Long-read single-cell sequencing reveals expressions of hypermutation clusters of isoforms in human liver cancer cells
Silvia Liu,
Yan-Ping Yu,
Bao-Guo Ren,
Tuval Ben-Yehezkel,
Caroline Obert,
Mat Smith,
Wenjia Wang,
Alina Ostrowska,
Alejandro Soto-Gutierrez,
Jian-Hua Luo
Affiliations
Silvia Liu
Department of Pathology, University of Pittsburgh, Pittsburgh, United States; High Throughput Genome Center, University of Pittsburgh, Pittsburgh, United States; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States
Yan-Ping Yu
Department of Pathology, University of Pittsburgh, Pittsburgh, United States; High Throughput Genome Center, University of Pittsburgh, Pittsburgh, United States; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States
Bao-Guo Ren
Department of Pathology, University of Pittsburgh, Pittsburgh, United States; High Throughput Genome Center, University of Pittsburgh, Pittsburgh, United States; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States
Tuval Ben-Yehezkel
Element Biosciences Inc, San Diego, United States
Caroline Obert
Element Biosciences Inc, San Diego, United States
Mat Smith
Element Biosciences Inc, San Diego, United States
Wenjia Wang
Biostatistics, University of Pittsburgh, Pittsburgh, United States
Alina Ostrowska
Department of Pathology, University of Pittsburgh, Pittsburgh, United States; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States
Alejandro Soto-Gutierrez
Department of Pathology, University of Pittsburgh, Pittsburgh, United States; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States
Department of Pathology, University of Pittsburgh, Pittsburgh, United States; High Throughput Genome Center, University of Pittsburgh, Pittsburgh, United States; Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, United States
The protein diversity of mammalian cells is determined by arrays of isoforms from genes. Genetic mutation is essential in species evolution and cancer development. Accurate long-read transcriptome sequencing at single-cell level is required to decipher the spectrum of protein expressions in mammalian organisms. In this report, we developed a synthetic long-read single-cell sequencing technology based on LOOPSeq technique. We applied this technology to analyze 447 transcriptomes of hepatocellular carcinoma (HCC) and benign liver from an individual. Through Uniform Manifold Approximation and Projection analysis, we identified a panel of mutation mRNA isoforms highly specific to HCC cells. The evolution pathways that led to the hyper-mutation clusters in single human leukocyte antigen molecules were identified. Novel fusion transcripts were detected. The combination of gene expressions, fusion gene transcripts, and mutation gene expressions significantly improved the classification of liver cancer cells versus benign hepatocytes. In conclusion, LOOPSeq single-cell technology may hold promise to provide a new level of precision analysis on the mammalian transcriptome.