4.8 Article

Massively parallel digital transcriptional profiling of single cells

期刊

NATURE COMMUNICATIONS
卷 8, 期 -, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/ncomms14049

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资金

  1. Canary Foundation
  2. Ellison Medical Foundation New Scholar Award [AG-NS-0577-09]
  3. National Cancer Institute [R01 CA 175215-01, U10CA180861]
  4. Outstanding New Environmental Scientist Award (ONES) (R01) from the National Institute of Environmental Health Sciences [R01ES019319]
  5. Congressionally Directed Medical Research Programs/US Department of Defense [W81XWH-10-1-0563]
  6. Pacific Ovarian Cancer Research Consortium Ovarian Cancer SPORE Award [P50 CA083636]
  7. Achievement Rewards for College Scientists (ARCS) Foundation Fellowship
  8. Ruth L. Kirschstein National Research service F30 Award for Individual Predoctoral MD/PhD Degree Fellows [NCI F30CA200247]
  9. STFC [ST/M001008/1] Funding Source: UKRI

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Characterizing the transcriptome of individual cells is fundamental to understanding complex biological systems. We describe a droplet-based system that enables 3' mRNA counting of tens of thousands of single cells per sample. Cell encapsulation, of up to 8 samples at a time, takes place in similar to 6 min, with similar to 50% cell capture efficiency. To demonstrate the system's technical performance, we collected transcriptome data from similar to 250k single cells across 29 samples. We validated the sensitivity of the system and its ability to detect rare populations using cell lines and synthetic RNAs. We profiled 68k peripheral blood mononuclear cells to demonstrate the system's ability to characterize large immune populations. Finally, we used sequence variation in the transcriptome data to determine host and donor chimerism at single-cell resolution from bone marrow mononuclear cells isolated from transplant patients.

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