TY - JOUR T1 - A pulmonologist's guide to perform and analyse cross-species single lung cell transcriptomics JF - European Respiratory Review JO - EUROPEAN RESPIRATORY REVIEW DO - 10.1183/16000617.0056-2022 VL - 31 IS - 165 SP - 220056 AU - Peter Pennitz AU - Holger Kirsten AU - Vincent D. Friedrich AU - Emanuel Wyler AU - Cengiz Goekeri AU - Benedikt Obermayer AU - Gitta A. Heinz AU - Mir-Farzin Mashreghi AU - Maren Büttner AU - Jakob Trimpert AU - Markus Landthaler AU - Norbert Suttorp AU - Andreas C. Hocke AU - Stefan Hippenstiel AU - Mario Tönnies AU - Markus Scholz AU - Wolfgang M. Kuebler AU - Martin Witzenrath AU - Katja Hoenzke AU - Geraldine Nouailles Y1 - 2022/09/30 UR - http://err.ersjournals.com/content/31/165/220056.abstract N2 - 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 We compared the single-cell transcriptomes from publicly available and unpublished datasets of the lungs in six different species: human (Homo sapiens), African green monkey (Chlorocebus sabaeus), pig (Sus domesticus), hamster (Mesocricetus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 ER -