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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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RNA Sequencing at Single Vesicle Resolution via 3D Printed Embedded Droplet Arrays.

Andrew A Brock1, Senthilkumar Duraivel2, Jinmai Jiang1

  • 1Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, Florida 32610, United States.

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|September 12, 2025
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Researchers developed a 3D printing method to analyze RNA in single extracellular vesicles (EVs). This platform reveals the diverse RNA cargo within individual EVs, aiding biomarker discovery.

Keywords:
3D printingRNA sequencingcellular heterogeneitydroplet manufacturingexosomesextracellular vesicles

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Area of Science:

  • Biotechnology
  • Molecular Biology
  • Nanotechnology

Background:

  • Single-cell RNA sequencing advanced cellular heterogeneity studies.
  • Methods for analyzing individual extracellular vesicle (EV) RNA cargo are limited.
  • EVs are crucial for intercellular communication and disease biomarker discovery.

Purpose of the Study:

  • To develop a novel platform for analyzing RNA heterogeneity in single extracellular vesicles (EVs).
  • To enable high-throughput sequencing of RNA cargo from individual EVs.
  • To explore the potential of EV RNA profiles for biomarker discovery.

Main Methods:

  • Developed a 3D printing platform to create droplet arrays in an organogel support.
  • Utilized interfacial instability for controlled droplet formation and trapping of single EVs and barcoded beads.
  • Performed in-droplet reactions, including PCR and cDNA synthesis, followed by library preparation and sequencing.
  • Optimized printing conditions for efficient loading of single EVs and beads within picoliter droplets.

Main Results:

  • Successfully sequenced poly(A)+ RNA from individual EVs, identifying 3689 unique barcodes.
  • Quantified an average of 3.32 poly(A)+ RNA molecules per EV.
  • Revealed heterogeneity in poly(A)+ RNA content within individual EVs, including mRNA, mitochondrial RNA, and noncoding RNAs.
  • Demonstrated the platform's capability to resolve RNA cargo heterogeneity in EVs.

Conclusions:

  • The 3D printing droplet array platform enables high-resolution analysis of single EV RNA cargo.
  • This technology can uncover significant heterogeneity in EV RNA content.
  • The platform holds promise for advancing biomarker discovery and clinical applications through EV analysis.