An ONT sequencing framework for hantavirus genome assembly, variant analysis, and defective viral genome characterization from whole-segment amplicons

Authors

Vandenabeele, L., Twohig, F. M., Tuiskunen Back, A., Sjoblom, M., Lantto, R., Svala, G., Tynell, J., Broddesson, S., Dyrdak, R., Christ, W., Riesle-Sbarbaro, S., Prescott, J. B., Bradfute, S. B., Depledge, D. P., Nilsson-Payant, B. E.

Abstract

Orthohantaviruses are zoonotic, tri-segmented negative-sense RNA viruses of rodents and other small mammals that can cause severe human disease. Whole genome sequencing remains difficult because of low viral loads, high sequence diversity, and an inherent instability of the viral L segment. Current tiled amplicon and hybrid-capture approaches do not capture the heterogeneity of virus populations, including defective viral genomes (DVGs), which have never been described for hantaviruses. Here, we present an Oxford Nanopore Technologies sequencing framework based on universal reverse transcription primers targeting the conserved genome termini of orthohantaviruses and a single species-specific primer pair per segment, enabling amplification and sequencing of complete S, M, and L segments. We also developed an accompanying bioinformatic pipeline that performs reference-guided assembly of hantavirus genomes, consensus generation, variant calling, and DVG classification using the newly developed ORCHID classification pipeline. We applied this approach to diverse Puumala virus strains from infected cell cultures and bank voles, to representative Old World and New World orthohantaviruses, and to highly pathogenic New World viruses in vivo. In all cases we were able to accurately reconstruct full hantavirus genomes. Notably, we found that hantavirus populations contain highly abundant DVGs and conserved L segment deletions, whereas the S and M segments remained largely intact. Together, this work provides a low-cost, broadly applicable and easily customisable workflow for hantavirus genomics and reveals DVGs as a previously unrecognized feature of hantavirus populations.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 21 Oct 2026.

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