作者
Xiaoping Han,Ziyu Zhou,Lijiang Fei,Huiyu Sun,Renying Wang,Yao Chen,Haide Chen,Jingjing Wang,Huanna Tang,Weifeng Ge,Yincong Zhou,Fang Ye,Mengmeng Jiang,Jinliang Wu,Yanyu Xiao,Xiaoning Jia,Tingyue Zhang,Xiaojie Ma,Qi Zhang,Xueli Bai,Shih–Wei Lai,Chengxuan Yu,Lijun Zhu,Rui Lin,Yuchi Gao,Min Wang,Yiqing Wu,Jianming Zhang,Ruoting Zhan,Saiyong Zhu,Hailan Hu,Changchun Wang,Ming Chen,He Huang,Tingbo Liang,Jianghua Chen,Weilin Wang,Dan Zhang,Guoji Guo
摘要
Single-cell analysis is a valuable tool for dissecting cellular heterogeneity in complex systems1. However, a comprehensive single-cell atlas has not been achieved for humans. Here we use single-cell mRNA sequencing to determine the cell-type composition of all major human organs and construct a scheme for the human cell landscape (HCL). We have uncovered a single-cell hierarchy for many tissues that have not been well characterized. We established a ‘single-cell HCL analysis’ pipeline that helps to define human cell identity. Finally, we performed a single-cell comparative analysis of landscapes from human and mouse to identify conserved genetic networks. We found that stem and progenitor cells exhibit strong transcriptomic stochasticity, whereas differentiated cells are more distinct. Our results provide a useful resource for the study of human biology.