Kim Ferguson, Sanika Khare, Herbert Gong, Dmitry Pokholok, Bryce Alves, Nate Chapin, Fan Zhang, Jerushah Thomas, Nicholas Pervolarakis, Emmanuel Jimenez,Brent Biddy, Felix Schleisinger, Robert James, Scale Bioscience

Large-scale single-cell RNA sequencing (scRNA-seq) studies, while powerful, face
challenges related to cost and the introduction of batch effects across numerous samples,
complicating data analysis and interpretation and hindering wider adoption. Scale Bio has
developed innovative, highly parallelized barcoding and multiplexing strategies (ScalePlex)
to address these limitations by boosting throughput and mitigating batch effects through
early sample pooling. We demonstrate this through two key experiments: leveraging
Quantum Scale data for genetic demultiplexing of PBMCs and achieving ultra-high
throughput profiling of a mouse brain.
Genetic demultiplexing involves pooling distinct samples before sequencing, followed by
bioinformatic identification of individual samples based on their genetic makeup. However,
this method often yields high doublet rates (up to 30%) and is limited by reference genome
quality and genetic diversity, with distinguishing inter-sample variation being particularly
difficult in diseases with high mutational burdens. To address these issues, we showcase
the utility of the Scale Bio scRNA-seq platform, with and without ScalePlex, for sample
demultiplexing by analyzing PBMCs pooled from 12 individuals, comparing its performance
to super-loaded conventional scRNA-seq. Our results demonstrate low doublet rates,
maximum utilization of sequencing reads, and clear, unambiguous sample identification
with the Scale Bio approach, outperforming conventional techniques and computational
tools.
Furthermore, we utilized Scale Bio's ultra-high-throughput capabilities by processing 4
million nuclei from eight mouse brain samples across 768 ScalePlex wells with unique
sample barcodes. This experiment achieved high cell capture rates, and deep and shallow
sequencing revealed robust cell recovery, high sensitivity comparable to smaller-scale
studies, and minimal batch effects. This underscores the feasibility and reproducibility of
ultra-high-throughput scRNA-seq using ScalePlex and QuantumScale.
In conclusion, the Scale Bio scRNA-seq platform, incorporating ScalePlex and
QuantumScale, offers a powerful solution to overcome current limitations in scRNA-seq. It
provides a cost-effective and less complex alternative to genetic demultiplexing with
superior resolution and multiplexing capabilities. Moreover, its ultra-high-throughput
capacity enables unprecedented scalability, paving the way for comprehensive cellular
analysis in complex biological systems and accelerating discoveries in the field.