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Related Concept Videos

Frequency-dependent Selection01:21

Frequency-dependent Selection

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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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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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Mutation, Gene Flow, and Genetic Drift01:09

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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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Overview
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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.
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Limits to Natural Selection01:38

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Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.
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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Discoal: flexible coalescent simulations with selection.

Andrew D Kern1,2, Daniel R Schrider2

  • 1Department of Genetics.

Bioinformatics (Oxford, England)
|August 26, 2016
PubMed
Summary
This summary is machine-generated.

Introducing discoal, a new coalescent simulator for population genetics. This flexible tool models selective sweeps, including hard and soft sweeps, under various evolutionary scenarios for enhanced population genetic analyses.

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Area of Science:

  • Population genetics
  • Evolutionary biology
  • Computational biology

Background:

  • Understanding the impact of selection on genetic variation is crucial in evolutionary biology.
  • Simulating complex evolutionary scenarios, such as selective sweeps, is essential for interpreting population genetic data.
  • Existing coalescent simulators may lack the flexibility to model various types of sweeps and demographic histories.

Purpose of the Study:

  • To introduce discoal, a novel coalescent simulator designed for flexible and feature-rich simulation of population samples.
  • To enable the simulation of various types of selective sweeps, including hard and soft sweeps, even at distant loci.
  • To incorporate complex evolutionary factors like recurrent mutation, recombination, gene conversion, and non-equilibrium demographic histories.

Main Methods:

  • Discoal is a coalescent simulator implemented in the C programming language.
  • It allows conditioning on allele fixation due to drift, hard sweeps, or soft sweeps.
  • The simulator accommodates recurrent mutation, recombination, gene conversion, and complex demographic histories without pre-specifying allele frequency trajectories.

Main Results:

  • Discoal can generate population samples incorporating selective sweeps in a flexible manner.
  • It supports simulations of sweeps occurring at varying genetic distances from the locus of interest.
  • The software handles complex evolutionary parameters, providing a versatile tool for population genetic modeling.

Conclusions:

  • Discoal offers a powerful and flexible platform for simulating population genetic data with selective sweeps.
  • Its ability to model diverse evolutionary scenarios makes it valuable for research in population genetics and evolutionary biology.
  • The freely available source code promotes accessibility and further development within the scientific community.