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单细胞转录组和表观基因组分析。

Single-Cell Analysis of the Transcriptome and Epigenome.

机构信息

Laboratory of Genetics and Genomics, National Institute on Aging (NIA), Intramural Research Program (IRP), National Institutes of Health (NIH), Baltimore, MD, USA.

Laboratory of Genetics and Genomics, and Computational Biology and Genomics Core, National Institute on Aging-Intramural Research Program, National Institute of Health, Baltimore, MD, USA.

出版信息

Methods Mol Biol. 2022;2399:21-60. doi: 10.1007/978-1-0716-1831-8_3.

DOI:10.1007/978-1-0716-1831-8_3
PMID:35604552
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9352558/
Abstract

Epigenome regulation has emerged as an important mechanism for the maintenance of organ function in health and disease. Dissecting epigenomic alterations and resultant gene expression changes in single cells provides unprecedented resolution and insight into cellular diversity, modes of gene regulation, transcription factor dynamics and 3D genome organization. In this chapter, we summarize the transformative single-cell epigenomic technologies that have deepened our understanding of the fundamental principles of gene regulation. We provide a historical perspective of these methods, brief procedural outline with emphasis on the computational tools used to meaningfully dissect information. Our overall goal is to aid scientists using these technologies in their favorite system of interest.

摘要

表观基因组调控已成为维持健康和疾病中器官功能的重要机制。解析单细胞中的表观基因组改变和由此产生的基因表达变化,为细胞多样性、基因调控模式、转录因子动力学和 3D 基因组组织提供了前所未有的分辨率和深入了解。在本章中,我们总结了变革性的单细胞表观基因组技术,这些技术加深了我们对基因调控基本原理的理解。我们提供了这些方法的历史背景,简要的程序概述,并重点介绍了用于有意义地解析信息的计算工具。我们的总体目标是帮助使用这些技术的科学家在他们感兴趣的系统中使用这些技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c3/9352558/e9063de540c0/nihms-1825971-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c3/9352558/1298e3a115b7/nihms-1825971-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c3/9352558/9897d7956085/nihms-1825971-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c3/9352558/e9063de540c0/nihms-1825971-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c3/9352558/1298e3a115b7/nihms-1825971-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c3/9352558/9897d7956085/nihms-1825971-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55c3/9352558/e9063de540c0/nihms-1825971-f0003.jpg

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4
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Methods Mol Biol. 2025;2908:99-109. doi: 10.1007/978-1-0716-4434-8_7.
5
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Am J Obstet Gynecol. 2025 Apr;232(4S):S1-S20. doi: 10.1016/j.ajog.2024.08.041. Epub 2025 Mar 11.
6
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Front Mol Neurosci. 2024 Sep 18;17:1462769. doi: 10.3389/fnmol.2024.1462769. eCollection 2024.
7
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8
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5
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6
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7
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