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Patterns of within-host genetic diversity in SARS-CoV-2

Authors :
Dominic P. Kwiatkowski
Grant Hall
Theresa Feltwell
Cristina V. Ariani
Stephen D. Bentley
Rachel Nelson
Inigo Martincorena
Iliana Georgana
Fahad A Khokhar
Michael Spencer Chapman
Andrew R. J. Lawson
Sónia Gonçalves
Gerry Tonkin-Hill
Ewan Harrison
M. Estée Török
Laura G Caller
Luke W. Meredith
Stefanie V Lensing
Surendra Parmar
Naomi R Park
William L Hamilton
Alex Alderton
Moritz Gerstung
David K. Jackson
Myra Hosmillo
Anna Yakovleva
Michael A. Quail
Sarah L Caddy
Charlotte J. Houldcroft
Yasmin Chaudhry
Ian Johnston
Jeffrey C. Barrett
Malte L Pinckert
Aminu S Jahun
Roberto Amato
Ian Goodfellow
John Sillitoe
Martin D. Curran
Cordelia Langford
Publication Year :
2020
Publisher :
Cold Spring Harbor Laboratory, 2020.

Abstract

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1,181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within and between host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........f055a287054a0113c42e18ee5084e869
Full Text :
https://doi.org/10.1101/2020.12.23.424229