Integrated analysis of RNA-seq datasets reveals novel targets and regulators of COVID-19 severity.
Thais Teixeira OliveiraJúlia Firme FreitasViviane Priscila Barros de MedeirosThiago Jesus da Silva XavierLucymara Fassarella Agnez-LimaPublished in: Life science alliance (2024)
During the COVID-19 pandemic, RNA-seq datasets were produced to investigate the virus-host relationship. However, much of these data remains underexplored. To improve the search for molecular targets and biomarkers, we performed an integrated analysis of multiple RNA-seq datasets, expanding the cohort and including patients from different countries, encompassing severe and mild COVID-19 patients. Our analysis revealed that severe COVID-19 patients exhibit overexpression of genes coding for proteins of extracellular exosomes, endomembrane system, and neutrophil granules (e.g., S100A9 , LY96 , and RAB1B ), which may play an essential role in the cellular response to infection. Concurrently, these patients exhibit down-regulation of genes encoding components of the T cell receptor complex and nucleolus, including TP53 , IL2RB , and NCL Finally, SPI1 may emerge as a central transcriptional factor associated with the up-regulated genes, whereas TP53, MYC, and MAX were associated with the down-regulated genes during COVID-19. This study identified targets and transcriptional factors, lighting on the molecular pathophysiology of syndrome coronavirus 2 infection.
Keyphrases
- rna seq
- single cell
- transcription factor
- sars cov
- end stage renal disease
- genome wide
- ejection fraction
- chronic kidney disease
- peritoneal dialysis
- cell proliferation
- mesenchymal stem cells
- machine learning
- artificial intelligence
- electronic health record
- case report
- respiratory syndrome coronavirus
- drug induced
- data analysis
- patient reported
- big data