Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.
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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. VIDEO ABSTRACT. |
Year of Publication | 2015
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Journal | Cell
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Volume | 161
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Issue | 5
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Pages | 1202-14
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Date Published | 2015 May 21
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ISSN | 1097-4172
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URL | |
DOI | 10.1016/j.cell.2015.05.002
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PubMed ID | 26000488
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PubMed Central ID | PMC4481139
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Grant list | F32 HD075541 / HD / NICHD NIH HHS / United States
R25 MH094612 / MH / NIMH NIH HHS / United States
U01MH105960 / MH / NIMH NIH HHS / United States
U01 MH105960 / MH / NIMH NIH HHS / United States
T32 AI074549 / AI / NIAID NIH HHS / United States
P50 HG006193 / HG / NHGRI NIH HHS / United States
Howard Hughes Medical Institute / United States
R25MH094612 / MH / NIMH NIH HHS / United States
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