Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Yu, QinQin; Ascensao, Joao A.; Okada, Takashi; Boyd, Olivia; Volz, Erik; Hallatschek, Oskar

doi:10.1371/journal.ppat.1012090

Title: Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Journal Article · 15 April 2024 · PLoS Pathogens

DOI: https://doi.org/10.1371/journal.ppat.1012090 · OSTI ID:2471151

^[1]; Ascensao, Joao A. ^[2]; Okada, Takashi ^[3]; Boyd, Olivia ^[4]; Volz, Erik ^[4];

^[5]

Harvard T. H. Chan School of Public Health, Boston, MA (United States); University of California, Berkeley, CA (United States)
University of California, Berkeley, CA (United States)
University of California, Berkeley, CA (United States); Kyoto University (Japan); RIKEN iTHEMS, Wako, Saitama (Japan)
Imperial College London (United Kingdom)
University of California, Berkeley, CA (United States); Leipzig University (Germany)

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don’t yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)

Sponsoring Organization:: Japan Society for the Promotion of Science (KAKENHI); MRC Centre for Global Infectious Disease Analysis; National Institutes of Health (NIH); National Science Foundation (NSF); USDOE; Wellcome Trust

Contributing Organization:: The COVID-19 Genomics UK (COG-UK) Consortium

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 2471151

Journal Information:: PLoS Pathogens, Journal Name: PLoS Pathogens Journal Issue: 4 Vol. 20; ISSN 1553-7374

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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60 APPLIED LIFE SCIENCES
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Title: Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

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