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Massively parallel digital transcriptional profiling of single cells

Grace X.Y. Zheng, Jessica M. Terry, Phillip Belgrader, Paul Ryvkin, Zachary W. Bent, Ryan Wilson, Solongo B. Ziraldo, Tobias D. Wheeler, Geoff P. McDermott, Junjie Zhu, Mark T. Gregory, Joe Shuga, Luz Montesclaros, Donald A. Masquelier, Stefanie Y. Nishimura, Michael Schnall-Levin, Paul W Wyatt, Christopher M. Hindson, Rajiv Bharadwaj, Alexander Wong, Kevin D. Ness, Lan W. Beppu, H. Joachim Deeg, Christopher McFarland, Keith R. Loeb, William J. Valente, Nolan G. Ericson, Emily A. Stevens, Jerald P. Radich, Tarjei S. Mikkelsen, Benjamin J. Hindson, Jason H. Bielas
doi: https://doi.org/10.1101/065912
Grace X.Y. Zheng
110x Genomics, Inc., Pleasanton, CA, USA
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Jessica M. Terry
110x Genomics, Inc., Pleasanton, CA, USA
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Phillip Belgrader
110x Genomics, Inc., Pleasanton, CA, USA
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Paul Ryvkin
110x Genomics, Inc., Pleasanton, CA, USA
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Zachary W. Bent
110x Genomics, Inc., Pleasanton, CA, USA
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Ryan Wilson
110x Genomics, Inc., Pleasanton, CA, USA
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Solongo B. Ziraldo
110x Genomics, Inc., Pleasanton, CA, USA
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Tobias D. Wheeler
110x Genomics, Inc., Pleasanton, CA, USA
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Geoff P. McDermott
110x Genomics, Inc., Pleasanton, CA, USA
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Junjie Zhu
110x Genomics, Inc., Pleasanton, CA, USA
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Mark T. Gregory
2Translational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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Joe Shuga
110x Genomics, Inc., Pleasanton, CA, USA
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Luz Montesclaros
110x Genomics, Inc., Pleasanton, CA, USA
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Donald A. Masquelier
110x Genomics, Inc., Pleasanton, CA, USA
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Stefanie Y. Nishimura
110x Genomics, Inc., Pleasanton, CA, USA
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Michael Schnall-Levin
110x Genomics, Inc., Pleasanton, CA, USA
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Paul W Wyatt
110x Genomics, Inc., Pleasanton, CA, USA
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Christopher M. Hindson
110x Genomics, Inc., Pleasanton, CA, USA
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Rajiv Bharadwaj
110x Genomics, Inc., Pleasanton, CA, USA
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Alexander Wong
110x Genomics, Inc., Pleasanton, CA, USA
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Kevin D. Ness
110x Genomics, Inc., Pleasanton, CA, USA
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Lan W. Beppu
2Translational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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H. Joachim Deeg
7Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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Christopher McFarland
8Seattle Cancer Care Alliance Clinical Immunogenetics Laboratory, Seattle, WA, USA
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Keith R. Loeb
5Department of Pathology, University of Washington, Seattle, WA, USA
7Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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William J. Valente
2Translational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
3Medical Scientist Training Program, University of Washington School of Medicine, Seattle, WA, USA
4Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, WA, USA
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Nolan G. Ericson
2Translational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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Emily A. Stevens
7Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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Jerald P. Radich
7Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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Tarjei S. Mikkelsen
110x Genomics, Inc., Pleasanton, CA, USA
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Benjamin J. Hindson
110x Genomics, Inc., Pleasanton, CA, USA
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  • For correspondence: jbielas@fredhutch.org ben@10xgenomics.com
Jason H. Bielas
2Translational Research Program, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
4Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, WA, USA
5Department of Pathology, University of Washington, Seattle, WA, USA
6Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
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  • For correspondence: jbielas@fredhutch.org ben@10xgenomics.com
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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 up to tens of thousands of single cells per sample. Cell encapsulation in droplets takes place in ∼6 minutes, with ∼50% cell capture efficiency, up to 8 samples at a time. The speed and efficiency allow the processing of precious samples while minimizing stress to cells. To demonstrate the system′s technical performance and its applications, we collected transcriptome data from ∼¼ million single cells across 29 samples. First, we validate the sensitivity of the system and its ability to detect rare populations using cell lines and synthetic RNAs. Then, we profile 68k peripheral blood mononuclear cells (PBMCs) to demonstrate the system′s ability to characterize large immune populations. Finally, we use sequence variation in the transcriptome data to determine host and donor chimerism at single cell resolution in bone marrow mononuclear cells (BMMCs) of transplant patients. This analysis enables characterization of the complex interplay between donor and host cells and monitoring of treatment response. This high-throughput system is robust and enables characterization of diverse biological systems with single cell mRNA analysis.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted July 26, 2016.
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Massively parallel digital transcriptional profiling of single cells
Grace X.Y. Zheng, Jessica M. Terry, Phillip Belgrader, Paul Ryvkin, Zachary W. Bent, Ryan Wilson, Solongo B. Ziraldo, Tobias D. Wheeler, Geoff P. McDermott, Junjie Zhu, Mark T. Gregory, Joe Shuga, Luz Montesclaros, Donald A. Masquelier, Stefanie Y. Nishimura, Michael Schnall-Levin, Paul W Wyatt, Christopher M. Hindson, Rajiv Bharadwaj, Alexander Wong, Kevin D. Ness, Lan W. Beppu, H. Joachim Deeg, Christopher McFarland, Keith R. Loeb, William J. Valente, Nolan G. Ericson, Emily A. Stevens, Jerald P. Radich, Tarjei S. Mikkelsen, Benjamin J. Hindson, Jason H. Bielas
bioRxiv 065912; doi: https://doi.org/10.1101/065912
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Massively parallel digital transcriptional profiling of single cells
Grace X.Y. Zheng, Jessica M. Terry, Phillip Belgrader, Paul Ryvkin, Zachary W. Bent, Ryan Wilson, Solongo B. Ziraldo, Tobias D. Wheeler, Geoff P. McDermott, Junjie Zhu, Mark T. Gregory, Joe Shuga, Luz Montesclaros, Donald A. Masquelier, Stefanie Y. Nishimura, Michael Schnall-Levin, Paul W Wyatt, Christopher M. Hindson, Rajiv Bharadwaj, Alexander Wong, Kevin D. Ness, Lan W. Beppu, H. Joachim Deeg, Christopher McFarland, Keith R. Loeb, William J. Valente, Nolan G. Ericson, Emily A. Stevens, Jerald P. Radich, Tarjei S. Mikkelsen, Benjamin J. Hindson, Jason H. Bielas
bioRxiv 065912; doi: https://doi.org/10.1101/065912

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