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Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets

Author(s)
Macosko, Evan Z.; Satija, Rahul; Nemesh, James; Shekhar, Karthik; Goldman, Melissa; Tirosh, Itay; Bialas, Allison R.; Kamitaki, Nolan; Martersteck, Emily M.; Trombetta, John J.; Weitz, David A.; Sanes, Joshua R.; McCarroll, Steven A.; Shalek, Alexander K; Regev, Aviv; Basu, Anindita, 1978-; ... Show more Show less
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Abstract
Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell’s RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts’ cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution.
Date issued
2015-05
URI
http://hdl.handle.net/1721.1/110604
Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science; Massachusetts Institute of Technology. Department of Biology; Massachusetts Institute of Technology. Department of Chemistry
Journal
Cell
Publisher
Elsevier
Citation
Macosko, Evan Z.; Basu, Anindita; Satija, Rahul; Nemesh, James; Shekhar, Karthik; Goldman, Melissa; Tirosh, Itay et al. “Highly Parallel Genome-Wide Expression Profiling of Individual Cells Using Nanoliter Droplets.” Cell 161, no. 5 (May 2015): 1202–1214 © 2015 Elsevier Inc
Version: Author's final manuscript
ISSN
0092-8674
1097-4172

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