Literature DB >> 15592468

Modular epistasis in yeast metabolism.

Daniel Segrè1, Alexander Deluna, George M Church, Roy Kishony.   

Abstract

Epistatic interactions, manifested in the effects of mutations on the phenotypes caused by other mutations, may help uncover the functional organization of complex biological networks. Here, we studied system-level epistatic interactions by computing growth phenotypes of all single and double knockouts of 890 metabolic genes in Saccharomyces cerevisiae, using the framework of flux balance analysis. A new scale for epistasis identified a distinctive trimodal distribution of these epistatic effects, allowing gene pairs to be classified as buffering, aggravating or noninteracting. We found that the ensuing epistatic interaction network could be organized hierarchically into function-enriched modules that interact with each other 'monochromatically' (i.e., with purely aggravating or purely buffering epistatic links). This property extends the concept of epistasis from single genes to functional units and provides a new definition of biological modularity, which emphasizes interactions between, rather than within, functional modules. Our approach can be used to infer functional gene modules from purely phenotypic epistasis measurements.

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Year:  2004        PMID: 15592468     DOI: 10.1038/ng1489

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


  274 in total

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2.  Dynamic epistasis for different alleles of the same gene.

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4.  The population genetics of mutations: good, bad and indifferent.

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5.  Deep epistasis in human metabolism.

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6.  Introduction to focus issue: genetic interactions.

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Review 7.  A systems-biology approach to modular genetic complexity.

Authors:  Gregory W Carter; Cynthia G Rush; Filiz Uygun; Nikita A Sakhanenko; David J Galas; Timothy Galitski
Journal:  Chaos       Date:  2010-06       Impact factor: 3.642

8.  FastANOVA: an Efficient Algorithm for Genome-Wide Association Study.

Authors:  Xiang Zhang; Fei Zou; Wei Wang
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9.  Quantitative analysis of fitness and genetic interactions in yeast on a genome scale.

Authors:  Anastasia Baryshnikova; Michael Costanzo; Yungil Kim; Huiming Ding; Judice Koh; Kiana Toufighi; Ji-Young Youn; Jiongwen Ou; Bryan-Joseph San Luis; Sunayan Bandyopadhyay; Matthew Hibbs; David Hess; Anne-Claude Gingras; Gary D Bader; Olga G Troyanskaya; Grant W Brown; Brenda Andrews; Charles Boone; Chad L Myers
Journal:  Nat Methods       Date:  2010-11-14       Impact factor: 28.547

10.  Natural Variation of Plant Metabolism: Genetic Mechanisms, Interpretive Caveats, and Evolutionary and Mechanistic Insights.

Authors:  Nicole E Soltis; Daniel J Kliebenstein
Journal:  Plant Physiol       Date:  2015-08-13       Impact factor: 8.340

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