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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.
Speciation Rates01:07

Speciation Rates

Overview
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).
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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.
Evolutionary Processes in Microbes01:26

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Microbial evolution occurs rapidly due to short generation times and a variety of genetic processes, including horizontal gene transfer, mutation, recombination, and genetic drift. These mechanisms collectively enable microbes to adapt swiftly to changing environments.Horizontal gene transfer (HGT) allows genes to move between different species and occurs through three main mechanisms: conjugation, transformation, and transduction. Conjugation involves direct cell-to-cell contact for DNA...
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Limits to Natural Selection

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Related Experiment Video

Updated: May 13, 2026

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

Evolutionary processes in finite populations.

Dirk M Lorenz1, Jeong-Man Park, Michael W Deem

  • 1Department of Physics, Rice University, Houston, Texas, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|March 19, 2013
PubMed
Summary

Finite populations evolve with lower average fitness than infinite populations, even on complex fitness landscapes. Evolutionary dynamics show size-dependent probabilities and mutation-rate-influenced fluctuations.

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Area of Science:

  • Evolutionary biology
  • Population genetics
  • Mathematical modeling

Background:

  • Understanding evolutionary dynamics in finite populations is crucial for predicting adaptation and diversity.
  • Infinite population models offer a simplified view, but real populations are finite, introducing stochastic effects.

Purpose of the Study:

  • To analyze the evolutionary process in large but finite populations on arbitrary fitness landscapes.
  • To quantify the deviation of finite population dynamics from infinite population approximations.
  • To investigate the impact of system size and mutation rate on evolutionary trajectories.

Main Methods:

  • Modeling the evolutionary process using a Markov-Moran process.
  • Deriving analytical results for time-averaged fitness and fluctuations.
  • Analyzing the system size dependence of path probabilities through the fitness landscape.

Main Results:

  • Time-averaged fitness in finite populations is lower than in infinite populations, to O(1/N).
  • Fluctuations in genotype counts can scale with inverse powers of the mutation rate.
  • The probability of traversing specific paths in the fitness landscape can exhibit non-monotonic behavior with population size.

Conclusions:

  • Finite population size introduces significant deviations from infinite population models, impacting evolutionary outcomes.
  • Stochastic effects, influenced by population size and mutation, play a critical role in shaping evolutionary trajectories.
  • The study highlights the importance of considering finite population dynamics for accurate evolutionary predictions.