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Single Nucleotide Polymorphisms-SNPs01:05

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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When the fitness of a trait is influenced by how common it is (i.e., its frequency) relative to different traits within a population, this is referred to as frequency-dependent selection. Frequency-dependent selection may occur between species or within a single species. This type of selection can either be positive—with more common phenotypes having higher fitness—or negative, with rarer phenotypes conferring increased fitness.
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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
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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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Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
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Types of Selection01:46

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Natural selection influences the frequencies of particular alleles and phenotypes within populations in several different ways. Primarily, natural selection can be directional, stabilizing, or disruptive. Directional selection favors one extreme trait and shifts the population towards that phenotype while selecting against individuals displaying alternate traits. Stabilizing selection favors an intermediate trait with a narrow range of variation. Deviation from the optimal phenotype towards an...
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Selective sweeps in SARS-CoV-2 variant competition.

Laura Boyle1, Sofia Hletko1, Jenny Huang1

  • 1Department of Mathematics, Duke University, Durham, NC 27708-0320.

Proceedings of the National Academy of Sciences of the United States of America
|November 16, 2022
PubMed
Summary
This summary is machine-generated.

A mathematical model shows that new infectious disease variants follow a logistic growth pattern, predicting rapid variant turnover. This model, applied to influenza data, accurately estimates increased infectivity and applies to any Susceptible-Infected-Removed (SIR) epidemic model.

Keywords:
covid variant competitionlogistic equationselective sweep

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Infectious Disease Dynamics

Background:

  • Understanding the dynamics of infectious disease variant competition is crucial for public health.
  • Existing Susceptible-Infected-Removed (SIR) models provide a framework for analyzing epidemic spread.
  • Predicting the emergence and dominance of new variants remains a significant challenge.

Purpose of the Study:

  • To develop a mathematical framework for predicting the competitive dynamics of infectious disease variants.
  • To validate the model using real-world influenza data.
  • To estimate key epidemiological parameters, such as increased infectivity of new variants.

Main Methods:

  • Applied a change of variables to the ordinary differential equation (ODE) governing a two-strain SIR model.
  • Derived a logistic differential equation to describe the fraction of cases from a new variant.
  • Fitted the derived logistic model to influenza data from the Global Initiative on Sharing All Influenza Data (GISAID).

Main Results:

  • The fraction of cases due to a new variant follows a logistic differential equation, analogous to selective sweeps.
  • The logistic model accurately predicts the rapid turnover of dominant variants observed in influenza data.
  • Parameter fitting provided sensible estimates for the increase in infectivity associated with new variants.

Conclusions:

  • The logistic differential equation provides a robust mathematical description of variant competition within SIR models.
  • This approach accurately forecasts rapid shifts in dominant strains during epidemics.
  • The methodology is broadly applicable to any epidemic modeled using SIR equations, offering a valuable tool for public health.