Evidence map›Paper›PMID 21156067›Full record

ArticleBMC genomics2010

Human transcriptional interactome of chromatin contribute to gene co-expression.

Xiao Dong, Chao Li, Yunqin Chen, Guohui Ding, Yixue Li

Abstract read
In one paragraph

Article in BMC genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Chromatin Hubs: A biological and computational outlook.Computational and structural biotechnology journal · 2022
    Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Unravelling global genome organization by 3C-seq.Seminars in cell & developmental biology · 2012
    Review
  12. Article
  13. 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.

Xiao DongKey Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, PR China.
Chao Li
Yunqin Chen
Guohui Ding
Yixue Li

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTranscriptional interactome of chromatin is one of the important mechanisms in gene transcription regulation. By chromatin conformation capture and 3D FISH experiments, several chromatin interactions cases among sequence-distant genes or even inter-chromatin genes were reported. However, on genomics level, there is still little evidence to support these mechanisms. Recently based on Hi-C experiment, a genome-wide picture of chromatin interactions in human cells was presented. It provides a useful material for analysing whether the mechanism of transcriptional interactome is common.

resultsThe main work here is to demonstrate whether the effects of transcriptional interactome on gene co-expression exist on genomic level. While controlling the effects of transcription factors control similarities (TCS), we tested the correlation between Hi-C interaction and the mutual ranks of gene co-expression rates (provided by COXPRESdb) of intra-chromatin gene pairs. We used 6,084 genes with both TF annotation and co-expression information, and matched them into 273,458 pairs with similar Hi-C interaction ranks in different cell types. The results illustrate that co-expression is strongly associated with chromatin interaction. Further analysis using GO annotation reveals potential correlation between gene function similarity, Hi-C interaction and their co-expression.

conclusionsAccording to the results in this research, the intra-chromatin interactome may have relation to gene function and associate with co-expression. This study provides evidence for illustrating the effect of transcriptional interactome on transcription regulation.

Indexed as

Gene Expression RegulationTranscription, GeneticChromatinChromosomes, HumanHumansNucleic Acid ConformationProtein BindingTranscription FactorsChromatinTranscription Factors

Identifiers

PMID21156067
PMCPMC3053592

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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.