A dynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology

Rambaut, Andrew; Holmes, Edward C.; O’Toole, Áine; Hill, Verity; McCrone, John; Ruis, Christopher; Plessis, Louis du; Pybus, Oliver G.

doi:10.1038/s41564-020-0770-5

Cited by 2,444 publications

(2,540 citation statements)

References 16 publications

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“…Our inference is also supported by the observation that a mutant of proCoV2 containing μ variants, but no α variants, was isolated in the United States on pandemic day 59. This means that the root of the SARS-CoV-2 phylogeny is on a lineage before α1 appeared, which is inconsistent with the previous inference 26 .…”

Section: A Mutational History Of Sars-cov-2contrasting

confidence: 69%

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic

Kumar

Tao

Weaver

et al. 2020

Preprint

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Severe acute respiratory syndrome coronavirus 2, SARS-CoV-2, was quickly identified as the cause of COVID-19 disease soon after its earliest reports. The knowledge of the contemporary evolution of SARS-CoV-2 is urgently needed not only for a retrospective on how, when, and why COVID-19 has emerged and spread, but also for creating remedies through efforts of science, technology, medicine, and public policy. Global sequencing of thousands of genomes has revealed many common genetic variants, which are the key to unraveling the early evolutionary history of SARS-CoV-2 and tracking its global spread over time. However, our knowledge of fundamental events in the evolution and spread of this coronavirus remains grossly incomplete and highly uncertain. Here, we present the heretofore cryptic mutational history, phylogeny, and dynamics of SARS-CoV-2 from an analysis of tens of thousands of high-quality genomes. The reconstructed mutational progression is highly concordant with the timing of coronavirus sampling dates. It predicts the progenitor genome whose earliest offspring without any non-synonymous mutations were still spreading worldwide months after the report of COVID-19. Over time, mutations gave rise to seven major lineages that spread episodically, some of which arose in Europe and North America after the genesis of the ancestral lineages in China. Mutational barcoding establishes that North American coronaviruses harbor very different genome signatures than coronaviruses prevalent in Europe and Asia that have converged over time. These spatiotemporal patterns continue to evolve as the pandemic progresses and can be viewed live online.

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Section: A Mutational History Of Sars-cov-2contrasting

confidence: 69%

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic

Kumar

Tao

Weaver

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…Our neighbor-joining tree based on distances from 9 clades suggests that SARS-CoV-2 appears originated from multiple zoonotic reservoirs instead of a single direct ancestor ( Figure S4). In addition, our classification rationales are largely in agreement with published reports [30]; for example, Cluster S is in accordance with previously defined S type [31] and Cluster G is in line with GISAID [32] defined the G clade. Cluster L is similar to the V and L clades combined, of GISAID.…”

Section: Clade-associated Biased Mutation Trend In Sars-cov-2 Revealesupporting

confidence: 89%

Compositional Variability and Mutation Spectra of Monophyletic SARS-CoV-2 Clades

Teng

Zhao

et al. 2020

Preprint

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COVID-19 and its causative pathogen SARS-CoV-2 have rushed the world into a staggering pandemic in a few months and a global fight against both is still going on. Here, we describe an analysis procedure where genome composition and its variables are related, through the genetic code, to molecular mechanisms based on understanding of RNA replication and its feedback loop from mutation to viral proteome sequence fraternity including effective sites on replicase-transcriptase complex. Our analysis starts with primary sequence information and identity-based phylogeny based on 22,051 SARS-CoV-2 genome sequences and evaluation of sequence variation patterns as mutation spectrum and its 12 permutations among organized clades tailored to two key mechanisms: strand-biased and function-associated mutations. Our findings include: (1) The most dominant mutation is C-to-U permutation whose abundant second-codon-position counts alter amino acid composition toward higher molecular weight and lower hydrophobicity albeit assumed most slightly deleterious. (2) The second abundance group includes: three negative-strand mutations U-to-C, A-to-G, G-to-A and a positive-strand mutation G-to-U generated through an identical mechanism as C-to-U. (3) A clade-associated and biased mutation trend is found attributable to elevated level of the negative-sense strand synthesis. (4) Within-clade permutation variation is very informative for associating non-synonymous mutations and viral proteome changes. These findings demand a bioinformatics platform where emerging mutations are mapped on to mostly subtle but fast-adjusting viral proteomes and transcriptomes to provide biological and clinical information after logical convergence for effective pharmaceutical and diagnostic applications. Such thoughts and actions are in desperate need, especially in the middle of the War against COVID-19.

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“…For SARS-CoV-2 lineage classification, consensus genomes were submitted to Pangolin software (https://github.com/cov-lineages/pangolin, downloaded on June 10 th , 2020) and to CoV-GLUE lineage system (http://cov-glue.cvr.gla.ac.uk/#/home, accessed on June 10 th , 2020) [25], both based on the nomenclature proposed by Rambaut et al [26]. An alignment including the consensus sequences generated and genomes from Brazilian sequences available on the GISAID Database classified as B1, B1.1 and the Brazilian clusters B1.1-BR/ B1.1-EU/BR (S1 Table) were submitted to a maximum likelihood phylogenic reconstruction using PhyML v.3.0 and the best model of nucleotide substitution was defined with Model Generator (GTR) to investigate the sublineage classification of the study sequences [16,27,28].…”

Section: Sars-cov-2 Classification and Phylogenetic Analysismentioning

confidence: 99%

SARS-CoV-2 genomic and quasispecies analyses in cancer patients reveal relaxed intrahost virus evolution

Siqueira

Goes

Alves

et al. 2020

Preprint

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Numerous factors have been identified to influence susceptibility to SARS-CoV-2 infection and disease severity. Cancer patients are more prone to clinically evolve to more severe COVID-19 conditions, but the determinants of such a more severe outcome remain largely unknown. We have determined the full-length SARS-CoV-2 genomic sequences of cancer patients and healthcare workers (HCW; non-cancer controls) by deep sequencing and investigated the within-host viral quasispecies of each infection, quantifying intrahost genetic diversity. Naso- and oropharyngeal SARS-CoV-2+ swabs from 57 cancer patients and 14 healthcare workers (HCW) from the Brazilian Cancer Institute were collected in April–May 2020. Complete genome amplification using ARTIC network V3 multiplex primers was performed followed by next-generation sequencing. Assemblies were conducted in Geneious R11, where consensus sequences were extracted and intrahost single nucleotide variants (iSNVs) were identified. Maximum likelihood phylogenetic analysis was performed using PhyMLv.3.0 and lineages were classified using Pangolin and CoV-GLUE. Phylogenetic analysis showed that all but one strain belonged to clade B1.1. Four genetically linked mutations known as the globally dominant SARS-CoV-2 haplotype (C241T, C3037T, C14408T and A23403G) were found in the majority of consensus sequences. SNV signatures of previously characterized Brazilian genomes were also observed in most samples. Another 85 SNVs were found at a lower frequency (1.4-19.7%). Cancer patients displayed a significantly higher intrahost viral genetic diversity compared to HCW (p = 0.009). Intrahost genetic diversity in cancer patients was independent of SARS-CoV-2 Ct values, and was not associated with disease severity, use of corticosteroids, or use of antivirals, characteristics that could influence viral diversity. Such a feature may explain, at least in part, the more adverse outcomes to which cancer/COVID-19 patients experience.Author SummaryCancer patients are more prone to clinically evolve to more severe COVID-19 conditions, but the determinants of such a more severe outcome remain largely unknown. In this study, phylogenetic and variation analysis of SARS-CoV-2 genomes from cancer patients and non-cancer healthcare workers at the Brazilian National Cancer Institute were characterized by deep sequencing. Viral genomes showed signatures characteristic of Brazilian viruses, consistent with the hypothesis of local, community transmission rather than virus importation from abroad. Despite most genomes in patients and healthcare workers belonging to the same lineage, intrahost variability was higher in cancer patients when compared to non-cancer counterparts. The intrahost genomic diversity analysis presented in our study highlights the relaxed evolution of SARS-CoV-2 in a vulnerable population of cancer patients. The high number of minor variations can result in the selection of immune escape variants, resistance to potential drugs, and/or increased pathogenicity. The impact of this higher intrahost variability over time warrants further investigation.

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A dynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology

Cited by 2,444 publications

References 16 publications

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic

Compositional Variability and Mutation Spectra of Monophyletic SARS-CoV-2 Clades

SARS-CoV-2 genomic and quasispecies analyses in cancer patients reveal relaxed intrahost virus evolution

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