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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.

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).

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.

Speciation Rates

Speciation Rates

Types of Selection

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...

Diffusion

Diffusion

Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...

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Transition Densities and Sample Frequency Spectra of Diffusion Processes with Selection and Variable Population Size.

Daniel Živković¹, Matthias Steinrücken², Yun S Song³

¹Section of Evolutionary Biology, Department of Biology, Ludwig-Maximilian University Munich, 82152 Munich, Germany zivkovic@bio.lmu.de.

|April 16, 2015

Summary

New models in population genetics now account for selection and changing population sizes. This study develops methods to compute the sample frequency spectrum, improving demographic parameter estimation and detecting selection impacts.

Keywords:

demography diffusion frequency spectrum selection transition density

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Area of Science:

Population Genetics
Evolutionary Biology
Quantitative Genetics

Background:

Empirical advances necessitate models integrating selection and demography.
Existing models often simplify population size dynamics.
Accurate modeling is crucial for understanding evolutionary processes.

Purpose of the Study:

To develop and apply methods for analyzing population genetic data under selection and variable effective population size.
To extend spectral representation methods for non-constant population sizes.
To investigate the impact of selection on demographic parameter estimation and detect selection signatures.

Main Methods:

Extended spectral representation for Wright-Fisher diffusion with genic selection and piecewise-constant population sizes.
Developed an efficient moment-based algorithm for sample frequency spectrum computation.
Applied methods to assess demographic inference under incorrect neutrality assumption and detect selection during population growth.

Main Results:

Accurate computation of the sample frequency spectrum is achievable with genic selection and variable population sizes.
Incorrect neutrality assumption can bias demographic parameter estimation.
The impact of negative selection is detectable even in rapidly growing populations.

Conclusions:

The developed methods provide powerful tools for analyzing complex population genetic scenarios.
Accurate demographic inference requires explicit consideration of selection.
These findings advance our understanding of evolutionary dynamics in natural populations.