Cano, Alejandro V, Gitschlag, Bryan L, Rozhoňová, Hana, Stoltzfus, Arlin, McCandlish, David M, Payne, Joshua L (May 2023) Mutation bias and the predictability of evolution. Philosophical Transactions of the Royal Society B: Biological Sciences, 378 (1877). p. 20220055. ISSN 0962-8436
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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'.
| Item Type: | Paper |
|---|---|
| Subjects: | bioinformatics bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification bioinformatics > genomics and proteomics > genetics & nucleic acid processing bioinformatics > genomics and proteomics evolution bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > mutations bioinformatics > genomics and proteomics > genetics & nucleic acid processing > population genetics |
| CSHL Authors: | |
| Communities: | CSHL labs > McCandlish lab |
| SWORD Depositor: | CSHL Elements |
| Depositing User: | CSHL Elements |
| Date: | 22 May 2023 |
| Date Deposited: | 20 Apr 2023 18:50 |
| Last Modified: | 08 Jan 2024 17:14 |
| PMCID: | PMC10067271 |
| Related URLs: | |
| URI: | https://repository.cshl.edu/id/eprint/40880 |
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