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Related Concept Videos

Frequency-dependent Selection01:21

Frequency-dependent Selection

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.Positive Frequency-Dependent SelectionIn positive...
Hardy-Weinberg Principle01:49

Hardy-Weinberg Principle

Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.In the early 20th century,...
Types of Selection01:46

Types of Selection

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...
Mutation, Gene Flow, and Genetic Drift01:09

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).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...
Conservative Site-specific Recombination and Phase Variation02:53

Conservative Site-specific Recombination and Phase Variation

Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
The recognition sites for Cre recombinase called LoxP...
Genetic Drift03:33

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.Life is not fair. A deer grazing contentedly in a field can have her meal cut tragically short by a bolt of lightning. If the doomed doe is one of only three in the population, 1/3 of the population’s gene pool is lost. Random events like this can...

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Related Experiment Video

Updated: Jul 3, 2026

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
06:18

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Published on: July 11, 2025

Confounding between recombination and selection, and the Ped/Pop method for detecting selection.

Paul F O'Reilly1, Ewan Birney, David J Balding

  • 1Department of Epidemiology and Public Health, Imperial College London, UK. paul.oreilly@imperial.ac.uk <paul.oreilly@imperial.ac.uk>

Genome Research
|July 12, 2008
PubMed
Summary
This summary is machine-generated.

Detecting natural selection is complicated by recombination. This study introduces a new method comparing pedigree and population recombination rates to accurately identify genetic selection, even in high-recombination areas.

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Identification of Homologous Recombination Events in Mouse Embryonic Stem Cells Using Southern Blotting and Polymerase Chain Reaction
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Identification of Homologous Recombination Events in Mouse Embryonic Stem Cells Using Southern Blotting and Polymerase Chain Reaction

Published on: November 20, 2018

Related Experiment Videos

Last Updated: Jul 3, 2026

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
06:18

Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

Published on: July 11, 2025

Identification of Homologous Recombination Events in Mouse Embryonic Stem Cells Using Southern Blotting and Polymerase Chain Reaction
08:01

Identification of Homologous Recombination Events in Mouse Embryonic Stem Cells Using Southern Blotting and Polymerase Chain Reaction

Published on: November 20, 2018

Area of Science:

  • Population Genetics
  • Evolutionary Biology
  • Genomics

Background:

  • Recent advancements in population genetics enable estimation of recombination rates and natural selection levels.
  • Positive selection and recombination interact, potentially confounding inferences of genetic variation.
  • Existing genome-wide scans for selection may be biased by recombination rates, particularly in humans.

Purpose of the Study:

  • To investigate the confounding effects of positive selection on recombination rate estimates.
  • To develop a novel genome-wide method for detecting recent natural selection.
  • To improve the power and accuracy of identifying adaptive evolution.

Main Methods:

  • Illustrated the impact of positive selection on population-based recombination estimates.
  • Introduced a new genome-wide approach using the ratio of pedigree-based to population-based recombination rates (Ped/Pop method).
  • Validated the Ped/Pop method through simulations and application to human genetic data (HapMap, Perlegen).

Main Results:

  • Modest positive selection significantly reduces population-based recombination rate estimates.
  • Human genome-wide selection scans favor regions with low recombination, indicating potential bias.
  • The Ped/Pop method demonstrates good power to detect completed selective sweeps and distinguish adaptive from neutral evolution.

Conclusions:

  • The interplay between selection and recombination necessitates refined methods for accurate genetic inference.
  • The Ped/Pop method offers a robust approach for detecting recent positive selection across the genome.
  • This method performs well in diverse genomic regions and remains effective long after selection events.