Evidence map›Paper›PMID 30188887›Full record

ArticlePLoS computational biology2018

Inter-nucleosomal communication between histone modifications for nucleosome phasing.

Weizhong Chen, Yi Liu, Shanshan Zhu, Guoyu Chen, Jing-Dong J Han

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 51% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. 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

5 authors at 2 institutions in 1 country.

Weizhong ChenKey Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Yi LiuKey Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Shanshan ZhuKey Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Guoyu ChenKey Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Jing-Dong J HanKey Laboratory of Computational Biology, CAS Center for Excellence in Molecular Cell Science, Collaborative Innovation Center for Genetics and Developmental Biology, Chinese Academy of Sciences-Max Planck Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.ORCID 0000-0002-9270-7139
Shanghai Institutes for Biological Sciences · CNBeijing Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Combinatorial effects of epigenetic modifications on transcription activity have been proposed as "histone codes". However, it is unclear whether there also exist inter-nucleosomal communications among epigenetic modifications at single nucleosome level, and if so, what functional roles they play. Meanwhile, how clear nucleosome patterns, such as nucleosome phasing and depletion, are formed at functional regions remains an intriguing enigma. To address these questions, we developed a Bayesian network model for interactions among different histone modifications across neighboring nucleosomes, based on the framework of dynamic Bayesian network (DBN). From this model, we found that robust inter-nucleosomal interactions exist around transcription start site (TSS), transcription termination sites (TTS) or around CTCF binding sites; and these inter-nucleosomal interactions are often involved in transcription regulation. In addition to these general principles, DBN also uncovered a novel specific epigenetic interaction between H2A.Z and H4K20me1 on neighboring nucleosomes, involved in nucleosome free region (NFR) and nucleosome phasing establishment or maintenance. The level of negative correlation between neighboring H2A.Z and H4K20me1 strongly correlate with the size of NFR and the strength of nucleosome phasing around TSS. Our study revealed inter-nucleosomal communications as important players in signal propagation, chromatin remodeling and transcription regulation.

Indexed as

Histone CodeBayes TheoremBinding SitesCD4-Positive T-LymphocytesChromatinChromatin Assembly and DisassemblyComputational BiologyEpigenesis, GeneticGene Expression RegulationHistonesHumansNucleosomesProtein Processing, Post-TranslationalSignal TransductionTranscription FactorsTranscription, GeneticChromatinHistonesNucleosomesTranscription Factors

Identifiers

PMID30188887
PMCPMC6126837
OpenAlexW2891617050

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.