Mutation bias and the predictability of evolution

Author:

Cano Alejandro V.12ORCID,Gitschlag Bryan L.3,Rozhoňová Hana12,Stoltzfus Arlin45,McCandlish David M.3,Payne Joshua L.12ORCID

Affiliation:

1. Institute of Integrative Biology, ETH Zurich, 8092 Zurich, Switzerland

2. Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland

3. Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA

4. Office of Data and Informatics, Material Measurement Laboratory, National Institute of Standards and Technology, Rockville, MD 20899, USA

5. Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA

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’.

Funder

John Templeton Foundation

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Publisher

The Royal Society

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology

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