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Spatial transcriptomics: recent developments and insights in respiratory research
The respiratory system’s complex cellular heterogeneity presents unique challenges to researchers in this field. Although bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) have provided insights into cell types and heterogeneity in the respiratory system, the relevant specific spatial l...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10433685/ https://www.ncbi.nlm.nih.gov/pubmed/37592342 http://dx.doi.org/10.1186/s40779-023-00471-x |
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author | Wang, Wen-Jia Chu, Liu-Xi He, Li-Yong Zhang, Ming-Jing Dang, Kai-Tong Gao, Chen Ge, Qin-Yu Wang, Zhou-Guang Zhao, Xiang-Wei |
author_facet | Wang, Wen-Jia Chu, Liu-Xi He, Li-Yong Zhang, Ming-Jing Dang, Kai-Tong Gao, Chen Ge, Qin-Yu Wang, Zhou-Guang Zhao, Xiang-Wei |
author_sort | Wang, Wen-Jia |
collection | PubMed |
description | The respiratory system’s complex cellular heterogeneity presents unique challenges to researchers in this field. Although bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) have provided insights into cell types and heterogeneity in the respiratory system, the relevant specific spatial localization and cellular interactions have not been clearly elucidated. Spatial transcriptomics (ST) has filled this gap and has been widely used in respiratory studies. This review focuses on the latest iterative technology of ST in recent years, summarizing how ST can be applied to the physiological and pathological processes of the respiratory system, with emphasis on the lungs. Finally, the current challenges and potential development directions are proposed, including high-throughput full-length transcriptome, integration of multi-omics, temporal and spatial omics, bioinformatics analysis, etc. These viewpoints are expected to advance the study of systematic mechanisms, including respiratory studies. |
format | Online Article Text |
id | pubmed-10433685 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-104336852023-08-18 Spatial transcriptomics: recent developments and insights in respiratory research Wang, Wen-Jia Chu, Liu-Xi He, Li-Yong Zhang, Ming-Jing Dang, Kai-Tong Gao, Chen Ge, Qin-Yu Wang, Zhou-Guang Zhao, Xiang-Wei Mil Med Res Review The respiratory system’s complex cellular heterogeneity presents unique challenges to researchers in this field. Although bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) have provided insights into cell types and heterogeneity in the respiratory system, the relevant specific spatial localization and cellular interactions have not been clearly elucidated. Spatial transcriptomics (ST) has filled this gap and has been widely used in respiratory studies. This review focuses on the latest iterative technology of ST in recent years, summarizing how ST can be applied to the physiological and pathological processes of the respiratory system, with emphasis on the lungs. Finally, the current challenges and potential development directions are proposed, including high-throughput full-length transcriptome, integration of multi-omics, temporal and spatial omics, bioinformatics analysis, etc. These viewpoints are expected to advance the study of systematic mechanisms, including respiratory studies. BioMed Central 2023-08-17 /pmc/articles/PMC10433685/ /pubmed/37592342 http://dx.doi.org/10.1186/s40779-023-00471-x 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Review Wang, Wen-Jia Chu, Liu-Xi He, Li-Yong Zhang, Ming-Jing Dang, Kai-Tong Gao, Chen Ge, Qin-Yu Wang, Zhou-Guang Zhao, Xiang-Wei Spatial transcriptomics: recent developments and insights in respiratory research |
title | Spatial transcriptomics: recent developments and insights in respiratory research |
title_full | Spatial transcriptomics: recent developments and insights in respiratory research |
title_fullStr | Spatial transcriptomics: recent developments and insights in respiratory research |
title_full_unstemmed | Spatial transcriptomics: recent developments and insights in respiratory research |
title_short | Spatial transcriptomics: recent developments and insights in respiratory research |
title_sort | spatial transcriptomics: recent developments and insights in respiratory research |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10433685/ https://www.ncbi.nlm.nih.gov/pubmed/37592342 http://dx.doi.org/10.1186/s40779-023-00471-x |
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