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

Science. 2019 Mar 29;363(6434):1463-1467. doi: 10.1126/science.aaw1219. Epub 2019 Mar 28.


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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

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


  • RNA, Messenger