Search research articles

关于 JoVE

概览领导团队博客 JoVE 帮助中心

作者

出版流程编辑委员会范围与政策同行评审常见问题投稿

图书馆员

用户评价订阅访问资源图书馆顾问委员会常见问题

研究

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments 存档

教育

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual 教师资源中心教师网站

使用条款与条件

相关概念视频

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序

Same author

CommAST Enables Antibiotic Susceptibility Testing at the Gut Microbiota Community Level.

Analytical chemistry·2026

Same author

Spatially resolved profiling of extracellular vesicles in tissues with Spatial-EV-seq.

Nature biotechnology·2026

Same author

The value of fast ripples in identifying extra-temporal epileptogenicity and predicting surgical outcomes in temporal plus epilepsy: A retrospective SEEG cohort study.

Epilepsy research·2026

Same author

Cyclic transformation of stable/metastable nucleic acid structures enables dynamic monitoring of ATP in living cells.

Chemical science·2026

Same author

Dual-Spatially Confined Assembly of DNA Nanowall Stiffens Tumor Cells to Enhance Adoptive T-Cell Immunotherapy.

Journal of the American Chemical Society·2026

Same author

Tracing Tumor-Derived Extracellular Vesicle Matrix Metalloproteinase 14 Using Dual-Target Orthogonal Barcoding-Based Microscale Thermophoretic Assays.

ACS nano·2026

Search research articles

相关实验视频

Updated: Jun 10, 2025

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

Published on: August 8, 2013

整合代谢性RNA标记基于时间解析的单细胞RNA测序与空间转录学,用于空间时间转录学分析.

Xiaoyong Chen^1,2, Shichao Lin³, Honghai You^1,2

¹Department of Neurosurgery, Neurosurgery Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, P. R. China.

|October 11, 2024

概括

将时间解析的单细胞RNA测序与空间转录学相结合,揭示了质母细胞细胞的通信驱动介质细胞过渡. 这种时空分析揭示了瘤微环境中的关键路径.

关键词:

在 EZH2 中使用.质母细胞瘤是一种质母细胞瘤.中细胞过渡转变.一个单细胞的单细胞.时间空间时间空间.

更多相关视频

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

Published on: January 16, 2018

相关实验视频

Last Updated: Jun 10, 2025

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

Published on: August 8, 2013

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

Metabolic Labeling and Profiling of Transfer RNAs Using Macroarrays

Published on: January 16, 2018

科学领域:

分子生物学分子生物学
基因组学就是基因组学.
癌症研究癌症研究

背景情况:

单细胞RNA测序 (scRNA-seq) 提供了对基因表达动态的见解,但缺乏空间背景.
空间组织和细胞间通信显著影响组织内的基因调节.
了解质母细胞瘤 (GBM) 进展需要将时间基因表达与空间细胞相互作用整合起来.

研究的目的:

开发和应用一个集成的时空分析方法,以分析GBM.
研究GBM中的转录动态和细胞间通信.
为了阐明驱动质母细胞瘤中介酶过渡的机制.

主要方法:

基于代谢性RNA标记的时间解析转录动态的Well-TEMP-seq.
与空间转录学集成,绘制细胞位置和相互作用的地图.
对基因表达模式和细胞间通信轴的分析.

主要成果:

确定了两种潜在的EZH2介导途径,驱动GBM中介细胞间转变.
揭示了恶性CCL2+细胞和IL10+瘤相关的巨细胞之间的交叉声.
发现了一个EZH2-FOSL2-CCL2轴,有助于GBM介质细胞过渡.

结论:

时间解析的scRNA-seq和空间转录学的整合为时空分析提供了一个强大的范式.
这种方法阐明了复杂的基因调节机制和疾病中的细胞过程.
这些发现有助于更好地了解GBM病原体和潜在的治疗点.