Document Type
Article
Journal Title
Genome Biology
Publication Date
2022
Volume
23
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.
MeSH Headings
Humans, SARS-CoV-2, Waste Water, RNA, Viral, Transcriptome, COVID-19
DOI Link
ISSN
1474-760X
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Baaijens, Jasmijn A.; Zulli, Alessandro; Ott, Isabel M.; Nika, Ioanna; van der Lugt, Mart J.; Petrone, Mary E.; Alpert, Tara; Fauver, Joseph R.; Kalinich, Chaney C.; Vogels, Chantal B. F.; Breban, Mallery I.; Duvallet, Claire; McElroy, Kyle A.; Ghaeli, Newsha; Imakaev, Maxim; Mckenzie-Bennett, Malaika F.; Robison, Keith; Plocik, Alex; Schilling, Rebecca; Pierson, Martha; Littlefield, Rebecca; Spencer, Michelle L.; Simen, Birgitte B.; Yale SARS-CoV-2 Genomic Surveillance Initiative; Hanage, William P.; Grubaugh, Nathan D.; Peccia, Jordan; and Baym, Michael, "Lineage Abundance Estimation for SARS-CoV-2 in Wastewater Using Transcriptome Quantification Techniques" (2022). Journal Articles: Epidemiology. 174.
https://digitalcommons.unmc.edu/coph_epidem_articles/174