ArticleCell reports methods2023
Blood RNA alternative splicing events as diagnostic biomarkers for infectious disease.
Article in Cell reports methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Exercise modulation of the alternative splicing landscape in human tissues.bioRxiv : the preprint server for biology · 2026Article
- SARS-CoV-2-induced dysregulation in ADAR editing patterns persists post viral clearance in individuals with mild COVID-19.Frontiers in cellular and infection microbiology · 2026Article
- Full-length mRNA sequencing resolves novel variation in 5' UTR length for genes expressed during human CD4 T-cell activation.Immunogenetics · 2025Article
- A computational framework to improve cross-platform implementation of transcriptomics signatures.EBioMedicine · 2024Review
- Tapioca: a platform for predicting de novo protein-protein interactions in dynamic contexts.Nature methods · 2024Article
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Authors and funding
26 authors.
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Abstract
Assays detecting blood transcriptome changes are studied for infectious disease diagnosis. Blood-based RNA alternative splicing (AS) events, which have not been well characterized in pathogen infection, have potential normalization and assay platform stability advantages over gene expression for diagnosis. Here, we present a computational framework for developing AS diagnostic biomarkers. Leveraging a large prospective cohort of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and whole-blood RNA sequencing (RNA-seq) data, we identify a major functional AS program switch upon viral infection. Using an independent cohort, we demonstrate the improved accuracy of AS biomarkers for SARS-CoV-2 diagnosis compared with six reported transcriptome signatures. We then optimize a subset of AS-based biomarkers to develop microfluidic PCR diagnostic assays. This assay achieves nearly perfect test accuracy (61/62 = 98.4%) using a naive principal component classifier, significantly more accurate than a gene expression PCR assay in the same cohort. Therefore, our RNA splicing computational framework enables a promising avenue for host-response diagnosis of infection.
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