Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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,...
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...
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
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,...
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Joint estimation of selection intensity and mutation rate under balancing selection with applications to HLA.

Genetics·2022
Same author

Estimation of coalescence probabilities and population divergence times from SNP data.

Heredity·2021
Same author

Transcontinental dispersal of <i>Anopheles gambiae</i> occurred from West African origin via serial founder events.

Communications biology·2019
Same author

Genome-wide divergence among invasive populations of Aedes aegypti in California.

BMC genomics·2019
Same author

F<sub>ST</sub> between archaic and present-day samples.

Heredity·2018
Same author

Partial genomic survival of cave bears in living brown bears.

Nature ecology & evolution·2018

Related Experiment Video

Updated: Jul 7, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

A Bayesian method for jointly estimating allele age and selection intensity.

Montgomery Slatkin1

  • 1Department of Integrative Biology, 3060 VLSB, University of California at Berkeley, Berkeley, CA 94720-3140, USA. slatkin@berkeley.edu

Genetics Research
|February 22, 2008
PubMed
Summary
This summary is machine-generated.

This study develops a Bayesian method to estimate past selection intensity and allele age, crucial for understanding genetic evolution. The approach is applied to G6PD allele frequency in Africa, revealing insights into population genetics.

More Related Videos

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

Related Experiment Videos

Last Updated: Jul 7, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

Area of Science:

  • Population genetics
  • Evolutionary biology
  • Statistical genetics

Background:

  • Estimating the age and selection intensity of alleles is fundamental to understanding evolutionary processes.
  • Previous methods often struggle with jointly inferring these two key parameters, especially for low-frequency alleles.

Purpose of the Study:

  • To develop a robust Bayesian framework for the joint estimation of allele age and selection intensity.
  • To create a practical computational method, importance sampling, applicable to low-frequency alleles.

Main Methods:

  • Formulation of a Bayesian model incorporating prior distributions from population genetics theory.
  • Development of an importance sampling algorithm for efficient estimation.
  • Application to scenarios with known haplotypes or inferred ancestral segment lengths.

Main Results:

  • The proposed method provides a principled approach to jointly infer allele age and selection intensity.
  • Demonstrated applicability to real-world data, exemplified by the G6PD A-allele in Africa.
  • Highlights the inherent stochasticity in allele frequency changes and recombination, setting accuracy limits.

Conclusions:

  • The Bayesian framework and importance sampling method offer a powerful tool for evolutionary genetic inference.
  • Accurate estimation of past selection is achievable, though limited by biological randomness.
  • Provides a foundation for further research into the evolutionary dynamics of genetic variants.