ArticleMicrobiology spectrum2023
Unambiguous detection of SARS-CoV-2 subgenomic mRNAs with single-cell RNA sequencing.
Article in Microbiology spectrum, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 10 citations in OpenAlex.
- scDEcrypter: Uncertainty-aware differential expression analysis for viral infection in scRNA-seq.bioRxiv : the preprint server for biology · 2026Article
- How benchmarking of bioinformatics tools is essential for informed workflow selection: a case study on SARS-CoV-2 subgenomic RNA detection.Frontiers in bioinformatics · 2026Article
- Conserved heavy/light contacts and germline preferences revealed by a large-scale analysis of natively paired human antibody sequences and structural data.Communications biology · 2025Article
- A fusion ORF3a-E subgenomic RNA involved in SARS-CoV-2 infection efficacy by influencing cellular protein synthesis.Frontiers in immunology · 2025Article
- Single cell RNA-seq: a novel tool to unravel virus-host interplay.Virusdisease · 2024Review
- Single-Cell RNA-Sequencing of RVFV Infection.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Article
- Systematic functional interrogation of SARS-CoV-2 host factors using Perturb-seq.Nature communications · 2023Article
- Single-cell RNA-seq methods to interrogate virus-host interactions.Seminars in immunopathology · 2023Review
- Protocols for SARS-CoV-2 infection in primary ocular cells and eye organoids.STAR protocols · 2022Article
Corrections and comments
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
Abstract
importanceSingle-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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.