Spatial Transcriptomics: Emerging Technologies in Tissue Gene Expression Profiling

28 April 2023, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Spatial transcriptomics technologies are providing new insights to study gene expression, allowing researchers to investigate the spatial organization of transcriptomes in cells and tissues. This approach enables the creation of high-resolution maps of gene expression patterns within their native spatial context, adding an extra layer of information to bulk sequencing data. Spatial transcriptomics has expanded significantly in recent years and is making a notable impact on a range of fields, including tissue architecture, developmental biology, cancer, neurodegenerative and infectious diseases. The latest advancements in spatial transcriptomics have resulted in the development of highly multiplexed methods, transcriptomic-wide analysis, and single-cell resolution, utilizing diverse technological approaches. In this perspective, we provide a detailed analysis of the molecular foundations behind the main spatial transcriptomics technologies, including methods based on microdissection, in situ sequencing, single-molecule FISH, spatial capturing, selection of regions of interest and single-cell or nuclei dissociation. We contextualize the detection and capturing efficiency, strengths, limitations, tissue compatibility, and applications of these techniques, as well as provide information on data analysis. In addition, this perspective discusses future directions and potential applications of spatial transcriptomics, highlighting the importance of the continued development to promote widespread adoption of these techniques within the research community.

Keywords

Spatial Transcriptomics
RNA imaging
In Situ Sequencing
single-molecule FISH
RNA-sequencing

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