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Detection of Low Copy Number Integrated Viral DNA Formed by In Vitro Hepatitis B Infection
Published on: November 7, 2018
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A hepatitis B virus (HBV) sequence variation graph improves sequence alignment and sample-specific consensus sequence
Dylan Duchen1, Steven Clipman2, Candelaria Vergara1
1Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, 21205, USA.
Biorxiv : the Preprint Server for Biology
|January 30, 2023
Summary
Hepatitis B virus (HBV) genome analysis is improved using graph-based alignment. This method enhances characterization of viral diversity for better drug development in chronic HBV infection.
Area of Science:
- Virology
- Genomics
- Bioinformatics
Background:
- Chronic Hepatitis B virus (HBV) infection affects over 250 million globally, lacking curative treatments.
- Viral diversity significantly impacts HBV pathogenesis and immune response.
- Current HBV sequencing analysis relies on linear reference genomes, limiting comprehensive genetic characterization.
Approach:
- Investigated graph-based alignment methods using simulated and real HBV sequencing data.
- Compared graph alignment to traditional linear reference-based alignment.
- Utilized phylogenetically representative 'genome graphs' for alignment.
Key Points:
- Graph-based alignment overcomes reference ambiguity inherent in linear approaches.
- This method improves the accuracy of aligning HBV sequencing data.
- Facilitates the creation of precise, sample-specific consensus sequences for HBV.
Conclusions:
- Graph-based alignment offers a superior approach for HBV genome characterization at population and intra-host levels.
- Enhanced genetic analysis can accelerate the development of new therapies for chronic HBV infection.
- This methodology holds broad potential for host-pathogen research beyond HBV.
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