Delineating genotypes and phenotypes of individual cells from long-read single cell transcriptomes

• Published in: bioRxiv : the preprint server for biology
• Main Authors: Shiau, Cheng-Kai, Lu, Lina, Kieser, Rachel, Fukumura, Kazutaka, Pan, Timothy, Lin, Hsiao-Yun, Yang, Jie, Tong, Eric L, Lee, GaHyun, Yan, Yuanqing, Huse, Jason T, Gao, Ruli
• Format: Journal Article
• Language: English
• Published: United States 03.02.2023

Single-cell nanopore sequencing of full-length mRNAs (scNanoRNAseq) is transforming singlecell multi-omics studies. However, challenges include computational complexity and dependence on short-read curation. To address this, we developed a comprehensive toolkit, scNanoGPS to calculate same-cell genotypes-phenotypes without short-read guidance. We applied scNanoGPS onto 23,587 long-read transcriptomes from 4 tumors and 2 cell lines. Standalone, scNanoGPS accurately deconvoluted error-prone long-reads into single-cells and single-molecules. Further, scNanoGPS simultaneously accessed both phenotypes (expressions/isoforms) and genotypes (mutations) of individual cells. Our analyses revealed that tumor and stroma/immune cells often expressed significantly distinct combinations of isoforms (DCIs). In a kidney tumor, we identified 924 genes with DCIs involved in cell-type-specific functions such as in tumor cells and in lymphocytes. Moreover, transcriptome-wide mutation analyses identified many cell-type-specific mutations including mutations in tumor cells and mutations in immune cells, highlighting critical roles of different populations in tumors. Together, scNanoGPS facilitates applications of single-cell long-read sequencing.