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Spatial Transcriptomic Technologies
Spatial transcriptomic technologies enable measurement of expression levels of genes systematically throughout tissue space, deepening our understanding of cellular organizations and interactions within tissues as well as illuminating biological insights in neuroscience, developmental biology and a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10453065/ https://www.ncbi.nlm.nih.gov/pubmed/37626852 http://dx.doi.org/10.3390/cells12162042 |
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author | Chen, Tsai-Ying You, Li Hardillo, Jose Angelito U. Chien, Miao-Ping |
author_facet | Chen, Tsai-Ying You, Li Hardillo, Jose Angelito U. Chien, Miao-Ping |
author_sort | Chen, Tsai-Ying |
collection | PubMed |
description | Spatial transcriptomic technologies enable measurement of expression levels of genes systematically throughout tissue space, deepening our understanding of cellular organizations and interactions within tissues as well as illuminating biological insights in neuroscience, developmental biology and a range of diseases, including cancer. A variety of spatial technologies have been developed and/or commercialized, differing in spatial resolution, sensitivity, multiplexing capability, throughput and coverage. In this paper, we review key enabling spatial transcriptomic technologies and their applications as well as the perspective of the techniques and new emerging technologies that are developed to address current limitations of spatial methodologies. In addition, we describe how spatial transcriptomics data can be integrated with other omics modalities, complementing other methods in deciphering cellar interactions and phenotypes within tissues as well as providing novel insight into tissue organization. |
format | Online Article Text |
id | pubmed-10453065 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104530652023-08-26 Spatial Transcriptomic Technologies Chen, Tsai-Ying You, Li Hardillo, Jose Angelito U. Chien, Miao-Ping Cells Review Spatial transcriptomic technologies enable measurement of expression levels of genes systematically throughout tissue space, deepening our understanding of cellular organizations and interactions within tissues as well as illuminating biological insights in neuroscience, developmental biology and a range of diseases, including cancer. A variety of spatial technologies have been developed and/or commercialized, differing in spatial resolution, sensitivity, multiplexing capability, throughput and coverage. In this paper, we review key enabling spatial transcriptomic technologies and their applications as well as the perspective of the techniques and new emerging technologies that are developed to address current limitations of spatial methodologies. In addition, we describe how spatial transcriptomics data can be integrated with other omics modalities, complementing other methods in deciphering cellar interactions and phenotypes within tissues as well as providing novel insight into tissue organization. MDPI 2023-08-10 /pmc/articles/PMC10453065/ /pubmed/37626852 http://dx.doi.org/10.3390/cells12162042 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Chen, Tsai-Ying You, Li Hardillo, Jose Angelito U. Chien, Miao-Ping Spatial Transcriptomic Technologies |
title | Spatial Transcriptomic Technologies |
title_full | Spatial Transcriptomic Technologies |
title_fullStr | Spatial Transcriptomic Technologies |
title_full_unstemmed | Spatial Transcriptomic Technologies |
title_short | Spatial Transcriptomic Technologies |
title_sort | spatial transcriptomic technologies |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10453065/ https://www.ncbi.nlm.nih.gov/pubmed/37626852 http://dx.doi.org/10.3390/cells12162042 |
work_keys_str_mv | AT chentsaiying spatialtranscriptomictechnologies AT youli spatialtranscriptomictechnologies AT hardillojoseangelitou spatialtranscriptomictechnologies AT chienmiaoping spatialtranscriptomictechnologies |