A human fetal lung cell atlas uncovers proximal-distal gradients of differentiation and key regulators of epithelial fates
A human fetal lung cell atlas uncovers proximal-distal gradients of differentiation and key regulators of epithelial fates
复制标题
DOI：
10.1016/j.cell.2022.11.005
复制
发表时间：
2022-12-08
期刊：
影响因子：
64.5
通讯作者：
Rawlins, Emma L.
中科院分区：
文献类型：
--
作者：
He, Peng;Lim, Kyungtae;Rawlins, Emma L.
我们提出了一个人类肺发育的多组细胞图谱，它结合了单细胞RNA和ATAC测序、高通量空间转录组学和单细胞成像。耦合单细胞的方法与空间分析允许全面的上皮细胞，间充质细胞，内皮细胞，和红细胞/白细胞隔室从5-22周后受孕。我们确定以前uncharacterized细胞状态在所有车厢。这些包括发育特异性分泌祖细胞和与人类小细胞肺癌相关的神经内分泌细胞亚型。我们的数据集可通过我们的网络界面（https：//www.example.com）获得。lungcellatlas.org为了说明它的一般效用，我们使用我们的细胞图谱来生成关于细胞-细胞信号传导和转录因子层级的预测，我们使用orga-noid模型严格测试这些预测。
We present a multiomic cell atlas of human lung development that combines single-cell RNA and ATAC sequencing, high-throughput spatial transcriptomics, and single-cell imaging. Coupling single-cell methods with spatial analysis has allowed a comprehensive cellular survey of the epithelial, mesenchymal, endothelial, and erythrocyte/leukocyte compartments from 5-22 post-conception weeks. We identify previously unchar-acterized cell states in all compartments. These include developmental-specific secretory progenitors and a subtype of neuroendocrine cell related to human small cell lung cancer. Our datasets are available through our web interface (https://lungcellatlas.org). To illustrate its general utility, we use our cell atlas to generate predictions about cell-cell signaling and transcription factor hierarchies which we rigorously test using orga-noid models.