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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...

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A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

COVID-19 of differing severity: from bulk to single-cell expression data analysis.

Linlin Tian¹, Min He¹, Huafeng Fan¹

¹Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, P.R. China.

Cell Cycle (Georgetown, Tex.)

|July 24, 2023

Summary

This study identifies key genes and pathways distinguishing mild from severe COVID-19. Findings reveal potential biomarkers and drug targets, including glucocorticoids, for improved diagnosis and treatment of coronavirus disease 2019.

Keywords:

COVID-19 bulk single-cell

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A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

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Published on: March 5, 2022

Area of Science:

Genomics and Bioinformatics
Immunology
Pharmacology

Background:

Coronavirus disease 2019 (COVID-19) presents a significant global health burden.
Biomarkers and targeted therapies for varying COVID-19 severity remain largely unidentified.

Purpose of the Study:

To identify critical molecular differences between mild COVID-19 (mCOVID-19) and severe COVID-19 (sCOVID-19).
To discover potential biomarkers, therapeutic targets, and immune cell involvement in COVID-19 pathogenesis.

Main Methods:

Weighted Gene Co-expression Network Analysis (WGCNA) on the GSE164805 dataset.
Construction of protein-protein interaction networks to identify hub genes.
Analysis of transcription factors, kinases, immune cell infiltration, and drug-gene interactions.
Single-cell RNA sequencing analysis and validation in peripheral blood mononuclear cells (PBMCs).

Main Results:

Identified 16 hub genes for mCOVID-19 and 10 for sCOVID-19.
Detected distinct pathway enrichments (TNFA signaling via NFKB for mCOVID-19, MYC targets V1 for sCOVID-19) and immune cell differences (e.g., macrophages).
Predicted glucocorticoids as potential therapeutic agents and found cell-type-specific expression of several hub genes.
Validated significant upregulation of mCOVID-19 hub genes in patient PBMCs.

Conclusions:

This study elucidates critical molecular signatures, pathways, and immune cell profiles associated with COVID-19 severity.
Identified hub genes and potential drug targets, particularly glucocorticoids, offer avenues for earlier diagnosis and effective treatment strategies.
Cell-type-specific gene expression patterns provide insights into the cellular basis of differential COVID-19 responses.