Cited by 46Evolution and Genetic DynamicsMathematical and Theoretical Epidemiology and Ecology ModelsStochastic processes and statistical mechanics

The fundamental theorem of natural selection with mutations

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Basener, William F., Sanford, John C.·2018·Journal of Mathematical Biology

Abstract

The mutation-selection process is the most fundamental mechanism of evolution. In 1935, R. A. Fisher proved his fundamental theorem of natural selection, providing a model in which the rate of change of mean fitness is equal to the genetic variance of a species. Fisher did not include mutations in his model, but believed that mutations would provide a continual supply of variance resulting in perpetual increase in mean fitness, thus providing a foundation for neo-Darwinian theory. In this paper we re-examine Fisher's Theorem, showing that because it disregards mutations, and because it is invalid beyond one instant in time, it has limited biological relevance. We build a differential equations model from Fisher's first principles with mutations added, and prove a revised theorem showing the rate of change in mean fitness is equal to genetic variance plus a mutational effects term. We refer to our revised theorem as the fundamental theorem of natural selection with mutations. Our expanded theorem, and our associated analyses (analytic computation, numerical simulation, and visualization), provide a clearer understanding of the mutation-selection process, and allow application of biologically realistic parameters such as mutational effects. The expanded theorem has biological implications significantly different from what Fisher had envisioned.

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  • Kimura's mutational spectrum implies a fitness decrease over time, in line with Haldane's Dilemma.

    “In particular, they showed that Kimura's mutational spectrum implies a fitness decreases over time, in line with the predictions of Haldane's Dilemma.”

    From Using statistical methods to model the fine-tuning of molecular machines and systems (2020) · cites this paper as Basener and Sanford (2018)

    The Numerical simulations section uses a gamma distribution attributed to Kimura and reports steadily declining fitness in a finite-population simulation. The Discussion likewise reports continuous decline under its modeled deleterious-to-beneficial mutation ratio. Our copy does not connect that result to Haldane’s Dilemma, and the decline is a result under the paper’s modeling conditions rather than an unqualified implication of Kimura’s spectrum. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • Basener and Sanford (2018) extended Fisher's Theorem to allow for arbitrary mutational spectra.

    “Basener and Sanford (2018) recently extended Fisher's Theorem, allowing for arbitrary mutational spectra.”

    From Using statistical methods to model the fine-tuning of molecular machines and systems (2020) · cites this paper as Basener and Sanford (2018)

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Authors
Basener, W. F., & Sanford, J. C.
Affiliations
Rochester Institute of Technology (US)
Corresponding author
Basener, William F.
Venue
Journal of Mathematical Biology
Published
2017-11-07
Volume
76
Issue
7
Pages
1589-1622
ISSN
  • 0303-6812 (ISSN-L)
  • 1432-1416
OpenAlex
W2767985017
Cited by
46
References
61
Citations by year
2026: 4 · 2025: 2 · 2024: 11 · 2023: 9 · 2022: 3 · 2021: 6 · 2020: 9 · 2019: 2
FWCI
2.00
Type
journal article
Language
en
Open access
Locations
  • Journal of Mathematical Biology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
  • Physical Sciences › Mathematics › Mathematical Physics › Stochastic processes and statistical mechanics
Keywords
fundamental theorem of natural selection, mutation-selection balance, mean fitness, genetic variance, mutation effects, neo-Darwinian theory, evolutionary dynamics, differential equation model
MeSH terms
Animals, Computer Simulation, Genetics, Population, Humans, Models, Genetic, Mutation, Population Dynamics, Selection, Genetic, Systems Analysis, Time Factors, Genetic Variation, Normal Distribution, Computational Biology, Genetic Determinism, Mathematical Concepts, Genetic Fitness

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