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From whole-mount to single-cell spatial assessment of gene expression in 3D
Unravelling spatio-temporal patterns of gene expression is crucial to understanding core biological principles from embryogenesis to disease. Here we review emerging technologies, providing automated, high-throughput, spatially resolved quantitative gene expression data. Novel techniques expand on c...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584572/ https://www.ncbi.nlm.nih.gov/pubmed/33097816 http://dx.doi.org/10.1038/s42003-020-01341-1 |
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author | Waylen, Lisa N. Nim, Hieu T. Martelotto, Luciano G. Ramialison, Mirana |
author_facet | Waylen, Lisa N. Nim, Hieu T. Martelotto, Luciano G. Ramialison, Mirana |
author_sort | Waylen, Lisa N. |
collection | PubMed |
description | Unravelling spatio-temporal patterns of gene expression is crucial to understanding core biological principles from embryogenesis to disease. Here we review emerging technologies, providing automated, high-throughput, spatially resolved quantitative gene expression data. Novel techniques expand on current benchmark protocols, expediting their incorporation into ongoing research. These approaches digitally reconstruct patterns of embryonic expression in three dimensions, and have successfully identified novel domains of expression, cell types, and tissue features. Such technologies pave the way for unbiased and exhaustive recapitulation of gene expression levels in spatial and quantitative terms, promoting understanding of the molecular origin of developmental defects, and improving medical diagnostics. |
format | Online Article Text |
id | pubmed-7584572 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75845722020-10-26 From whole-mount to single-cell spatial assessment of gene expression in 3D Waylen, Lisa N. Nim, Hieu T. Martelotto, Luciano G. Ramialison, Mirana Commun Biol Review Article Unravelling spatio-temporal patterns of gene expression is crucial to understanding core biological principles from embryogenesis to disease. Here we review emerging technologies, providing automated, high-throughput, spatially resolved quantitative gene expression data. Novel techniques expand on current benchmark protocols, expediting their incorporation into ongoing research. These approaches digitally reconstruct patterns of embryonic expression in three dimensions, and have successfully identified novel domains of expression, cell types, and tissue features. Such technologies pave the way for unbiased and exhaustive recapitulation of gene expression levels in spatial and quantitative terms, promoting understanding of the molecular origin of developmental defects, and improving medical diagnostics. Nature Publishing Group UK 2020-10-23 /pmc/articles/PMC7584572/ /pubmed/33097816 http://dx.doi.org/10.1038/s42003-020-01341-1 Text en © The Author(s) 2020 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/. |
spellingShingle | Review Article Waylen, Lisa N. Nim, Hieu T. Martelotto, Luciano G. Ramialison, Mirana From whole-mount to single-cell spatial assessment of gene expression in 3D |
title | From whole-mount to single-cell spatial assessment of gene expression in 3D |
title_full | From whole-mount to single-cell spatial assessment of gene expression in 3D |
title_fullStr | From whole-mount to single-cell spatial assessment of gene expression in 3D |
title_full_unstemmed | From whole-mount to single-cell spatial assessment of gene expression in 3D |
title_short | From whole-mount to single-cell spatial assessment of gene expression in 3D |
title_sort | from whole-mount to single-cell spatial assessment of gene expression in 3d |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584572/ https://www.ncbi.nlm.nih.gov/pubmed/33097816 http://dx.doi.org/10.1038/s42003-020-01341-1 |
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