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Spatial epigenome–transcriptome co-profiling of mammalian tissues
Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context(1–5). However, current methods capture only one layer of omics information at a time, precluding the possibility of examining t...
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/PMC10076218/ https://www.ncbi.nlm.nih.gov/pubmed/36922587 http://dx.doi.org/10.1038/s41586-023-05795-1 |
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author | Zhang, Di Deng, Yanxiang Kukanja, Petra Agirre, Eneritz Bartosovic, Marek Dong, Mingze Ma, Cong Ma, Sai Su, Graham Bao, Shuozhen Liu, Yang Xiao, Yang Rosoklija, Gorazd B. Dwork, Andrew J. Mann, J. John Leong, Kam W. Boldrini, Maura Wang, Liya Haeussler, Maximilian Raphael, Benjamin J. Kluger, Yuval Castelo-Branco, Gonçalo Fan, Rong |
author_facet | Zhang, Di Deng, Yanxiang Kukanja, Petra Agirre, Eneritz Bartosovic, Marek Dong, Mingze Ma, Cong Ma, Sai Su, Graham Bao, Shuozhen Liu, Yang Xiao, Yang Rosoklija, Gorazd B. Dwork, Andrew J. Mann, J. John Leong, Kam W. Boldrini, Maura Wang, Liya Haeussler, Maximilian Raphael, Benjamin J. Kluger, Yuval Castelo-Branco, Gonçalo Fan, Rong |
author_sort | Zhang, Di |
collection | PubMed |
description | Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context(1–5). However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research. |
format | Online Article Text |
id | pubmed-10076218 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-100762182023-04-07 Spatial epigenome–transcriptome co-profiling of mammalian tissues Zhang, Di Deng, Yanxiang Kukanja, Petra Agirre, Eneritz Bartosovic, Marek Dong, Mingze Ma, Cong Ma, Sai Su, Graham Bao, Shuozhen Liu, Yang Xiao, Yang Rosoklija, Gorazd B. Dwork, Andrew J. Mann, J. John Leong, Kam W. Boldrini, Maura Wang, Liya Haeussler, Maximilian Raphael, Benjamin J. Kluger, Yuval Castelo-Branco, Gonçalo Fan, Rong Nature Article Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context(1–5). However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research. Nature Publishing Group UK 2023-03-15 2023 /pmc/articles/PMC10076218/ /pubmed/36922587 http://dx.doi.org/10.1038/s41586-023-05795-1 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Zhang, Di Deng, Yanxiang Kukanja, Petra Agirre, Eneritz Bartosovic, Marek Dong, Mingze Ma, Cong Ma, Sai Su, Graham Bao, Shuozhen Liu, Yang Xiao, Yang Rosoklija, Gorazd B. Dwork, Andrew J. Mann, J. John Leong, Kam W. Boldrini, Maura Wang, Liya Haeussler, Maximilian Raphael, Benjamin J. Kluger, Yuval Castelo-Branco, Gonçalo Fan, Rong Spatial epigenome–transcriptome co-profiling of mammalian tissues |
title | Spatial epigenome–transcriptome co-profiling of mammalian tissues |
title_full | Spatial epigenome–transcriptome co-profiling of mammalian tissues |
title_fullStr | Spatial epigenome–transcriptome co-profiling of mammalian tissues |
title_full_unstemmed | Spatial epigenome–transcriptome co-profiling of mammalian tissues |
title_short | Spatial epigenome–transcriptome co-profiling of mammalian tissues |
title_sort | spatial epigenome–transcriptome co-profiling of mammalian tissues |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076218/ https://www.ncbi.nlm.nih.gov/pubmed/36922587 http://dx.doi.org/10.1038/s41586-023-05795-1 |
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