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Lineage abundance estimation for SARS-CoV-2 in wastewater using transcriptome quantification techniques

Authors :
Jasmijn A. Baaijens
Alessandro Zulli
Isabel M. Ott
Ioanna Nika
Mart J. van der Lugt
Mary E. Petrone
Tara Alpert
Joseph R. Fauver
Chaney C. Kalinich
Chantal B. F. Vogels
Mallery I. Breban
Claire Duvallet
Kyle A. McElroy
Newsha Ghaeli
Maxim Imakaev
Malaika F. Mckenzie-Bennett
Keith Robison
Alex Plocik
Rebecca Schilling
Martha Pierson
Rebecca Littlefield
Michelle L. Spencer
Birgitte B. Simen
Yale SARS-CoV-2 Genomic Surveillance Initiative
William P. Hanage
Nathan D. Grubaugh
Jordan Peccia
Michael Baym
Source :
Genome Biology, Vol 23, Iss 1, Pp 1-20 (2022)
Publication Year :
2022
Publisher :
BMC, 2022.

Abstract

Abstract Effectively monitoring the spread of SARS-CoV-2 mutants is essential to efforts to counter the ongoing pandemic. Predicting lineage abundance from wastewater, however, is technically challenging. We show that by sequencing SARS-CoV-2 RNA in wastewater and applying algorithms initially used for transcriptome quantification, we can estimate lineage abundance in wastewater samples. We find high variability in signal among individual samples, but the overall trends match those observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in mutant prevalence in situations where clinical sequencing is unavailable.

Details

Language :
English
ISSN :
1474760X
Volume :
23
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Genome Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.fc8864066ac8466fa436697afeaf32ee
Document Type :
article
Full Text :
https://doi.org/10.1186/s13059-022-02805-9