Pang, Fulong Yu, Huihui Fan, Yanyan Ping, Li Wang, Chaohan Xu and 2 more

Abstract 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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
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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

12 authors.

Hongying ZhaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Tingting LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Ling LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Guanxiong ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Lin PangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Fulong YuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Huihui FanCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yanyan PingCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Li WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Chaohan XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Yun Xiao1] College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China [2] Key Laboratory of Cardiovascular Medicine Research, Harbin Medical University, Ministry of Education.
Xia LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epigenetic modification can affect many important biological processes, such as cell proliferation and apoptosis. It can alter chromatin conformation and contribute to gene regulation. To investigate how chromatin states associated with network motifs, we assembled chromatin state-modified regulatory networks by combining 269 ChIP-seq data and chromatin states in four cell types. We found that many chromatin states were significantly associated with network motifs, especially for feedforward loops (FFLs). These distinct chromatin state compositions contribute to different expression levels and translational control of targets in FFLs. Strikingly, the chromatin state-modified FFLs were highly cell-specific and, to a large extent, determined cell-selective functions, such as the embryonic stem cell-specific bivalent modification-related FFL with an important role in poising developmentally important genes for expression. Besides, comparisons of chromatin state-modified FFLs between cancerous/stem and primary cell lines revealed specific type of chromatin state alterations that may act together with motif structural changes cooperatively contribute to cell-to-cell functional differences. Combination of these alterations could be helpful in prioritizing candidate genes. Together, this work highlights that a dynamic epigenetic dimension can help network motifs to control cell-specific functions.

Indexed as

Epigenesis, GeneticGene Regulatory NetworksNucleotide MotifsCell LineChromatinGene Expression RegulationGene Knockdown TechniquesHumansNeoplasmsOrgan SpecificityTranscription, GeneticChromatin

Identifiers

PMID26169043
PMCPMC4500950

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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.