(A) FACS-sorting scheme for the enrichment of astrocytes, qNSCs, aNSCs, and NPCs from the SVZs of adult mice, and microfluidic-based single cell RNA-seq library generation and sequencing. Checkered bar in the FACS-sorting scheme indicates that the presence of Prominin 1 was not selected for. Note that while Prominin 1 enriches for NSCs, the astrocyte population could contain some qNSCs and the qNSC population could contain some astrocytes ().
(B) Principal component analysis (PCA) on all 329 high-quality single cells.
(C) 3-dimensional PCA on all 288 cells excluding oligodendrocyte-like cells and seven outlying cells.

(A) Minimum spanning tree generated for all qNSCs, aNSCs, and NPCs ordered by Monocle using all detected genes.
(B) Expression of key genes associated with quiescence (Id3), activation (Egfr and Rpl32) and cell cycle (Cdk1 and Ccna2) (FPKM) in each cell plotted with respect to pseudotime produced by Monocle in Figure 2A. Cells are color-coded by their FACS-sorting identity.
(C) Histogram of Ki67 fluorescence values measured by intracellular FACS in purified populations of qNSCs, aNSCs, and NPCs. Histogram values normalized to mode.
(D) Percentage of Ki67-negative cells measured by intracellular FACS in purified populations of aNSCs and NPCs. Two-sided Wilcoxon signed-rank test. ** p≤0.005.
(E) Machine learning algorithm to obtain consensus-ordering genes. The list of consensus-ordering genes is in .
(F) Minimum spanning tree generated for all qNSCs, aNSCs, and NPCs ordered by Monocle using FPKM of the consensus-ordering genes ().
(G) Expression (FPKM) of key genes related to quiescence (Id3), activation (Egfr and Rpl32), cell cycle (Cdk4 and Cdk1), and neuronal differentiation (Dlx2, Dcx) (FPKM) in each cell is plotted with respect to pseudotime produced by Monocle when all qNSCs, aNSCs, and NPCs are ordered using the consensus-ordering genes. Cells are color-coded by their FACS-sorting identity (indicated on top). Bottom: name of the intermediary states (qNSC-like, aNSC-early, aNSC-mid, aNSC-late, and NPC-like).

(A) Diffusion map using the 2500 most variable genes in the dataset for all qNSCs, aNSCs, and NPCs. Cells are colored by the identity of the intermediate states defined in .
(B) PCA using the consensus-ordering genes () for all qNSCs, aNSCs, and NPCs. Cells are colored as in Figure 3A.
(C) Spanning tree produced by Monocle when all qNSCs, aNSCs, and NPCs are ordered using the consensus-ordering genes (). Black line represents pseudotime “track” through the single cell lineage. Cells are colored as in Figure 3A.
(D) Expression (FPKM) of genes relevant to the transition between the indicated stages in each cell, plotted with respect to pseudotime produced by Monocle when all qNSCs, aNSCs, and NPCs are ordered using the consensus-ordering genes (). Cells are colored as in Figure 3A.
(E–H) Gene-set enrichments for genes ranked by Z-score for differential expression between cells in intermediate states defined in Figure 3A. Enrichments expressed as [−log10(FDR)] and directionality and color indicate the intermediate state in which the gene set is enriched. Gene sets presented are those for which FDR<0.2.
(I) Expression (FPKM) of markers of astrocytes (Atp1a2, Gja1, Ntsr2) and neurogenesis (Dlx1, Dlx2) in each cell plotted as a function of pseudotime. GLAST (Slc1a3), a marker of astrocytes that was previously used in FACS sorting studies is presented as a comparison on top. Cells are colored as in Figure 3A.
(J) Markers of astrocytes (Atp1a2, Ntsr2, Gja1) and mediators of self-renewal (Jag1, Fgfr3) are correlated with each other and are anticorrelated with early markers of neuronal differentiation (Dlx1, Dlx2) in aNSC-mid and aNSC-late cells. Carpet plot showing correlation (Spearman’s rho) between individual genes in all aNSC-mid and aNSC-late cells.

(A) Predicted GFP fluorescence states of aNSCs from a GFP-high state in which the GFAP-GFP promoter is active to a GFP-low state in which the cells have committed to differentiation but retain some GFP, and finally to the NPC state which do not express GFP.
(B–E) (upper) Gene expression in single cells grouped by molecular subtype as defined in . Gene expression expressed as log2(FPKM+1). (lower) Gene expression measured by RT-qPCR in subpopulations of aNSCs divided by their level of GFAP-GFP expression (GFAP-GFP high aNSC, GFAP-GFP mid aNSC, GFAP-GFP low aNSC) and NPCs. P-value from one-sided Wilcoxon signed-rank test. * p≤0.05.
(F) Correlation between expression of key markers of NSCs and neurogenesis in aNSC populations divided by GFAP-GFP. Carpet plot showing correlation (Spearman’s rho) between individual genes in all aNSC-subpopulations divided by level of GFAP-GFP. Color of box indicates correlation (Spearman’s rho) between a given gene pair (scale on upper left).

(A) Preparation of single cell RNA-sequencing libraries from passage 3 neurospheres (NS) derived from FACS-sorted aNSCs.
(B) PCA with qNSCs, aNSCs, and NPCs using expression [log2(FPKM+1)] of the consensus-ordering genes from machine learning models (). NS single cells are projected onto the resulting principal component space. Cells are colored by identity defined in and NS single cells are black.
(C) Gene-set enrichments for genes ranked by Z-score for differential expression between single NS cells and in vivo aNSCs and NPCs. Enrichments expressed as [−log10(FDR)] and directionality and color indicate the intermediate state in which the gene set is enriched (FDR<0.2).
(D) Expression of genes associated with astrocyte identity, self-renewal, and neurogenesis in in vitro NS single cells and in vivo NSCs. Violin plots showing gene expression in the cellular states defined in as well as in NS single cells.
(E) Expression of genes associated with inflammatory signatures in single NS cells and in vivo NSCs. Data presented as in Figure 5D.

(A) Comparison of FACS sorting schemes implemented in our study and in the Llorens-Bobadilla study.
(B) PCA on all qNSCs, aNSCs, and NPCs from our study, using the expression [log2(FPKM+1)] of the 2500 most variable genes in these cells. All NSCs and TAPs from the Llorens-Bobadilla study are projected on to the resulting principal component space. Cells colored by FACS sorting identity indicated on the right.
(C–D) Regulators of activation and differentiation exhibit similar dynamics in NSCs and progeny isolated by divergent FACS sorting schemes. Expression (FPKM) of key markers of activation and differentiation in each cell plotted as a function of pseudotime generated by Monocle ordering using the consensus-ordering genes identified by machine learning () for (C) all qNSCs, aNSCs, and NPCs from our study and (D) NSCs and TAPs analyzed in Llorens-Bobadilla, et al. 2015. Cells colored by FACS-sorting identity, indicated on top.

(A) Schematic outlining the approaches for generating pseudotime expression heatmaps and for correlating gene rankings by average pseudotime of expression (APE, see ) for different single cell datasets.
(B) Heatmap representing the expression of all detected genes ranked by APE defined in our study. Expression plotted as a function of pseudotime. Left panel: expression from our study (qNSCs, aNSCs, and NPCs), pseudotime defined by Monocle ordering using consensus-ordering genes identified by machine learning (). Right panel: expression from the Llorens-Bobadilla study (NSCs and TAPs), pseudotime defined by Monocle ordering using consensus-ordering genes ().
(C) Heatmap representing expression of the 20 genes with highest values of APE (expressed most exclusively in NPCs) in our dataset. Left panel: expression from our study (qNSCs, aNSCs, and NPCs), pseudotime defined as in Figure 7B. Right panel: expression from the Llorens-Bobadilla study (NSCs and TAPs), pseudotime defined as in Figure 7B.
(D) Smooth scatter plot representing gene ranks by average pseudotime of expression (APE) in (x-axis) qNSCs, aNSCs, and NPCs from our study ordered by Monocle using the consensus-ordering genes identified by machine learning () and (y-axis) NSCs and TAPs from the Llorens-Bobadilla study ordered by Monocle using the consensus-ordering genes identified by machine learning () (Spearman’s rho = 0.63, p < 2.2e⁻¹⁶).
(E) Smooth scatter plot representing gene rankings by average pseudotime of expression (APE) in (x-axis) qNSCs, aNSCs, and NPCs from the current study ordered as in Figure 7D and (y-axis) differentiating myoblasts ordered by Monocle from () (Spearman’s rho = 0.17, p < 2.2e⁻¹⁶).
(F) Smooth scatter plot representing gene rankings by average pseudotime of expression (APE) in (x-axis) qNSCs, aNSCs, and NPCs from our study ordered as in Figure 7D and (y-axis) hippocampal NSCs ordered by Waterfall in the study by Shin and colleagues () (Spearman’s rho = 0.38, p < 2.2e⁻¹⁶).