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ScRNA-seq and ST-seq in liver research

Spatial transcriptomics, which combine gene expression data with spatial information, has quickly expanded in recent years. With application of this method in liver research, our knowledge about liver development, regeneration, and diseases have been greatly improved. While this field is moving forw...

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Detalles Bibliográficos
Autores principales: He, Jia, Deng, Chengxiang, Krall, Leonard, Shan, Zhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9895469/
https://www.ncbi.nlm.nih.gov/pubmed/36732412
http://dx.doi.org/10.1186/s13619-022-00152-5
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author He, Jia
Deng, Chengxiang
Krall, Leonard
Shan, Zhao
author_facet He, Jia
Deng, Chengxiang
Krall, Leonard
Shan, Zhao
author_sort He, Jia
collection PubMed
description Spatial transcriptomics, which combine gene expression data with spatial information, has quickly expanded in recent years. With application of this method in liver research, our knowledge about liver development, regeneration, and diseases have been greatly improved. While this field is moving forward, a variety of problems still need to be addressed, including sensitivity, limited capacity to obtain exact single-cell information, data processing methods, as well as others. Methods like single-cell RNA sequencing (scRNA-seq) are usually used together with spatial transcriptome sequencing (ST-seq) to clarify cell-specific gene expression. In this review, we explore how advances of scRNA-seq and ST-seq, especially ST-seq, will pave the way to new opportunities to investigate fundamental questions in liver research. Finally, we will discuss the strengths, limitations, and future perspectives of ST-seq in liver research.
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spelling pubmed-98954692023-02-16 ScRNA-seq and ST-seq in liver research He, Jia Deng, Chengxiang Krall, Leonard Shan, Zhao Cell Regen Review Spatial transcriptomics, which combine gene expression data with spatial information, has quickly expanded in recent years. With application of this method in liver research, our knowledge about liver development, regeneration, and diseases have been greatly improved. While this field is moving forward, a variety of problems still need to be addressed, including sensitivity, limited capacity to obtain exact single-cell information, data processing methods, as well as others. Methods like single-cell RNA sequencing (scRNA-seq) are usually used together with spatial transcriptome sequencing (ST-seq) to clarify cell-specific gene expression. In this review, we explore how advances of scRNA-seq and ST-seq, especially ST-seq, will pave the way to new opportunities to investigate fundamental questions in liver research. Finally, we will discuss the strengths, limitations, and future perspectives of ST-seq in liver research. Springer Nature Singapore 2023-02-03 /pmc/articles/PMC9895469/ /pubmed/36732412 http://dx.doi.org/10.1186/s13619-022-00152-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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
He, Jia
Deng, Chengxiang
Krall, Leonard
Shan, Zhao
ScRNA-seq and ST-seq in liver research
title ScRNA-seq and ST-seq in liver research
title_full ScRNA-seq and ST-seq in liver research
title_fullStr ScRNA-seq and ST-seq in liver research
title_full_unstemmed ScRNA-seq and ST-seq in liver research
title_short ScRNA-seq and ST-seq in liver research
title_sort scrna-seq and st-seq in liver research
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9895469/
https://www.ncbi.nlm.nih.gov/pubmed/36732412
http://dx.doi.org/10.1186/s13619-022-00152-5
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