Long-read single-cell sequencing reveals expressions of hypermutation clusters of isoforms in human liver cancer cells.
Silvia LiuYan-Ping YuBao-Guo RenTuval Ben-YehezkelCaroline ObertMat SmithWenjia WangAlina OstrowskaAlejandro Soto-GutierrezJian-Hua LuoPublished in: eLife (2024)
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.
Keyphrases
- single cell
- rna seq
- genome wide
- high throughput
- copy number
- genome wide identification
- single molecule
- dna methylation
- endothelial cells
- binding protein
- genome wide analysis
- gene expression
- cell proliferation
- oxidative stress
- cell cycle arrest
- mass spectrometry
- magnetic resonance
- gram negative
- big data
- transcription factor
- cell death
- small molecule
- squamous cell
- contrast enhanced
- genetic diversity