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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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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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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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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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Detecting consistent patterns of directional adaptation using differential selection codon models.

Sahar Parto1, Nicolas Lartillot2

  • 1Département de Biochimie et Médecine Moléculaire, Centre Robert Cedergren, Bio-Informatique et Génomique, Université de Montréal, Montréal, Québec, Canada. sahar.parto@umontreal.ca.

BMC Evolutionary Biology
|June 25, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a new codon model to detect consistent molecular adaptations driven by environmental changes. The model identifies specific protein-coding adaptations linked to varying external conditions, like host genetics.

Keywords:
BayesianEvolutionHIVHLAMCMCSelectionVirus adaptation

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Area of Science:

  • Evolutionary biology
  • Molecular evolution
  • Bioinformatics

Background:

  • Phylogenetic codon models analyze selective pressures on protein-coding genes.
  • Existing models often assume a constant fitness landscape over time.
  • Environmental changes can drive systematic, reproducible molecular adaptations across lineages.

Purpose of the Study:

  • To develop a codon-based model detecting consistent adaptation patterns.
  • To quantify fine-grained adaptations in protein-coding sequences due to external conditions.
  • To investigate how organisms adapt to changing environments.

Main Methods:

  • Introduced a codon-based differential selection model.
  • Modeled global mutational pressure and site-specific amino acid preferences.
  • Implemented the phylogenetic model within a Bayesian Markov Chain Monte Carlo (MCMC) framework.
  • Validated the model using simulations and applied it to HIV sequences.

Main Results:

  • The differential selection model successfully detected and quantified consistent adaptation patterns.
  • Identified specific coding positions under differential selection linked to external conditions.
  • Applied to HIV data, the model characterized adaptations associated with different Human Leukocyte Antigen (HLA) alleles.

Conclusions:

  • The differential selection model effectively identifies molecular adaptations linked to environmental changes.
  • This approach can reveal reproducible evolutionary patterns across independent lineages.
  • The model has broad applications in viral evolution and the study of life-history strategies.