Evidence map›Paper›PMID 31653198›Full record

ArticleBMC genomics2019

7C: Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs.

Jonas Ibn-Salem, Miguel A Andrade-Navarro

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Machine and Deep Learning Methods for Predicting 3D Genome Organization.Methods in molecular biology (Clifton, N.J.) · 2025
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. TF-COMB - Discovering grammar of transcription factor binding sites.Computational and structural biotechnology journal · 2022
    Article
  7. Article
  8. 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

2 authors at 1 institution in 1 country.

Jonas Ibn-SalemFaculty of Biology, Johannes Gutenberg University of Mainz, 55128, Mainz, Germany. j.ibn-salem@uni-mainz.de.ORCID http://orcid.org/0000-0001-9886-113X
Miguel A Andrade-NavarroFaculty of Biology, Johannes Gutenberg University of Mainz, 55128, Mainz, Germany. andrade@uni-mainz.de.
Johannes Gutenberg University Mainz · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKnowledge of the three-dimensional structure of the genome is necessary to understand how gene expression is regulated. Recent experimental techniques such as Hi-C or ChIA-PET measure long-range chromatin interactions genome-wide but are experimentally elaborate, have limited resolution and such data is only available for a limited number of cell types and tissues.

resultsWhile ChIP-seq was not designed to detect chromatin interactions, the formaldehyde treatment in the ChIP-seq protocol cross-links proteins with each other and with DNA. Consequently, also regions that are not directly bound by the targeted TF but interact with the binding site via chromatin looping are co-immunoprecipitated and sequenced. This produces minor ChIP-seq signals at loop anchor regions close to the directly bound site. We use the position and shape of ChIP-seq signals around CTCF motif pairs to predict whether they interact or not. We implemented this approach in a prediction method, termed Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs (7C). We applied 7C to all CTCF motif pairs within 1 Mb in the human genome and validated predicted interactions with high-resolution Hi-C and ChIA-PET. A single ChIP-seq experiment from known architectural proteins (CTCF, Rad21, Znf143) but also from other TFs (like TRIM22 or RUNX3) predicts loops accurately. Importantly, 7C predicts loops in cell types and for TF ChIP-seq datasets not used in training.

conclusion7C predicts chromatin loops which can help to associate TF binding sites to regulated genes. Furthermore, profiling of hundreds of ChIP-seq datasets results in novel candidate factors functionally involved in chromatin looping. Our method is available as an R/Bioconductor package: http://bioconductor.org/packages/sevenC .

Indexed as

Chromatin Immunoprecipitation SequencingNucleotide MotifsCCCTC-Binding FactorChromatinChromosomesHeLa CellsHumansProtein ConformationCCCTC-Binding FactorChromatin3C4C5C6C7CChIA-PETChIP-seqChromatin interactionsChromatin loopsHi-CPredictionThree-dimensional genome architectureTranscription factors

Identifiers

PMID31653198
PMCPMC6814980
OpenAlexW2982240859

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.