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
Author Information
Evan Z Macosko: 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.
Anindita Basu: 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.
Rahul Satija: 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.
James Nemesh: 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.
Karthik Shekhar: Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
Melissa Goldman: 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.
Itay Tirosh: Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
Allison R Bialas: The Program in Cellular and Molecular Medicine, Children's Hospital Boston, Boston, MA 02115, USA.
Nolan Kamitaki: 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.
Emily M Martersteck: Department of Molecular and Cellular Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
John J Trombetta: Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
David A Weitz: School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA; Department of Physics, Harvard University, Cambridge, MA 02138, USA.
Joshua R Sanes: Department of Molecular and Cellular Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
Alex K Shalek: 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.
Aviv Regev: 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.
Steven A McCarroll: 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.
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.
