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Jessica M. Terry

10X Genomics (United States)

Publishes on Single-cell and spatial transcriptomics, Analytical chemistry methods development, Advanced biosensing and bioanalysis techniques. 39 papers and 11.6k citations.

39Publications
11.6kTotal Citations

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Top publicationsby citations

Massively parallel digital transcriptional profiling of single cells
Grace Zheng, Jessica M. Terry, Phillip Belgrader et al.|Nature Communications|2017
Cited by 7.7kOpen Access

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.

Massively parallel digital transcriptional profiling of single cells
Grace Zheng, Jessica M. Terry, Phillip Belgrader et al.|bioRxiv (Cold Spring Harbor Laboratory)|2016
Cited by 872Open Access

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.