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A pulmonologist's guide to perform and analyse cross-species single lung cell transcriptomics.
Pennitz, Peter; Kirsten, Holger; Friedrich, Vincent D; Wyler, Emanuel; Goekeri, Cengiz; Obermayer, Benedikt; Heinz, Gitta A; Mashreghi, Mir-Farzin; Büttner, Maren; Trimpert, Jakob; Landthaler, Markus; Suttorp, Norbert; Hocke, Andreas C; Hippenstiel, Stefan; Tönnies, Mario; Scholz, Markus; Kuebler, Wolfgang M; Witzenrath, Martin; Hoenzke, Katja; Nouailles, Geraldine.
Afiliación
  • Pennitz P; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases and Respiratory Medicine, Berlin, Germany.
  • Kirsten H; Both authors contributed equally to this work.
  • Friedrich VD; University of Leipzig, Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig, Germany.
  • Wyler E; Both authors contributed equally to this work.
  • Goekeri C; University of Leipzig, Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig, Germany.
  • Obermayer B; Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), Leipzig, Germany.
  • Heinz GA; Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany.
  • Mashreghi MF; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases and Respiratory Medicine, Berlin, Germany.
  • Büttner M; Cyprus International University, Faculty of Medicine, Nicosia, Cyprus.
  • Trimpert J; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Core Unit Bioinformatics, Berlin, Germany.
  • Landthaler M; Deutsches Rheuma-Forschungszentrum Berlin (DRFZ), A Leibniz Institute, Therapeutic Gene Regulation, Berlin, Germany.
  • Suttorp N; Deutsches Rheuma-Forschungszentrum Berlin (DRFZ), A Leibniz Institute, Therapeutic Gene Regulation, Berlin, Germany.
  • Hocke AC; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Center for Regenerative Therapies (BCRT), Berlin, Germany.
  • Hippenstiel S; University of Bonn, Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, Bonn, Germany.
  • Tönnies M; Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Systems Medicine, Bonn, Germany.
  • Scholz M; Freie Universität Berlin, Institute of Virology, Berlin, Germany.
  • Kuebler WM; Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Berlin, Germany.
  • Witzenrath M; Humboldt-Universität zu Berlin, Institute for Biology, IRI Life Sciences, Berlin, Germany.
  • Hoenzke K; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases and Respiratory Medicine, Berlin, Germany.
  • Nouailles G; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases and Respiratory Medicine, Berlin, Germany.
Eur Respir Rev ; 31(165)2022 Sep 30.
Article en En | MEDLINE | ID: mdl-35896273
ABSTRACT
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Transcriptoma / Neumólogos Límite: Animals / Humans Idioma: En Revista: Eur Respir Rev Año: 2022 Tipo del documento: Article País de afiliación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Transcriptoma / Neumólogos Límite: Animals / Humans Idioma: En Revista: Eur Respir Rev Año: 2022 Tipo del documento: Article País de afiliación: Alemania
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