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Related Experiment Video

Updated: Nov 12, 2025

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Published on: June 30, 2023

Subgenomic RNA identification in SARS-CoV-2 genomic sequencing data.

Matthew D Parker^1,2,3, Benjamin B Lindsey^4,5, Shay Leary⁶

¹Sheffield Bioinformatics Core, The University of Sheffield, Sheffield S10 2HQ, United Kingdom.

Genome Research

|March 16, 2021

Summary

This summary is machine-generated.

We developed periscope, a tool to detect and quantify subgenomic RNAs (sgRNAs) in SARS-CoV-2 genomes. This method accurately identifies canonical and noncanonical sgRNAs, aiding COVID-19 research.

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Area of Science:

Virology
Molecular Biology
Bioinformatics

Background:

Subgenomic RNAs (sgRNAs) are crucial intermediates for SARS-CoV-2 gene expression.
Understanding sgRNA dynamics is essential for comprehending viral replication and pathogenesis.
Current methods for sgRNA detection and quantification have limitations.

Purpose of the Study:

To develop and validate 'periscope,' a novel tool for detecting and quantifying SARS-CoV-2 subgenomic RNAs (sgRNAs).
To analyze sgRNA profiles in a large cohort of SARS-CoV-2 genomes.
To assess the fidelity of variant transmission from genomic RNA to sgRNAs.

Main Methods:

Development of the 'periscope' tool utilizing local alignment to detect leader sequences on SARS-CoV-2 reads.
Application of periscope to 1155 SARS-CoV-2 genomes from Sheffield, UK.
Validation using orthogonal datasets, in vitro cell systems (VeroE6 ACE2+/-), and technical replicates.

Main Results:

Periscope successfully detected and quantified canonical sgRNAs, except for ORF10, at expected abundances.
Recurrent noncanonical sgRNAs were identified.
High fidelity of variant transmission from genomic RNA to sgRNAs was observed.
Periscope demonstrated reproducibility and identified optimal read counts for analysis.

Conclusions:

Periscope is a robust and reproducible tool for comprehensive SARS-CoV-2 sgRNA analysis.
The tool can be applied globally to all sequenced COVID-19 samples.
Findings contribute to a deeper understanding of SARS-CoV-2 gene expression and evolution.