Advertisement

In Situ Sequencing: A High-Throughput, Multi-Targeted Gene Expression Profiling Technique for Cell Typing in Tissue Sections

Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 2148)

Abstract

Recent advances of image-based in situ mRNA quantification methods allow to visualize where in a tissue section a set of genes is expressed. It enables to map large numbers of genes in parallel and by capturing cellular boundaries allows to assign genes to cells. Here, we present a high-throughput, multi-targeted gene expression profiling technique called in situ sequencing that is capable of localizing hundreds of genes simultaneously and supports cell type classifications that follow transcriptome-based taxonomy. In situ sequencing is a targeted, amplified, and barcoded approach using padlock probes (PLPs) and rolling circle amplification (RCA). The current protocol relies on mRNA fixation, mRNA reverse transcription, residual mRNA degradation, and PLP hybridization. PLPs are amplified by RCA and labeled with fluorophore-conjugated probes, allowing their detection under conventional fluorescence microscopes.

Key words

In situ sequencing Rolling circle amplification Single-cell Padlock probe Single-molecule Spatial transcriptomics 

References

  1. 1.
    Lein E, Borm LE, Linnarsson S (2017) The promise of spatial transcriptomics for neuroscience in the era of molecular cell typing. Science 358:64–69CrossRefGoogle Scholar
  2. 2.
    Strell C, Hilscher MM, Laxman N et al (2019) Placing RNA in context and space - methods for spatially resolved transcriptomics. FEBS J 286:1468–1481CrossRefGoogle Scholar
  3. 3.
    Ke R, Mignardi M, Pacureanu A et al (2013) In situ sequencing for RNA analysis in preserved tissue and cells. Nat Methods 10:857–860CrossRefGoogle Scholar
  4. 4.
    Nilsson M, Malmgren H, Samiotaki M et al (1994) Padlock probes: circularizing oligonucleotides for localized DNA detection. Science 265:2085–2088CrossRefGoogle Scholar
  5. 5.
    Nilsson M, Banér J, Mendel-Hartvig M et al (2002) Making ends meet in genetic analysis using padlock probes. Hum Mutat 19:410–415CrossRefGoogle Scholar
  6. 6.
    Fire A, Xu SQ (1995) Rolling replication of short DNA circles. Proc Natl Acad Sci U S A 92:4641–4645CrossRefGoogle Scholar
  7. 7.
    Krzywkowski T, Nilsson M (2018) Padlock probes to detect single nucleotide polymorphisms. Methods Mol Biol (Clifton, NJ) 1649:209–229CrossRefGoogle Scholar
  8. 8.
    Krzywkowski T, Hauling T, Nilsson M (2017) In situ single-molecule RNA genotyping using padlock probes and rolling circle amplification. Methods Mol Biol (Clifton, NJ) 1492:59–76CrossRefGoogle Scholar
  9. 9.
    Zeisel A, Muñoz-Manchado AB, Codeluppi S et al (2015) Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347:1138–1142CrossRefGoogle Scholar
  10. 10.
    Tasic B, Menon V, Nguyen TN et al (2016) Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat Neurosci 19:335–346CrossRefGoogle Scholar
  11. 11.
    Zeisel A, Hochgerner H, Lönnerberg P et al (2018) Molecular architecture of the mouse nervous system. Cell 174:999–1014.e22CrossRefGoogle Scholar
  12. 12.
    Tasic B, Yao Z, Graybuck LT et al (2018) Shared and distinct transcriptomic cell types across neocortical areas. Nature 563:72CrossRefGoogle Scholar
  13. 13.
    Harris KD, Hochgerner H, Skene NG et al (2018) Classes and continua of hippocampal CA1 inhibitory neurons revealed by single-cell transcriptomics. PLoS Biol 16:e2006387CrossRefGoogle Scholar
  14. 14.
    Yuste R, Hawrylycz M, Aalling N et al (2019) A community-based transcriptomics classification and nomenclature of neocortical cell types. arXiv preprint arXiv:1909:03083Google Scholar
  15. 15.
    Qian X, Harris KD, Hauling T et al (2019) A spatial atlas of inhibitory cell types in mouse hippocampus. Nat Methods. 2019 Nov 18.  https://doi.org/10.1038/s41592-019-0631-4
  16. 16.
    Tiklová K, Björklund ÅK, Lahti L et al (2019) Single-cell RNA sequencing reveals midbrain dopamine neuron diversity emerging during mouse brain development. Nat Commun 10:581CrossRefGoogle Scholar
  17. 17.
    Soldatov R, Kaucka M, Kastriti ME et al (2019) Spatiotemporal structure of cell fate decisions in murine neural crest. Science 364:eaas9536CrossRefGoogle Scholar
  18. 18.
    Gyllborg D, Mattsson Langseth C, Qian X et al (2019) Hybridization-based In Situ Sequencing (HybISS): spatial transcriptomic detection in human and mouse brain tissue. bioRxiv preprint  https://doi.org/10.1101/2020.02.03.931618
  19. 19.
    Carpenter AE, Jones TR, Lamprecht MR et al (2006) CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol 7:R100CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  1. 1.Molecular Diagnostics, Science for Life Laboratory, Department of Biochemistry and BiophysicsStockholm UniversitySolnaSweden
  2. 2.In situ sequencing facility, Science for Life Laboratory, Department of Biochemistry and BiophysicsStockholm UniversitySolnaSweden

Personalised recommendations