A global view of pleiotropy and phenotypically derived gene function in yeast

A global view of pleiotropy and phenotypically derived gene function in yeast Pleiotropy, the ability of a single mutant gene to cause multiple mutant phenotypes, is a relatively common but poorly understood phenomenon in biology. Perhaps the greatest challenge in the analysis of pleiotropic genes is determining whether phenotypes associated with a mutation result from the loss of a single function or of multiple functions encoded by the same gene. Here we estimate the degree of pleiotropy in yeast by measuring the phenotypes of 4710 mutants under 21 environmental conditions, finding that it is significantly higher than predicted by chance. We use a biclustering algorithm to group pleiotropic genes by common phenotype profiles. Comparisons of these clusters to biological process classifications, synthetic lethal interactions, and protein complex data support the hypothesis that this method can be used to genetically define cellular functions. Applying these functional classifications to pleiotropic genes, we are able to dissect phenotypes into groups associated with specific gene functions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Molecular Systems Biology Wiley

A global view of pleiotropy and phenotypically derived gene function in yeast

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Publisher
Wiley
Copyright
Copyright © 2013 Wiley Periodicals, Inc
ISSN
1744-4292
eISSN
1744-4292
D.O.I.
10.1038/msb4100004
Publisher site
See Article on Publisher Site

Abstract

Pleiotropy, the ability of a single mutant gene to cause multiple mutant phenotypes, is a relatively common but poorly understood phenomenon in biology. Perhaps the greatest challenge in the analysis of pleiotropic genes is determining whether phenotypes associated with a mutation result from the loss of a single function or of multiple functions encoded by the same gene. Here we estimate the degree of pleiotropy in yeast by measuring the phenotypes of 4710 mutants under 21 environmental conditions, finding that it is significantly higher than predicted by chance. We use a biclustering algorithm to group pleiotropic genes by common phenotype profiles. Comparisons of these clusters to biological process classifications, synthetic lethal interactions, and protein complex data support the hypothesis that this method can be used to genetically define cellular functions. Applying these functional classifications to pleiotropic genes, we are able to dissect phenotypes into groups associated with specific gene functions.

Journal

Molecular Systems BiologyWiley

Published: Jan 1, 2005

References

  • Molecular biology of iron acquisition in Saccharomyces cerevisiae
    Askwith, CC; de Silva, D; Kaplan, J
  • Glucose repression in yeast
    Carlson, M

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