Massively parallel digital transcriptional profiling of single cells

Nature Communications - Tập 8 Số 1
Grace Zheng1, Jessica M. Terry1, Phillip Belgrader1, Paul Ryvkin1, Zachary Bent1, Ryan J. Wilson1, Solongo B. Ziraldo1, Tobias D. Wheeler1, Geoff P. McDermott1, Junjie Zhu1, Mark Gregory2, Joe Shuga1, Luz Montesclaros1, Jason G. Underwood1, Donald A Masquelier1, Stefanie Y. Nishimura1, Michael Schnall-Levin1, Paul W. Wyatt1, Christopher M. Hindson1, Rajiv Bharadwaj1, Alexander Wong1, Kevin D. Ness1, Lan Beppu3, H. Joachim Deeg3, Christopher McFarland4, Keith R. Loeb3, William J. Valente2, Nolan G. Ericson2, Emily A. Stevens3, Jerald P. Radich3, Tarjei S. Mikkelsen1, Benjamin J. Hindson1, Jason H. Bielas5
110x Genomics Inc., Pleasanton, 94566, California, USA
2Public Health Sciences Division, Translational Research Program, Fred Hutchinson Cancer Research Center, Seattle, 98109, Washington, USA
3Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, 98109, Washington, USA
4Seattle Cancer Care Alliance Clinical Immunogenetics Laboratory, Seattle, 98109, Washington, USA
5Department of Pathology, University of Washington, Seattle, 98195, Washington, USA

Tóm tắt

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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Tài liệu tham khảo

Shalek, A. K. et al. Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature 498, 236–240 (2013).

Wills, Q. F. et al. Single-cell gene expression analysis reveals genetic associations masked in whole-tissue experiments. Nat. Biotechnol. 31, 748–752 (2013).

Liu, S. & Trapnell, C. Single-Cell Transcriptome Sequencing: Recent Advances and Remaining Challenges Vol. 5 F1000 Research (2016).

Jaitin, D. A. et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 343, 776–779 (2014).

Pollen, A. A. et al. Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat. Biotechnol. 32, 1053–1058 (2014).

Fluidigm. Single-cell whole genome sequencing on the C1 System: a performance evaluation https://www.fluidigm.com/binaries/content/documents/fluidigm/marketing/single-cell-whole-genome-sequencing/single-cell-whole-genome-sequencing/fluidigm%3Afile (2016).

Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).

Klein, A. M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).

Soumillon, M., Cacchiarelli, D., Semrau, S., van Oudenaarden, A. & Mikkelsen, T. S. Characterization of directed differentiation by high-throughput single-cell RNA-seq. Preprint at http://biorxiv.org/content/early/2014/03/05/003236 (2016).

Zheng, G. X. et al. Haplotyping germline and cancer genomes with high-throughput linked-read sequencing. Nat. Biotechnol. 34, 303–311 (2016).

Narasimhan, V. M. et al. Health and population effects of rare gene knockouts in adult humans with related parents. Science 352, 474–477 (2016).

Mostovoy, Y. et al. A hybrid approach for de novo human genome sequence assembly and phasing. Nat. Methods 13, 587–590 (2016).

Hindson, B. J. et al. High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal. Chem. 83, 8604–8610 (2011).

Brennecke, P. et al. Accounting for technical noise in single-cell RNA-seq experiments. Nat. Methods 10, 1093–1095 (2013).

Sherlock, G. Analysis of large-scale gene expression data. Curr. Opin. Immunol. 12, 201–205 (2000).

van der Maaten, L. J. P. & Hinton, G. E Visualizing high-dimensional data using t-SNE. J. Mach. Learn. Res. 9, 2579–2605 (2008).

Stem Cell Technologies. Frequencies of cell types in human peripheral blood. Available at: http://www.stemcell.com/media/files/wallchart/WA10006-Frequencies_Cell%20Types_Human_Peripheral_Blood.pdf (2016).

Borrego, F., Masilamani, M., Marusina, A. I., Tang, X. & Coligan, J. E The CD94/NKG2 family of receptors: from molecules and cells to clinical relevance. Immunol. Res. 35, 263–278 (2006).

Chu, P. G. & Arber, D. A CD79: a review. Appl. Immunohistochem. Mol. Morphol. 9, 97–106 (2001).

Schiopu, A. & Cotoi, O. S S100A8 and S100A9: DAMPs at the crossroads between innate immunity, traditional risk factors, and cardiovascular disease. Mediat. Inflamm. 2013, 828354 (2013).

Turman, M. A., Yabe, T., McSherry, C., Bach, F. H. & Houchins, J. P Characterization of a novel gene (NKG7) on human chromosome 19 that is expressed in natural killer cells and T cells. Hum. Immunol. 36, 34–40 (1993).

Lubberts, E The IL-23-IL-17 axis in inflammatory arthritis. Nat. Rev. Rheumatol. 11, 562 (2015).

Ronchetti, S. et al. Glucocorticoid-induced tumour necrosis factor receptor-related protein: a key marker of functional regulatory T cells. J. Immunol. Res. 2015, 171520 (2015).

Lin, Y. Y. et al. Transcriptional regulator Id2 is required for the CD4 T cell immune response in the development of experimental autoimmune encephalomyelitis. J. Immunol. 189, 1400–1405 (2012).

Greer, A. M. et al. Serum IgE clearance is facilitated by human FcepsilonRI internalization. J. Clin. Invest. 124, 1187–1198 (2014).

Harman, A. N. et al. Identification of lineage relationships and novel markers of blood and skin human dendritic cells. J. Immunol. 190, 66–79 (2013).

Satija, R. Seurat: R toolkit for single cell genomics. http://www.satijalab.org/seurat.html (2016).

Seattle Cancer Care Alliance. Chimerism testing/engraftment analysis. http://www.seattlecca.org/healthcare-professionals/clinical-labs/clinical-immunogenetics-laboratory/chimerism-testing (2016).

Patel, A. P. et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344, 1396–1401 (2014).

Tirosh, I. et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352, 189–196 (2016).

Lee, M. C. et al. Single-cell analyses of transcriptional heterogeneity during drug tolerance transition in cancer cells by RNA sequencing. Proc. Natl. Acad. Sci. USA 111, E4726–E4735 (2014).

Kim, K. T. et al. Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells. Genome Biol. 16, 127 (2015).

Vardiman, J. W. et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood 114, 937–951 (2009).

Zhong, J. F. et al. A microfluidic processor for gene expression profiling of single human embryonic stem cells. Lab Chip 8, 68–74 (2008).

Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

Garrison, E. & Marth, G. Haplotype-based variant detection from short-read sequencing. Preprint at https://arxiv.org/abs/1207.3907 (2012).

van der Maaten, L. Barnes-Hut-SNE Preprint at arXiv:1301.3342 [cs.LG] (2013).

Stephens, M. Dealing with label switching in mixture models. J. R. Stat. Soc. Ser. B 62, 795–809 (2000).

Liu, Q. et al. Significance of CD71 expression by flow cytometry in diagnosis of acute leukemia. Leuk. Lymphoma 55, 892–898 (2014).

Novershtern, N. et al. Densely interconnected transcriptional circuits control cell states in human hematopoiesis. Cell 144, 296–309 (2011).

Bonora, M. et al. Molecular mechanisms of cell death: central implication of ATP synthase in mitochondrial permeability transition. Oncogene 34, 1475–1486 (2015).

Schinke, C. et al. IL8-CXCR2 pathway inhibition as a therapeutic strategy against MDS and AML stem cells. Blood 125, 3144–3152 (2015).