The current status of gene expression profilings in COVID‐19 patients

Abstract

Abstract Background The global pandemic of coronavirus disease 2019 (COVID‐19) caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has swept through every part of the world. Because of its impact, international efforts have been underway to identify the variants of SARS‐CoV‐2 by genome sequencing and to understand the gene expression changes in COVID‐19 patients compared to healthy donors using RNA sequencing (RNA‐seq) assay. Within the last two and half years since the emergence of SARS‐CoV‐2, a large number of OMICS data of COVID‐19 patients have accumulated. Yet, we are still far from understanding the disease mechanism. Further, many people suffer from long‐term effects of COVID‐19; calling for a more systematic way to data mine the generated OMICS data, especially RNA‐seq data. Methods By searching gene expression omnibus (GEO) using the key terms, COVID‐19 and RNA‐seq, 108 GEO entries were identified. Each of these studies was manually examined to categorize the studies into bulk or single‐cell RNA‐seq (scRNA‐seq) followed by an inspection of their original articles. Results The currently available RNA‐seq data were generated from various types of patients’ samples, and COVID‐19 related sample materials have been sequenced at the level of RNA, including whole blood, different components of blood [e.g., plasma, peripheral blood mononuclear cells (PBMCs), leukocytes, lymphocytes, monocytes, T cells], nasal swabs, and autopsy samples (e.g., lung, heart, liver, kidney). Of these, RNA‐seq studies using whole blood, PBMCs, nasal swabs and autopsy/biopsy samples were reviewed to highlight the major findings from RNA‐seq data analysis. Conclusions Based on the bulk and scRNA‐seq data analysis, severe COVID‐19 patients display shifts in cell populations, especially those of leukocytes and monocytes, possibly leading to cytokine storms and immune silence. These RNA‐seq data form the foundation for further gene expression analysis using samples from individuals suffering from long COVID.

Keywords

• biomarker
• COVID‐19
• gene expression
• RNA‐seq