|Publication Type||Journal Article|
|Year of Publication||2019|
|Authors||Rodriques, SG, Stickels, RR, Goeva, A, Martin, CA, Murray, E, Vanderburg, CR, Welch, J, Chen, LM, Chen, F, Macosko, EZ|
|Date Published||2019 03 29|
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.
|Grant List||DP2 AG058488 / AG / NIA NIH HHS / United States |
DP5 OD024583 / OD / NIH HHS / United States