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Updated: Dec 22, 2025
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A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA
Published on: December 2, 2009
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Ultra-high throughput single-cell analysis of proteins and RNAs by split-pool synthesis
Maeve O'Huallachain1,2, Felice-Alessio Bava3, Mary Shen1,2
1Roche Sequencing Solutions, Pleasanton, CA, USA.
Communications Biology
|May 9, 2020
Summary
We developed Quantum Barcoding (QBC), a cost-effective method for simultaneously analyzing millions of cells. This ultra-high throughput technique enables targeted protein and RNA detection without cell isolation, advancing single-cell omics research.
Area of Science:
- Molecular Biology
- Genomics
- Proteomics
Background:
- Single-cell omics are crucial for understanding cellular heterogeneity and function.
- Current single-cell analysis workflows are often expensive and complex, limiting accessibility.
- There is a need for scalable and cost-effective methods for high-throughput single-cell analysis.
Purpose of the Study:
- To present a novel method for simultaneous, ultra-high throughput single-cell barcoding.
- To enable targeted analysis of proteins and RNAs within millions of cells.
- To reduce the cost and complexity associated with single-cell omics workflows.
Main Methods:
- Developed Quantum Barcoding (QBC), a technique that avoids single-cell isolation.
- Utilized sequential rounds of classical split-pool synthesis to dynamically build cell-specific oligo barcodes within cells.
- Employed minimal instrumentation, including four 96-well plates and a multichannel pipette.
Main Results:
- Successfully demonstrated QBC in mouse and human model systems.
- Enabled targeted analysis of up to 50 antibodies for proteins and over 70 targeted RNA regions.
- Showcased the method's applicability to multi-modal protein and RNA analyses.
Conclusions:
- QBC offers a scalable and versatile approach to single-cell analysis.
- The technology transforms sequencing instruments into multi-parameter flow cytometers.
- QBC significantly enhances the accessibility and efficiency of high-throughput single-cell omics.
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