ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2023
Mutation bias and the predictability of evolution.
Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 32 citations in OpenAlex.
- Intraspecific sequence variation and complete genomes refine the identification of rapidly evolved regions in humans.Cell genomics · 2026Article
- Emergence Biases in Molecular Evolution.Genome biology and evolution · 2026Review
- Evolvability: progress and key questions.Bioscience · 2025Review
- FoTeRs: a novel family of telomere-associated retrotransposons in Fusarium oxysporum.Mobile DNA · 2025Article
- Convergent Evolution and the Epigenome.Epigenomes · 2025Review
- The Genomic Kaleidoscope: On the Hidden Dimensions of Within-Species Genomic Diversity.Genome biology and evolution · 2025Review
- Evolution and evolvability of rifampicin resistance across the bacterial tree of life.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A Segregating Structural Variant Defines Novel Venom Phenotypes in the Eastern Diamondback Rattlesnake.Molecular biology and evolution · 2025Article
- Anticipating protein evolution with successor sequence predictor.Journal of cheminformatics · 2025Article
- The highly rugged yet navigable regulatory landscape of the bacterial transcription factor TetR.Nature communications · 2024Article
- Does strain-level persistence of lactobacilli in long-term back-slopped sourdoughs inform on domestication of food-fermenting lactic acid bacteria?Applied and environmental microbiology · 2024Article
- Library-Assisted Evolution in Eukaryotic Cells Yield Adenine Base Editors with Enhanced Editing Specificity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Assessing the predictability of fungicide resistance evolution through in vitro selection.Journal of plant diseases and protection : scientific journal of the German Phytomedical Society (DPG) · 2024Article
- Interdisciplinary approaches to predicting evolutionary biology.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
- Mutation bias and the predictability of evolution.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Distribution of mutation rates challenges evolutionary predictability.Microbiology (Reading, England) · 2023Article
- "Bet hedging" against climate change in developing and adult animals: roles for stochastic gene expression, phenotypic plasticity, epigenetic inheritance and adaptation.Frontiers in physiology · 2023Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Predicting evolutionary outcomes is an important research goal in a diversity of contexts. The focus of evolutionary forecasting is usually on adaptive processes, and efforts to improve prediction typically focus on selection. However, adaptive processes often rely on new mutations, which can be strongly influenced by predictable biases in mutation. Here, we provide an overview of existing theory and evidence for such mutation-biased adaptation and consider the implications of these results for the problem of prediction, in regard to topics such as the evolution of infectious diseases, resistance to biochemical agents, as well as cancer and other kinds of somatic evolution. We argue that empirical knowledge of mutational biases is likely to improve in the near future, and that this knowledge is readily applicable to the challenges of short-term prediction. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.
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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.