Evidence map›Paper›PMID 24098147›Full record

ArticlePLoS genetics2013

Incorporating motif analysis into gene co-expression networks reveals novel modular expression pattern and new signaling pathways.

Shisong Ma, Smit Shah, Hans J Bohnert, Michael Snyder, Savithramma P Dinesh-Kumar

Abstract read
In one paragraph

Article in PLoS genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

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47citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

47 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Protein expression/secretion boost by a novel unique 21-mer cis-regulatory motif (Exin21) via mRNA stabilization.Molecular therapy : the journal of the American Society of Gene Therapy · 2023
    Article
  5. BLSSpeller to discover novel regulatory motifs in maize.DNA research : an international journal for rapid publication of reports on genes and genomes · 2022
    Article
  6. Article
  7. Article
  8. Frontiers in genetics · 2022
    Article
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  10. Article
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  16. Article
  17. Review
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Shisong MaDepartment of Plant Biology and the Genome Center, College of Biological Sciences, University of California, Davis, Davis, California, United States of America.
Smit Shah
Hans J Bohnert
Michael Snyder
Savithramma P Dinesh-Kumar

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding of gene regulatory networks requires discovery of expression modules within gene co-expression networks and identification of promoter motifs and corresponding transcription factors that regulate their expression. A commonly used method for this purpose is a top-down approach based on clustering the network into a range of densely connected segments, treating these segments as expression modules, and extracting promoter motifs from these modules. Here, we describe a novel bottom-up approach to identify gene expression modules driven by known cis-regulatory motifs in the gene promoters. For a specific motif, genes in the co-expression network are ranked according to their probability of belonging to an expression module regulated by that motif. The ranking is conducted via motif enrichment or motif position bias analysis. Our results indicate that motif position bias analysis is an effective tool for genome-wide motif analysis. Sub-networks containing the top ranked genes are extracted and analyzed for inherent gene expression modules. This approach identified novel expression modules for the G-box, W-box, site II, and MYB motifs from an Arabidopsis thaliana gene co-expression network based on the graphical Gaussian model. The novel expression modules include those involved in house-keeping functions, primary and secondary metabolism, and abiotic and biotic stress responses. In addition to confirmation of previously described modules, we identified modules that include new signaling pathways. To associate transcription factors that regulate genes in these co-expression modules, we developed a novel reporter system. Using this approach, we evaluated MYB transcription factor-promoter interactions within MYB motif modules.

Indexed as

Computational BiologyGene Regulatory NetworksAlgorithmsArabidopsisCluster AnalysisGene Expression Regulation, PlantNucleotide MotifsPromoter Regions, GeneticSignal TransductionTranscription FactorsTranscription Factors

Identifiers

PMID24098147
PMCPMC3789834

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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.