Evidence map›Paper›PMID 27391817›Full record

ArticleGenome biology2016

Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity.

Vera Pancaldi, Enrique Carrillo-de-Santa-Pau, Biola Maria Javierre, David Juan, Peter Fraser, Mikhail Spivakov, Alfonso Valencia, Daniel Rico

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
4.2field-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

35 citing papers in PubMed, 67 citations in OpenAlex.

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  18. DAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    Article
  19. Mapping nucleosome and chromatin architectures: A survey of computational methods.Computational and structural biotechnology journal · 2022
    Review
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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

8 authors at 2 institutions in 2 countries.

Vera PancaldiStructural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain. vpancaldi@cnio.es.
Enrique Carrillo-de-Santa-PauStructural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
Biola Maria JavierreNuclear Dynamics Programme, The Babraham Institute, Cambridge, UK.
David JuanStructural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
Peter FraserNuclear Dynamics Programme, The Babraham Institute, Cambridge, UK.
Mikhail SpivakovNuclear Dynamics Programme, The Babraham Institute, Cambridge, UK.
Alfonso ValenciaStructural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
Daniel RicoStructural Biology and BioComputing Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain. drico@cnio.es.ORCID 0000-0002-6561-2310
Spanish National Cancer Research Centre · ESBabraham Institute · GB

Funding

Biotechnology and Biological Sciences Research Council BBS/E/B/000C0404Medical Research Council MR/L007150/1
6 · The paper itself

Abstract

backgroundNetwork analysis is a powerful way of modeling chromatin interactions. Assortativity is a network property used in social sciences to identify factors affecting how people establish social ties. We propose a new approach, using chromatin assortativity, to integrate the epigenomic landscape of a specific cell type with its chromatin interaction network and thus investigate which proteins or chromatin marks mediate genomic contacts.

resultsWe use high-resolution promoter capture Hi-C and Hi-Cap data as well as ChIA-PET data from mouse embryonic stem cells to investigate promoter-centered chromatin interaction networks and calculate the presence of specific epigenomic features in the chromatin fragments constituting the nodes of the network. We estimate the association of these features with the topology of four chromatin interaction networks and identify features localized in connected areas of the network. Polycomb group proteins and associated histone marks are the features with the highest chromatin assortativity in promoter-centered networks. We then ask which features distinguish contacts amongst promoters from contacts between promoters and other genomic elements. We observe higher chromatin assortativity of the actively elongating form of RNA polymerase 2 (RNAPII) compared with inactive forms only in interactions between promoters and other elements.

conclusionsContacts among promoters and between promoters and other elements have different characteristic epigenomic features. We identify a possible role for the elongating form of RNAPII in mediating interactions among promoters, enhancers, and transcribed gene bodies. Our approach facilitates the study of multiple genome-wide epigenomic profiles, considering network topology and allowing the comparison of chromatin interaction networks.

Indexed as

EpigenomicsAnimalsChromatinChromatin Assembly and DisassemblyComputational BiologyEmbryonic Stem CellsGenomeHistone CodeHistonesHumansMicePromoter Regions, GeneticRegulatory Sequences, Nucleic AcidChromatinHistones3D genomeAssortativityChromatin Interaction NetworkEmbryonic stem cellsEnhancersEpigenomicsPolycombPromoter Capture Hi-CRNA polymerase

Identifiers

PMID27391817
PMCPMC4939006
OpenAlexW2461061549

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.