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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Evolutionary accessibility of mutational pathways.

Jasper Franke1, Alexander Klözer, J Arjan G M de Visser

  • 1Institute of Theoretical Physics, University of Cologne, Köln, Germany.

Plos Computational Biology
|August 31, 2011
PubMed
Summary

Evolutionary adaptation is predictable, as fitness landscapes offer accessible pathways to optimal states. However, numerous alternative pathways limit evolutionary repeatability.

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Area of Science:

  • Evolutionary Biology
  • Genetics
  • Computational Biology

Background:

  • Fitness landscapes illustrate how mutation combinations affect traits.
  • Understanding accessibility of optimal states is key to predicting evolutionary adaptation.
  • The combination of mutation effects can be complex and non-additive.

Purpose of the Study:

  • To theoretically investigate the accessibility of the globally optimal state on various model fitness landscapes.
  • To define and analyze 'accessible' mutational pathways.
  • To compare theoretical predictions with empirical data from Aspergillus niger.

Main Methods:

  • Theoretical modeling of fitness landscapes with varying ruggedness and neutrality.
  • Defining accessible pathways by minimal mutations and fitness increase at each step.
  • Empirical analysis of an 8-locus fitness landscape in Aspergillus niger.

Main Results:

  • High probability of accessible pathways to the optimal state as landscape dimensionality increases.
  • The number of alternative accessible pathways grows unboundedly.
  • Empirical data supports theoretical predictions of high accessibility, robust across different mutation subsets.

Conclusions:

  • Globally optimal configurations are generally accessible for genome-wide evolution.
  • The high number of alternative accessible pathways limits the repeatability of evolutionary trajectories.
  • The generic topology of sequence spaces underlies the robustness of these findings.