scNanoGPS – high throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors

Single-cell nanopore sequencing of full-length mRNAs transforms single-cell multi-omics studies. However, challenges include high sequencing errors and dependence on short-reads and/or barcode whitelists. To address these, researchers at Northwestern University Feinberg School of Medicine have developed scNanoGPS to calculate same-cell genotypes (mutations) and phenotypes (gene/isoform expressions) without short-read nor whitelist guidance. The researchers apply scNanoGPS onto 23,587 long-read transcriptomes from 4 tumors and 2 cell-lines. Standalone, scNanoGPS deconvolutes error-prone long-reads into single-cells and single-molecules, and simultaneously accesses both phenotypes and genotypes of individual cells. Their analyses reveal that tumor and stroma/immune cells express distinct combination of isoforms (DCIs). In a kidney tumor, they identified 924 DCI genes involved in cell-type-specific functions such as PDE10A in tumor cells and CCL3 in lymphocytes. Transcriptome-wide mutation analyses identified many cell-type-specific mutations including VEGFA mutations in tumor cells and HLA-A mutations in immune cells, highlighting the critical roles of different mutant populations in tumors. Together, scNanoGPS facilitates applications of single-cell long-read sequencing technologies.

Schematic diagrams of scNanoRNAseq and scNanoGPS workflows

a Experimental workflow and library structure of scNanoRNAseq. b Computational workflow of scNanoGPS.

Availability – Software is available at GitHub: https://github.com/gaolabtools/scNanoGPS