Unambiguous detection of SARS-CoV-2 subgenomic mRNAs with single cell RNA sequencing

Abstract

AbstractSingle cell RNA sequencing (scRNAseq) studies have provided critical insight into the pathogenesis of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), the causative agent of COronaVIrus Disease 2019 (COVID-19). scRNAseq workflows are generally designed for the detection and quantification of eukaryotic host mRNAs and not viral RNAs. The performance of different scRNAseq methods to study SARS-CoV-2 RNAs has not been thoroughly evaluated. Here, we compare different scRNAseq methods for their ability to quantify and detect SARS-CoV-2 RNAs with a focus on subgenomic mRNAs (sgmRNAs), which are produced only during active viral replication and not present in viral particles. We present a data processing strategy, single cell CoronaVirus sequencing (scCoVseq), which quantifies reads unambiguously assigned to sgmRNAs or genomic RNA (gRNA). Compared to standard 10X Genomics Chromium Next GEM Single Cell 3′ (10X 3′) and Chromium Next GEM Single Cell V(D)J (10X 5′) sequencing, we find that 10X 5′ with an extended R1 sequencing strategy maximizes the unambiguous detection of sgmRNAs by increasing the number of reads spanning leader-sgmRNA junction sites. Differential gene expression testing and KEGG enrichment analysis of infected cells compared with bystander or mock cells showed an enrichment for COVID19-associated genes, supporting the ability of our method to accurately identify infected cells. Our method allows for quantification of coronavirus sgmRNA expression at single-cell resolution, and thereby supports high resolution studies of the dynamics of coronavirus RNA synthesis.ImportanceSingle cell RNA sequencing (scRNAseq) has emerged as a valuable tool to study host-viral interactions particularly in the context of COronaVIrus Disease-2019 (COVID-19). scRNAseq has been developed and optimized for analyzing eukaryotic mRNAs, and the ability of scRNAseq to measure RNAs produced by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has not been fully characterized. Here we compare the performance of different scRNAseq methods to detect and quantify SARS-CoV-2 RNAs and develop an analysis workflow to specifically quantify unambiguous reads derived from SARS-CoV-2 genomic RNA and subgenomic mRNAs. Our work demonstrates the strengths and limitations of scRNAseq to measure SARS-CoV-2 RNA and identifies experimental and analytical approaches that allow for SARS-CoV-2 RNA detection and quantification. These developments will allow for studies of coronavirus RNA biogenesis at single-cell resolution to improve our understanding of viral pathogenesis.