UMass Chan Medical School Faculty Publications

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Program in Molecular Medicine

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Article Preprint


Epidemiology | Genetics and Genomics | Immunology and Infectious Disease | Infectious Disease | Microbiology | Virus Diseases


Repeated emergence of SARS-CoV-2 variants with increased fitness necessitates rapid detection and characterization of new lineages. To address this need, we developed PyR0, a hierarchical Bayesian multinomial logistic regression model that infers relative prevalence of all viral lineages across geographic regions, detects lineages increasing in prevalence, and identifies mutations relevant to fitness. Applying PyR0 to all publicly available SARS-CoV-2 genomes, we identify numerous substitutions that increase fitness, including previously identified spike mutations and many non-spike mutations within the nucleocapsid and nonstructural proteins. PyR0 forecasts growth of new lineages from their mutational profile, identifies viral lineages of concern as they emerge, and prioritizes mutations of biological and public health concern for functional characterization.


Epidemiology, SARS-CoV-2 variants, mutations, viral lineages, fitness

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DOI of Published Version



Obermeyer F, Jankowiak M, Barkas N, Schaffner SF, Pyle JD, Yurkovetskiy L, Bosso M, Park DJ, Babadi M, MacInnis BL, Luban J, Sabeti PC, Lemieux JE. Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness. medRxiv [Preprint]. 2022 Feb 16:2021.09.07.21263228. doi: 10.1101/2021.09.07.21263228. Update in: Science. 2022 May 24;:abm1208. PMID: 35194619; PMCID: PMC8863165. Link to preprint on medRxiv.


This article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.

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Now published in Science doi: 10.1126/science.abm1208

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Creative Commons Attribution-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 License.