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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Published on: February 3, 2023

Mutational effects and population dynamics during viral adaptation challenge current models.

Craig R Miller1, Paul Joyce, Holly A Wichman

  • 1Department of Biological Sciences, University of Idaho, Moscow, Idaho 83844, USA. crmiller@uidaho.edu

Genetics
|November 3, 2010
PubMed
Summary

Haploid organism adaptation was tested using bacteriophage ID11. Results reveal complex evolutionary dynamics, challenging current models of fitness landscapes.

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Area of Science:

  • Evolutionary biology
  • Microbial genetics
  • Population genetics

Background:

  • Adaptation in haploid organisms is theoretically modeled but lacks empirical testing.
  • Microvirid bacteriophage (ID11) serves as a model system for studying rapid evolution.

Purpose of the Study:

  • To empirically investigate adaptation dynamics in a haploid organism under different population sizes.
  • To characterize genetic variation and fitness landscape during serial passage adaptation.
  • To assess the impact of bottleneck size on evolutionary trajectories and mutation patterns.

Main Methods:

  • Serial passage adaptation of bacteriophage ID11 at two bottleneck sizes (10^4 and 10^6).
  • Fitness assays and whole-genome sequencing of 631 individual isolates.
  • Analysis of genetic variation, haplotype diversity, and mutation distributions.

Main Results:

  • Observed extensive genetic variation, including beneficial, neutral, and deleterious mutations.
  • Small bottleneck lines showed less diversity and approached conditions of complex dynamics.
  • Large bottleneck lines exhibited significant clonal interference, multiple beneficial mutations, and leapfrog events.
  • Distinct distributions of first- and second-step adaptive mutations were identified, with second-step mutations having smaller selection coefficients.

Conclusions:

  • The fitness landscape of bacteriophage ID11 is neither smooth nor fully uncorrelated, challenging existing models.
  • Bottleneck size critically influences adaptation dynamics, genetic diversity, and the prevalence of evolutionary mechanisms like clonal interference.
  • Empirical data from this study provide crucial insights into the complexities of microbial adaptation and evolutionary landscapes.