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Novel transmission routes can allow infectious diseases to spread, often with devastating consequences. Ectoparasitic varroa mites vector a diversity of RNA viruses, having switched hosts from the eastern to western honey bees (Apis cerana to Apis mellifera). They provide an opportunity to explore how novel transmission routes shape disease epidemiology. As the principal driver of the spread of deformed wing viruses (mainly DWV-A and DWV-B), varroa infestation has also driven global honey bee health declines. The more virulent DWV-B strain has been replacing the original DWV-A strain in many regions over the past two decades. Yet, how these viruses originated and spread remains poorly understood. Here, we use a phylogeographic analysis based on whole-genome data to reconstruct the origins and demography of DWV spread. We found that, rather than reemerging in western honey bees after varroa switched hosts, as suggested by previous work, DWV-A most likely originated in East Asia and spread in the mid-20th century. It also showed a massive population size expansion following the varroa host switch. By contrast, DWV-B was most likely acquired more recently from a source outside East Asia and appears absent from the original varroa host. These results highlight the dynamic nature of viral adaptation, whereby a vector’s host switch can give rise to competing and increasingly virulent disease pandemics. The evolutionary novelty and rapid global spread of these host–virus interactions, together with observed spillover into other species, illustrate how increasing globalization poses urgent threats to biodiversity and food security.

As a phoretic parasite and virus vector, the mite Varroa destructor and the associated Deformed wing virus (DWV) form a lethal combination to the honey bee, Apis mellifera. Routine acaricide treatment has been reported to reduce the diversity of mites and select for tolerance against these treatments. Further, different DWV strains face selective pressures when transmitted via mites. In this study, the haplotypes of Varroa mites and associated DWV variants were quantified using long reads. A single haplotype dominated the mite mitochondrial gene cytochrome oxidase subunit I, reflecting an ancient bottleneck. However, highly polymorphic genes were present across the mite genome, suggesting the diversity of mites could be actively maintained at a regional level. DWV detected in both mites and honey bees show a dominant variant with only a few low-frequency alternate haplotypes. The relative abundances of DWV haplotypes isolated from honey bees and mites were highly consistent, suggesting that some variants are favored by ongoing selection.

Additional file of Genomic survey of the ectoparasitic mite Varroa destructor, a major pest of the honey bee Apis mellifera

Supplementary figures

Additional file 4 : Supplemental Table 3. Common genes identified in multiple studies that measured impacts of disease on honey bee gene expression.

Additional file 7:Microsatellite loci used in Varroa destructor polymorphism survey. Table lists contig containing the microsatellite locus, forward and reverse primer sequences, expected product size based on the reference contig, and the 5' start coordinate on the contig for the forward primer. (PDF 12 KB)

Additional file 5 : Supplemental Text 1. Additional textual highlights of our results regarding individual genes found associated with honey bee mite and virus interactions in prior work.

Additional file 1:Annotation statistics for filtered high G+C contigs. Annotation statistics derived from the BLAST2GO annotation tool [34]. A. Distribution of BLASTX hits (E ≤ 10-10) by organism. Note that the "Others" category is typically the most abundant in this type of analysis because of the wide taxonomic distributions of many conserved proteins. B. Distribution of BLASTX hits by sequence similarity score. C. Distribution of BLASTX hits by expectation. (PDF 2 MB)

Additional file 1 : Fig. S1. Heatmap of the sample-to-sample distance in R_mite v. R_control and S_mite v. S_control samples compiled using the R package DESeq2 with a customized map function, ( http://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#heatmap-of-the-sample-to-sample-distances ). Fig. S2. A) Principal Component Analysis of Gene Expression Data produced by DESeq 2 for R_mite, R_control, S_mite, and S_control. Note that PC1 captures 74% of the total variance between the samples, and shows the extreme divergence of R_mite from S_mite and S_control. PC2 provides differentiation of R_control from R_mite, revealing much of the gene expression differences attributable to mite infestation of the R genetic background. B) Principal Component Analysis of Differential Gene Expression data, contrasting R bees injected with virus, R_Virus, S bees injected with virus, S_Virus, and R & S bees injected only with a phosphate buffer solution, R_PBS and S_PBS; R_Virus and S_Virus are divergent in RNA sequencing data that comprise principal component 1; Principal component 2 captures the different responses to virus versus control injection in the R samples, and differences between the two S samples in response to buffer injection. Fig. S3. a) Scatterplot in semantic space of GO BP enrichment for UP in R_virus v. S_virus, FDR 1.5. b) Scatterplot in semantic space of GO MF enrichment from HymenopteraMine set operation of Asymmetric Difference of UP in R_virus v. S_virus MINUS UP in R_virus v. R_PBS, genes with FDR 1.5. Fig. S4. A) Mean Deformed wing virus levels separated by colony and by injection of viruses versus control (PBS). Diamond plot points indicate 95% confidence intervals B) Individual means and standard error estimates for each set of eight bees by colony and virus exposure.

Additional file 2 File S2 code used for the statistics.

International audience; Insects and their arthropod relatives including mites, spiders, and crustaceans play major roles in the world's terrestrial, aquatic, and marine ecosystems. Arthropods compete with humans for food and transmit devastating diseases. They also comprise the most diverse and successful branch of metazoan evolution, with millions of extant species. Here, we describe an international effort to guide arthropod genomic efforts, from species prioritization to methodology and informatics. The 5000 arthropod genomes initiative (i5K) community met formally in 2012 to discuss a roadmap for sequencing and analyzing 5000 high-priority arthropods and is continuing this effort via pilot projects, the development of standard operating procedures, and training of students and career scientists, With university, governmental, and industry support, the i5K Consortium aspires to deliver sequences and analytical tools for each of the arthropod branches and each of the species having beneficial and negative effects on humankind.

Background The first generation of genome sequence assemblies and annotations have had a significant impact upon our understanding of the biology of the sequenced species, the phylogenetic relationships among species, the study of populations within and across species, and have informed the biology of humans. As only a few Metazoan genomes are approaching finished quality (human, mouse, fly and worm), there is room for improvement of most genome assemblies. The honey bee (Apis mellifera) genome, published in 2006, was noted for its bimodal GC content distribution that affected the quality of the assembly in some regions and for fewer genes in the initial gene set (OGSv1.0) compared to what would be expected based on other sequenced insect genomes. Results Here, we report an improved honey bee genome assembly (Amel_4.5) with a new gene annotation set (OGSv3.2), and show that the honey bee genome contains a number of genes similar to that of other insect genomes, contrary to what was suggested in OGSv1.0. The new genome assembly is more contiguous and complete and the new gene set includes ~5000 more protein-coding genes, 50% more than previously reported. About 1/6 of the additional genes were due to improvements to the assembly, and the remaining were inferred based on new RNAseq and protein data. Conclusions Lessons learned from this genome upgrade have important implications for future genome sequencing projects. Furthermore, the improvements significantly enhance genomic resources for the honey bee, a key model for social behavior and essential to global ecology through pollination.