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Science DOI:10.1126/science.aaw1219

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

Publication TypeJournal Article
Year of Publication2019
AuthorsRodriques, SG, Stickels, RR, Goeva, A, Martin, CA, Murray, E, Vanderburg, CR, Welch, J, Chen, LM, Chen, F, Macosko, EZ
Date Published2019 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.


Alternate JournalScience
PubMed ID30923225
Grant ListDP2 AG058488 / AG / NIA NIH HHS / United States
DP5 OD024583 / OD / NIH HHS / United States