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Nat Commun. 2017 Jan 16;8:14049. doi: 10.1038/ncomms14049.

Massively parallel digital transcriptional profiling of single cells.

Author information

1
10x Genomics Inc., Pleasanton, California, 94566, USA.
2
Translational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA.
3
Department of Genome Sciences, University of Washington, Seattle, Washington 98195, USA.
4
Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA.
5
Seattle Cancer Care Alliance Clinical Immunogenetics Laboratory, Seattle, Washington 98109, USA.
6
Department of Pathology, University of Washington, Seattle, Washington 98195, USA.
7
Medical Scientist Training Program, University of Washington School of Medicine, Seattle, Washington 98195, USA.
8
Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, Washington 98195, USA.
9
Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA.

Abstract

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 ∼6 min, with ∼50% cell capture efficiency. To demonstrate the system's technical performance, we collected transcriptome data from ∼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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