Single-cell RNA sequencing of mouse lower respiratory tract epithelial cells: a meta-analysis
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 dis...
Gespeichert in:
| Hauptverfasser: | , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
11 May 2023
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| In: |
Cells & development
Year: 2023, Jahrgang: 174, Pages: 1-7 |
| ISSN: | 2667-2901 |
| DOI: | 10.1016/j.cdev.2023.203847 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.cdev.2023.203847 Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S2667290123000232 
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| Verfasserangaben: | Leila R. Martins, Hanno Glimm, Claudia Scholl |
MARC
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| 520 | |a 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. | ||
| 650 | 4 | |a Epithelial cells | |
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