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Mutation, Gene Flow, and Genetic Drift

Mutation, Gene Flow, and Genetic Drift

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).

Viral Recombination

Viral Recombination

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.

Viral Mutations

Viral Mutations

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...

Genetic Drift

Genetic Drift

Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.

Retrovirus Life Cycles

Retrovirus Life Cycles

Retroviruses have a single-stranded RNA genome that undergoes a special form of replication. Once the retrovirus has entered the host cell, an enzyme called reverse transcriptase synthesizes double-stranded DNA from the retroviral RNA genome. This DNA copy of the genome is then integrated into the host’s genome inside the nucleus via an enzyme called integrase. Consequently, the retroviral genome is transcribed into RNA whenever the host’s genome is transcribed, allowing the...

Size and Structure of Viral Genomes

Size and Structure of Viral Genomes

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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Updated: Mar 18, 2026

A Mouse Model for the Transition of Streptococcus pneumoniae from Colonizer to Pathogen upon Viral Co-Infection Recapitulates Age-Exacerbated Illness

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S2M: A Stochastic Simulation Model of Poliovirus Genetic State Transition.

Carol L Ecale Zhou¹

¹Computation Applications and Research Department, Lawrence Livermore National Laboratory, Livermore, CA, USA.

Bioinformatics and Biology Insights

|July 8, 2016

Summary

This study introduces S2M, a simulation model for viral genetic variation, to understand how poliovirus vaccine strains revert to neurovirulent forms. Simulations reveal how replication error, recombination, and defective particles influence viral evolution and disease potential.

Keywords:

Mahoney Sabin genetic state transition genome evolution modeling picornavirus recombination replication simulation

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Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Area of Science:

Virology
Computational Biology
Genetics

Background:

Understanding genetic variation in quasispecies viruses is crucial for predicting disease dynamics.
Polio vaccine strains can revert to neurovirulent forms, causing vaccine-derived poliovirus.
Molecular mechanisms driving genetic state transitions require robust modeling approaches.

Purpose of the Study:

To present S2M, a stochastic simulation model for exploring genetic diversity in viruses.
To model the transition from benign vaccine strains (Sabin-1) to virulent wild-type (Mahoney) poliovirus.
To investigate the impact of replication error, recombination, and defective interfering particles on viral evolution.

Main Methods:

Developed S2M, a cell-based stochastic simulation model incorporating in-cell replication and infection cycles.
Initialized populations with Sabin-1 and Mahoney poliovirus genotypes.
Quantified genetic changes, genome fitness, neurovirulence, and cloud diversity under varying conditions.
Adjusted parameters like error rates and recombination presence via command line for hypothetical outcome generation.

Main Results:

Simulations demonstrated the influence of replication error and recombination rates on poliovirus evolution towards Mahoney resemblance.
The presence or absence of defective interfering particles significantly affected end-state outcomes.
Model outcomes provided insights into the complex interplay of factors driving viral genetic transitions.

Conclusions:

S2M effectively models genetic variation and state transitions in quasispecies viruses like poliovirus.
The study highlights the non-intuitive contributions of specific molecular mechanisms to viral evolution and pathogenicity.
The model serves as a valuable tool for generating hypothetical scenarios in viral dynamics research.