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Mapping the Mouse Cell Atlas by Microwell-Seq.

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Affiliations

  • 1. Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China; Stem Cell Institute, Zhejiang University, Hangzhou 310058, China.
      Authors
    • Han X 1
    • Wang R 1
    • Fei L 1
    • Sun H 1
    • Lai S 1
    • Zhou Z 1
    • Chen H 1
    • Ye F 1
    • Jiang M 1
    • Jiang X 1
    (10 authors)
  • 2. College of Life Sciences, Zhejiang University, Hangzhou 310003, China; Stem Cell Institute, Zhejiang University, Hangzhou 310058, China.
      Authors
    • Zhou Y 2
    • Chen M 2
    (2 authors)
  • 3. Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA 02115, USA.
      Authors
    • Saadatpour A 3
    • Yuan GC 3
    (2 authors)
  • 4. Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China.
      Authors
    • Huang D 4
    • Xu Y 4
    • Huang W 4
    (3 authors)
  • 5. Institute of Applied Mechanics, Zhejiang University, Hangzhou 310027, China.
      Authors
    • Mao J 5
    • Li T 5
    (2 authors)
    • Show all (13)

ORCIDs linked to this article

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Cell, 01 Feb 2018, 172(5):1091-1107.e17
https://doi.org/10.1016/j.cell.2018.02.001 PMID: 29474909 

This article has been corrected. See Cell. 2018 May 17;173(5):1307.

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.

Full text links 

Read article at publisher's site: https://doi.org/10.1016/j.cell.2018.02.001

Read article for free, from open access legal sources, via Unpaywall: http://www.cell.com/article/S0092867418301168/pdfUnpaywall

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Funding 

Funders who supported this work.

973 Program (1)

Fundamental Research Funds for the Central Universities (1)

National Key Program on Stem Cell and Translational Research (1)

National Natural Science Foundation of China (3)

Zhejiang Provincial Natural Science Foundation of China (1)