RT Journal Article SR Electronic T1 Massively parallel digital transcriptional profiling of single cells JF bioRxiv FD Cold Spring Harbor Laboratory SP 065912 DO 10.1101/065912 A1 Grace X.Y. Zheng A1 Jessica M. Terry A1 Phillip Belgrader A1 Paul Ryvkin A1 Zachary W. Bent A1 Ryan Wilson A1 Solongo B. Ziraldo A1 Tobias D. Wheeler A1 Geoff P. McDermott A1 Junjie Zhu A1 Mark T. Gregory A1 Joe Shuga A1 Luz Montesclaros A1 Donald A. Masquelier A1 Stefanie Y. Nishimura A1 Michael Schnall-Levin A1 Paul W Wyatt A1 Christopher M. Hindson A1 Rajiv Bharadwaj A1 Alexander Wong A1 Kevin D. Ness A1 Lan W. Beppu A1 H. Joachim Deeg A1 Christopher McFarland A1 Keith R. Loeb A1 William J. Valente A1 Nolan G. Ericson A1 Emily A. Stevens A1 Jerald P. Radich A1 Tarjei S. Mikkelsen A1 Benjamin J. Hindson A1 Jason H. Bielas YR 2016 UL http://biorxiv.org/content/early/2016/07/26/065912.abstract AB 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.