Massively parallel single-nucleus RNA-seq with DroNc-seq

Naomi Habib, Inbal Avraham-Davidi, Anindita Basu, Tyler Burks, Karthik Shekhar, Matan Hofree, Sourav R. Choudhury, François Aguet, Ellen Gelfand, Kristin Ardlie, David A. Weitz, Orit Rozenblatt-Rosen, Feng Zhang, Aviv Regev*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

608 Scopus citations

Abstract

Single-nucleus RNA sequencing (sNuc-seq) profiles RNA from tissues that are preserved or cannot be dissociated, but it does not provide high throughput. Here, we develop DroNc-seq: massively parallel sNuc-seq with droplet technology. We profile 39,111 nuclei from mouse and human archived brain samples to demonstrate sensitive, efficient, and unbiased classification of cell types, paving the way for systematic charting of cell atlases.

Original languageAmerican English
Pages (from-to)955-958
Number of pages4
JournalNature Methods
Volume14
Issue number10
DOIs
StatePublished - 1 Oct 2017
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2017 Nature America, Inc., part of Springer Nature. All rights reserved.

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