Highly parallel and efficient single cell mRNA sequencing with paired picoliter chambers

ScRNA-seq has the ability to reveal accurate and precise cell types and states. Existing scRNA-seq platforms utilize bead-based technologies uniquely barcoding individual cells, facing practical challenges for precious samples with limited cell number. Here, we present a scRNA-seq platform, named Pa...

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Veröffentlicht in:Nature communications 2020-04, Vol.11 (1), p.2118-2118, Article 2118
Hauptverfasser: Zhang, Mingxia, Zou, Yuan, Xu, Xing, Zhang, Xuebing, Gao, Mingxuan, Song, Jia, Huang, Peifeng, Chen, Qin, Zhu, Zhi, Lin, Wei, Zare, Richard N., Yang, Chaoyong
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Sprache:eng
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Zusammenfassung:ScRNA-seq has the ability to reveal accurate and precise cell types and states. Existing scRNA-seq platforms utilize bead-based technologies uniquely barcoding individual cells, facing practical challenges for precious samples with limited cell number. Here, we present a scRNA-seq platform, named Paired-seq, with high cells/beads utilization efficiency, cell-free RNAs removal capability, high gene detection ability and low cost. We utilize the differential flow resistance principle to achieve single cell/barcoded bead pairing with high cell utilization efficiency (95%). The integration of valves and pumps enables the complete removal of cell-free RNAs, efficient cell lysis and mRNA capture, achieving highest mRNA detection accuracy (R = 0.955) and comparable sensitivity. Lower reaction volume and higher mRNA capture and barcoding efficiency significantly reduce the cost of reagents and sequencing. The single-cell expression profile of mES and drug treated cells reveal cell heterogeneity, demonstrating the enormous potential of Paired-seq for cell biology, developmental biology and precision medicine. Single-cell RNA-seq can reveal accurate and precise cell types and states. Here the authors present an scRNA-seq platform, Paired-seq, which uses differential flow resistance to achieve 95% cell utilisation efficiency for improved cell-free RNA removal and gene detection.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-020-15765-0