Evidence map›Paper›PMID 17284674›Full record

ArticleGenome research2007

Identification of muscle-specific regulatory modules in Caenorhabditis elegans.

Guoyan Zhao, Lawrence A Schriefer, Gary D Stormo

Open access · bronzeAbstract readComparative Study
In one paragraph

Article in Genome research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
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  5. The Transcriptional Regulator SnoN Promotes the Proliferation of Cerebellar Granule Neuron Precursors in the Postnatal Mouse Brain.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2019
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  6. Modeling thePeerJ · 2017
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  15. Genome-wide identification of cis-regulatory motifs and modules underlying gene coregulation using statistics and phylogeny.Proceedings of the National Academy of Sciences of the United States of America · 2010
    Article
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  20. Information flow analysis of interactome networks.PLoS computational biology · 2009
    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

3 authors at 1 institution in 1 country.

Guoyan ZhaoDepartment of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
Lawrence A Schriefer
Gary D Stormo
Washington University in St. Louis · US

Funding

INSTITUTIONAL TRAINING GRANT IN GENOMIC SCIENCET32HG000045 · NHGRI · WASHINGTON UNIVERSITY · PI MICHAEL R BRENT, Barak A Cohen · 1997 to 2026
$8.4M
DNA PATTERN IDENTIFICATION AND ANALYSISR01HG000249 · NHGRI · WASHINGTON UNIVERSITY · PI STORMO, GARY D · 1990 to 2017
$5.6M
Regulatory modules: identification and verificationF32GM073444 · NIGMS · WASHINGTON UNIVERSITY · PI ZHAO, GUOYAN · 2005 to 2007
$104k
NHGRI NIH HHS 5 T32 HG000045-08NHGRI NIH HHS HG00249NHGRI NIH HHS R01 HG000249NHGRI NIH HHS T32 HG000045NIGMS NIH HHS 1 F32 GM73444-01NIGMS NIH HHS F32 GM073444
6 · The paper itself

Abstract

Transcriptional regulation is the major regulatory mechanism that controls the spatial and temporal expression of genes during development. This is carried out by transcription factors (TFs), which recognize and bind to their cognate binding sites. Recent studies suggest a modular organization of TF-binding sites, in which clusters of transcription-factor binding sites cooperate in the regulation of downstream gene expression. In this study, we report our computational identification and experimental verification of muscle-specific cis-regulatory modules in Caenorhabditis elegans. We first identified a set of motifs that are correlated with muscle-specific gene expression. We then predicted muscle-specific regulatory modules based on clusters of those motifs with characteristics similar to a collection of well-studied modules in other species. The method correctly identifies 88% of the experimentally characterized modules with a positive predictive value of at least 65%. The prediction accuracy of muscle-specific expression on an independent test set is highly significant (P<0.0001). We performed in vivo experimental tests of 12 predicted modules, and 10 of those drive muscle-specific gene expression. These results suggest that our method is highly accurate in identifying functional sequences important for muscle-specific gene expression and is a valuable tool for guiding experimental designs.

Indexed as

AnimalsCaenorhabditis elegansComputational BiologyGene Expression Regulation, DevelopmentalGenomicsGreen Fluorescent ProteinsMuscle, SkeletalRegulatory Elements, TranscriptionalTranscription FactorsGreen Fluorescent ProteinsTranscription Factors

Identifiers

PMID17284674
PMCPMC1800926
OpenAlexW2152069975

What OpenQuestion holds

Textmetadata
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.