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Mapping the Mouse Cell Atlas by Microwell-Seq

  • Xiaoping Han*
  • , Renying Wang
  • , Yincong Zhou
  • , Lijiang Fei
  • , Huiyu Sun
  • , Shujing Lai
  • , Assieh Saadatpour
  • , Ziming Zhou
  • , Haide Chen
  • , Fang Ye
  • , Daosheng Huang
  • , Yang Xu
  • , Wentao Huang
  • , Mengmeng Jiang
  • , Xinyi Jiang
  • , Jie Mao
  • , Yao Chen
  • , Chenyu Lu
  • , Jin Xie
  • , Qun Fang
  • Yibin Wang, Rui Yue, Tiefeng Li, He Huang, Stuart H. Orkin, Guo-Cheng Yuan, Ming Chen, Guoji Guo*
*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)1091-1107
JournalCell
Volume172
Issue number5
Online published22 Feb 2018
DOIs
Publication statusPublished - 22 Feb 2018
Externally publishedYes

Research Keywords

  • single cell RNA-seq
  • mouse cell atlas
  • Microwell-seq
  • scMCA analysis
  • mammalian cell map
  • cellular heterogeneity
  • cross-tissue cellular network
  • cell type classification
  • single-cell analysis

Policy Impact

  • Cited in Policy Documents

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