Novel Long-Read Sequencing Method for Characterisation of Hepatitis B Transcripts Show High Expression of Chimeric HBV/Human RNA.
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Stenbäck JB, Ringlander J, Andersson M, Thomsen JHD, Abrahamsson S, Rydell GE, Lindh M
Liver Int. 46 (3) e70521 [2026-03-00; online 2026-02-13]
Hepatitis B virus (HBV) genomes integrated into human DNA significantly contribute to surface antigen (HBsAg) production and may drive hepatocellular carcinoma (HCC). Long-read sequencing methods like Nanopore offer advantages over short-read next-generation sequencing (NGS) by providing continuous reads of whole transcripts, but their application to HBV integration analysis remains limited. To develop and apply a method combining semi-nested PCR with Nanopore sequencing to analyse HBV transcripts, including canonical RNA, HBV-human fusion transcripts, and spliced forms in patients with HBV- or hepatitis D virus (HDV)-induced liver disease. Nine liver-transplanted patients with HBV- or HDV-related cirrhosis or HCC were studied. Semi-nested PCR was used to amplify all HBV transcripts, followed by Nanopore sequencing. The approach allowed differentiation between canonical (cccDNA-derived) and fusion transcripts. Reads containing the 3' redundancy beyond nucleotide 1826, exclusive to cccDNA-derived RNA, were quantified to determine the source of HBV RNA. Unique and total HBV-human fusion RNA reads correlated with serum levels of HBV DNA and HBsAg. Integration-derived RNA accounted for a median of 97% (range: 16%-100%) of HBV RNA. PreS1 RNA levels were much lower than preS2 but sufficient for HDV particle production in an HDV patient without cccDNA-derived transcripts. This method enables a simplified and comprehensive analysis of HBV transcripts. The results highlight the predominance of integration-derived RNA and support the presence of cccDNA-independent hepatitis D virus production. Nanopore sequencing offers valuable insights into HBV and HDV biology, supporting its role in understanding viral pathogenesis and therapeutic targeting.
Clinical Genomics [Collaborative]
Clinical Genomics Gothenburg [Collaborative]
PubMed 41684309
DOI 10.1111/liv.70521
Crossref 10.1111/liv.70521