Subgenomic RNA identification in SARS-CoV-2 genomic sequencing data.
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ABSTRACT:
SUBMITTER: Parker MD
PROVIDER: S-EPMC8015849 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Single 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.
| S-EPMC8629185 | biostudies-literature
Project description:Single-cell RNA sequencing (scRNA-Seq) 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). scRNA-Seq library preparation methods and data processing workflows are generally designed for the detection and quantification of eukaryotic host mRNAs and not viral RNAs. Here, we compare different scRNA-Seq library preparation methods for their ability to quantify and detect SARS-CoV-2 RNAs with a focus on subgenomic mRNAs (sgmRNAs). We show that compared to 10X Genomics Chromium Next GEM Single Cell 3' (10X 3') libraries or 10X Genomics Chromium Next GEM Single Cell V(D)J (10X 5') libraries sequenced with standard read configurations, 10X 5' libraries sequenced with an extended length read 1 (R1) that covers both cell barcode and transcript sequence (termed "10X 5' with extended R1") increase the number of unambiguous reads spanning leader-sgmRNA junction sites. We further present a data processing workflow, single-cell coronavirus sequencing (scCoVseq), which quantifies reads unambiguously assigned to viral sgmRNAs or viral genomic RNA (gRNA). We find that combining 10X 5' with extended R1 library preparation/sequencing and scCoVseq data processing maximizes the number of viral UMIs per cell quantified by scRNA-Seq. Corresponding sgmRNA expression levels are highly correlated with expression in matched bulk RNA-Seq data sets quantified with established tools for SARS-CoV-2 analysis. Using this scRNA-Seq approach, we find that SARS-CoV-2 gene expression is highly correlated across individual infected cells, which suggests that the proportion of viral sgmRNAs remains generally consistent throughout infection. Taken together, these results and corresponding data processing workflow enable robust quantification of coronavirus sgmRNA expression at single-cell resolution, thereby supporting high-resolution studies of viral RNA processes in individual cells. IMPORTANCE Single-cell RNA sequencing (scRNA-Seq) has emerged as a valuable tool to study host-virus interactions, especially for coronavirus disease 2019 (COVID-19). Here we compare the performance of different scRNA-Seq library preparation methods and sequencing strategies to detect SARS-CoV-2 RNAs and develop a data processing workflow to quantify unambiguous sequence reads derived from SARS-CoV-2 genomic RNA and subgenomic mRNAs. After establishing a workflow that maximizes the detection of SARS-CoV-2 subgenomic mRNAs, we explore patterns of SARS-CoV-2 gene expression across cells with variable levels of total viral RNA, assess host gene expression differences between infected and bystander cells, and identify non-canonical and lowly abundant SARS-CoV-2 RNAs. The sequencing and data processing strategies developed here can enhance studies of coronavirus RNA biology at single-cell resolution and thereby contribute to our understanding of viral pathogenesis.
| S-EPMC10580996 | biostudies-literature
Project description:Sub-genomic RNA identification in SARS-CoV-2 Genomic Sequencing Data
| PRJEB40972 | ENA
Project description:The widespread Coronavirus Disease 2019 (COVID-19) is caused by infection with the novel coronavirus SARS-CoV-2. Currently, we have a limited toolset available for visualizing SARS-CoV-2 in cells and tissues, particularly in tissues from patients who died from COVID-19. Generally, single-molecule RNA FISH techniques have shown mixed results in formalin fixed paraffin embedded tissues such as those preserved from human autopsies. Here, we present a platform for preparing autopsy tissue for visualizing SARS-CoV-2 RNA using RNA FISH with amplification by hybridization chain reaction (HCR). We developed probe sets that target different regions of SARS-CoV-2 (including ORF1a and N) as well as probe sets that specifically target SARS-CoV-2 subgenomic mRNAs. We validated these probe sets in cell culture and tissues (lung, lymph node, and placenta) from infected patients. Using this technology, we observe distinct subcellular localization patterns of the ORF1a and N regions, with the ORF1a concentrated around the nucleus and the N showing a diffuse distribution across the cytoplasm. In human lung tissue, we performed multiplexed RNA FISH HCR for SARS-CoV-2 and cell-type specific marker genes. We found viral RNA in cells containing the alveolar type 2 (AT2) cell marker gene ( SFTPC ) and the alveolar macrophage marker gene ( MARCO ), but did not identify viral RNA in cells containing the alveolar type 1 (AT1) cell marker gene ( AGER ). Moreover, we observed distinct subcellular localization patterns of viral RNA in AT2 cells and alveolar macrophages, consistent with phagocytosis of infected cells. In sum, we demonstrate the use of RNA FISH HCR for visualizing different RNA species from SARS-CoV-2 in cell lines and FFPE autopsy specimens. Furthermore, we multiplex this assay with probes for cellular genes to determine what cell-types are infected within the lung. We anticipate that this platform could be broadly useful for studying SARS-CoV-2 pathology in tissues as well as extended for other applications including investigating the viral life cycle, viral diagnostics, and drug screening.
| S-EPMC8366794 | biostudies-literature
Project description:BackgroundGiven the persistence of viral RNA in clinically recovered coronavirus disease 2019 (COVID-19) patients, subgenomic RNAs (sgRNAs) have been reported as potential molecular viability markers for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, few data are available on their longitudinal kinetics, compared with genomic RNA (gRNA), in clinical samples.MethodsWe analyzed 536 samples from 205 patients with COVID-19 from placebo-controlled, outpatient trials of peginterferon Lambda-1a (Lambda; n = 177) and favipiravir (n = 359). Nasal swabs were collected at 3 time points in the Lambda (days 1, 4, and 6) and favipiravir (days 1, 5, and 10) trials. N-gene gRNA and sgRNA were quantified by quantitative reverse transcription polymerase chain reaction. To investigate the decay kinetics in vitro, we measured gRNA and sgRNA in A549ACE2+ cells infected with SARS-CoV-2, following treatment with remdesivir or dimethylsulfoxide control.ResultsAt 6 days in the Lambda trial and 10 days in the favipiravir trial, sgRNA remained detectable in 51.6% (32/62) and 49.5% (51/106) of the samples, respectively. Cycle threshold (Ct) values for gRNA and sgRNA were highly linearly correlated (marginal R 2 = 0.83), and the rate of increase did not differ significantly in the Lambda trial (1.36 cycles/d vs 1.36 cycles/d; P = .97) or the favipiravir trial (1.03 cycles/d vs 0.94 cycles/d; P = .26). From samples collected 15-21 days after symptom onset, sgRNA was detectable in 48.1% (40/83) of participants. In SARS-CoV-2-infected A549ACE2+ cells treated with remdesivir, the rate of Ct increase did not differ between gRNA and sgRNA.ConclusionsIn clinical samples and in vitro, sgRNA was highly correlated with gRNA and did not demonstrate different decay patterns to support its application as a viability marker.
| S-EPMC8291522 | biostudies-literature
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent responsible for the ongoing pandemic of coronavirus disease 2019 (COVID-19). Single cell RNA sequencing (scRNAseq) studies have been valuable for studying SARS-CoV-2 pathogenesis, but the performance of these methods to detect and quantify viral RNAs has not been evaluated. Here we develop an analysis pipeline, single cell coronavirus sequencing (scCoVseq), to quantify unambiguous reads derived from coronavirus genomic (gRNA) and subgenomic mRNAs (sgmRNAs). We use this method to compare the ability of scRNAseq methods developed by 10X Genomics to detect and quantify SARS-CoV-2 RNAs, with particular focus on sgmRNAs. We find that while sequencing libraries from 10X Genomics Chromium Next Gem Single Cell V(D)J (10X 5') contain more unambiguous reads derived from sgmRNAs due to the presence of reads spanning junctions between the viral 5' leader and sgmRNA open reading frames. We demonstrate that by extending read 1 (R1) of 10X 5' leaders we can further increase the number of unambiguous reads from SARS-CoV-2 sgmRNA resulting in more UMIs per sgmRNA per cell. Using this method, which we call 10X 5' Extended R1, we are able quantify viral sgmRNA production per cell, which we believe will improve understanding regarding the dynamics of coronavirus RNA biogenesis over time and across cell types and viruses. We believe this will improve our understanding of coronavirus pathogenesis.
2023-07-30 | GSE189900 | GEO
Project description:Background and Objectives: SARS-CoV-2 is the first global threat and life-changing event of the twenty-first century. Although efficient treatments and vaccines have been developed, due to the virus's ability to mutate in key regions of the genome, whole viral genome sequencing is needed for efficient monitoring, evaluation of the spread, and even the adjustment of the molecular diagnostic assays. Materials and Methods: In this study, Nanopore and Ion Torrent sequencing technologies were used to detect the main SARS-CoV-2 circulating strains in Timis County, Romania, between February 2021 and May 2022. Results: We identified 22 virus lineages belonging to seven clades: 20A, 20I (Alpha, V1), 21B (Kappa), 21I (Delta), 21J (Delta), 21K (Omicron), and 21L (Omicron). Conclusions: Results obtained with both methods are comparable, and we confirm the utility of Nanopore sequencing in large-scale epidemiological surveillance due to the lower cost and reduced time for library preparation.
| S-EPMC9788413 | biostudies-literature
Project description:Understanding viral load in patients infected with SARS-CoV-2 is critical to epidemiology and infection control. Previous studies have demonstrated that SARS-CoV-2 RNA can be detected for many weeks after symptom onset. The clinical significance of this finding is unclear and, in most patients, likely does not represent active infection. There are, however, patients who shed infectious virus for weeks. Detection of subgenomic RNA transcripts expressed by SARS-CoV-2 has been proposed to represent productive infection and may be a tractable marker for monitoring infectivity. Here, we use RT-PCR to quantify total and subgenomic nucleocapsid (N) and envelope (E) transcripts in 190 SARS-CoV-2 positive samples collected on hospital admission. We relate these findings to duration of symptoms. We find that all transcripts decline at the same rate; however, subgenomic E becomes undetectable before other transcripts. In Kaplan-Meier analysis the median duration of symptoms to a negative test is 14 days for sgE and 25 days for sgN. There is a linear decline in subgenomic RNA compared to total RNA suggesting subgenomic transcript copy number is highly dependent on copy number of total transcripts. The mean difference between total N and subgenomic N is 16-fold (4.0 cycles) and the mean difference between total E and sub-genomic E is 137-fold (7.1 cycles). This relationship is constant over duration of symptoms allowing prediction of subgenomic copy number from total copy number. Although Subgenomic E is undetectable at a time that may more closely reflect the duration of infectivity, its utility in determining active infection may be no more useful than a copy number threshold determined for total transcripts.
| S-EPMC7941648 | biostudies-literature
Project description:Respiratory virus challenge studies involve administration of the challenge virus and sampling to assess for protection from the same anatomical locations. It can therefore be difficult to differentiate actively replicating virus from input challenge virus. For SARS-CoV-2, specific monitoring of actively replicating virus is critical to investigate the protective and therapeutic efficacy of vaccines, monoclonal antibodies, and antiviral drugs. We developed a SARS-CoV-2 subgenomic RNA (sgRNA) RT-PCR assay to differentiate productive infection from inactivated or neutralized virus. Subgenomic RNAs are generated after cell entry and are poorly incorporate into mature virions, and thus may provide a marker for actively replicating virus. We show envelope (E) sgRNA was degraded by RNase in infected cell lysates, while genomic RNA (gRNA) was protected, presumably due to packaging into virions. To investigate the capacity of the sgRNA assay to distinguish input challenge virus from actively replicating virus in vivo, we compared the E sgRNA assay to a standard nucleoprotein (N) or E total RNA assay in convalescent rhesus macaques and in antibody-treated rhesus macaques after experimental SARS-CoV-2 challenge. In both studies, the E sgRNA assay was negative, suggesting protective efficacy, whereas the N and E total RNA assays remained positive. These data suggest the potential utility of sgRNA to monitor actively replicating virus in prophylactic and therapeutic SARS-CoV-2 studies.ImportanceDeveloping therapeutic and prophylactic countermeasures for the SARS-CoV-2 virus is a public health priority. During challenge studies, respiratory viruses are delivered and sampled from the same anatomical location. It is therefore important to distinguish actively replicating virus from input challenge virus. The most common assay for detecting SARS-CoV-2 virus, reverse transcription polymerase chain reaction (RT-PCR) targeting nucleocapsid total RNA, cannot distinguish neutralized input virus from replicating virus. In this study, we assess SARS-CoV-2 subgenomic RNA as a potential measure of replicating virus in rhesus macaques.
| S-EPMC8103707 | biostudies-literature
Project description:Little is known about Subgenomic RNA (sgRNA) dynamics in patients with Coronavirus diseases 2019 (COVID-19). We collected 147 throat swabs, 74 gut swabs and 46 plasma samples from 117 COVID-19 patients recruited in the LOTUS China trial (ChiCTR2000029308) and compared E and orf7a sgRNA load in patients with different illness duration, outcome, and comorbidities. Both sgRNAs were detected in all the three types of samples, with longest duration of 25, 13, and 17 days for E sgRNA, and 32, 28, and 17 days for orf7a sgRNA in throat, gut, and plasma, respectively. A total of 95% (57/60) of patients had no E sgRNA detected after 10 days post treatment, though 86% of them were still E RNA positive. High correlation on titer was observed between sgRNA encoding E and orf7a gene. sgRNA showed similar variation in the standard care and Lopinavir-Ritonavir group. Patients with diabetes and heart diseases showed higher pharyngeal E sgRNA at the first day (P = 0.016 and 0.013, respectively) but no difference at five days after treatment, compared with patients without such commodities. Patients with hypertension and cerebrovascular diseases showed no difference in the pharyngeal sgRNA levels at both one and five days after treatment, compared with patients without these two commodities. E sgRNA levels in the initial infection showed no correlation with the serum antibody against spike, nucleoprotein, and receptor binding domains at ten days later. sgRNA lasted a long period in COVID-19 patients and might have little effect on humoral response.
| S-EPMC8762994 | biostudies-literature