Evidence map›Paper›PMID 24957848›Full record

ArticleEvolution; international journal of organic evolution2014

Effects of epistasis on infectivity range during host-parasite coevolution.

Ben Ashby, Sunetra Gupta, Angus Buckling

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Antigenic evolution of SARS-CoV-2 in immunocompromised hosts.Evolution, medicine, and public health · 2023
    Article
  2. Article
  3. Coevolutionary theory of hosts and parasites.Journal of evolutionary biology · 2022
    Review
  4. Article
  5. Coevolution of parasite virulence and host mating strategies.Proceedings of the National Academy of Sciences of the United States of America · 2015
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ben AshbyDepartment of Zoology, University of Oxford, South Parks Road, Oxford, OX1 3PS, United Kingdom. ben.ashby@zoo.ox.ac.uk.
Sunetra Gupta
Angus Buckling

Funding

Biotechnology and Biological Sciences Research Council
6 · The paper itself

Abstract

Understanding how parasites adapt to changes in host resistance is crucial to evolutionary epidemiology. Experimental studies have demonstrated that parasites are more capable of adapting to gradual, rather than sudden changes in host phenotype, as the latter may require multiple mutations that are unlikely to arise simultaneously. A key, but as yet unexplored factor is precisely how interactions between mutations (epistasis) affect parasite evolution. Here, we investigate this phenomenon in the context of infectivity range, where parasites may experience selection to infect broader sets of genotypes. When epistasis is strongly positive, we find that parasites are unlikely to evolve broader infectivity ranges if hosts exhibit sudden, rather than gradual changes in phenotype, in close agreement with empirical observations. This is due to a low probability of fixing multiple mutations that individually confer no immediate advantage. When epistasis is weaker, parasites are more likely to evolve broader infectivity ranges if hosts make sudden changes in phenotype, which can be explained by a balance between mutation supply and selection. Thus, we demonstrate that both the rate of phenotypic change in hosts and the form of epistasis between mutations in parasites are crucial in shaping the evolution of infectivity range.

Indexed as

Biological EvolutionEpistasis, GeneticModels, GeneticGenetic FitnessGenotypeHost-Parasite InteractionsPhenotypeEpistasisgeneralismhost-parasite coevolutioninfectivity rangemultiple mutationsresistance

Identifiers

PMID24957848
PMCPMC4261995

What OpenQuestion holds

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Registered trials

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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.