High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors.

Single cell Nanopore sequencing of full-length RNAs (scNanoRNAseq) is transforming single cell multi-omics analysis, however it is computationally challenged and relying on paralleled short-read sequencing to curate errors. We developed scNanoGPS to calculate same-cell genotypes-phenotypes from scNanoRNAseq data and eliminate dependance on short-reads guidance. To test its accuracy, robustness and applications, we analyzed 6 single nuclei transcriptomes composited of 4 frozen tumors and 2 cancer cell lines. Our results showed that scNanoGPS accurately deconvoluted raw long-reads into single-cells and single-molecules without short-reads guidance and calculated same-cell gene expressions, isoforms, and mutations and copy numbers simultaneously for thousands of cells. In a kidney tumor, we can identify cell-type-specific alternatively spliced genes enriched in important tumorigenic pathways, in addition to expression levels. Further, we detected transcriptome-wide mutations of each cell-type, enabling direct cell-lineage (genotype) and cell-fate (phenotype) alignment to investigate tumor progression. Together, scNanoGPS addresses major computational challenges and largely simplifies experimental workflow of scNanoRNAseq. Single nucleus suspensions of all samples were loaded onto 10X Genomics Chromium instrucment for barcoding with scRNAseq protocol. A portion of barcoded cDNAs were fragmented to perform paralleled 3'scRNAseq on Novaseq 6000. Another portion of full-length cDNAs were sent for Oxford Nanopore sequencing on PromethION.