Apr 25, 2016

Predictability of Genetic Interactions from Functional Gene Modules

BioRxiv : the Preprint Server for Biology
Jonathan H Young, Edward M Marcotte


Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets. Yet experimentally determining whether genes interact is technically non-trivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally-related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high-predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel gene...Continue Reading

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Mentioned in this Paper

Saccharomyces cerevisiae allergenic extract
Cross Validation
Genetic Markers
Gene Delivery Systems
Drug Interactions
Drosophila melanogaster
Saccharomyces cerevisiae

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