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

Evan Z Macosko; Anindita Basu; Rahul Satija; James Nemesh; Karthik Shekhar; Melissa Goldman; Itay Tirosh; Allison R Bialas; Nolan Kamitaki; Emily M Martersteck; John J Trombetta; David A Weitz; Joshua R Sanes; Alex K Shalek; Aviv Regev; Steven A McCarroll

doi:10.1016/j.cell.2015.05.002

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

Cell. 2015 May 21;161(5):1202-1214. doi: 10.1016/j.cell.2015.05.002.

Authors

Evan Z Macosko¹, Anindita Basu², Rahul Satija³, James Nemesh⁴, Karthik Shekhar⁵, Melissa Goldman⁶, Itay Tirosh⁵, Allison R Bialas⁷, Nolan Kamitaki⁴, Emily M Martersteck⁸, John J Trombetta⁵, David A Weitz⁹, Joshua R Sanes⁸, Alex K Shalek¹⁰, Aviv Regev¹¹, Steven A McCarroll¹²

Affiliations

¹ Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA. Electronic address: emacosko@genetics.med.harvard.edu.
² Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
³ Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; New York Genome Center, New York, NY 10013, USA; Department of Biology, New York University, New York, NY 10003, USA.
⁴ Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
⁵ Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
⁶ Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
⁷ The Program in Cellular and Molecular Medicine, Children's Hospital Boston, Boston, MA 02115, USA.
⁸ Department of Molecular and Cellular Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
⁹ School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA; Department of Physics, Harvard University, Cambridge, MA 02138, USA.
¹⁰ Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA; Institute for Medical Engineering and Science and Department of Chemistry, MIT, Cambridge, MA 02139, USA.
¹¹ Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Department of Biology, MIT, Cambridge, MA 02139, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA.
¹² Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA. Electronic address: mccarroll@genetics.med.harvard.edu.

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.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Animals
Gene Expression Profiling / methods*
Genome-Wide Association Study*
High-Throughput Nucleotide Sequencing
Mice
Microfluidic Analytical Techniques*
Retina / cytology*
Sequence Analysis, RNA
Single-Cell Analysis*

Associated data

GEO/GSE63473

Abstract

Publication types

MeSH terms

Associated data

Grants and funding