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      Virus replication in the honey bee parasite, Varroa destructor

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          ABSTRACT

          The ectoparasitic mite Varroa destructor is the leading threat to the health of Western honey bees ( Apis mellifera) primarily through its action as a vector of viruses. However, it is unclear which of the viruses transmitted by V. destructor actively infect and replicate in mites, which could facilitate increased transmission. To better understand the role of V. destructor as a vector, we took advantage of differences between bee and mite antiviral RNA interference pathways to identify the host specificity of replicating viruses. We used small RNA sequencing of individual V. destructor mites to examine viral small interfering RNA (vsiRNA) profiles of deformed wing virus genotypes (DWV-A and DWV-B), associated with colony declines, as well as nine other viruses present in our samples. We found active replication of six V. destructor-associated viruses, including a novel virus, Varroa destructor virus 9 (VDV-9), and replication of two honey bee-associated viruses, including both DWV-A and -B genotypes, confirming that mites are biological vectors for important bee pathogens. We show that the antiviral RNAi response can be used to define the host range of viruses in host-parasite interactions, such as honey bees and their parasites, enabling a better understanding of the role of a vector in the evolution and spread of honey bee pathogens.

          IMPORTANCE

          The parasitic mite Varroa destructor is a significant driver of worldwide colony losses of our most important commercial pollinator, the Western honey bee Apis mellifera. Declines in honey bee health are frequently attributed to the viruses that mites vector to honey bees, yet whether mites passively transmit viruses as a mechanical vector or actively participate in viral amplification and facilitate replication of honey bee viruses is debated. Our work investigating the antiviral RNA interference response in V. destructor demonstrates that key viruses associated with honey bee declines actively replicate in mites, indicating that they are biological vectors, and the host range of bee-associated viruses extends to their parasites, which could impact virus evolution, pathogenicity, and spread.

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

              Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review and editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: Writing – review and editing
                Role: InvestigationRole: MethodologyRole: Writing – review and editing
                Role: ResourcesRole: Writing – review and editing
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: Writing – review and editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review and editing
                Role: Editor
                Journal
                J Virol
                J Virol
                jvi
                Journal of Virology
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                0022-538X
                1098-5514
                December 2023
                15 November 2023
                15 November 2023
                : 97
                : 12
                : e01149-23
                Affiliations
                [1 ]School of Life and Environmental Sciences, University of Sydney; , Sydney, New South Wales, Australia
                [2 ]Institute of Plant Genetics, Heinrich-Heine University; , Duesseldorf, Germany
                [3 ]Academic Support Unit, Research and Advanced Instrumentation, University of the Sunshine Coast; , Sippy Downs, Queensland, Australia
                Wageningen University & Research; , Wageningen, the Netherlands
                Author notes
                Address correspondence to Emily J. Remnant, emily.remnant@ 123456sydney.edu.au

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0002-3808-8365
                Article
                01149-23 jvi.01149-23
                10.1128/jvi.01149-23
                10746231
                37966226
                a64bebd7-be41-4413-a3d7-89ad4d0f3f60
                Copyright © 2023 Damayo et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 26 July 2023
                : 06 October 2023
                Page count
                supplementary-material: 2, authors: 6, Figures: 5, Tables: 1, References: 99, Pages: 20, Words: 12186
                Funding
                Funded by: Faculty of Science, University of Sydney;
                Award ID: Re-entry Fellowship
                Award Recipient :
                Funded by: School of Life and Environmental Sciences, University of Sydney;
                Award ID: Seed Funding Grant
                Award Recipient :
                Categories
                Cellular Response to Infection
                evolution, Evolution
                Custom metadata
                December 2023

                Microbiology & Virology
                honey bee viruses,antiviral sirna,rna interference,mite vector,virus replication

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