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Genes Confer Similar Robustness to Environmental, Stochastic, and Genetic Perturbations in Yeast

Overview of attention for article published in PLOS ONE, February 2010
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Title
Genes Confer Similar Robustness to Environmental, Stochastic, and Genetic Perturbations in Yeast
Published in
PLOS ONE, February 2010
DOI 10.1371/journal.pone.0009035
Pubmed ID
Authors

Ben Lehner

Abstract

Gene inactivation often has little or no apparent consequence for the phenotype of an organism. This property-enetic (or mutational) robustness-is pervasive, and has important implications for disease and evolution, but is not well understood. Dating back to at least Waddington, it has been suggested that mutational robustness may be related to the requirement to withstand environmental or stochastic perturbations. Here I show that global quantitative data from yeast are largely consistent with this idea. Considering the effects of mutations in all nonessential genes shows that genes that confer robustness to environmental or stochastic change also buffer the effects of genetic change, and with similar efficacy. This means that selection during evolution for environmental or stochastic robustness (also referred to as canalization) may frequently have the side effect of increasing genetic robustness. A dynamic environment may therefore promote the evolution of phenotypic complexity. It also means that "hub" genes in genetic interaction (synthetic lethal) networks are generally genes that confer environmental resilience and phenotypic stability.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 6%
Spain 3 2%
United Kingdom 3 2%
Mexico 2 1%
Italy 1 <1%
Switzerland 1 <1%
Saudi Arabia 1 <1%
Portugal 1 <1%
Canada 1 <1%
Other 1 <1%
Unknown 134 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 32%
Researcher 38 24%
Professor > Associate Professor 15 10%
Student > Bachelor 13 8%
Student > Master 11 7%
Other 21 13%
Unknown 8 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 106 68%
Biochemistry, Genetics and Molecular Biology 21 13%
Computer Science 7 4%
Medicine and Dentistry 4 3%
Economics, Econometrics and Finance 2 1%
Other 7 4%
Unknown 10 6%