ArticleEvolution; international journal of organic evolution2014
Rates of fitness decline and rebound suggest pervasive epistasis.
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 58 papers.
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Who cites it
58 citing papers in PubMed.
- Review
- Rapid evolution in necromass use under resource limitation reduces persistence in producer-decomposer microbial biospheres.Communications biology · 2026Article
- Historical contingency limits adaptive diversification in a spatially structured environment.Evolution letters · 2026Article
- The mutational landscape of Bacillus subtilis conditional hypermutators shows how proofreading skews DNA polymerase error rates.Nucleic acids research · 2025Article
- Lethal mutagenesis and the transient within-host dynamics of viral adaptation.Virus evolution · 2025Article
- Dysfunctional β-cell longevity in diabetes relies on energy conservation and positive epistasis.Life science alliance · 2024Article
- Article
- Unpredictability of the Fitness Effects of Antimicrobial Resistance Mutations Across Environments in Escherichia coli.Molecular biology and evolution · 2024Article
- Global epistasis in plasmid-mediated antimicrobial resistance.Molecular systems biology · 2024Review
- Changing fitness effects of mutations through long-term bacterial evolution.Science (New York, N.Y.) · 2024Article
- Environmental modulation of global epistasis in a drug resistance fitness landscape.Nature communications · 2023Article
- Epistasis and evolution: recent advances and an outlook for prediction.BMC biology · 2023Review
- Epistasis decreases with increasing antibiotic pressure but not temperature.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
- Adaptation of the yeast gene knockout collection is near-perfectly predicted by fitness and diminishing return epistasis.G3 (Bethesda, Md.) · 2022Article
- Selection in a growing colony biases results of mutation accumulation experiments.Scientific reports · 2022Article
- Fitness of evolving bacterial populations is contingent on deep and shallow history but only shallow history creates predictable patterns.Proceedings. Biological sciences · 2022Article
- Mutational robustness changes during long-term adaptation in laboratory budding yeast populations.eLife · 2022Article
- Idiosyncratic epistasis leads to global fitness-correlated trends.Science (New York, N.Y.) · 2022Article
- Precise measurement of the fitness effects of spontaneous mutations by droplet digital PCR in Burkholderia cenocepacia.Genetics · 2021Article
- Historical Contingency Causes Divergence in Adaptive Expression of the lac Operon.Molecular biology and evolution · 2021Article
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Authors and funding
4 authors.
Funding
Abstract
Unraveling the factors that determine the rate of adaptation is a major question in evolutionary biology. One key parameter is the effect of a new mutation on fitness, which invariably depends on the environment and genetic background. The fate of a mutation also depends on population size, which determines the amount of drift it will experience. Here, we manipulate both population size and genotype composition and follow adaptation of 23 distinct Escherichia coli genotypes. These have previously accumulated mutations under intense genetic drift and encompass a substantial fitness variation. A simple rule is uncovered: the net fitness change is negatively correlated with the fitness of the genotype in which new mutations appear--a signature of epistasis. We find that Fisher's geometrical model can account for the observed patterns of fitness change and infer the parameters of this model that best fit the data, using Approximate Bayesian Computation. We estimate a genomic mutation rate of 0.01 per generation for fitness altering mutations, albeit with a large confidence interval, a mean fitness effect of mutations of -0.01, and an effective number of traits nine in mutS(-) E. coli. This framework can be extended to confront a broader range of models with data and test different classes of fitness landscape models.
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