Population heterogeneity in mutation rate increases the frequency of higher-order mutants and reduces long-term mutational load

Helen K. Alexander, Stephanie I. Mayer, Sebastian Bonhoeffer

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Mutation rate is a crucial evolutionary parameter that has typically been treated as a constant in population genetic analyses. However, the propensity to mutate is likely to vary among co-existing individuals within a population, due to genetic polymorphisms, heterogeneous environmental influences, and random physiological fluctuations. We review the evidence for mutation rate heterogeneity and explore its consequences by extending classic population genetic models to allow an arbitrary distribution of mutation rate among individuals, either with or without inheritance. With this general new framework, we rigorously establish the effects of heterogeneity at various evolutionary timescales. In a single generation, variation of mutation rate about the mean increases the probability of producing zero or many simultaneous mutations on a genome. Over multiple generations of mutation and selection, heterogeneity accelerates the appearance of both deleterious and beneficial multi-point mutants. At mutation-selection balance, higher-order mutant frequencies are likewise boosted, while lower-order mutants exhibit subtler effects; nonetheless, population mean fitness is always enhanced. We quantify the dependencies on moments of the mutation rate distribution and selection coefficients, and clarify the role of mutation rate inheritance. While typical methods of estimating mutation rate will recover only the population mean, analyses assuming mutation rate is fixed to this mean could underestimate the potential for multi-locus adaptation, including medically relevant evolution in pathogenic and cancerous populations. We discuss the potential to empirically parameterize mutation rate distributions, which have to date hardly been quantified.
Original languageEnglish
Article numbermsw244
Pages (from-to)419–436
Number of pages18
JournalMolecular Biology and Evolution
Volume34
Issue number2
Early online date11 Nov 2016
DOIs
Publication statusPublished - 1 Feb 2017

Keywords / Materials (for Non-textual outputs)

  • transient mutagenesis
  • population genetics
  • cancer
  • bacteria
  • hypermutator
  • adaptation

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