Evidence map›Paper›PMID 21529718›Full record

ArticleCell2011

A high-resolution C. elegans essential gene network based on phenotypic profiling of a complex tissue.

Rebecca A Green, Huey-Ling Kao, Anjon Audhya, Swathi Arur, Jonathan R Mayers, Heidi N Fridolfsson, Monty Schulman, Siegfried Schloissnig, Sherry Niessen, Kimberley Laband and 8 more

Abstract read
In one paragraph

Article in Cell, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 146 papers.

0numbers the graph read from it
0cells of the map it votes in
146citing 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

146 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Apoptosis promotes fertility inbioRxiv : the preprint server for biology · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. ADR-2 regulates fertility and oocyte fate inbioRxiv : the preprint server for biology · 2024
    Article
  18. Article
  19. Article
  20. Article

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Rebecca A GreenLudwig Institute for Cancer Research, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, 92093, USA.
Huey-Ling Kao
Anjon Audhya
Swathi Arur
Jonathan R Mayers
Heidi N Fridolfsson
Monty Schulman
Siegfried Schloissnig
Sherry Niessen
Kimberley Laband
Shaohe Wang
Daniel A Starr
Anthony A Hyman
Tim Schedl
Arshad Desai
Fabio Piano
Kristin C Gunsalus
Karen Oegema

Funding

Analysis of Centrosome DynamicsR01GM074207 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI OEGEMA, KAREN F · 2006 to 2025
$6.6M
Mechanisms of Nuclear Migration and AnchorageR01GM073874 · NIGMS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI STARR, DANIEL A · 2006 to 2019
$4.5M
A Systematic RNAi-based Map of C. elegans EmbryogenesisR01HD046236 · NICHD · NEW YORK UNIVERSITY · PI GUNSALUS, KRISTIN C, PIANO, FABIO · 2004 to 2013
$4.5M
Molecular Mechanisms that Regulate Lysosomal Protein TransportR01GM088151 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI AUDHYA, ANJON · 2010 to 2019
$3.0M
A systems biology approach to mammalian early embryogenesisR01GM085503 · NIGMS · NEW YORK UNIVERSITY · PI GUNSALUS, KRISTIN C, NOYES, NICOLE · 2008 to 2011
$1.5M
MPK -1 ERK SUBSTRATES AND THE CONTROL OF GERMLINE DEVELOPMENTR01GM085150 · NIGMS · WASHINGTON UNIVERSITY · PI SCHEDL, TIM · 2008 to 2011
$1.3M
NICHD NIH HHS R01 HD046236NIGMS NIH HHS R01 GM073874NIGMS NIH HHS R01 GM074207NIGMS NIH HHS R01 GM085150NIGMS NIH HHS R01 GM085503NIGMS NIH HHS R01 GM088151
6 · The paper itself

Abstract

High-content screening for gene profiling has generally been limited to single cells. Here, we explore an alternative approach-profiling gene function by analyzing effects of gene knockdowns on the architecture of a complex tissue in a multicellular organism. We profile 554 essential C. elegans genes by imaging gonad architecture and scoring 94 phenotypic features. To generate a reference for evaluating methods for network construction, genes were manually partitioned into 102 phenotypic classes, predicting functions for uncharacterized genes across diverse cellular processes. Using this classification as a benchmark, we developed a robust computational method for constructing gene networks from high-content profiles based on a network context-dependent measure that ranks the significance of links between genes. Our analysis reveals that multi-parametric profiling in a complex tissue yields functional maps with a resolution similar to genetic interaction-based profiling in unicellular eukaryotes-pinpointing subunits of macromolecular complexes and components functioning in common cellular processes.

Indexed as

Gene Regulatory NetworksGenetic TechniquesAnimalsCaenorhabditis elegansComputational BiologyEmbryo, NonmammalianGene Knockdown TechniquesGonadsPhenotype

Identifiers

PMID21529718
PMCPMC3086541

What OpenQuestion holds

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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.