Reference: Carter GW, et al. (2012) Use of pleiotropy to model genetic interactions in a population. PLoS Genet 8(10):e1003010

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Abstract


Systems-level genetic studies in humans and model systems increasingly involve both high-resolution genotyping and multi-dimensional quantitative phenotyping. We present a novel method to infer and interpret genetic interactions that exploits the complementary information in multiple phenotypes. We applied this approach to a population of yeast strains with randomly assorted perturbations of five genes involved in mating. We quantified pheromone response at the molecular level and overall mating efficiency. These phenotypes were jointly analyzed to derive a network of genetic interactions that mapped mating-pathway relationships. To determine the distinct biological processes driving the phenotypic complementarity, we analyzed patterns of gene expression to find that the pheromone response phenotype is specific to cellular fusion, whereas mating efficiency was a combined measure of cellular fusion, cell cycle arrest, and modifications in cellular metabolism. We applied our novel method to global gene expression patterns to derive an expression-specific interaction network and demonstrate applicability to global transcript data. Our approach provides a basis for interpretation of genetic interactions and the generation of specific hypotheses from populations assayed for multiple phenotypes.

Reference Type
Journal Article
Authors
Carter GW, Hays M, Sherman A, Galitski T
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Interaction Annotations


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Interactor Interactor Type Assay Annotation Action Modification Phenotype Source Reference

Gene Ontology Annotations


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Gene Gene Ontology Term Qualifier Aspect Method Evidence Source Assigned On Annotation Extension Reference

Phenotype Annotations


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Gene Phenotype Experiment Type Mutant Information Strain Background Chemical Details Reference

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Regulator Target Experiment Assay Construct Conditions Strain Background Reference