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Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.
Macosko, Evan Z; Basu, Anindita; 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; Shalek, Alex K; Regev, Aviv; McCarroll, Steven A.
Afiliação
  • Macosko EZ; 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:
  • Basu A; 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.
  • Satija R; 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.
  • Nemesh J; 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.
  • Shekhar K; Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
  • Goldman M; 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.
  • Tirosh I; Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
  • Bialas AR; The Program in Cellular and Molecular Medicine, Children's Hospital Boston, Boston, MA 02115, USA.
  • Kamitaki N; 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.
  • Martersteck EM; Department of Molecular and Cellular Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
  • Trombetta JJ; Klarman Cell Observatory, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
  • Weitz DA; School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA; Department of Physics, Harvard University, Cambridge, MA 02138, USA.
  • Sanes JR; Department of Molecular and Cellular Biology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA.
  • Shalek AK; 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.
  • Regev A; 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.
  • McCarroll SA; 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:
Cell ; 161(5): 1202-1214, 2015 May 21.
Article em En | MEDLINE | ID: mdl-26000488
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Retina / Perfilação da Expressão Gênica / Técnicas Analíticas Microfluídicas / Estudo de Associação Genômica Ampla / Análise de Célula Única Limite: Animals Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Retina / Perfilação da Expressão Gênica / Técnicas Analíticas Microfluídicas / Estudo de Associação Genômica Ampla / Análise de Célula Única Limite: Animals Idioma: En Ano de publicação: 2015 Tipo de documento: Article