Evidence map›Paper›PMID 24603674›Full record

ArticlePLoS genetics2014

The functional consequences of variation in transcription factor binding.

Darren A Cusanovich, Bryan Pavlovic, Jonathan K Pritchard, Yoav Gilad

Open access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 139 papers.

0numbers the graph read from it
0cells of the map it votes in
139citing papers in PubMed
12.2field-weighted citation impact, top 1% 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

139 citing papers in PubMed, 235 citations in OpenAlex.

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  13. Binding profiles for 961Genome research · 2024
    Article
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  18. White-opaque switching inMicrobiology and molecular biology reviews : MMBR · 2024
    Review
  19. RummaGEO: Automatic Mining of Human and Mouse Gene Sets from GEO.bioRxiv : the preprint server for biology · 2024
    Article
  20. Article

79 more citing papers are in PubMed but not listed here.

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 3 institutions in 1 country.

Darren A CusanovichDepartment of Human Genetics, University of Chicago, Chicago, Illinois, United States of America.
Bryan PavlovicDepartment of Human Genetics, University of Chicago, Chicago, Illinois, United States of America; Howard Hughes Medical Institute, University of Chicago, Chicago, Illinois, United States of America.
Jonathan K PritchardDepartment of Human Genetics, University of Chicago, Chicago, Illinois, United States of America; Howard Hughes Medical Institute, University of Chicago, Chicago, Illinois, United States of America; Departments of Genetics and Biology and Howard Hughes Medical Institute, Stanford University, Stanford, California, United States of America.
Yoav GiladDepartment of Human Genetics, University of Chicago, Chicago, Illinois, United States of America.
University of Chicago · USHoward Hughes Medical Institute · USStanford University · US

Funding

PREDOCTORAL TRAINING IN GENETICS AND REGULATIONT32GM007197 · NIGMS · UNIVERSITY OF CHICAGO · PI ROTHMAN-DENES, LUCIA B. B · 1985 to 2020
$17.0M
Analysis and interpretation of noncoding regulatory variationR01MH084703 · NIMH · UNIVERSITY OF CHICAGO · PI GILAD, YOAV, PRITCHARD, JONATHAN K · 2008 to 2015
$3.4M
Mapping QTLs Associated with Variation in RNA Decay RatesR01HG006123 · NHGRI · UNIVERSITY OF CHICAGO · PI GILAD, YOAV · 2011 to 2013
$1.3M
Howard Hughes Medical InstituteNHGRI NIH HHS HG006123NHGRI NIH HHS R01 HG006123NIGMS NIH HHS T32 GM007197NIMH NIH HHS R01 MH084703
6 · The paper itself

Abstract

One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly play an important role in determining gene expression outputs, yet the regulatory logic underlying functional transcription factor binding is poorly understood. Many studies have focused on characterizing the genomic locations of TF binding, yet it is unclear to what extent TF binding at any specific locus has functional consequences with respect to gene expression output. To evaluate the context of functional TF binding we knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line. We then identified genes whose expression was affected by the knockdowns. We intersected the gene expression data with transcription factor binding data (based on ChIP-seq and DNase-seq) within 10 kb of the transcription start sites of expressed genes. This combination of data allowed us to infer functional TF binding. Using this approach, we found that only a small subset of genes bound by a factor were differentially expressed following the knockdown of that factor, suggesting that most interactions between TF and chromatin do not result in measurable changes in gene expression levels of putative target genes. We found that functional TF binding is enriched in regulatory elements that harbor a large number of TF binding sites, at sites with predicted higher binding affinity, and at sites that are enriched in genomic regions annotated as "active enhancers."

Indexed as

Enhancer Elements, GeneticBinding SitesChromatinDNAGene Expression RegulationGenome, HumanHapMap ProjectHumansOligonucleotide Array Sequence AnalysisProtein BindingRegulatory Elements, TranscriptionalRegulatory Sequences, Nucleic AcidTranscription FactorsChromatinDNATranscription Factors

Identifiers

PMID24603674
PMCPMC3945204
OpenAlexW2001294950

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.