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Evolutionary Accessibility of Mutational Pathways

Overview of attention for article published in PLoS Computational Biology, August 2011
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Title
Evolutionary Accessibility of Mutational Pathways
Published in
PLoS Computational Biology, August 2011
DOI 10.1371/journal.pcbi.1002134
Pubmed ID
Authors

Jasper Franke, Alexander Klözer, J. Arjan G. M. de Visser, Joachim Krug

Abstract

Functional effects of different mutations are known to combine to the total effect in highly nontrivial ways. For the trait under evolutionary selection ('fitness'), measured values over all possible combinations of a set of mutations yield a fitness landscape that determines which mutational states can be reached from a given initial genotype. Understanding the accessibility properties of fitness landscapes is conceptually important in answering questions about the predictability and repeatability of evolutionary adaptation. Here we theoretically investigate accessibility of the globally optimal state on a wide variety of model landscapes, including landscapes with tunable ruggedness as well as neutral 'holey' landscapes. We define a mutational pathway to be accessible if it contains the minimal number of mutations required to reach the target genotype, and if fitness increases in each mutational step. Under this definition accessibility is high, in the sense that at least one accessible pathway exists with a substantial probability that approaches unity as the dimensionality of the fitness landscape (set by the number of mutational loci) becomes large. At the same time the number of alternative accessible pathways grows without bounds. We test the model predictions against an empirical 8-locus fitness landscape obtained for the filamentous fungus Aspergillus niger. By analyzing subgraphs of the full landscape containing different subsets of mutations, we are able to probe the mutational distance scale in the empirical data. The predicted effect of high accessibility is supported by the empirical data and is very robust, which we argue reflects the generic topology of sequence spaces. Together with the restrictive assumptions that lie in our definition of accessibility, this implies that the globally optimal configuration should be accessible to genome wide evolution, but the repeatability of evolutionary trajectories is limited owing to the presence of a large number of alternative mutational pathways.

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Geographical breakdown

Country Count As %
United States 6 4%
Spain 2 1%
United Kingdom 2 1%
France 1 <1%
Austria 1 <1%
Indonesia 1 <1%
Portugal 1 <1%
Germany 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 130 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 51 35%
Researcher 35 24%
Student > Master 12 8%
Student > Bachelor 8 5%
Student > Doctoral Student 7 5%
Other 21 14%
Unknown 13 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 62 42%
Biochemistry, Genetics and Molecular Biology 25 17%
Physics and Astronomy 14 10%
Computer Science 5 3%
Mathematics 5 3%
Other 19 13%
Unknown 17 12%