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Evolution of Genetic Potential

Overview of attention for article published in PLoS Computational Biology, August 2005
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Title
Evolution of Genetic Potential
Published in
PLoS Computational Biology, August 2005
DOI 10.1371/journal.pcbi.0010032
Pubmed ID
Authors

Lauren Ancel Meyers, Fredric D Ancel, Michael Lachmann

Abstract

Organisms employ a multitude of strategies to cope with the dynamical environments in which they live. Homeostasis and physiological plasticity buffer changes within the lifetime of an organism, while stochastic developmental programs and hypermutability track changes on longer time-scales. An alternative long-term mechanism is "genetic potential"--a heightened sensitivity to the effects of mutation that facilitates rapid evolution to novel states. Using a transparent mathematical model, we illustrate the concept of genetic potential and show that as environmental variability decreases, the evolving population reaches three distinct steady state conditions: (1) organismal flexibility, (2) genetic potential, and (3) genetic robustness. As a specific example of this concept we examine fluctuating selection for hydrophobicity in a single amino acid. We see the same three stages, suggesting that environmental fluctuations can produce allele distributions that are distinct not only from those found under constant conditions, but also from the transient allele distributions that arise under isolated selective sweeps.

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The data shown below were compiled from readership statistics for 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 5%
Germany 2 2%
United Kingdom 2 2%
Vietnam 1 <1%
Australia 1 <1%
Sweden 1 <1%
Switzerland 1 <1%
Norway 1 <1%
South Africa 1 <1%
Other 2 2%
Unknown 112 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 26%
Researcher 30 23%
Professor > Associate Professor 13 10%
Professor 12 9%
Student > Master 10 8%
Other 20 15%
Unknown 12 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 66 50%
Biochemistry, Genetics and Molecular Biology 13 10%
Computer Science 7 5%
Physics and Astronomy 6 5%
Mathematics 5 4%
Other 17 13%
Unknown 17 13%