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Mapping Gene Expression in the Spatial Dimension

Yingwen Chen, Weizhou Qian, Li Lin, Linfeng Cai, Kun Yin, Shaowei Jiang, Jia Song, Ray P. S. Han, Chaoyong Yang

2021Small Methods17 citationsDOI

Abstract

The main function and biological processes of tissues are determined by the combination of gene expression and spatial organization of their cells. RNA sequencing technologies have primarily interrogated gene expression without preserving the native spatial context of cells. However, the emergence of various spatially-resolved transcriptome analysis methods now makes it possible to map the gene expression to specific coordinates within tissues, enabling transcriptional heterogeneity between different regions, and for the localization of specific transcripts and novel spatial markers to be revealed. Hence, spatially-resolved transcriptome analysis technologies have broad utility in research into human disease and developmental biology. Here, recent advances in spatially-resolved transcriptome analysis methods are summarized, including experimental technologies and computational methods. Strengths, challenges, and potential applications of those methods are highlighted, and perspectives in this field are provided.

Topics & Concepts

TranscriptomeComputational biologyBiologyContext (archaeology)Gene expressionSpatial contextual awarenessGeneRNA-SeqFunction (biology)Expression (computer science)Regulation of gene expressionDimension (graph theory)GeneticsComputer scienceArtificial intelligenceMathematicsProgramming languagePure mathematicsPaleontologySingle-cell and spatial transcriptomicsCell Image Analysis TechniquesGene expression and cancer classification
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