scFAST-seq reveals a wide diversity of transcripts, CNV events, and regulatory activity in adrenocortical tumor

The emergence of single-cell multi-omics technologies has enabled researchers to identify rare cell populations and investigate gene regulation with unmatched resolution, advancing cancer research. However, each technique comes with its own distinct advantages and drawbacks. In this study, we compared two high-throughput droplet-based single-cell RNA sequencing (scRNA-seq) technologies-10X Chromium 3' scRNA-seq and SeekGene scFAST-seq-using two paired samples derived from adrenocortical tumor. scFAST-seq exhibited a higher ratio of long non-coding RNAs, along with an increased number of detected genes and transcripts, while ribosomal RNA was underrepresented. Although the overlap in top cell type markers was relatively low, the relative abundances of cell populations were alike in both datasets. Also gene markers showed to be specific for scFAST-seq and 3' scRNA-seq displayed minimal general variability in gene expression. We noted changes in RNA dynamics across the datasets, identified through RNA velocity analysis and fewer copy number variations (CNV) detected by CNV analysis. Furthermore, we found variations in regulon activity in 3' scRNA-seq and scFAST-seq datasets. In conclusion, our research offers essential insights for selecting the most suitable scRNA-seq approach.