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

Abstract

Gene expression at fine scale Mapping gene expression at the single-cell level within tissues remains a technical challenge. Rodriques et al. developed a method called Slide-seq, whereby RNA was spatially resolved from tissue sections by transfer onto a surface covered with DNA-barcoded beads. Applying Slide-seq to regions of a mouse brain revealed spatial gene expression patterns in the Purkinje layer of the cerebellum and axes of variation across Purkinje cell compartments. The authors used this method to dissect the temporal evolution of cell type–specific responses in a mouse model of traumatic brain injury. Science , this issue p. 1463

Keywords

Computational biologyGene expressionRNABiologyCerebellumRNA-SeqGeneGenomeCell typeScalabilityDNA sequencingCellTranscriptomeGeneticsComputer scienceNeuroscienceDatabase

MeSH Terms

AnimalsBrain InjuriesTraumaticCell SizeCerebellumDisease ModelsAnimalFrozen SectionsGene Expression RegulationGenome-Wide Association StudyHigh-Throughput Nucleotide SequencingHippocampusMicePurkinje CellsRNAMessengerSequence AnalysisRNASingle-Cell AnalysisTranscriptionGenetic

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Publication Info

Year: 2019
Type: article
Volume: 363
Issue: 6434
Pages: 1463-1467
Citations: 2285
Access: Closed

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APA Style

                            
                                
                                    Samuel G. Rodriques, 
                                
                                    Robert R. Stickels, 
                                
                                    Aleksandrina Goeva
                                
                                et al.
                            
                            (2019). 
                            Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. 
                            Science
                            , 363
                            (6434)
                            , 1463-1467.
                            https://doi.org/10.1126/science.aaw1219
                        

Identifiers

DOI: 10.1126/science.aaw1219
PMID: 30923225
PMCID: PMC6927209

Data Quality

Data completeness: 90%