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Mutations are heritable changes in an organism’s genome involving alterations in the base sequence of DNA or RNA. These changes can influence cellular processes and phenotypic traits, potentially transforming the unaltered wild type into a mutant form. Such changes, termed forward mutations, are pivotal in shaping the genetic diversity of organisms.RNA viruses exhibit the highest mutation rates due to the absence of robust proofreading mechanisms during genome replication. In contrast,...
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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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The extinction time under mutational meltdown driven by high mutation rates.

Lucy Lansch-Justen1,2, Davide Cusseddu1,3, Mark A Schmitz1

  • 1Instituto Gulbenkian de Ciência Oeiras Portugal.

Ecology and Evolution
|July 11, 2022
PubMed
Summary
This summary is machine-generated.

Mutational meltdown, driven by accumulating harmful mutations, can lead to population extinction. This study quantifies extinction time, crucial for developing antiviral therapies using mutagenic drugs against RNA viruses.

Keywords:
evolutionary theoryextinctionlethal mutagenesismutagenic drugsmutational meltdown

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Area of Science:

  • Evolutionary Biology
  • Population Genetics
  • Theoretical Ecology

Background:

  • Mutational meltdown is an eco-evolutionary process where accumulating deleterious mutations lead to population decline and extinction.
  • Understanding extinction dynamics is vital for applications like antiviral therapies using mutagenic drugs.

Purpose of the Study:

  • To estimate the extinction time of populations experiencing high mutation rates.
  • To assess the feasibility and success of antiviral treatments based on mutagenic drugs.

Main Methods:

  • Analytical calculations of extinction time.
  • Stochastic simulations of population dynamics under high mutation rates.

Main Results:

  • Accurate analytical predictions for mean extinction time were derived.
  • Deleterious mutation rate significantly impacts extinction time.
  • Intermediate selection coefficients minimize extinction time.
  • Simulation results showed low variation in extinction time for given parameters.

Conclusions:

  • The study provides a quantitative framework for predicting mutational meltdown.
  • Findings support the potential of mutagenic drugs for RNA virus treatment.
  • Extinction time is sensitive to mutation rate and selection coefficient.