From whole-mount to single-cell spatial assessment of gene expression in 3D

Lisa N. Waylen, Hieu T. Nim, Luciano G. Martelotto, Mirana Ramialison

Research output: Contribution to journalReview ArticleResearchpeer-review

46 Citations (Scopus)


Unravelling spatio-temporal patterns of gene expression is crucial to understanding core biological principles from embryogenesis to disease. Here we review emerging technologies, providing automated, high-throughput, spatially resolved quantitative gene expression data. Novel techniques expand on current benchmark protocols, expediting their incorporation into ongoing research. These approaches digitally reconstruct patterns of embryonic expression in three dimensions, and have successfully identified novel domains of expression, cell types, and tissue features. Such technologies pave the way for unbiased and exhaustive recapitulation of gene expression levels in spatial and quantitative terms, promoting understanding of the molecular origin of developmental defects, and improving medical diagnostics.

Original languageEnglish
Article number602
Number of pages11
JournalCommunications Biology
Issue number1
Publication statusPublished - 23 Oct 2020


  • data acquisition
  • transcriptomics

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