Evidence map›Paper›PMID 19282476›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2009

Genome-wide discovery of functional transcription factor binding sites by comparative genomics: the case of Stat3.

Francesco Vallania, Davide Schiavone, Sarah Dewilde, Emanuela Pupo, Serge Garbay, Raffaele Calogero, Marco Pontoglio, Paolo Provero, Valeria Poli

Abstract readValidation Study
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
–field-weighted citation impact
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

53 citing papers in PubMed.

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  18. Article
  19. Nucleus, Mitochondrion, or Reticulum? STAT3 à La Carte.International journal of molecular sciences · 2018
    Review
  20. STAT3 in Skeletal Muscle Function and Disorders.International journal of molecular sciences · 2018
    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

9 authors.

Francesco VallaniaMolecular Biotechnology Center and Department of Genetics, Biology and Biochemistry and Department of Clinical and Biological Sciences, University of Turin, Via Nizza 52, 10126 Turin, Italy.
Davide Schiavone
Sarah Dewilde
Emanuela Pupo
Serge Garbay
Raffaele Calogero
Marco Pontoglio
Paolo Provero
Valeria Poli

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The identification of direct targets of transcription factors is a key problem in the study of gene regulatory networks. However, the use of high throughput experimental methods, such as ChIP-chip and ChIP-sequencing, is limited by their high cost and strong dependence on cellular type and context. We developed a computational method for the genome-wide identification of functional transcription factor binding sites based on positional weight matrices, comparative genomics, and gene expression profiling. The method was applied to Stat3, a transcription factor playing crucial roles in inflammation, immunity and oncogenesis, and able to induce distinct subsets of target genes in different cell types or conditions. A newly generated positional weight matrix enabled us to assign affinity scores of high specificity, as measured by EMSA competition assays. Phylogenetic conservation with 7 vertebrate species was used to select the binding sites most likely to be functional. Validation was carried out on predicted sites within genes identified as differentially expressed in the presence or absence of Stat3 by microarray analysis. Twelve of the fourteen sites tested were bound by Stat3 in vivo, as assessed by Chromatin Immunoprecipitation, allowing us to identify 9 Stat3 transcriptional targets. Given its high validation rate, and the availability of large transcription factor-dependent gene expression datasets obtained under diverse experimental conditions, our approach appears to be a valid alternative to high-throughput experimental assays for the discovery of novel direct targets of transcription factors.

Indexed as

GenomeAnimalsBinding SitesCell LineElectrophoretic Mobility Shift AssayGene Expression ProfilingGenomicsMethodsMiceMice, KnockoutSTAT3 Transcription FactorTranscription FactorsSTAT3 Transcription FactorTranscription Factors

Identifiers

PMID19282476
PMCPMC2664024

What OpenQuestion holds

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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.