ArticleHeredity2018
Long-term evolution on complex fitness landscapes when mutation is weak.
Article in Heredity, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Inference and Visualization of Complex Genotype-Phenotype Maps.Molecular biology and evolution · 2026Article
- Inference and visualization of complex genotype-phenotype maps withbioRxiv : the preprint server for biology · 2025Article
- Graph-structured populations elucidate the role of deleterious mutations in long-term evolution.Nature communications · 2025Article
- Master regulators of biological systems in higher dimensions.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Impact of population size on early adaptation in rugged fitness landscapes.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
- Higher-order epistasis and phenotypic prediction.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Genetic architecture and adaptation of flowering time among environments.The New phytologist · 2021Article
- The evolutionary scaling of cellular traits imposed by the drift barrier.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
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Authors and funding
1 author.
Funding
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Abstract
Understanding evolution on complex fitness landscapes is difficult both because of the large dimensionality of sequence space and the stochasticity inherent to population-genetic processes. Here, I present an integrated suite of mathematical tools for understanding evolution on time-invariant fitness landscapes when mutations occur sufficiently rarely that the population is typically monomorphic and evolution can be modeled as a sequence of well-separated fixation events. The basic intuition behind this suite of tools is that surrounding any particular genotype lies a region of the fitness landscape that is easy to evolve to, while other pieces of the fitness landscape are difficult to evolve to (due to distance, being across a fitness valley, etc.). I propose a rigorous definition for this "dynamical neighborhood" of a genotype which captures several aspects of the distribution of waiting times to evolve from one genotype to another. The neighborhood structure of the landscape as a whole can be summarized as a matrix, and I show how this matrix can be used to approximate the expected waiting time for certain evolutionary events to occur and to provide an intuitive interpretation to existing formal results on the index of dispersion of the molecular clock.
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