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Fitness effects of mutations to SARS-CoV-2 proteins

View ORCID ProfileJesse D. Bloom, View ORCID ProfileRichard A. Neher
doi: https://doi.org/10.1101/2023.01.30.526314
Jesse D. Bloom
1Basic Sciences and Computational Biology, Fred Hutchinson Cancer Center
2Department of Genome Sciences, University of Washington
3Howard Hughes Medical Institute
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  • For correspondence: jbloom@fredhutch.org richard.neher@unibas.ch
Richard A. Neher
4Biozentrum, University of Basel
5Swiss Institute of Bioinformatics
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  • For correspondence: jbloom@fredhutch.org richard.neher@unibas.ch
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ABSTRACT

Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino-acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.

Competing Interest Statement

JDB is on the scientific advisory boards of Apriori Bio, Aerium Therapeutics, Invivyd, the Vaccine Company, and Oncorus. JDB receives royalty payments as an inventor on Fred Hutch licensed patents related to deep mutational scanning of viral proteins.

Footnotes

  • https://jbloomlab.github.io/SARS2-mut-fitness/

  • https://github.com/jbloomlab/SARS2-mut-fitness

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted January 31, 2023.
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Fitness effects of mutations to SARS-CoV-2 proteins
Jesse D. Bloom, Richard A. Neher
bioRxiv 2023.01.30.526314; doi: https://doi.org/10.1101/2023.01.30.526314
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Fitness effects of mutations to SARS-CoV-2 proteins
Jesse D. Bloom, Richard A. Neher
bioRxiv 2023.01.30.526314; doi: https://doi.org/10.1101/2023.01.30.526314

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