Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Sep 22, 2025

Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

30.1K

Analyzing single cell transcriptome data from severe COVID-19 patients.

Nasna Nassir1,2, Richa Tambi1,2, Asma Bankapur1

  • 1College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE.

STAR Protocols
|May 18, 2022
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Multifocal Skeletal Muscle Mineralisation Following Severe Trauma and Prolonged Critical Illness: A Case Report.

Cureus·2026
Same author

Persistence of large P. aeruginosa aggregates despite reduced airway burden in people with cystic fibrosis on CFTR modulator therapy.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society·2026
Same author

Evaluating the Use of Tumor Bank DNA to Validate Genetic Factors Impacting Opioid Response in Patients with Advanced Cancer.

Current oncology (Toronto, Ont.)·2026
Same author

The effect of <i>Staphylococcus aureus</i> on the persistence of <i>Pseudomonas aeruginosa</i> due to aggregation in cystic fibrosis airway infections.

iScience·2026
Same author

Evaluation of FASP for Mass Spectrometry-Based Untargeted Metabolomics Analysis of Urine Samples.

Journal of proteome research·2026
Same author

Current understanding and future directions in severe asthma through artificial intelligence-integrated multi-omic approaches.

European respiratory review : an official journal of the European Respiratory Society·2026
This summary is machine-generated.

This study outlines a protocol to identify cell types and genes linked to severe COVID-19 using single-cell transcriptomics. Findings reveal specific cell types and marker genes associated with severe disease, validated across multiple models.

Area of Science:

  • Genomics
  • Immunology
  • Computational Biology

Background:

  • Single-cell transcriptomics offers high resolution for understanding complex diseases like COVID-19.
  • Identifying cellular mechanisms underlying COVID-19 severity is crucial for therapeutic development.

Purpose of the Study:

  • To develop and present a protocol for identifying cell types and regulatory genes associated with severe COVID-19.
  • To pinpoint cellular players and molecular markers contributing to COVID-19 pathogenesis.

Main Methods:

  • Utilized single-cell transcriptomics data to analyze gene expression patterns.
  • Constructed a COVID-19 comorbid disease-associated gene list from diverse databases and literature.
  • Performed gene enrichment analysis to characterize identified cell types.
Keywords:
BioinformaticsGene ExpressionGenomicsHealth SciencesImmunologyMolecular BiologyRNAseq

More Related Videos

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.7K
High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

4.4K

Related Experiment Videos

Last Updated: Sep 22, 2025

Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

30.1K
Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.7K
High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
14:58

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

4.4K

Main Results:

  • Identified specific cell types exhibiting upregulated comorbid disease genes in severe COVID-19.
  • Detected upregulation of distinct marker genes exclusively in severe COVID-19 associated cell types.
  • Validated findings through *in silico*, *in vivo*, and *in vitro* cellular models.

Conclusions:

  • The protocol effectively identifies cell types and marker genes critical to severe COVID-19.
  • This approach provides a framework for understanding cellular contributions to disease severity.
  • Findings pave the way for targeted therapeutic strategies against severe COVID-19.