| Literature DB >> 32214235 |
Xiaoping Han1,2, Ziming Zhou3, Lijiang Fei3, Huiyu Sun3, Renying Wang3, Yao Chen4, Haide Chen3,5, Jingjing Wang3,5, Huanna Tang6, Wenhao Ge7, Yincong Zhou8, Fang Ye3, Mengmeng Jiang3, Junqing Wu3, Yanyu Xiao3, Xiaoning Jia9, Tingyue Zhang3, Xiaojie Ma10, Qi Zhang11, Xueli Bai11, Shujing Lai3, Chengxuan Yu3, Lijun Zhu7, Rui Lin12, Yuchi Gao13, Min Wang14, Yiqing Wu4, Jianming Zhang15, Renya Zhan16, Saiyong Zhu10, Hailan Hu9, Changchun Wang17, Ming Chen8, He Huang18,19,20, Tingbo Liang11, Jianghua Chen6, Weilin Wang7, Dan Zhang4, Guoji Guo21,22,23,24,25.
Abstract
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.Entities:
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Year: 2020 PMID： 32214235 DOI： 10.1038/s41586-020-2157-4
Source DB: PubMed Journal: Nature ISSN： 0028-0836 Impact factor: 49.962