Spatial genomic analysis: A multiplexed transcriptional profiling method that reveals subpopulations of cells within intact tissues

Antti Lignell, Laura Kerosuo

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review


Here, we present Spatial Genomic Analysis (SGA), a quantitative single-cell transcriptional profiling method that takes advantage of single-molecule imaging of individual transcripts for up to a hundred genes. SGA relies on a machine learning-based image analysis pipeline that performs cell segmentation and transcript counting in a robust way. SGA is suitable for various in situ applications and was originally developed to address heterogeneity in the neural crest, which is a transient embryonic stem cell population important for formation of various vertebrate body structures. After being specified as multipotent neural crest stem cells in the dorsal neural tube, they go through an epithelial to mesenchymal transition in order to migrate to different destinations around the body, and gradually turn from stem cells to progenitors prior to final commitment. The molecular details of this process remain largely unknown, and upon their emergence, the neural crest cells have been considered as a single homogeneous population. Technical limitations have restricted the possibility to parse the neural crest cell pool into subgroups according to multiplex gene expression properties. By using SGA, we were able to identify subgroups inside the neural crest niche in the dorsal neural tube. The high sensitivity of the method allows detection of low expression levels and we were able to determine factors not previously shown to be present in neural crest stem cells, such as pluripotency or lineage markers. Finally, SGA analysis also provides prediction of gene relationships within individual cells, and thus has broad utility for powerful transcriptome analyses in original biological contexts. © 2018, Springer Science+Business Media New York.
Original languageEnglish
Title of host publicationStem Cell Niche
EditorsKursad Turksen
Number of pages13
PublisherHumana press
Publication date2019
ISBN (Print)978-1-4939-9507-3
ISBN (Electronic)978-1-4939-9508-0
Publication statusPublished - 2019
MoE publication typeA3 Book chapter

Publication series

NameMethods in Molecular Biology
ISSN (Electronic)1064-3745

Fields of Science

  • Chicken embryo
  • HCR
  • Hybridization chain reaction
  • In vivo single-cell analysis
  • Neural crest stem cell niche
  • Neural crest stem cells
  • Pluripotency
  • Quantitative single-molecule fluorescent in situ hybridization
  • SGA
  • Single-molecule microscopy
  • smFISH
  • Spatial genomic analysis
  • Spatial genomics
  • Spatial tissue transcriptome analysis
  • RNA
  • transcriptome
  • animal cell
  • cell membrane
  • cell subpopulation
  • cell volume
  • DNA probe
  • embryo
  • embryonic stem cell
  • epithelial mesenchymal transition
  • gene expression profiling
  • genomics
  • image analysis
  • image processing
  • machine learning
  • neural crest
  • neural crest cell
  • neural tube
  • nonhuman
  • quantitative analysis
  • RNA degradation
  • single molecule imaging
  • spatial analysis
  • stem cell niche
  • 1182 Biochemistry, cell and molecular biology

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