Evidence map›Paper›PMID 22721266›Full record

ArticleBMC genomics2012

Transcription factor co-localization patterns affect human cell type-specific gene expression.

Dennis Wang, Augusto Rendon, Willem Ouwehand, Lorenz Wernisch

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 32% 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, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. LRIG and cancer prognosis.Acta oncologica (Stockholm, Sweden) · 2014
    Review
  6. Article
  7. Article
  8. Review
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

4 authors at 2 institutions in 1 country.

Dennis WangMRC Biostatistics Unit, Institute of Public Health, Robinson Way, Cambridge, UK. dennis.wang@mrc-bsu.cam.ac.uk
Augusto Rendon
Willem Ouwehand
Lorenz Wernisch
University of Cambridge · GBMRC Biostatistics Unit · GB

Funding

British Heart Foundation RG/09/012/28096Department of Health RP-PG-0310-1002Medical Research Council MC_U105260799
6 · The paper itself

Abstract

backgroundCellular development requires the precise control of gene expression states. Transcription factors are involved in this regulatory process through their combinatorial binding with DNA. Information about transcription factor binding sites can help determine which combinations of factors work together to regulate a gene, but it is unclear how far the binding data from one cell type can inform about regulation in other cell types.

resultsBy integrating data on co-localized transcription factor binding sites in the K562 cell line with expression data across 38 distinct hematopoietic cell types, we developed regression models to describe the relationship between the expression of target genes and the transcription factors that co-localize nearby. With K562 binding sites identifying the predictors, the proportion of expression explained by the models is statistically significant only for monocytic cells (p-value< 0.001), which are closely related to K562. That is, cell type specific binding patterns are crucial for choosing the correct transcription factors for the model. Comparison of predictors obtained from binding sites in the GM12878 cell line with those from K562 shows that the amount of difference between binding patterns is directly related to the quality of the prediction. By identifying individual genes whose expression is predicted accurately by the binding sites, we are able to link transcription factors FOS, TAF1 and YY1 to a sparsely studied gene LRIG2. We also find that the activity of a transcription factor may be different depending on the cell type and the identity of other co-localized factors.

conclusionOur approach shows that gene expression can be explained by a modest number of co-localized transcription factors, however, information on cell-type specific binding is crucial for understanding combinatorial gene regulation.

Indexed as

Gene Expression RegulationBinding SitesCell Line, TumorChromatin ImmunoprecipitationGenome, HumanHumansK562 CellsMembrane GlycoproteinsProto-Oncogene Proteins c-fosProto-Oncogene Proteins c-mycTranscription FactorsYY1 Transcription FactorLRIG2 protein, humanMembrane GlycoproteinsProto-Oncogene Proteins c-fosProto-Oncogene Proteins c-mycTranscription FactorsYY1 protein, humanYY1 Transcription Factor

Identifiers

PMID22721266
PMCPMC3441573
OpenAlexW2020114580

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.