Blood Transcriptomics Analysis Offers Insights into Variant-specific Immune Response to SARS-CoV-2
Authors
Affiliations
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 propose that RNA-seq should be considered a 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 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 196 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 BLASTp-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.
Data-driven projections of candidate enhancer-activating SNPs in immune regulation.
Hoffmann M, Vaz T, Chhatrala S, Hennighausen L BMC Genomics. 2025; 26(1):197.
PMID: 40011812 PMC: 11863423. DOI: 10.1186/s12864-025-11374-7.
Hoffmann M, Hennighausen L Sci Rep. 2025; 15(1):6202.
PMID: 39979591 PMC: 11842829. DOI: 10.1038/s41598-025-90788-5.