ArticleGenetics2014
Environment determines epistatic patterns for a ssDNA virus.
Article in Genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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.
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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.
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Who cites it
14 citing papers in PubMed.
- The importance of epistasis in the evolution of viral pathogens.Virus evolution · 2025Review
- Saturation Mutagenesis Genome Engineering of Infective ΦX174 BacteriophageACS synthetic biology · 2020Article
- Recent insights into the genotype-phenotype relationship from massively parallel genetic assays.Evolutionary applications · 2019Review
- Article
- Selecting among three basic fitness landscape models: Additive, multiplicative and stickbreaking.Theoretical population biology · 2018Article
- Additive Phenotypes Underlie Epistasis of Fitness Effects.Genetics · 2018Article
- Mutation-Driven Parallel Evolution during Viral Adaptation.Molecular biology and evolution · 2017Article
- Article
- Dynamics of molecular evolution in RNA virus populations depend on sudden versus gradual environmental change.Evolution; international journal of organic evolution · 2017Article
- Epistatic Interactions in the Arabinose Cis-Regulatory Element.Molecular biology and evolution · 2016Article
- Article
- Evaluating the within-host fitness effects of mutations fixed during virus adaptation to different ecotypes of a new host.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2015Article
- What can we learn from fitness landscapes?Current opinion in microbiology · 2014Review
- Evolutionary inevitability of sexual antagonism.Proceedings. Biological sciences · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
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Abstract
Despite the accumulation of substantial quantities of information about epistatic interactions among both deleterious and beneficial mutations in a wide array of experimental systems, neither consistent patterns nor causal explanations for these interactions have yet emerged. Furthermore, the effects of mutations depend on the environment in which they are characterized, implying that the environment may also influence epistatic interactions. Recent work with beneficial mutations for the single-stranded DNA bacteriophage ID11 demonstrated that interactions between pairs of mutations could be understood by means of a simple model that assumes that mutations have additive phenotypic effects and that epistasis arises through a nonlinear phenotype-fitness map with a single intermediate optimum. To determine whether such a model could also explain changes in epistatic patterns associated with changes in environment, we measured epistatic interactions for these same mutations under conditions for which we expected to find the wild-type ID11 at different distances from its phenotypic optimum by assaying fitnesses at three different temperatures: 33°, 37°, and 41°. Epistasis was present and negative under all conditions, but became more pronounced as temperature increased. We found that the additive-phenotypes model explained these patterns as changes in the parameters of the phenotype-fitness map, but that a model that additionally allows the phenotypes to vary across temperatures performed significantly better. Our results show that ostensibly complex patterns of fitness effects and epistasis across environments can be explained by assuming a simple structure for the genotype-phenotype relationship.
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Registered trials
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.