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Related Concept Videos

RNA-seq03:21

RNA-seq

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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...
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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
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Exosomes are stable, lipid bilayer-enclosed vesicles capable of crossing biological barriers. They can carry a wide range of molecules required for intercellular communication. Once exosomes are released from the cell where they originated, they enter a recipient cell through various pathways such as fusion, receptor-mediated endocytosis, macropinocytosis, and phagocytosis.
Stahl et al. discovered exosomes in 1983, but the exosomes were initially considered waste products released from the...
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Related Experiment Video

Updated: Aug 29, 2025

Author Spotlight: Exploring the Mechanisms of MicroRNA Loading into Extracellular Vesicles in Cancer Progression
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Transcriptomic Features in a Single Extracellular Vesicle via Single-Cell RNA Sequencing.

Tao Luo1,2,3, Si-Yi Chen2, Zhi-Xin Qiu4

  • 1Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China.

Small Methods
|September 6, 2022
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Summary

This study quantifies RNA in single extracellular vesicles (EVs), revealing gene number variation and distinct transcriptomic profiles between K562 and mesenchymal stem cell-derived EVs. It offers the first high-throughput single-EV transcriptome analysis.

Keywords:
extracellular vesiclesheterogeneitymarker genessingle-extracellular vesicle analysistranscriptome

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Area of Science:

  • Biochemistry
  • Molecular Biology
  • Cell Biology

Background:

  • Extracellular vesicles (EVs) are crucial for intercellular communication, carrying functional molecules like RNA.
  • Previous research has lacked quantitative data on the RNA content within individual EVs.
  • Understanding single-EV transcriptomics is vital for deciphering EV function and heterogeneity.

Purpose of the Study:

  • To profile the transcriptomic features and heterogeneity of single extracellular vesicles (EVs).
  • To determine the exact number of RNA molecules within individual EVs.
  • To investigate the differences in RNA cargo between EVs from different cell types.

Main Methods:

  • Utilized the 10x Genomics platform for high-throughput RNA profiling of single EVs.
  • Employed calcein-AM for labeling intact EVs and flow cytometry for concentration detection.
  • Applied the CB2 algorithm with adaptive thresholds to accurately identify EVs and distinguish them from background noise.

Main Results:

  • Quantified RNA content per single EV, ranging from 6 to 148 genes (mean 52).
  • Identified high percentages of ribosomal and mitochondrial genes, and eukaryotic translation elongation factor 1 alpha across all EV samples.
  • Observed distinct gene expression patterns: hemoglobin genes in K562-EVs and cytoskeleton genes in mesenchymal stem cell (MSC)-EVs.
  • Revealed significant EV heterogeneity through clustering based on marker genes.
  • Demonstrated a correlation between EV clusters, parental cells, and cell origins.

Conclusions:

  • This study presents the first high-throughput transcriptome analysis at the single-EV level.
  • The findings provide novel insights into the heterogeneity and molecular composition of EVs.
  • The results enhance the understanding of EV biology and their potential roles in intercellular communication.