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Combining Short- and Long-Read Sequencing Technologies to Identify SARS-CoV-2 Variants in Wastewater Jayme, Gabrielle; Liu, Ju-Ling; Galvez, Jose Hector; Reiling, Sarah Julia; Celikkol, Sukriye; N’Guessan, Arnaud; Lee, Sally; Chen, Shu-Huang; Tsitouras, Alexandra; Sanchez-Quete, Fernando; Maere, Thomas; Goitom, Eyerusalem; Hachad, Mounia; Mercier, Elisabeth; Loeb, Stephanie Katharine; Vanrolleghem, Peter A.; Dorner, Sarah; Delatolla, Robert; Shapiro, B. Jesse; Frigon, Dominic; Ragoussis, Jiannis; Snutch, Terrance P.
Abstract
During the COVID-19 pandemic, the monitoring of SARS-CoV-2 RNA in wastewater was used to track the evolution and emergence of variant lineages and gauge infection levels in the community, informing appropriate public health responses without relying solely on clinical testing. As more sublineages were discovered, it increased the difficulty in identifying distinct variants in a mixed population sample, particularly those without a known lineage. Here, we compare the sequencing technology from Illumina and from Oxford Nanopore Technologies, in order to determine their efficacy at detecting variants of differing abundance, using 248 wastewater samples from various Quebec and Ontario cities. Our study used two analytical approaches to identify the main variants in the samples: the presence of signature and marker mutations and the co-occurrence of signature mutations within the same amplicon. We observed that each sequencing method detected certain variants at different frequencies as each method preferentially detects mutations of distinct variants. Illumina sequencing detected more mutations with a predominant lineage that is in low abundance across the population or unknown for that time period, while Nanopore sequencing had a higher detection rate of mutations that are predominantly found in the high abundance B.1.1.7 (Alpha) lineage as well as a higher sequencing rate of co-occurring mutations in the same amplicon. We present a workflow that integrates short-read and long-read sequencing to improve the detection of SARS-CoV-2 variant lineages in mixed population samples, such as wastewater.
Item Metadata
Title |
Combining Short- and Long-Read Sequencing Technologies to Identify SARS-CoV-2 Variants in Wastewater
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Creator |
Jayme, Gabrielle; Liu, Ju-Ling; Galvez, Jose Hector; Reiling, Sarah Julia; Celikkol, Sukriye; N’Guessan, Arnaud; Lee, Sally; Chen, Shu-Huang; Tsitouras, Alexandra; Sanchez-Quete, Fernando; Maere, Thomas; Goitom, Eyerusalem; Hachad, Mounia; Mercier, Elisabeth; Loeb, Stephanie Katharine; Vanrolleghem, Peter A.; Dorner, Sarah; Delatolla, Robert; Shapiro, B. Jesse; Frigon, Dominic; Ragoussis, Jiannis; Snutch, Terrance P.
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Contributor | |
Publisher |
Multidisciplinary Digital Publishing Institute
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Date Issued |
2024-09-21
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Description |
During the COVID-19 pandemic, the monitoring of SARS-CoV-2 RNA in wastewater was used to track the evolution and emergence of variant lineages and gauge infection levels in the community, informing appropriate public health responses without relying solely on clinical testing. As more sublineages were discovered, it increased the difficulty in identifying distinct variants in a mixed population sample, particularly those without a known lineage. Here, we compare the sequencing technology from Illumina and from Oxford Nanopore Technologies, in order to determine their efficacy at detecting variants of differing abundance, using 248 wastewater samples from various Quebec and Ontario cities. Our study used two analytical approaches to identify the main variants in the samples: the presence of signature and marker mutations and the co-occurrence of signature mutations within the same amplicon. We observed that each sequencing method detected certain variants at different frequencies as each method preferentially detects mutations of distinct variants. Illumina sequencing detected more mutations with a predominant lineage that is in low abundance across the population or unknown for that time period, while Nanopore sequencing had a higher detection rate of mutations that are predominantly found in the high abundance B.1.1.7 (Alpha) lineage as well as a higher sequencing rate of co-occurring mutations in the same amplicon. We present a workflow that integrates short-read and long-read sequencing to improve the detection of SARS-CoV-2 variant lineages in mixed population samples, such as wastewater.
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Subject | |
Genre | |
Type | |
Language |
eng
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Date Available |
2024-10-11
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Provider |
Vancouver : University of British Columbia Library
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Rights |
CC BY 4.0
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DOI |
10.14288/1.0445556
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URI | |
Affiliation | |
Citation |
Viruses 16 (9): 1495 (2024)
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Publisher DOI |
10.3390/v16091495
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Peer Review Status |
Reviewed
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Scholarly Level |
Faculty; Researcher
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
CC BY 4.0