Single-cell RNA sequencing of mouse lower respiratory tract epithelial cells: A meta-analysis

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Leila R Martins - , German Cancer Research Center (DKFZ) (Author)
  • Hanno Glimm - , National Center for Tumor Diseases (Partners: UKD, MFD, HZDR, DKFZ), German Cancer Consortium (DKTK) Partner Site Dresden, German Cancer Research Center (DKFZ), University Hospital Carl Gustav Carus Dresden (Author)
  • Claudia Scholl - , German Cancer Research Center (DKFZ) (Author)

Abstract

The respiratory system is a vital component of our body, essential for both oxygen uptake and immune defense. Knowledge of cellular composition and function in different parts of the respiratory tract provides the basis for a better understanding of the pathological processes involved in various diseases such as chronic respiratory diseases and cancer. Single-cell RNA sequencing (scRNA-seq) is a proficient approach for the identification and transcriptional characterization of cellular phenotypes. Although the mouse is an essential tool for the study of lung development, regeneration, and disease, a scRNA-seq mouse atlas of the lung in which all epithelial cell types are included and annotated systematically is lacking. Here, we established a single-cell transcriptome landscape of the mouse lower respiratory tract by performing a meta-analysis of seven different studies in which mouse lungs and trachea were analyzed by droplet and/or plate-based scRNA-seq technologies. We provide information on the best markers for each epithelial cell type, propose surface markers for the isolation of viable cells, harmonized the annotation of cell types, and compare the mouse single-cell transcriptomes with human scRNA-seq data of the lung.

Details

Original languageEnglish
Article number203847
Pages (from-to)203847
JournalCells & development
Volume174
Publication statusPublished - Jun 2023
Peer-reviewedYes

External IDs

Scopus 85158863918

Keywords

Sustainable Development Goals

Keywords

  • Animals, Mice, Humans, Gene Expression Profiling, Sequence Analysis, RNA, High-Throughput Nucleotide Sequencing, Transcriptome/genetics, Epithelial Cells/metabolism