High throughput error corrected Nanopore single cell transcriptome sequencing.

Area of Science:

• Single-cell genomics
• Transcriptomics
• Molecular biology

Background:

• Droplet-based high-throughput single-cell sequencing advances understanding of cell heterogeneity.
• Short-read sequencing in single-cell approaches loses crucial splicing and sequence information.
• Existing long-read single-cell methods suffer from low sequencing depth and inaccurate unique molecular identifier (UMI) assignment.

Purpose of the Study:

• Introduce ScNaUmi-seq, a novel approach combining high-throughput Oxford Nanopore sequencing with accurate cell barcode and UMI assignment.
• Overcome limitations of current single-cell sequencing techniques for comprehensive transcript analysis.
• Enable high-accuracy, full-length sequence information at high sequencing depths.

Main Methods:

• Integration of droplet-based single-cell isolation (10x Genomics) with Oxford Nanopore long-read sequencing.
• Development of an accurate cell barcode and UMI assignment strategy.
• Implementation of UMI-guided error correction for high-accuracy transcript sequencing.

Main Results:

• ScNaUmi-seq achieves high throughput and accurate cell barcode/UMI assignment.
• The method generates high-accuracy, full-length transcript sequence data.
• Analysis of embryonic mouse brain reveals transcript isoform diversity, splicing, and SNVs (RNA editing) at the single-cell level.

Conclusions:

• ScNaUmi-seq provides a powerful tool for comprehensive single-cell transcriptomic analysis.
• The approach enables detailed characterization of splicing and RNA editing in individual cells.
• ScNaUmi-seq advances the study of cell-to-cell heterogeneity by preserving full-length transcript information.