Spatial transcriptome uncovers the mouse lung architectures and functions

Revealing the relationships between the tissue structures and transcriptomic information is significant for understanding the mechanisms and principles underpinning the biological processes in lung development and diseases. The widely transcriptomic technics, including bulk and single-cell RNA sequencing, cannot accurately restore the tissue location of the gene expression. The advanced spatial transcriptomic tools can fill this gap properly with in-situ RNA capturing and spatial barcode labeling and translating. However, the published spatial transcriptome data of lung is rare or low-quality. Here we harnessed the large-view and high-resolution capabilities of Stereo-seq, one of the most advanced spatial transcriptome tools, in a 5-week-old female mouse to uncover the lung functions with their tissue location resolved. We also found a gradient expression of a bunch of genes related to cell proliferation along the axis of the proximal-to-distal trachea. All the data provided by the study pave the way for further studies in lung development and disease in the future.

揭示组织结构与转录组信息之间的关联，对于解析肺发育与疾病相关生物学过程的核心机制与调控原理具有重要意义。当前主流转录组学技术（包括批量RNA测序与单细胞RNA测序）无法精准还原基因表达的组织定位信息。先进的空间转录组学工具可通过原位RNA捕获与空间条形码标记及解码技术填补这一空白，但目前已公开的肺部空间转录组数据较为稀缺且质量欠佳。本研究借助当前最先进的空间转录组学工具之一——斯特莱测序（Stereo-seq）的大视场、高分辨率优势，以5周龄雌性小鼠为研究对象，解析了具备精确组织定位信息的肺脏功能特征。同时，本研究还发现一批与细胞增殖相关的基因沿气管近端至远端轴呈现梯度表达模式。本研究所提供的全部数据，可为未来肺发育与肺部疾病领域的后续研究奠定坚实基础。