Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Infectious Diseases and Respiratory Medicine, Berlin, Germany.
Both authors contributed equally to this work.
Eur Respir Rev. 2022 Jul 27;31(165). doi: 10.1183/16000617.0056-2022. Print 2022 Sep 30.
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 We compared the single-cell transcriptomes from publicly available and unpublished datasets of the lungs in six different species: human (), African green monkey (), pig (), hamster (), rat () and mouse () by employing RNA velocity and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.
单细胞 RNA 测序正在被广泛应用于以全新的分辨率深度研究生物过程。同时分析多种异质细胞类型的转录组的能力对于以细胞为中心的肺部研究特别有价值，因为各种常驻和募集的细胞对于维持器官功能是必不可少的。我们通过 RNA 速度和基于配体-受体共表达的细胞间通讯等技术，比较了来自六个不同物种（人（）、非洲绿猴（）、猪（）、仓鼠（）、大鼠（）和小鼠（））的公开和未发表的肺部单细胞转录组数据集。具体来说，我们展示了一种用于种间数据整合的工作流程，应用了单一统一的基因命名法，进行了细胞特异性聚类，并确定了每个物种的标记基因。总的来说，结合新测序和公开数据集的综合方法可以帮助识别健康和患病肺部组织中的物种特异性转录组特征，并为未来的呼吸研究选择合适的模型。
