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Spatial transcriptomics in neuroscience
The brain is one of the most complex living tissue types and is composed of an exceptional diversity of cell types displaying unique functional connectivity. Single-cell RNA sequencing (scRNA-seq) can be used to efficiently map the molecular identities of the various cell types in the brain by provi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10618223/ https://www.ncbi.nlm.nih.gov/pubmed/37779145 http://dx.doi.org/10.1038/s12276-023-01093-y |
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author | Jung, Namyoung Kim, Tae-Kyung |
author_facet | Jung, Namyoung Kim, Tae-Kyung |
author_sort | Jung, Namyoung |
collection | PubMed |
description | The brain is one of the most complex living tissue types and is composed of an exceptional diversity of cell types displaying unique functional connectivity. Single-cell RNA sequencing (scRNA-seq) can be used to efficiently map the molecular identities of the various cell types in the brain by providing the transcriptomic profiles of individual cells isolated from the tissue. However, the lack of spatial context in scRNA-seq prevents a comprehensive understanding of how different configurations of cell types give rise to specific functions in individual brain regions and how each distinct cell is connected to form a functional unit. To understand how the various cell types contribute to specific brain functions, it is crucial to correlate the identities of individual cells obtained through scRNA-seq with their spatial information in intact tissue. Spatial transcriptomics (ST) can resolve the complex spatial organization of cell types in the brain and their connectivity. Various ST tools developed during the past decade based on imaging and sequencing technology have permitted the creation of functional atlases of the brain and have pulled the properties of neural circuits into ever-sharper focus. In this review, we present a summary of several ST tools and their applications in neuroscience and discuss the unprecedented insights these tools have made possible. |
format | Online Article Text |
id | pubmed-10618223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106182232023-11-02 Spatial transcriptomics in neuroscience Jung, Namyoung Kim, Tae-Kyung Exp Mol Med Review Article The brain is one of the most complex living tissue types and is composed of an exceptional diversity of cell types displaying unique functional connectivity. Single-cell RNA sequencing (scRNA-seq) can be used to efficiently map the molecular identities of the various cell types in the brain by providing the transcriptomic profiles of individual cells isolated from the tissue. However, the lack of spatial context in scRNA-seq prevents a comprehensive understanding of how different configurations of cell types give rise to specific functions in individual brain regions and how each distinct cell is connected to form a functional unit. To understand how the various cell types contribute to specific brain functions, it is crucial to correlate the identities of individual cells obtained through scRNA-seq with their spatial information in intact tissue. Spatial transcriptomics (ST) can resolve the complex spatial organization of cell types in the brain and their connectivity. Various ST tools developed during the past decade based on imaging and sequencing technology have permitted the creation of functional atlases of the brain and have pulled the properties of neural circuits into ever-sharper focus. In this review, we present a summary of several ST tools and their applications in neuroscience and discuss the unprecedented insights these tools have made possible. Nature Publishing Group UK 2023-10-02 /pmc/articles/PMC10618223/ /pubmed/37779145 http://dx.doi.org/10.1038/s12276-023-01093-y Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Review Article Jung, Namyoung Kim, Tae-Kyung Spatial transcriptomics in neuroscience |
title | Spatial transcriptomics in neuroscience |
title_full | Spatial transcriptomics in neuroscience |
title_fullStr | Spatial transcriptomics in neuroscience |
title_full_unstemmed | Spatial transcriptomics in neuroscience |
title_short | Spatial transcriptomics in neuroscience |
title_sort | spatial transcriptomics in neuroscience |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10618223/ https://www.ncbi.nlm.nih.gov/pubmed/37779145 http://dx.doi.org/10.1038/s12276-023-01093-y |
work_keys_str_mv | AT jungnamyoung spatialtranscriptomicsinneuroscience AT kimtaekyung spatialtranscriptomicsinneuroscience |