Evidence map›Paper›PMID 17897480›Full record

ArticleJournal of biology2007

A global analysis of genetic interactions in Caenorhabditis elegans.

Alexandra B Byrne, Matthew T Weirauch, Victoria Wong, Martina Koeva, Scott J Dixon, Joshua M Stuart, Peter J Roy

Abstract read
In one paragraph

Article in Journal of biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.

0numbers the graph read from it
0cells of the map it votes in
86citing 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

86 citing papers in PubMed.

  1. Article
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  6. Biomolecules · 2022
    Review
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  9. Article
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  11. Article
  12. The AncestralG3 (Bethesda, Md.) · 2020
    Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. Article
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  19. Review
  20. Review

26 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

7 authors.

Alexandra B ByrneDepartment of Medical Genetics and Microbiology, The Terrence Donnelly Centre for Cellular and Biomolecular Research, 160 College St, University of Toronto, Toronto, ON, M5S 3E1, Canada.
Matthew T Weirauch
Victoria Wong
Martina Koeva
Scott J Dixon
Joshua M Stuart
Peter J Roy

Funding

Predoctoral Bioinformatics Training at UCSCT32GM070386 · NIGMS · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI HUGHEY, RICHARD · 2004 to 2008
$652k
Canadian Institutes of Health ResearchNIGMS NIH HHS 1 T32 GM070386-01NIGMS NIH HHS T32 GM070386
6 · The paper itself

Abstract

backgroundUnderstanding gene function and genetic relationships is fundamental to our efforts to better understand biological systems. Previous studies systematically describing genetic interactions on a global scale have either focused on core biological processes in protozoans or surveyed catastrophic interactions in metazoans. Here, we describe a reliable high-throughput approach capable of revealing both weak and strong genetic interactions in the nematode Caenorhabditis elegans.

resultsWe investigated interactions between 11 'query' mutants in conserved signal transduction pathways and hundreds of 'target' genes compromised by RNA interference (RNAi). Mutant-RNAi combinations that grew more slowly than controls were identified, and genetic interactions inferred through an unbiased global analysis of the interaction matrix. A network of 1,246 interactions was uncovered, establishing the largest metazoan genetic-interaction network to date. We refer to this approach as systematic genetic interaction analysis (SGI). To investigate how genetic interactions connect genes on a global scale, we superimposed the SGI network on existing networks of physical, genetic, phenotypic and coexpression interactions. We identified 56 putative functional modules within the superimposed network, one of which regulates fat accumulation and is coordinated by interactions with bar-1(ga80), which encodes a homolog of beta-catenin. We also discovered that SGI interactions link distinct subnetworks on a global scale. Finally, we showed that the properties of genetic networks are conserved between C. elegans and Saccharomyces cerevisiae, but that the connectivity of interactions within the current networks is not.

conclusionsSynthetic genetic interactions may reveal redundancy among functional modules on a global scale, which is a previously unappreciated level of organization within metazoan systems. Although the buffering between functional modules may differ between species, studying these differences may provide insight into the evolution of divergent form and function.

Indexed as

AnimalsCaenorhabditis elegansCaenorhabditis elegans ProteinsModels, GeneticRNA InterferenceCaenorhabditis elegans Proteins

Identifiers

PMID17897480
PMCPMC2373897

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.