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

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

Naomi Habib  1   2   3 , Inbal Avraham-Davidi  1 , Anindita Basu  1   4 , Tyler Burks  1 , Karthik Shekhar  1 , Matan Hofree  1 , Sourav R Choudhury  2   3 , François Aguet  2 , Ellen Gelfand  2 , Kristin Ardlie  2 , David A Weitz  4   5 , Orit Rozenblatt-Rosen  1 , Feng Zhang  2   3 , Aviv Regev  1   6
Affiliations

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

Naomi Habib et al. Nat Methods. 2017 Oct.

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.

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Conflict of interest statement

Competing Financial Interests Statement

N.H., A.B., I.A.D., D.A.W., F.Z. and A.R. are co-inventors on international patent application PCT/US16/59239 of Broad Institute, Harvard and MIT, relating to inventions of methods of this manuscript.

Figures

Figure 1
Figure 1. DroNc-seq: Massively parallel single nucleus RNA-Seq
(a) Overview. (b) DroNc-seq of adult frozen mouse hippocampus and prefrontal cortex. A two-dimensional tSNE plot of 13,133 DroNc-seq nuclei profiles (>10,000 reads and >200 genes per nucleus) from hippocampus (hip; 4 samples) and prefrontal cortex (PFC; 4 samples). Nuclei (dots) are colored by cluster membership and labelled post hoc by cell types and anatomical distinctions (exPFC=glutamatergic neurons from the PFC, exCA1/3=pyramidal neurons from the Hip CA region, GABA=GABAergic interneurons, exDG=granule neurons from the Hip dentate gyrus region, ASC=astrocytes, NSC=neuronal stem cells, MG=microglia, ODC=oligodendrocytes, OPC=oligodendrocyte precursor cells, NSC=neuronal stem cells, SMC=smooth muscle cells, END= endothelial cells). Clusters are grouped by cell types as in Supplementary Fig. 3a. Flagged clusters (Supplementary Fig. 3b and Supplementary Table 3, Methods) were removed. (c) Fraction of nuclei from each brain region associated with each cell type. Cell types are defined as in Supplementary Fig. 3a and sorted from left by types enriched in PFC vs. Hip. (d) Cell type signatures. The average expression of differentially expressed signature genes (rows, Methods) in each DroNc-seq mouse brain cell subset (columns). (e) DroNc-seq cell-type expression signatures in the mouse brain agree with previous studies. Pairwise correlations of the average expression (Methods) for the genes in each cell-type signature defined by DroNc-seq and in cell-types defined by sNuc-Seq in the mouse hippocampus (left) and scRNA-seq in the visual cortex (right). (f) Sub-sets of mouse GABAergic neurons. tSNE embedding of 816 DroNc-seq nuclei profiles from the GABAergic neurons cluster (Clusters 10–11 in Fig. 1b; inset, blue), color coded by sub-cluster membership. (g,h) Congruence of GABAergic neurons sub-clusters defined here (from j) with subsets defined from nuclei profiles in the mouse hippocampus (g) and single cell profiles in the mouse visual cortex (h). Dot plot shows the proportion of cells in each cluster defined by the other two datasets that were classified to each DroNc-seq cluster using a multi-class random forest classifier (as in, Methods) trained on the DroNc-seq sub-clusters.
Figure 2
Figure 2. DroNc-seq distinguishes cell types and signatures in adult post-mortem human brain tissue
(a) Cell-type clusters. tSNE embedding of 14,963 DroNc-seq nuclei profiles (each with >10,000 reads and >200 genes) from adult frozen human hippocampus (Hip, 4 samples) and prefrontal cortex (PFC, 3 samples) from five donors. Nuclei are color-coded by cluster membership and clusters are labeled post-hoc (abbreviations as in Fig. 1b). (b) Marker genes. Shown is the same plot as in (a) but with nuclei colored by the expression level of known cell-type marker genes. (SLC17A7 – excitatory neurons, GAD1 – GABAergic neurons, PPFIA2 – exDG, SLC1A2 – ASC, MBP – ODC, PDGFRA – OPC). (c) Fraction of nuclei from each brain region associated with each cell type. Cell types are defined as in Supplementary Fig. 7a and sorted from left by types enriched in PFC vs. Hip. (d) Cell type expression signatures. The average expression of differentially expressed signature genes (Methods, rows) in each DroNc-seq human brain cell subset (columns; defined as in Supplementary Fig. 7a). (e) DroNc-seq cell-type expression signatures in the human brain agree with previous mouse datasets. Pairwise correlations of the average expression (Methods) for the genes in each cell-type signature defined by DroNc-seq (rows) and cell-types defined by sNuc-Seq in the mouse hippocampus (left, columns) and scRNA-seq in the visual cortex (right, columns). (f–i) GABAergic neurons sub-clusters. (f) tSNE embedding of 1,500 DroNc-seq nuclei profiles from the GABAergic neurons cluster (clusters 5–6 in Fig. 2a; inset), color coded by sub-cluster membership. (g) Average expression of canonical GABAergic marker genes (rows) in each of the nuclei sub-clusters (columns) defined in (f). (h,i) Mapping of human GABAergic neurons sub-cluster defined here (columns, from f) to subsets defined from nuclei profiles in the mouse hippocampus (h) and single cell profiles in the mouse visual cortex (i) (rows). Dot plot shows the proportion of cells in each cluster defined by the other two datasets that were classified to each DroNc-seq cluster (as in Fig. 1k,l, Methods).
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