Mutation bias shapes the spectrum of adaptive substitutions

Cano, Alejandro V, Rozhoňová, Hana, Stoltzfus, Arlin, McCandlish, David M, Payne, Joshua L (February 2022) Mutation bias shapes the spectrum of adaptive substitutions. Proceedings of the National Academy of Sciences of USA, 119 (7). e2119720119-e2119720119. ISSN 0027-8424

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Abstract

Evolutionary adaptation often occurs by the fixation of beneficial mutations. This mode of adaptation can be characterized quantitatively by a spectrum of adaptive substitutions, i.e., a distribution for types of changes fixed in adaptation. Recent work establishes that the changes involved in adaptation reflect common types of mutations, raising the question of how strongly the mutation spectrum shapes the spectrum of adaptive substitutions. We address this question with a codon-based model for the spectrum of adaptive amino acid substitutions, applied to three large datasets covering thousands of amino acid changes identified in natural and experimental adaptation in Saccharomyces cerevisiae, Escherichia coli, and Mycobacterium tuberculosis Using species-specific mutation spectra based on prior knowledge, we find that the mutation spectrum has a proportional influence on the spectrum of adaptive substitutions in all three species. Indeed, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover the species-specific mutation spectra. However, we also find that the predictive power of the model differs substantially between the three species. To better understand these differences, we use population simulations to explore the factors that influence how closely the spectrum of adaptive substitutions mirrors the mutation spectrum. The results show that the influence of the mutation spectrum decreases with increasing mutational supply ([Formula: see text]) and that predictive power is strongly affected by the number and diversity of beneficial mutations.

Item Type:	Paper
Subjects:	bioinformatics > genomics and proteomics > design > amino acid design diseases & disorders > Bacterial Infections bioinformatics bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification diseases & disorders bioinformatics > genomics and proteomics > genetics & nucleic acid processing bioinformatics > genomics and proteomics bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification organism description > yeast > Saccharomyces organism description > bacteria organism description > bacteria > escherichia coli evolution bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > gene regulation bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function > gene regulation bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > mutations diseases & disorders > Bacterial Infections > tuberculosis organism description > yeast
CSHL Authors:	McCandlish, David
Communities:	CSHL labs > McCandlish lab
SWORD Depositor:	CSHL Elements
Depositing User:	CSHL Elements
Date:	15 February 2022
Date Deposited:	16 Feb 2022 15:24
Last Modified:	11 Jan 2024 19:05
PMCID:	PMC8851560
URI:	https://repository.cshl.edu/id/eprint/40516

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