Evidence map›Paper›PMID 31951609›Full record

ArticlePLoS computational biology2020

Limits on amplifiers of natural selection under death-Birth updating.

Josef Tkadlec, Andreas Pavlogiannis, Krishnendu Chatterjee, Martin A Nowak

Abstract read
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Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

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31citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

31 citing papers in PubMed.

  1. Mixed updating in structured populations.PLoS computational biology · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Colonization times in Moran process on graphs.PLoS computational biology · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Fixation times on directed graphs.PLoS computational biology · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Evolutionary dynamics of mutants that modify population structure.Journal of the Royal Society, Interface · 2023
    Article
  14. Article
  15. Article
  16. Article
  17. Fixation dynamics on hypergraphs.PLoS computational biology · 2023
    Article
  18. Article
  19. Categorizing update mechanisms for graph-structured metapopulations.Journal of the Royal Society, Interface · 2023
    Article
  20. Suppressors of fixation can increase average fitness beyond amplifiers of selection.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Josef TkadlecIST Austria, Klosterneuburg, Austria.ORCID 0000-0002-1097-9684
Andreas PavlogiannisLab for Automated Reasoning and Analysis, EPFL, Lausanne, Switzerland.
Krishnendu ChatterjeeIST Austria, Klosterneuburg, Austria.
Martin A NowakProgram for Evolutionary Dynamics, Department of Organismic and Evolutionary Biology, Department of Mathematics, Harvard University, Cambridge, Massachusetts, United States of America.ORCID 0000-0001-5489-0908

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The fixation probability of a single mutant invading a population of residents is among the most widely-studied quantities in evolutionary dynamics. Amplifiers of natural selection are population structures that increase the fixation probability of advantageous mutants, compared to well-mixed populations. Extensive studies have shown that many amplifiers exist for the Birth-death Moran process, some of them substantially increasing the fixation probability or even guaranteeing fixation in the limit of large population size. On the other hand, no amplifiers are known for the death-Birth Moran process, and computer-assisted exhaustive searches have failed to discover amplification. In this work we resolve this disparity, by showing that any amplification under death-Birth updating is necessarily bounded and transient. Our boundedness result states that even if a population structure does amplify selection, the resulting fixation probability is close to that of the well-mixed population. Our transience result states that for any population structure there exists a threshold r⋆ such that the population structure ceases to amplify selection if the mutant fitness advantage r is larger than r⋆. Finally, we also extend the above results to δ-death-Birth updating, which is a combination of Birth-death and death-Birth updating. On the positive side, we identify population structures that maintain amplification for a wide range of values r and δ. These results demonstrate that amplification of natural selection depends on the specific mechanisms of the evolutionary process.

Indexed as

Models, BiologicalComputational BiologyMutationPopulation DensityPopulation DynamicsSelection, GeneticStochastic Processes

Identifiers

PMID31951609
PMCPMC6968837

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.