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健康与疾病中的空间转录组学。

Spatial transcriptomics in health and disease.

机构信息

Division of Nephrology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA.

Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.

出版信息

Nat Rev Nephrol. 2024 Oct;20(10):659-671. doi: 10.1038/s41581-024-00841-1. Epub 2024 May 8.

DOI:10.1038/s41581-024-00841-1
PMID:38719971
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11392631/
Abstract

The ability to localize hundreds of macromolecules to discrete locations, structures and cell types in a tissue is a powerful approach to understand the cellular and spatial organization of an organ. Spatially resolved transcriptomic technologies enable mapping of transcripts at single-cell or near single-cell resolution in a multiplex manner. The rapid development of spatial transcriptomic technologies has accelerated the pace of discovery in several fields, including nephrology. Its application to preclinical models and human samples has provided spatial information about new cell types discovered by single-cell sequencing and new insights into the cell-cell interactions within neighbourhoods, and has improved our understanding of the changes that occur in response to injury. Integration of spatial transcriptomic technologies with other omics methods, such as proteomics and spatial epigenetics, will further facilitate the generation of comprehensive molecular atlases, and provide insights into the dynamic relationships of molecular components in homeostasis and disease. This Review provides an overview of current and emerging spatial transcriptomic methods, their applications and remaining challenges for the field.

摘要

将数百种生物大分子定位到组织中离散的位置、结构和细胞类型的能力,是理解器官细胞和空间组织的一种强大方法。空间分辨转录组学技术能够以多重方式在单细胞或接近单细胞分辨率的水平上对转录本进行定位。空间转录组学技术的快速发展加速了包括肾脏病学在内的多个领域的发现步伐。它在临床前模型和人类样本中的应用,为单细胞测序发现的新细胞类型提供了空间信息,并深入了解了局部细胞间的相互作用,从而增进了我们对损伤反应中发生的变化的理解。将空间转录组学技术与其他组学方法(如蛋白质组学和空间表观遗传学)相结合,将进一步促进全面分子图谱的生成,并深入了解在稳态和疾病中分子成分的动态关系。本文综述了当前和新兴的空间转录组学方法、它们的应用以及该领域的剩余挑战。

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2
High resolution spatial profiling of kidney injury and repair using RNA hybridization-based in situ sequencing.利用基于 RNA 杂交的原位测序技术对肾脏损伤和修复进行高分辨率空间分析。
Nat Commun. 2024 Feb 15;15(1):1396. doi: 10.1038/s41467-024-45752-8.
3
The chromatin landscape of healthy and injured cell types in the human kidney.
基于聚类的空间转录组数据细胞类型反卷积
Nucleic Acids Res. 2025 Jul 19;53(14). doi: 10.1093/nar/gkaf714.
4
Advances in spatial transcriptomics and its application in the musculoskeletal system.空间转录组学的进展及其在肌肉骨骼系统中的应用。
Bone Res. 2025 May 16;13(1):54. doi: 10.1038/s41413-025-00429-w.
5
Deep scSTAR: leveraging deep learning for the extraction and enhancement of phenotype-associated features from single-cell RNA sequencing and spatial transcriptomics data.深度scSTAR:利用深度学习从单细胞RNA测序和空间转录组学数据中提取和增强表型相关特征。
Brief Bioinform. 2025 May 1;26(3). doi: 10.1093/bib/bbaf160.
6
Rigor and Reproducibility of Spatial Transcriptomics Performed on Clinically Sourced Human Tissues.对临床来源的人体组织进行空间转录组学研究的严谨性和可重复性。
Lab Invest. 2025 Apr 29;105(9):104190. doi: 10.1016/j.labinv.2025.104190.
7
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Oncol Res. 2025 Mar 19;33(4):821-836. doi: 10.32604/or.2024.053772. eCollection 2025.
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