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Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease
In the past decade, single-cell technologies have proliferated and improved from their technically challenging beginnings to become common laboratory methods capable of determining the expression of thousands of genes in thousands of cells simultaneously. The field has progressed by taking the CNS a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10191412/ https://www.ncbi.nlm.nih.gov/pubmed/37198436 http://dx.doi.org/10.1038/s41582-023-00809-y |
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author | Piwecka, Monika Rajewsky, Nikolaus Rybak-Wolf, Agnieszka |
author_facet | Piwecka, Monika Rajewsky, Nikolaus Rybak-Wolf, Agnieszka |
author_sort | Piwecka, Monika |
collection | PubMed |
description | In the past decade, single-cell technologies have proliferated and improved from their technically challenging beginnings to become common laboratory methods capable of determining the expression of thousands of genes in thousands of cells simultaneously. The field has progressed by taking the CNS as a primary research subject — the cellular complexity and multiplicity of neuronal cell types provide fertile ground for the increasing power of single-cell methods. Current single-cell RNA sequencing methods can quantify gene expression with sufficient accuracy to finely resolve even subtle differences between cell types and states, thus providing a great tool for studying the molecular and cellular repertoire of the CNS and its disorders. However, single-cell RNA sequencing requires the dissociation of tissue samples, which means that the interrelationships between cells are lost. Spatial transcriptomic methods bypass tissue dissociation and retain this spatial information, thereby allowing gene expression to be assessed across thousands of cells within the context of tissue structural organization. Here, we discuss how single-cell and spatially resolved transcriptomics have been contributing to unravelling the pathomechanisms underlying brain disorders. We focus on three areas where we feel these new technologies have provided particularly useful insights: selective neuronal vulnerability, neuroimmune dysfunction and cell-type-specific treatment response. We also discuss the limitations and future directions of single-cell and spatial RNA sequencing technologies. |
format | Online Article Text |
id | pubmed-10191412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-101914122023-05-19 Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease Piwecka, Monika Rajewsky, Nikolaus Rybak-Wolf, Agnieszka Nat Rev Neurol Review Article In the past decade, single-cell technologies have proliferated and improved from their technically challenging beginnings to become common laboratory methods capable of determining the expression of thousands of genes in thousands of cells simultaneously. The field has progressed by taking the CNS as a primary research subject — the cellular complexity and multiplicity of neuronal cell types provide fertile ground for the increasing power of single-cell methods. Current single-cell RNA sequencing methods can quantify gene expression with sufficient accuracy to finely resolve even subtle differences between cell types and states, thus providing a great tool for studying the molecular and cellular repertoire of the CNS and its disorders. However, single-cell RNA sequencing requires the dissociation of tissue samples, which means that the interrelationships between cells are lost. Spatial transcriptomic methods bypass tissue dissociation and retain this spatial information, thereby allowing gene expression to be assessed across thousands of cells within the context of tissue structural organization. Here, we discuss how single-cell and spatially resolved transcriptomics have been contributing to unravelling the pathomechanisms underlying brain disorders. We focus on three areas where we feel these new technologies have provided particularly useful insights: selective neuronal vulnerability, neuroimmune dysfunction and cell-type-specific treatment response. We also discuss the limitations and future directions of single-cell and spatial RNA sequencing technologies. Nature Publishing Group UK 2023-05-17 2023 /pmc/articles/PMC10191412/ /pubmed/37198436 http://dx.doi.org/10.1038/s41582-023-00809-y Text en © Springer Nature Limited 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Review Article Piwecka, Monika Rajewsky, Nikolaus Rybak-Wolf, Agnieszka Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease |
title | Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease |
title_full | Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease |
title_fullStr | Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease |
title_full_unstemmed | Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease |
title_short | Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease |
title_sort | single-cell and spatial transcriptomics: deciphering brain complexity in health and disease |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10191412/ https://www.ncbi.nlm.nih.gov/pubmed/37198436 http://dx.doi.org/10.1038/s41582-023-00809-y |
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