TY - JOUR
T1 - Lineage abundance estimation for SARS-CoV-2 in wastewater using transcriptome quantification techniques
AU - Baaijens, Jasmijn A.
AU - Zulli, Alessandro
AU - Ott, Isabel M.
AU - Nika, Ioanna
AU - van der Lugt, Mart J.
AU - Petrone, Mary E.
AU - Alpert, Tara
AU - Fauver, Joseph R.
AU - Kalinich, Chaney C.
AU - More Authors, null
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85141707696&partnerID=8YFLogxK
U2 - 10.1186/s13059-022-02805-9
DO - 10.1186/s13059-022-02805-9
M3 - Article
C2 - 36348471
AN - SCOPUS:85141707696
VL - 23
JO - Genome Biology (Online)
JF - Genome Biology (Online)
SN - 1474-760X
IS - 1
M1 - 236
ER -