RT Journal Article
SR Electronic
T1 A pulmonologist's guide to perform and analyse cross-species single lung cell transcriptomics
JF European Respiratory Review
JO EUROPEAN RESPIRATORY REVIEW
FD European Respiratory Society
SP 220056
DO 10.1183/16000617.0056-2022
VO 31
IS 165
A1 Peter Pennitz
A1 Holger Kirsten
A1 Vincent D. Friedrich
A1 Emanuel Wyler
A1 Cengiz Goekeri
A1 Benedikt Obermayer
A1 Gitta A. Heinz
A1 Mir-Farzin Mashreghi
A1 Maren Büttner
A1 Jakob Trimpert
A1 Markus Landthaler
A1 Norbert Suttorp
A1 Andreas C. Hocke
A1 Stefan Hippenstiel
A1 Mario Tönnies
A1 Markus Scholz
A1 Wolfgang M. Kuebler
A1 Martin Witzenrath
A1 Katja Hoenzke
A1 Geraldine Nouailles
YR 2022
UL http://err.ersjournals.com/content/31/165/220056.abstract
AB Single-cell ribonucleic acid sequencing is becoming widely employed to study biological processes at a novel resolution depth. The ability to analyse transcriptomes of multiple heterogeneous cell types in parallel is especially valuable for cell-focused lung research where a variety of resident and recruited cells are essential for maintaining organ functionality. We compared the single-cell transcriptomes from publicly available and unpublished datasets of the lungs in six different species: human (Homo sapiens), African green monkey (Chlorocebus sabaeus), pig (Sus domesticus), hamster (Mesocricetus auratus), rat (Rattus norvegicus) and mouse (Mus musculus) by employing RNA velocity and intercellular communication based on ligand–receptor co-expression, among other techniques. Specifically, we demonstrated a workflow for interspecies data integration, applied a single unified gene nomenclature, performed cell-specific clustering and identified marker genes for each species. Overall, integrative approaches combining newly sequenced as well as publicly available datasets could help identify species-specific transcriptomic signatures in both healthy and diseased lung tissue and select appropriate models for future respiratory research.The COVID-19 pandemic led to an increase in publicly available single-cell RNA sequencing data. This review provides an up-to-date framework and readily adoptable tools to measure such data in lungs and compare it with existing data across species. https://bit.ly/3wHCoHe