Our ‘Dataset of the Week’ series features publicly available omics datasets of scientific value, intending to promote data sharing and reuse.

This week’s dataset is RNA-sequencing data from the publication titled ‘Systems biological assessment of immunity to mild versus severe COVID-19 infection in humans', published in Science (Sep 2020).

SARS-CoV-2 induces a plethora of symptoms in infected individuals. Immune response, combined with a host of other factors such as pre-existing comorbidities and age, significantly affects clinical phenotypes and patient outcomes. This paper uses multiple computational biology techniques to delve deeper into the immunological underpinnings of SARS-CoV-2 infections.

Key Findings of the Publication

• SARS-CoV-2 infection severely impaired the normal functioning of dendritic cells and prevented them from mounting a robust immune response.
• RNA-seq analysis of peripheral blood mononuclear cells (PBMCs) showed that the expression levels of human leukocyte antigen class DR (HLA-DR) and numerous proinflammatory cytokines were diminished in cells of myeloid origins.
• On the other hand, molecules associated with disease severity such as EN-RAGE, TNFSF14 and oncostatin M, were significantly upregulated.
• Single-cell RNA sequencing analysis of myeloid cells from COVID-19 patients revealed diminished expression of type I interferons, as is observed in the case of other zoonotic coronavirus diseases such as SARS and MERS.

Significance of the Dataset

This dataset contains gene expression data from the immune cells of COVID-19 patients and healthy controls and could serve as a valuable resource in understanding the key molecular players and immune mechanisms involved in modulating the host immune response.

Experimental Design

PBMCs were isolated from the plasma samples of COVID-19 patients and healthy subjects (17 samples per group) and bulk RNA-sequencing analysis was performed.

Useful Links

• The dataset (GSE152418): https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE152418
• The publication: https://science.sciencemag.org/content/369/6508/1210
• The curated and analyzed report from the dataset: https://omixwiki.elucidata.io/486/gse152418/systems-biological-assessment-of