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Between- and within-host mutation of dengue virus.
Sachith Maduranga1, Braulio Mark Valencia2, Chathurani Sigera3
1School of Biomedical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, 2052, NSW, Australia; Kirby Institute, University of New South Wales, Sydney, 2052, NSW, Australia.
Virology
|November 29, 2025
Summary
Dengue virus (DENV) genomes show high mutation rates, with haplotype analysis revealing more mutation hotspots than consensus sequencing. This highlights the importance of haplotype-level analysis for understanding viral evolution and diversity in acute infections.
Area of Science:
- Virology
- Genomics
- Molecular Biology
Background:
- RNA viruses, including Dengue virus (DENV), exhibit high mutation rates, leading to quasi-species within hosts.
- Previous studies have focused on consensus sequences, potentially overlooking crucial genomic variability at the haplotype level.
Purpose of the Study:
- To characterize mutation hotspots in DENV genomes at both consensus and haplotype levels.
- To compare the insights gained from consensus versus haplotype sequencing in acute viral infections.
Main Methods:
- Near full-length DENV genomes were sequenced using Oxford Nanopore Technology (ONT).
- Consensus sequences were generated using Minimap-2; haplotypes were reconstructed with Nano-Q.
- Genomic variability was assessed using Shannon Entropy (SE), and diversifying selection was identified using Datamonkey suite tools (FEL, MEME, FUBAR).
Main Results:
- Haplotype analysis revealed more sites with high mutability and codons under diversifying selection compared to consensus analysis.
- At the consensus level, NS2A showed the most high-entropy sites (adjusted for gene length); at the haplotype level, NS1 showed the most.
- Ninety DENV genomes (DENV1, DENV2, DENV3) from Sri Lankan patients were successfully characterized.
Conclusions:
- Haplotype-level analysis is crucial for uncovering the full spectrum of viral genomic variability in acute RNA virus infections.
- Consensus-level analysis may obscure significant mutational hotspots and selective pressures present within viral populations.
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