Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution.
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IF: 63.714
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Cited by: 1,179
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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.

Keywords

Spatial Gene Expression
Slide-seq

MeSH terms

Animals
Brain Injuries, Traumatic
Cell Size
Cerebellum
Disease Models, Animal
Frozen Sections
Gene Expression Regulation
Genome-Wide Association Study
High-Throughput Nucleotide Sequencing
Hippocampus
Mice
Purkinje Cells
RNA, Messenger
Sequence Analysis, RNA
Single-Cell Analysis
Transcription, Genetic

Authors

Rodriques, Samuel G
Stickels, Robert R
Goeva, Aleksandrina
Martin, Carly A
Murray, Evan
Vanderburg, Charles R
Welch, Joshua
Chen, Linlin M
Chen, Fei
Macosko, Evan Z

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