This article has been Reviewed by the following groups
Bulk RNA sequencing (RNA-seq) of blood is typically used for gene expression analysis in biomedical research but is still rarely used in clinical practice. In this study, we argue that RNA-seq should be considered a routine diagnostic tool, as it offers not only insights into aberrant gene expression and splicing but also delivers additional readouts on immune cell type composition as well as B-cell and T-cell receptor (BCR/TCR) repertoires. We demonstrate that RNA-seq offers vital insights into a patient’s immune status via integrative analysis of RNA-seq data from patients infected with various SARS-CoV-2 variants (in total 240 samples with up to 200 million reads sequencing depth). We compare the results of computational cell-type deconvolution methods (e.g., MCP-counter, xCell, EPIC, quanTIseq) to complete blood count data, the current gold standard in clinical practice. We observe varying levels of lymphocyte depletion and significant differences in neutrophil levels between SARS-CoV-2 variants. Additionally, we identify B and T cell receptor (BCR/TCR) sequences using the tools MiXCR and TRUST4 to show that - combined with sequence alignments and pBLAST - they could be used to classify a patient’s disease. Finally, we investigated the sequencing depth required for such analyses and concluded that 10 million reads per sample is sufficient. In conclusion, our study reveals that computational cell-type deconvolution and BCR/TCR methods using bulk RNA-seq analyses can supplement missing CBC data and offer insights into immune responses, disease severity, and pathogen-specific immunity, all achievable with a sequencing depth of 10 million reads per sample.
Computational deconvolution of transcriptomes can estimate immune cell abundances in SARS-CoV-2 patients, supplementing missing CBC data.
10 million RNA sequencing reads per sample suffice for analyzing immune responses and disease severity, including BCR/TCR identification.
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Alex Mentzer, Bana Alamad
Review 2: "Blood Transcriptomics Analysis Offers Insights into Variant-specific Immune Response to SARS-CoV-2"
Overall, both reviewers suggest focusing on the comparison of deconvolution algorithms and exhibit concerns about the practicality of RNA-seq as a routine diagnostic tool due to cost and complexity factors.
Strength of evidence
Reviewers: R Shankar (Michigan State University) | 📘📘📘📘📘
A Mentzer (University of Oxford) & B Alamad (University of Oxford) | 📙📙 ◻️◻️◻️