采用DroNc-seq技术的大规模平行单核RNA测序

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

作者信息

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

机构信息

Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

出版信息

Nat Methods. 2017 Oct;14(10):955-958. doi: 10.1038/nmeth.4407. Epub 2017 Aug 28.

DOI:10.1038/nmeth.4407

PMID:28846088

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5623139/

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.

摘要

单核RNA测序（sNuc-seq）可对保存的或无法解离的组织中的RNA进行分析，但通量不高。在此，我们开发了DroNc-seq：一种采用微滴技术的大规模平行单核RNA测序方法。我们对来自小鼠和人类存档脑样本的39111个细胞核进行了分析，以展示对细胞类型的灵敏、高效且无偏差的分类，为细胞图谱的系统绘制铺平了道路。