Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution

Abstract

Spatial positions of cells in tissues strongly influence function, yet a high-throughput, genome-wide readout of gene expression with cellular resolution is lacking. We developed Slide-seq, a method for transferring RNA from tissue sections onto a surface covered in DNA-barcoded beads with known positions, allowing the locations of the RNA to be inferred by sequencing. Using Slide-seq, we localized cell types identified by single-cell RNA sequencing datasets within the cerebellum and hippocampus, characterized spatial gene expression patterns in the Purkinje layer of mouse cerebellum, and defined the temporal evolution of cell type-specific responses in a mouse model of traumatic brain injury. These studies highlight how Slide-seq provides a scalable method for obtaining spatially resolved gene expression data at resolutions comparable to the sizes of individual cells.

Figure 1:. High-resolution RNA capture from tissue by Slide-seq.

(A) Left: Schematic of array generation. A monolayer of randomly deposited, DNA barcoded beads (termed a “puck”) is spatially indexed by SOLiD sequencing. Top Right: A representative puck with sequenced barcodes shown in black. Bottom Right: A composite image of the same puck colored by the base calls for a single base of SOLiD sequencing. (B) Schematic of the sample preparation procedure developed for Slide-seq. (C) Top left: tSNE representation of Slide-seq beads from a coronal mouse hippocampus slice with colors indicating clusters. Right: the spatial position of each bead is shown, colored by the cluster assignments shown in the tSNE. Bottom left: Inset indicating the position of a single-cell-thickness ependymal cell layer (black arrow). (D) As in (C), but for the indicated tissue type (see Fig. S2 for clustering and cluster identities). All scale bars 500 μm.

Figure 2:. Localization of cell types in cerebellum and hippocampus using Slide-seq.

(A) Schematic for assigning cell types from scRNA-seq datasets to Slide-seq beads using NMF and NNLS regression (NMFreg). (B) Loadings of individual cell types, defined by scRNA-seq cerebellum (9) on each bead of one 3 mm-diameter coronal cerebellar puck (red, cell type location, gray, Purkinje loadings plotted as a counterstain). Other cell types are in Fig. S6. (C) Left: Number of cell types assigned per bead (Fig. S3). Right: The number of beads called as each scRNAseq-defined cell type for cerebellar pucks (mean ± std. N=7 pucks). (D) Projections of hippocampal volume with NMFreg cell type calls for CA1 (green), CA2/3 (blue) and dentate gyrus (Red). Top left: Sagittal projection. Top right: Coronal projection. Bottom left: Horizontal projection. Bottom right: axis orientations for each of the projections. (E) Composite image of metagenes for six different cell types. All scale bars 250 μm. All metagenes are listed in Table S2.

Figure 3:. Identification of novel variation in cerebellar gene expression by Slide-seq.

(A) Heatmap illustrating the separation of Purkinje-expressed genes into two clusters by spatial gene correlation. The i,jth entry is the number of genes found to overlap with both gene i and j in the Purkinje cluster (6). (B) For genes with significant expression (p<0.001, Fisher exact test) in the nodulus-uvula region (6), the fraction of reads localized to the nodulus/uvula and to the VI/VII boundary is shown. Pcp4, a ubiquitous marker for Purkinje cells, is in gray. (C) An Aldoc metagene in cyan. A Cck metagene in red. (D) A H2-D1 metagene in yellow. A Hspb1 metagene in blue. All scale bars show 250 μm. All metagenes are listed in Table S2.

Figure 4:. Slide-seq identifies local transcriptional responses to injury:

(A) Top: All mapped beads for a coronal hippocampal slice from a mouse sacrificed 2 hours after injury, with circle radius proportional to transcripts. Bottom: genes marking the injury. (B) As in (A), for a mouse sacrificed 3 days after injury. Top and middle right: DAPI image of an adjacent slice. Panels with black backgrounds show NMFreg cell types as density plots. Scale bar: 250 μm (6). (C) As in (B), for a mouse sacrificed 2 weeks following injury. Bottom scale bar: 500 μm. (D) Spatial density profiles for the puck in (B) (6). (E) Spatial density profiles for the puck in (C). Lyz2 is plotted as a marker of macrophages. The vertical axis in (D) and (E) represents cell-type density in arbitrary units (6). (F) The thickness of the features in (D) and (E) (mean ± std., N=6 for scar, N=6 for penetration, N=3 for mitosis layer). (G-J) Gene ontology-derived metagenes for the puck in (B) (top) or (C) (bottom). Warmer colors correspond to greater metagene counts. (K) The IEG metagene (Table S2) for two 2-week pucks. Circular images in (A-C) refer to the scale bar in (A). All scale bars for images with blue backgrounds 500 μm. Red arrows indicate the injury.