Single nucleus RNA-Seq (sNuc-Seq) profiles RNA from tissues that are preserved or cannot be dissociated, but does not provide the throughput required to analyse many cells from complex tissues. Here, Researchers from the Broad Institute of MIT and Harvard develop DroNc-Seq, massively parallel sNuc-Seq with droplet technology. They profile 29,543 nuclei from mouse and human archived brain samples to demonstrate sensitive, efficient and unbiased classification of cell types, paving the way for charting systematic cell atlases.
DroNc-Seq: Massively parallel single nucleus RNA-Seq
(a) Overview of DroNc-Seq. Quality measures. (b) Distribution of number of genes detected (X axis) in DroNc-Seq of nuclei isolated from 3T3 mouse cells line, mouse frozen brain tissue, and human frozen archived brain tissue (Methods). (c) Distribution of number of genes detected per 3T3 cell (by Drop-Seq) or nucleus (by DroNc-Seq). (d) The percent of reads (Y axis) mapped to the: genome, exons, introns, intergenic regions and rRNA loci (X axis) of the mouse genome, for cells and nuclei. (e) Scatter plot comparing the average expression levels detected in single 3T3 nuclei (Y-axis, by DroNc-seq) and cells (X-axis, by Drop-Seq). Red dots mark outlier genes highly expressed in one but not the other experiment. (f) A 2 dimensional t-stochastic neighbourhood embedding (tSNE) plot of 5,592 DroNc-Seq nuclei profiles from adult frozen mouse hippocampus (hip) (3 samples) and prefrontal cortex (PFC) (2 samples, each with >20,000 reads per nucleus), colored by clustering and labelled post hoc by cell types and anatomical distinctions