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

Author

Listed:
  • Cheng-Kai Shiau

    (Northwestern University Feinberg School of Medicine
    Northwestern University)

  • Lina Lu

    (Northwestern University Feinberg School of Medicine
    Northwestern University)

  • Rachel Kieser

    (Houston Methodist Research Institute)

  • Kazutaka Fukumura

    (University of Texas MD Anderson Cancer Center)

  • Timothy Pan

    (Northwestern University Feinberg School of Medicine
    Northwestern University
    Northwestern University)

  • Hsiao-Yun Lin

    (Northwestern University Feinberg School of Medicine
    Northwestern University)

  • Jie Yang

    (New York University Langone School of Medicine)

  • Eric L. Tong

    (University of Texas at Austin)

  • GaHyun Lee

    (Northwestern University Feinberg School of Medicine)

  • Yuanqing Yan

    (Northwestern University Feinberg School of Medicine)

  • Jason T. Huse

    (University of Texas MD Anderson Cancer Center)

  • Ruli Gao

    (Northwestern University Feinberg School of Medicine
    Northwestern University
    Northwestern University)

Abstract

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, we develop scNanoGPS to calculate same-cell genotypes (mutations) and phenotypes (gene/isoform expressions) without short-read nor whitelist guidance. We 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. Our analyses reveal that tumor and stroma/immune cells express distinct combination of isoforms (DCIs). In a kidney tumor, we identify 924 DCI genes involved in cell-type-specific functions such as PDE10A in tumor cells and CCL3 in lymphocytes. Transcriptome-wide mutation analyses identify 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.

Suggested Citation

  • Cheng-Kai Shiau & Lina Lu & Rachel Kieser & Kazutaka Fukumura & Timothy Pan & Hsiao-Yun Lin & Jie Yang & Eric L. Tong & GaHyun Lee & Yuanqing Yan & Jason T. Huse & Ruli Gao, 2023. "High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-39813-7
    DOI: 10.1038/s41467-023-39813-7
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