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Massively parallel digital transcriptional profiling of single cells
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,...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5241818/ https://www.ncbi.nlm.nih.gov/pubmed/28091601 http://dx.doi.org/10.1038/ncomms14049 |
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author | Zheng, Grace X. Y. Terry, Jessica M. Belgrader, Phillip Ryvkin, Paul Bent, Zachary W. Wilson, Ryan Ziraldo, Solongo B. Wheeler, Tobias D. McDermott, Geoff P. Zhu, Junjie Gregory, Mark T. Shuga, Joe Montesclaros, Luz Underwood, Jason G. Masquelier, Donald A. Nishimura, Stefanie Y. Schnall-Levin, Michael Wyatt, Paul W. Hindson, Christopher M. Bharadwaj, Rajiv Wong, Alexander Ness, Kevin D. Beppu, Lan W. Deeg, H. Joachim McFarland, Christopher Loeb, Keith R. Valente, William J. Ericson, Nolan G. Stevens, Emily A. Radich, Jerald P. Mikkelsen, Tarjei S. Hindson, Benjamin J. Bielas, Jason H. |
author_facet | Zheng, Grace X. Y. Terry, Jessica M. Belgrader, Phillip Ryvkin, Paul Bent, Zachary W. Wilson, Ryan Ziraldo, Solongo B. Wheeler, Tobias D. McDermott, Geoff P. Zhu, Junjie Gregory, Mark T. Shuga, Joe Montesclaros, Luz Underwood, Jason G. Masquelier, Donald A. Nishimura, Stefanie Y. Schnall-Levin, Michael Wyatt, Paul W. Hindson, Christopher M. Bharadwaj, Rajiv Wong, Alexander Ness, Kevin D. Beppu, Lan W. Deeg, H. Joachim McFarland, Christopher Loeb, Keith R. Valente, William J. Ericson, Nolan G. Stevens, Emily A. Radich, Jerald P. Mikkelsen, Tarjei S. Hindson, Benjamin J. Bielas, Jason H. |
author_sort | Zheng, Grace X. Y. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5241818 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-52418182017-02-02 Massively parallel digital transcriptional profiling of single cells Zheng, Grace X. Y. Terry, Jessica M. Belgrader, Phillip Ryvkin, Paul Bent, Zachary W. Wilson, Ryan Ziraldo, Solongo B. Wheeler, Tobias D. McDermott, Geoff P. Zhu, Junjie Gregory, Mark T. Shuga, Joe Montesclaros, Luz Underwood, Jason G. Masquelier, Donald A. Nishimura, Stefanie Y. Schnall-Levin, Michael Wyatt, Paul W. Hindson, Christopher M. Bharadwaj, Rajiv Wong, Alexander Ness, Kevin D. Beppu, Lan W. Deeg, H. Joachim McFarland, Christopher Loeb, Keith R. Valente, William J. Ericson, Nolan G. Stevens, Emily A. Radich, Jerald P. Mikkelsen, Tarjei S. Hindson, Benjamin J. Bielas, Jason H. Nat Commun Article 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. Nature Publishing Group 2017-01-16 /pmc/articles/PMC5241818/ /pubmed/28091601 http://dx.doi.org/10.1038/ncomms14049 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Zheng, Grace X. Y. Terry, Jessica M. Belgrader, Phillip Ryvkin, Paul Bent, Zachary W. Wilson, Ryan Ziraldo, Solongo B. Wheeler, Tobias D. McDermott, Geoff P. Zhu, Junjie Gregory, Mark T. Shuga, Joe Montesclaros, Luz Underwood, Jason G. Masquelier, Donald A. Nishimura, Stefanie Y. Schnall-Levin, Michael Wyatt, Paul W. Hindson, Christopher M. Bharadwaj, Rajiv Wong, Alexander Ness, Kevin D. Beppu, Lan W. Deeg, H. Joachim McFarland, Christopher Loeb, Keith R. Valente, William J. Ericson, Nolan G. Stevens, Emily A. Radich, Jerald P. Mikkelsen, Tarjei S. Hindson, Benjamin J. Bielas, Jason H. Massively parallel digital transcriptional profiling of single cells |
title | Massively parallel digital transcriptional profiling of single cells |
title_full | Massively parallel digital transcriptional profiling of single cells |
title_fullStr | Massively parallel digital transcriptional profiling of single cells |
title_full_unstemmed | Massively parallel digital transcriptional profiling of single cells |
title_short | Massively parallel digital transcriptional profiling of single cells |
title_sort | massively parallel digital transcriptional profiling of single cells |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5241818/ https://www.ncbi.nlm.nih.gov/pubmed/28091601 http://dx.doi.org/10.1038/ncomms14049 |
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