High-definition spatial transcriptomics for in situ tissue profiling(Dataset ID: STDS0000064)

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Genes: 17,296
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PMID: 31501547
Summary
Visualization
Data
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Dataset information
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How to cite
Dataset information
Summary:
Tissue function relies on the precise spatial organization of cells characterized by distinct molecular profiles. Single-cell RNA-Seq captures molecular profiles but not spatial organization. Conversely, spatial profiling assays to date have lacked global transcriptome information, throughput or single-cell resolution. Here, we develop High-Density Spatial Transcriptomics (HDST), a method for RNA-Seq at high spatial resolution. Spatially barcoded reverse transcription oligonucleotides are coupled to beads that are randomly deposited into tightly packed individual microsized wells on a slide. The position of each bead is decoded with sequential hybridization using complementary oligonucleotides providing a unique bead-specific spatial address. We then capture, and spatially in situ barcode, RNA from the histological tissue sections placed on the HDST array. HDST recovers hundreds of thousands of transcript-coupled spatial barcodes per experiment at 2 μm resolution. We demonstrate HDST in the mouse brain, use it to resolve spatial expression patterns and cell types, and show how to combine it with histological stains to relate expression patterns to tissue architecture and anatomy. HDST opens the way to spatial analysis of tissues at high resolution.
Overall design:
Three sections of the main olfactory bulb from adult C57BL/6J mice
Technology:
HDST
Platform:
Illumina NextSeq 500
Species:
Mus musculus
Tissues:
Brain
Development stage:
12 weeks
Submission date: 2019-05-03Update date: 2019-09-20
Sample number: 3
DOI: To be continue
Contributors
Sanja Vickovic,Ludvig Bergenstråhle
Contact: vickovic@broadinstitute.org
Accessions
GEO Series Accessions: GSE130682
How to cite
  • Cite database of STOmicsDB:
    [1] Xu, Zhicheng et al. "STOmicsDB: a comprehensive database for spatial transcriptomics data sharing, analysis and visualization." Nucleic acids research vol. 52,D1 (2024): D1053-D1061. doi: 10.1093/nar/gkad933'
  • Cite visualization dataset:
    [2] Sanja Vickovic,Ludvig Bergenstråhle. High-definition spatial transcriptomics for in situ tissue profiling[DS/OL]. STOmicsDB, 2019[2019-05-03]. https://db.cngb.org/stomics/datasets/STDS0000064/. doi: xxxxxx
    #Format: {contributors}. {title}[DS/OL]. STOmicsDB, {the year of submission data}[{submission data}]. {dataset link}. doi: {doi ID}
  • Cite original data article:
    Citation: Vickovic, Sanja et al. “High-definition spatial transcriptomics for in situ tissue profiling.” Nature methods vol. 16,10 (2019): 987-990. doi:10.1038/s41592-019-0548-y