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Hardy-Weinberg Principle

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.

Mutation, Gene Flow, and Genetic Drift

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).

Frequency-dependent Selection

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.

What is Population Genetics?

What is Population Genetics?

A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.

Genetic Drift

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.

Gene Flow

Gene Flow

Gene flow is the transfer of genes among populations, resulting from either the dispersal of gametes or from the migration of individuals.

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Related Experiment Video

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Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

A path integral approach for allele frequency dynamics under polygenic selection.

Nathan W Anderson¹, Lloyd Kirk¹, Joshua G Schraiber²

¹Department of Integrative Biology, University of Wisconsin-Madison, Madison, WI 53706, USA.

|November 12, 2024

Summary

This study extends path integral methods to predict allele frequency changes under selection in evolve-and-resequence experiments. The new analytic expressions help identify genetic architectures of complex polygenic traits.

Keywords:

diffusion approximation evolve and resequence polygenic selection transition density

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Mutagenesis and Functional Selection Protocols for Directed Evolution of Proteins in E. coli

Mutagenesis and Functional Selection Protocols for Directed Evolution of Proteins in E. coli

Published on: March 16, 2011

Area of Science:

Quantitative genetics
Evolutionary biology
Population genetics

Background:

Polygenic traits pose challenges for genetic architecture studies and phenotype prediction.
Evolve-and-resequence (E&R) experiments identify trait loci via allele frequency changes (AFCs) under selection.
Distinguishing selection from genetic drift in AFCs is difficult, especially for complex traits.

Purpose of the Study:

To extend path integral methods for predicting AFCs under selection in quantitative genetics.
To derive analytic expressions for allele transition probabilities under stabilizing and adaptive selection.
To improve the design of E&R experiments for uncovering polygenic architectures.

Main Methods:

Applied the perturbation approximation, a path integral method, to quantitative genetics selection scenarios.
Derived analytic expressions for allele transition probabilities.
Utilized these expressions to analyze AFCs for selection detection and E&R experimental design.

Main Results:

Developed novel analytic expressions for allele frequency dynamics under stabilizing and adaptive selection.
Provided a framework to better distinguish selection from drift in E&R experiments.
Characterized optimal E&R experimental designs for studying polygenic traits.

Conclusions:

The extended path integral approach enhances the analysis of E&R experiments for complex traits.
This work provides tools to better understand the genetic basis of adaptation and trait evolution.
Improved experimental designs will facilitate the discovery of genetic architectures underlying polygenic traits.