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 |
Journal | Science |
Volume | 363 |
Issue | 6434 |
Pages | 1463-1467 |
Date Published | 2019 03 29 |
ISSN | 1095-9203 |
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. |
DOI | 10.1126/science.aaw1219 |
Pubmed | |
Alternate Journal | Science |
PubMed ID | 30923225 |
Grant List | DP2 AG058488 / AG / NIA NIH HHS / United States DP5 OD024583 / OD / NIH HHS / United States |
Science DOI:10.1126/science.aaw1219
Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution.
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