Patterns of within-host genetic diversity in SARS-CoV-2
Author:
Tonkin-Hill GerryORCID, Martincorena Inigo, Amato Roberto, Lawson Andrew R J, Gerstung Moritz, Johnston Ian, Jackson David K, Park Naomi R, Lensing Stefanie V, Quail Michael A, Gonçalves Sónia, Ariani Cristina, Chapman Michael Spencer, Hamilton William L, Meredith Luke W, Hall Grant, Jahun Aminu S, Chaudhry Yasmin, Hosmillo Myra, Pinckert Malte L, Georgana Iliana, Yakovleva Anna, Caller Laura G, Caddy Sarah L, Feltwell Theresa, Khokhar Fahad A, Houldcroft Charlotte J, Curran Martin D, Parmar Surendra, Alderton Alex, Nelson Rachel, Harrison Ewan, Sillitoe John, Bentley Stephen D, Barrett Jeffrey C, Torok M. Estee, Goodfellow Ian G, Langford Cordelia, Kwiatkowski DominicORCID, ,
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.
Publisher
Cold Spring Harbor Laboratory
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