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Amplicon-based analyses of single-nucleotide polymorphisms reveal the genetic structure of a forest insect baculovirus

Christian Oehlmann,Jiangbin Fan,Michael J Rihlmann,Hannes Lemme,Jörg Müller,Birgit Ruoff,J. Wennmann,Johannes A. Jehle

Published 2025 in Virus Evolution

ABSTRACT

Abstract Amplicon-based next-generation sequencing (aNGS) is a powerful tool in diagnostics and genetic studies. We developed an aNGS approach to study the population structure of the Lymantria dispar multiple nucleopolyhedrovirus (LdMNPV), a specific pathogen of the spongy moth Lymantria dispar, a devastating lepidopteran pest in European, Asian, and American deciduous forests. Naturally occurring pathogens, such as LdMNPV, are frequently reported to cause epizootics and a rapid decline of insect pest populations. DNA samples of pooled LdMNPV-infected larvae from forest regions in Northern Bavaria (Germany) were subjected to whole genome sequencing (WGS) and aNGS optimization. Then, five marker regions were identified in the genome of LdMNPV for PCR amplification, covering 21 highly specific single-nucleotide polymorphism (SNP) positions that enabled comprehensive analysis at the intra- and intersample levels. These markers were used in aNGS analyses of 70 single larvae collected in 12 forest sites, followed by SNP-based hierarchical clustering on principal components (HCPC). This approach identified three LdMNPV population clusters consisting of homogenous (pure) and heterogeneous (mixed) LdMNPV samples. To explain the genetic variability within each sample, a model based on linear optimization was developed and validated by comparing the predictions from aNGS and WGS data. The analyses showed that LdMNPV from Bavarian forests carried genetic variants highly similar to those present in the commercial product Gypchek®, developed for biocontrol. The distribution of genetic characteristics showed some trends of geographic and temporal prevalence, which are indicative of short-distance and long-distance transmission. The aNGS approach offers a fast, cost-effective, and comprehensive insight into the natural population structure of LdMNPV.

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