Evidence map›Paper›PMID 25311558›Full record

ArticleEvolution; international journal of organic evolution2014

Properties of selected mutations and genotypic landscapes under Fisher's geometric model.

François Blanquart, Guillaume Achaz, Thomas Bataillon, Olivier Tenaillon

Abstract read
In one paragraph

Article in Evolution; international journal of organic evolution, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

42 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Fisher's Geometric Model as a Tool to Study Speciation.Cold Spring Harbor perspectives in biology · 2024
    Review
  6. Article
  7. Article
  8. Article
  9. Evolutionary rescue on genotypic fitness landscapes.Journal of the Royal Society, Interface · 2023
    Article
  10. A null model for the distribution of fitness effects of mutations.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  11. Epistasis decreases with increasing antibiotic pressure but not temperature.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Article
  12. Global epistasis on fitness landscapes.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

François BlanquartBioinformatics Research Centre, University of Aarhus, 8000C, Aarhus, Denmark. francois.blanquart@normalesup.org.
Guillaume Achaz
Thomas Bataillon
Olivier Tenaillon

Funding

European Research Council 310944
6 · The paper itself

Abstract

The fitness landscape-the mapping between genotypes and fitness-determines properties of the process of adaptation. Several small genotypic fitness landscapes have recently been built by selecting a handful of beneficial mutations and measuring fitness of all combinations of these mutations. Here, we generate several testable predictions for the properties of these small genotypic landscapes under Fisher's geometric model of adaptation. When the ancestral strain is far from the fitness optimum, we analytically compute the fitness effect of selected mutations and their epistatic interactions. Epistasis may be negative or positive on average depending on the distance of the ancestral genotype to the optimum and whether mutations were independently selected, or coselected in an adaptive walk. Simulations show that genotypic landscapes built from Fisher's model are very close to an additive landscape when the ancestral strain is far from the optimum. However, when it is close to the optimum, a large diversity of landscape with substantial roughness and sign epistasis emerged. Strikingly, small genotypic landscapes built from several replicate adaptive walks on the same underlying landscape were highly variable, suggesting that several realizations of small genotypic landscapes are needed to gain information about the underlying architecture of the fitness landscape.

Indexed as

Genetic FitnessModels, GeneticMutationSelection, GeneticAdaptation, PhysiologicalBacteriaEpistasis, GeneticGenotypeAdaptationepistasisexperimental evolutionNK modelRough Mount Fujiselection

Identifiers

PMID25311558
PMCPMC4326662

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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.