Evidence map›Paper›PMID 21378980›Full record

ArticleNature methods2011

Mapping of signaling networks through synthetic genetic interaction analysis by RNAi.

Thomas Horn, Thomas Sandmann, Bernd Fischer, Elin Axelsson, Wolfgang Huber, Michael Boutros

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Article in Nature methods, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 110 papers.

0numbers the graph read from it
0cells of the map it votes in
110citing 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

110 citing papers in PubMed.

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

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Thomas HornGerman Cancer Research Center (Deutsches Krebsforschungszentrum), Division Signaling and Functional Genomics and Heidelberg University, Department of Cell and Molecular Biology, Faculty of Medicine Mannheim, Heidelberg, Germany.
Thomas Sandmann
Bernd Fischer
Elin Axelsson
Wolfgang Huber
Michael Boutros

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The analysis of synthetic genetic interaction networks can reveal how biological systems achieve a high level of complexity with a limited repertoire of components. Studies in yeast and bacteria have taken advantage of collections of deletion strains to construct matrices of quantitative interaction profiles and infer gene function. Yet comparable approaches in higher organisms have been difficult to implement in a robust manner. Here we report a method to identify genetic interactions in tissue culture cells through RNAi. By performing more than 70,000 pairwise perturbations of signaling factors, we identified >600 interactions affecting different quantitative phenotypes of Drosophila melanogaster cells. Computational analysis of this interaction matrix allowed us to reconstruct signaling pathways and identify a conserved regulator of Ras-MAPK signaling. Large-scale genetic interaction mapping by RNAi is a versatile, scalable approach for revealing gene function and the connectivity of cellular networks.

Indexed as

Gene Expression ProfilingRNA InterferenceAnimalsCell LineComputational BiologyDrosophila melanogasterDrosophila ProteinsEpistasis, GeneticGenetic TechniquesSignal TransductionDrosophila Proteins

Identifiers

PMID21378980

What OpenQuestion holds

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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.