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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
JournalScience
Volume363
Issue6434
Pages1463-1467
Date Published2019 03 29
ISSN1095-9203
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.

DOI10.1126/science.aaw1219
Pubmed

http://www.ncbi.nlm.nih.gov/pubmed/30923225?dopt=Abstract

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