Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China; Stem Cell Institute, Zhejiang University, Hangzhou 310058, China.
Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China; Stem Cell Institute, Zhejiang University, Hangzhou 310058, China.
Cell. 2018 Feb 22;172(5):1091-1107.e17. doi: 10.1016/j.cell.2018.02.001.
Single-cell RNA sequencing (scRNA-seq) technologies are poised to reshape the current cell-type classification system. However, a transcriptome-based single-cell atlas has not been achieved for complex mammalian systems. Here, we developed Microwell-seq, a high-throughput and low-cost scRNA-seq platform using simple, inexpensive devices. Using Microwell-seq, we analyzed more than 400,000 single cells covering all of the major mouse organs and constructed a basic scheme for a mouse cell atlas (MCA). We reveal a single-cell hierarchy for many tissues that have not been well characterized previously. We built a web-based "single-cell MCA analysis" pipeline that accurately defines cell types based on single-cell digital expression. Our study demonstrates the wide applicability of the Microwell-seq technology and MCA resource.
单细胞 RNA 测序 (scRNA-seq) 技术有望重塑当前的细胞类型分类系统。然而，基于转录组的单细胞图谱尚未在复杂的哺乳动物系统中实现。在这里，我们开发了一种高通量、低成本的 scRNA-seq 平台 Microwell-seq，该平台使用简单、廉价的设备。使用 Microwell-seq，我们分析了超过 400,000 个单细胞，涵盖了所有主要的小鼠器官，并构建了小鼠细胞图谱 (MCA) 的基本方案。我们揭示了许多以前没有很好描述的组织的单细胞层次结构。我们构建了一个基于网络的“单细胞 MCA 分析”管道，该管道可以基于单细胞数字表达准确定义细胞类型。我们的研究表明 Microwell-seq 技术和 MCA 资源具有广泛的适用性。
