CoV-Spectrum: analysis of globally shared SARS-CoV-2 data to identify and characterize new variants

Chen, Chaoran; Nadeau, Sarah; Yared, Michael; Voinov, Philippe; Xie, Ning; Roemer, Cornelius; Stadler, Tanja

doi:10.1093/bioinformatics/btab856

Cited by 260 publications

(299 citation statements)

References 12 publications

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“…Since April, the frequency of Delta among the Russian samples has been growing, reaching 98 per cent by early July 2021, with the estimated daily logistic growth rate of 9.74 per cent (95 per cent CI: 9.28 per cent-10.2 per cent). This growth rate is comparable with that observed in other countries ( Chen et al. 2021 ; Public Health England 2021 ).…”

Section: Resultssupporting

confidence: 89%

The rise and spread of the SARS-CoV-2 AY.122 lineage in Russia

et al. 2022

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Delta has outcompeted most preexisting variants of SARS-CoV-2, becoming the globally predominant lineage by mid-2021. Its subsequent evolution has led to emergence of multiple sublineages, most of which are well-mixed between countries. By contrast, here we show that nearly the entire Delta epidemic in Russia has probably descended from a single import event, or from multiple closely timed imports from a single poorly sampled geographic location. Indeed, over 90% of Delta samples in Russia are characterized by the nsp2:K81N+ORF7a:P45L pair of mutations which is rare outside Russia, putting them in the AY.122 sublineage. The AY.122 lineage was frequent in Russia among Delta samples from the start, and has not increased in frequency in other countries where it has been observed, suggesting that its high prevalence in Russia has probably resulted from a random founder effect rather than a transmission advantage. The apartness of the genetic composition of the Delta epidemic in Russia makes Russia somewhat unusual, although not exceptional, among other countries.

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Section: Resultssupporting

confidence: 89%

The rise and spread of the SARS-CoV-2 AY.122 lineage in Russia

et al. 2022

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“…SARS-CoV-2 RNA detected from wastewater in a large catchment area (471,000 people) provides anonymised data. Clinical data used for comparison were obtained from the publicly available database accessible through CovSpectrum (cov-spectrum.org) [ 28 ].…”

Section: Methodsmentioning

confidence: 99%

Inferring transmission fitness advantage of SARS-CoV-2 variants of concern from wastewater samples using digital PCR, Switzerland, December 2020 through March 2021

et al. 2022

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Background Throughout the COVID-19 pandemic, SARS-CoV-2 genetic variants of concern (VOCs) have repeatedly and independently arisen. VOCs are characterised by increased transmissibility, increased virulence or reduced neutralisation by antibodies obtained from prior infection or vaccination. Tracking the introduction and transmission of VOCs relies on sequencing, typically whole genome sequencing of clinical samples. Wastewater surveillance is increasingly used to track the introduction and spread of SARS-CoV-2 variants through sequencing approaches. Aim Here, we adapt and apply a rapid, high-throughput method for detection and quantification of the relative frequency of two deletions characteristic of the Alpha, Beta, and Gamma VOCs in wastewater. Methods We developed drop-off RT-dPCR assays and an associated statistical approach implemented in the R package WWdPCR to analyse temporal dynamics of SARS-CoV-2 signature mutations (spike Δ69–70 and ORF1a Δ3675–3677) in wastewater and quantify transmission fitness advantage of the Alpha VOC. Results Based on analysis of Zurich wastewater samples, the estimated transmission fitness advantage of SARS-CoV-2 Alpha based on the spike Δ69–70 was 0.34 (95% confidence interval (CI): 0.30–0.39) and based on ORF1a Δ3675–3677 was 0.53 (95% CI: 0.49–0.57), aligning with the transmission fitness advantage of Alpha estimated by clinical sample sequencing in the surrounding canton of 0.49 (95% CI: 0.38–0.61). Conclusion Digital PCR assays targeting signature mutations in wastewater offer near real-time monitoring of SARS-CoV-2 VOCs and potentially earlier detection and inference on transmission fitness advantage than clinical sequencing.

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“…a particular VOC represented in a database). To find these signature mutations, we first calculated the prevalence of substitutions in thousands of publicly available consensus sequences collected during 2020 and added data from CoV-Spectrum (Chen et al 2021) to include under-represented lineages or lineages that emerged after 2020 ( Methods ). These variant lineages were named using the PANGO lineage designation scheme (Rambaut et al 2020).…”

Section: Resultsmentioning

confidence: 99%

“…the number of mutations that have a minimum prevalence of 90% among the consensus sequences of the lineage. To find these signature mutations, we first calculated the prevalence of substitutions in thousands of publicly available consensus sequences collected during 2020 and added data from CoV-Spectrum about under-represented lineage in the database or lineages that emerged during 2021 (C. Chen et al 2021). The database contains 755 lineages and is available at https://github.com/arnaud00013/Wastewater_surveillance_pipeline/blob/main/Post_variant_calling_analysis/Database_all_mutations_prevalence_in_SC2_lineages_consensus_sequences_as_of_2021_07_08.json.…”

Section: Methodsmentioning

confidence: 99%

Detection of prevalent SARS-CoV-2 variant lineages in wastewater and clinical sequences from cities in Québec, Canada

N’Guessan

Tsitouras

Sanchez-Quete

et al. 2022

Preprint

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Wastewater-based epidemiology has emerged as a promising tool to monitor pathogens in a population, particularly when clinical diagnostic capacities become overwhelmed. During the ongoing COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), several jurisdictions have tracked viral concentrations in wastewater to inform public health authorities. While some studies have also sequenced SARS-CoV-2 genomes from wastewater, there have been relatively few direct comparisons between viral genetic diversity in wastewater and matched clinical samples from the same region and time period. Here we report sequencing and inference of SARS-CoV-2 mutations and variant lineages (including variants of concern) in 936 wastewater samples and thousands of matched clinical sequences collected between March 2020 and July 2021 in the cities of Montreal, Quebec City, and Laval, representing almost half the population of the Canadian province of Quebec. We benchmarked our sequencing and variant-calling methods on known viral genome sequences to establish thresholds for inferring variants in wastewater with confidence. We found that variant frequency estimates in wastewater and clinical samples are correlated over time in each city, with similar dates of first detection. Across all variant lineages, wastewater detection is more concordant with targeted outbreak sequencing than with semi-random clinical swab sampling. Most variants were first observed in clinical and outbreak data due to higher sequencing rate. However, wastewater sequencing is highly efficient, detecting more variants for a given sampling effort. This shows the potential for wastewater sequencing to provide useful public health data, especially at places or times when sufficient clinical sampling is infrequent or infeasible.

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CoV-Spectrum: analysis of globally shared SARS-CoV-2 data to identify and characterize new variants

Cited by 260 publications

References 12 publications

The rise and spread of the SARS-CoV-2 AY.122 lineage in Russia

The rise and spread of the SARS-CoV-2 AY.122 lineage in Russia

Inferring transmission fitness advantage of SARS-CoV-2 variants of concern from wastewater samples using digital PCR, Switzerland, December 2020 through March 2021

Detection of prevalent SARS-CoV-2 variant lineages in wastewater and clinical sequences from cities in Québec, Canada

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