Single cell RNA-seq with ultra-high sensitivity and a streamlined workflow
The new plexWell Rapid Single Cell RNA Library Prep Kit uses an optimised chemistry for highly sensitive full-length cDNA synthesis. It captures the complexity of the transcriptome, including splice variants, fusion transcripts and SNPs.
The innovative tagmentation-based library preparation reduces hand-on time, removes the need for sample normalization and allows for highly multiplexed sequencing.
The plexWell Rapid Single Cell RNA Library Prep Kit was benchmarked against common Smart-seq protocols (1,2) using a challenging sample with ultra-low cellular RNA content.
The plexWell Kit achieved the highest sensitivity (Fig.1). Furthermore, the plexWell Kit delivered a very uniform gene body coverage, the highest percentage of uniquely mapping reads, the highest exon- and the lowest intron-mapping rate.
Fig.1: Benchmarking the plexWell Rapid Single Cell RNA Library Prep Kit, and downsampling effects on gene detection. CD45+ human PBMCs were processed in 96-well plates according to the manufacturer’s instructions or published protocols (1,2).
Data from Simone Picelli, Single Cell Genomics Platform, IOB, Basel, Switzerland.
The plexWell Rapid Single Cell RNA Library Prep Kit facilitates library preparation with a unique barcoding scheme and built-in automatic normalization, reducing the need for sample QC. The whole process from sorted cells to sequencing-ready libraries can be completed in the same day, without any specialized equipment.
Fig.2: plexWell workflow vs. conventional library preparation.
plexWell auto-normalization ensures a highly even read distribution across single cells. Different sets of barcodes are available for multiplexing up to 1152 cells in one sequencing run.
Fig.3: All 96 cDNA samples were quantified and normalized for the Smart-seq2 workflow. For the plexWell workflow, cDNAs were diluted, by applying a global dilution factor derived from QC data for only 24 of the samples.
- Picelli et al., Nature Protocols 9(1):171-81 (2014)
- Hagermann-Jenssen et al., Nature Biotechnology 38(6):708-714 (2020)
