Variant abundance estimation for SARS-CoV-2 in wastewater using RNA-Seq quantification

Author:

Baaijens Jasmijn A.ORCID,Zulli AlessandroORCID,Ott Isabel M.ORCID,Petrone Mary E.ORCID,Alpert TaraORCID,Fauver Joseph R.ORCID,Kalinich Chaney C.ORCID,Vogels Chantal B.F.ORCID,Breban Mallery I.ORCID,Duvallet ClaireORCID,McElroy Kyle,Ghaeli Newsha,Imakaev MaximORCID,Mckenzie-Bennett Malaika,Robison KeithORCID,Plocik AlexORCID,Schilling Rebecca,Pierson Martha,Littlefield Rebecca,Spencer Michelle,Simen Birgitte B.ORCID,Hanage William P.ORCID,Grubaugh Nathan D.ORCID,Peccia JordanORCID,Baym MichaelORCID,

Abstract

AbstractEffectively monitoring the spread of SARS-CoV-2 variants is essential to efforts to counter the ongoing pandemic. Wastewater monitoring of SARS-CoV-2 RNA has proven an effective and efficient technique to approximate COVID-19 case rates in the population. Predicting variant abundances from wastewater, however, is technically challenging. Here we show that by sequencing SARS-CoV-2 RNA in wastewater and applying computational techniques initially used for RNA-Seq quantification, we can estimate the abundance of variants in wastewater samples. We show by sequencing samples from wastewater and clinical isolates in Connecticut U.S.A. between January and April 2021 that the temporal dynamics of variant strains broadly correspond. We further show that this technique can be used with other wastewater sequencing techniques by expanding to samples taken across the United States in a similar timeframe. We find high variability in signal among individual samples, and limited ability to detect the presence of variants with clinical frequencies <10%; nevertheless, the overall trends match what we 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 variant prevalence in situations where clinical sequencing is unavailable or impractical.

Publisher

Cold Spring Harbor Laboratory

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