Massively parallel single-nucleus RNA-seq with DroNc-seq
Author(s)
Avraham-Davidi, Inbal
Burks, Tyler
Shekhar, Karthik
Hofree, Matan
Aguet, François
Gelfand, Ellen
Ardlie, Kristin
Weitz, David A
Rozenblatt-Rosen, Orit
Zhang, Feng
Date Issued
August 2017
Journal
Nature Methods
Publisher
Nature Publishing Group
Citation
Habib, Naomi et al. “Massively Parallel Single-Nucleus RNA-Seq with DroNc-Seq.” Nature Methods 14, 10 (August 2017): 955–958 © 2017 Nature America
Version
Author's final manuscript
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. Keywords: Cellular neuroscience; Gene expression; Gene expression analysis; RNA sequencing
MIT Department
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
McGovern Institute for Brain Research at MIT
Koch Institute for Integrative Cancer Research at MIT
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1038/nmeth.4407
