By examining gene expression in individual cells through single-cell RNA sequencing (scRNA-seq), researchers can untangle the cellular complexity within a heterogeneous sample such as tumor or other disease tissues (Hay et al. 2020). scRNA-seq can identify subpopulations with unique gene expression profiles and biomarkers that may be correlated with drug resistance or cancer progression.
Current scRNA-seq methods with full gene-body coverage have never been scaled up to satisfy users' need for cell throughput (i.e., existing methods are limited to up to 384 single cells per run). However, widely used end-counting technologies only give partial information due to the lack of full gene-body coverage. Scientists need new technologies with both high cell throughput and full gene-body coverage so they can leverage the data to get extra insights besides gene counting, such as transcript-level information including alternative splicing and gene fusions. To address this long-standing need, we developed the Shasta™ Total RNA-Seq Kit (workflow illustrated in Figure 1), enabling scientists to get scRNA-seq libraries for up to 100,000 cells per run with full gene-body coverage for the very first time.
Evaluation of the Shasta Total RNA-Seq Kit demonstrated the kit has a low doublet rate, full gene-body coverage, high sensitivity, and high-throughput capability. Data generated with Shasta Total RNA-Seq enables annotation of different cell populations in a heterogeneous sample. Embracing scalability and sensitivity, the Shasta Total RNA-Seq Kit will be a powerful biomarker discovery tool for scientists to better understand disease mechanisms and find more optimal treatment strategies for cancer and other diseases.
Figure 1. Shasta Total RNA-Seq workflow. Library preparation begins with (1) single-cell suspension, cell fixation, and RNA fragmentation. (2) Permeabilized cells serve as containers for in situ reverse transcription, which adds sample-specific barcodes with template-switching oligos (TSOs) with up to 96 different barcodes, thus allowing scientists to load up to 96 different samples per experiment. (3) Cells are harvested and dispensed into 5,184 nanowells using the Shasta Single-Cell System, followed by (4) cell lysis and incorporation of barcodes with 72 i5 and 72 i7 primers. (5) The products are harvested from the chip and converted into sequencing-ready libraries after off-chip PCR and purification, during which rRNA-derived sequences are removed using our signature ZapR™ technology. Finally, (6) sequencing is performed, followed by data analysis using the easy-to-use Cogent™ NGS tools.
