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Related Concept Videos

Viral Mutations00:36

Viral Mutations

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A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
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Viral Recombination00:57

Viral Recombination

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Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
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Mutations in Microorganisms01:18

Mutations in Microorganisms

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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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Size and Structure of Viral Genomes01:26

Size and Structure of Viral Genomes

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Viral genomes exhibit remarkable diversity in size, structure, and composition, influencing their replication strategies and interactions with host cells. These genomes consist of either DNA or RNA and may be linear or circular. Additionally, they can be single-stranded or double-stranded, with each configuration affecting how the virus propagates within a host. RNA viruses, for instance, generally have smaller genomes than DNA viruses, a factor that contributes to their high mutation rates and...
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Retroviruses02:33

Retroviruses

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Retroviruses and retrotransposons both insert copies of their genetic elements into the genome of the host cell. Thus, the viral genes are passed on when the host genome is replicated or translated. A typical retroviral DNA sequence contains 3-4 genes that encode the different proteins required for its structural assembly and function as a molecular parasite. This DNA is transcribed into a single mRNA, which is very similar in structure to conventional mRNAs, i.e., it is capped at the 5’...
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Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

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In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
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Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency

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Endogenous viral mutations, evolutionary selection, and containment policy design.

Patrick Mellacher1

  • 1Graz Schumpeter Centre, University of Graz, Graz, Austria.

Journal of Economic Interaction and Coordination
|January 12, 2022
PubMed
Summary

The novel coronavirus can evolve indefinitely if containment strategies are too relaxed, favoring variants that evade immunity. Understanding viral evolution is crucial for effective, long-term epidemic control.

Keywords:
Agent-based modelCovid-19PandemicPhylodynamic modelSARS-CoV2SIR model

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Area of Science:

  • Epidemiology
  • Viral Evolution
  • Public Health Policy

Background:

  • The novel coronavirus (SARS-CoV-2) evolution is influenced by mutations and antigenic drift, impacting its infectiousness and immune evasion.
  • Understanding evolutionary trajectories is key to predicting and managing viral spread and disease dynamics.

Purpose of the Study:

  • To analyze the evolutionary dynamics of the novel coronavirus using an epidemiological model.
  • To investigate how containment policies influence viral evolution and long-term epidemic outcomes.

Main Methods:

  • Analytical study of a simple epidemiological model incorporating mutations and antigenic drift.
  • Agent-based simulation model with Monte Carlo simulations to explore aggregate dynamics.

Main Results:

  • Fitter variants exhibit higher infectiousness, longer disease duration, and shorter latent periods.
  • Containment policies targeting symptomatic individuals can favor variants with longer incubation periods and more asymptomatic cases.
  • Reduced mortality does not inherently provide an evolutionary advantage.
  • Viral evolution can be indefinite under relaxed containment and high immune escape.
  • Short-term epidemiological outcomes may not distinguish between slow and rapid viral evolution.

Conclusions:

  • Containment policy design significantly impacts the speed and direction of viral evolution.
  • Long-term epidemic control requires accounting for viral mutation and immune escape propensity.
  • Continuous genetic and antigenic surveillance is vital, even in the early epidemic stages.