- Research article
- Open Access
Genomic survey of the ectoparasitic mite Varroa destructor, a major pest of the honey bee Apis mellifera
© Cornman et al; licensee BioMed Central Ltd. 2010
- Received: 18 March 2010
- Accepted: 25 October 2010
- Published: 25 October 2010
The ectoparasitic mite Varroa destructor has emerged as the primary pest of domestic honey bees (Apis mellifera). Here we present an initial survey of the V. destructor genome carried out to advance our understanding of Varroa biology and to identify new avenues for mite control. This sequence survey provides immediate resources for molecular and population-genetic analyses of Varroa-Apis interactions and defines the challenges ahead for a comprehensive Varroa genome project.
The genome size was estimated by flow cytometry to be 565 Mbp, larger than most sequenced insects but modest relative to some other Acari. Genomic DNA pooled from ~1,000 mites was sequenced to 4.3× coverage with 454 pyrosequencing. The 2.4 Gbp of sequencing reads were assembled into 184,094 contigs with an N50 of 2,262 bp, totaling 294 Mbp of sequence after filtering. Genic sequences with homology to other eukaryotic genomes were identified on 13,031 of these contigs, totaling 31.3 Mbp. Alignment of protein sequence blocks conserved among V. destructor and four other arthropod genomes indicated a higher level of sequence divergence within this mite lineage relative to the tick Ixodes scapularis. A number of microbes potentially associated with V. destructor were identified in the sequence survey, including ~300 Kbp of sequence deriving from one or more bacterial species of the Actinomycetales. The presence of this bacterium was confirmed in individual mites by PCR assay, but varied significantly by age and sex of mites. Fragments of a novel virus related to the Baculoviridae were also identified in the survey. The rate of single nucleotide polymorphisms (SNPs) in the pooled mites was estimated to be 6.2 × 10-5per bp, a low rate consistent with the historical demography and life history of the species.
This survey has provided general tools for the research community and novel directions for investigating the biology and control of Varroa mites. Ongoing development of Varroa genomic resources will be a boon for comparative genomics of under-represented arthropods, and will further enhance the honey bee and its associated pathogens as a model system for studying host-pathogen interactions.
- Codon Usage
- Varroa Mite
- Mite Control
- Individual Mite
- Abundant Transposable Element
Honey bees (Apis mellifera) are an important agricultural commodity providing honey, other bee products, and pollination services [1, 2]. Domesticated honey bees in the United States and elsewhere have been in decline in recent years, despite an increasing need for honey bee pollination services . This fact is often blamed on increasing challenges from pests and pathogens, as well as episodes of severe decline such as the enigmatic 'colony collapse disorder' (CCD) .
Among the most detrimental of honey bee pests is the ectoparasitic mite Varroa destructor. V. destructor and its closely related congener, V. jacobsoni, are native to Asia where they parasitize the Eastern honey bee, A. cerana. V. destructor was only identified as a morphologically and genetically distinct species from V. jacobsoni relatively recently . V. destructor began to appear in Asian colonies of A. mellifera during the last century and is now widely distributed, inadvertently aided by trade in bees and bee products.
Mite-infested bee colonies suffer directly from parasitism of pupae and adults, and indirectly from viral and microbial pathogens that the mites vector [7, 8]. Feeding by mites induces an immunosupression in bees that leads to increased titres of pre-existing infections , further compounding their impact. The economic toll of V. destructor on apiculture is estimated to be millions of U.S. dollars per year, and chemical control agents are worrisome both for their collateral effects on bee health and the potential for honey contamination .
Varroa-honey bee interactions are mediated to a large extent via chemical cues, and bees have numerous mechanisms to control Varroa populations (reviewed in [5, 11]). Varroa mites reproduce on honey bee pupae, using chemical signals produced by the developing honey bee larvae to target appropriately aged hosts. The mature female offspring of reproductive Varroa emerge with the adult honey bee, and subsequently move to nurse bees (which are engaged in brood care), thereby allowing them to remain in close proximity to the brood [12, 13]. Honey bees resist 'Varroatosis', the infestation of colonies by Varroa mites, via grooming of adult infested bees, removal of infested pupae (hygienic behavior), and physiological resistance mechanisms . Recent successes in breeding Varroa-resistant bees, including the selection of 'Russian' bees with longstanding exposure to mites [14, 15], indicate that a better understanding of how bees and mites interact with each other can lead to novel management strategies.
Comparative studies of the fragility of the A. mellifera - V. destructor interaction, which has apparently prevented most Asian lineages of V. destructor as well as other Varroa species from colonizing A. mellifera[6, 16–18], supports the hypothesis that mite olfaction or other requirements for mite reproduction may be suitable control targets. A molecular-genetic approach to develop such innovative controls would clearly benefit from further insights into Varroa genomics, which could be exploited in conjunction with tools already extant for honey bee. Prior to this study, genes for only two non-mitochondrial V. destructor proteins had been deposited in GenBank, a sodium channel gene (AAN37408.1) and a glycoprotein (ACU30143.1). Genome sequencing will greatly expand this gene catalog, and may also uncover unforeseen targets for novel and specific acaricides, such as divergence in metabolic pathways between mites and bees or the discovery of important microbial interactions.
High-throughput, shotgun sequencing of whole genomes allows the rapid identification of thousands of genic sequences, greatly facilitating molecular and population-genetic studies that would otherwise proceed in piecemeal and laborious fashion. Here we report an initial sequence survey of the V. destructor genome in conjunction with a flow-cytometric estimate of genome size. Our annotations and analysis should aid investigators seeking molecular approaches to mite control. They will also provide a guide for a planned full genome project for this species , one of several genomics initiatives that are unfolding the molecular interactions between honey bees and a constellation of potentially interacting pathogens [4, 7, 20, 21].
Of the eight genetically distinct lineages of V. destructor that parasitize A. cerana in Asia, two have been identified on A. mellifera[6, 18, 22, 23]. Anderson  designated these lineages the Japan (J) and Korea (K) 'haplotypes' in reference to mitochondrial DNA makers, but they are concordantly distinct at nuclear markers as well . Genetic differentiation within lineages is low , likely reflecting the population-genetic impact of life-history traits  such as full-sib mating and male haploidy , as well as potential population bottlenecks tied to host-shift events and subsequent range expansion [18, 23]. In this study, we have analyzed the K haplotype of V. destructor from A. mellifera, the predominant haplotype presently found in North America . We have identified over 13,000 contigs with sequences homologous to other species; many of these have recognized domains and/or functional annotations transferred from other arthropods. Interestingly, V. destructor appears to have experienced a higher rate of protein evolution than Ixodes scapularis since their divergence from the most recent common ancestor over 300 million years ago. Sequences attributable to a range of microbes were identified, including a large number of sequences from one or more novel actinomycete bacteria, the presence of which was confirmed by PCR in individual mites but not in adult honey bees. We also identified a novel virus related to the Baculoviridae that was abundant in the genomic survey. Finally, we found a low level of nucleotide polymorphism in the sequenced sample of ~1,000 mites, consistent with expectation . This bodes well for future efforts to sequence and assemble a reference genome for this species and to identify genetic variation that correlates with host-interaction traits among Varroa strains and species.
Sequencing, assembly, and filtering
Statistics of the Varroa destructor genome sequence survey
Number of contigs
Sum of contig length (Mbp)
Maximum contig length (bp)
Mean contig length (bp)
N50 contig length (bp)
Contigs ≥ 1,000 bp
Contigs ≥ 5,000 bp
Contigs ≥10,000 bp
As detailed in the Methods, the small physical size of V. destructor required the collection of large numbers of mites from multiple honey bee colonies in order to obtain sufficient DNA for this survey. While mites were carefully cleaned and examined under a dissection microscope to remove any non-target organisms that might have been collected inadvertently, whole-organism extractions necessarily entail the possible inclusion of associated microbes, particularly gut microbes. The gut flora may include symbiotic, commensal, and pathogenic prokaryotes and eukaryotes, which are often important components of the ecology of arthropod species. We therefore filtered the assembled contigs based on G+C content, coverage, and sequence homology, in order to minimize the mis-annotation of microbial sequences as V. destructor, as well as to identify novel microbes of interest. Comparable strategies have been successfully applied to the classification of metagenomic samples (e.g., ).
The strong secondary mode of high G+C contigs in Figure 3 and taxonomically coherent BLAST hits (Figure 4) suggests that one or more Actinomycete species were particularly abundant in the sequenced sample. Together these contigs totaled ~300 Kbp of sequence, which were further analyzed with the BLAST2GO annotation tool . Additional file 1 includes BLAST2GO output that summarizes the distribution of BLASTX hits among these contigs with respect to matched species, expectation, and sequence similarity. All of the most frequently matched organisms are members of Actinomycetales. Ribosomal sequences were also found that had strong similarity to this clade, the closest match (98% identity) being to the genus Segniliparus.
Frequency of infection of individual mites by a novel actinomycete bacterium identified in the V. destructor sequence survey
Evidence for a novel virus related to the Baculoviridae in the sequenced sample of Varroa destructor
Pfam domain description
Reported in Baculoviridae?
Ribonucleotide reductase, barrel domain
Ribonucleotide reductase, small chain
Kinesin motor domain
BRO family, N-terminal domain
Chitin binding domain
Pacifastin inhibitor (LCMII)
Baculovirus hypothetical protein
Matrixin (matrix metalloprotease)
Protein of unknown function (DUF666)
Protein of unknown function (DUF686)
Zinc knuckle (retroviral gag protein)
Baculovirus BRO family, N-terminal domain
Collagen triple helix repeat
Collagen triple helix repeat
Amelogenin (cell adhesion protein)
Alpha/beta hydrolase fold
Phage integrase family
Collagen triple helix repeat
Collagen triple helix repeat
Protein of unknown function (DUF686)
Matrixin (matrix metalloprotease)
V. destructor annotation and evolutionary comparison with other arthropods
We used BLASTX (for genomic contigs) and BLASTP (for ORFs of 90 residues or more) to identify genic sequences in the assembly. Sequences were initially searched against a database of five arthropod peptide predictions (Drosophila melanogaster, Anopheles gambiae, Pediculus humanus [a representative non-Dipteran insect], Daphnia pulex, and I. scapularis), with a minimum expectation of 10-8, and then secondarily against the eukaryotic Refseq database at the same expectation. In total, 13,031 contigs were identified with BLAST-detected similarity to database sequences (listed in Additional file 3). These contigs had a median length of 1,967 bp and summed to 31.3 Mbp, and represent roughly 10% of the total assembled sequence (294 Mbp after filtering). ORFs with significant Pfam domains are listed in Additional file 4 and the sequences are provided in Additional file 5.
The Varroa destructor glycolysis/gluconeogenesis pathway is well represented in the genome sequence survey
Annotated in A. gambiae
Annotated in I. scapularis
Closest contig match in the V. destructor assembly (BLASTX)
glyceraldehyde 3-phosphate dehydrogenase
pyruvate dehydrogenase E1 component, subunit alpha
pyruvate dehydrogenase E1 component, subunit beta
pyruvate dehydrogenase E2 component
Protein-encoding transposable elements in V. destructor
Nucleotide polymorphism in V. destructor
Life-history traits of V. destructor that act to reduce genetic polymorphism within family lineages include male haploidy  and a predominance of full-sib mating. Genetic variation within a population can nonetheless be high in principle if populations are admixtures of distinct lineages. High-frequency polymorphisms, whether due to admixture or heterozygosity, can cause difficulties for shotgun assembly algorithms because they weaken the computational discrimination of allelic and non-allelic sequences. On the other hand, polymorphisms may be useful as genetic markers for population-genetic studies. It is therefore of interest to estimate levels of genetic polymorphism in the sequenced sample (~1,000 mites drawn from three adjacent colonies). We used the program SWAP454  to estimate the occurrence of moderate- to high-frequency SNPs, i.e. those present in reads at a minimum ratio of 0.1 to the assembly reference base. SNP calls also required a minimum of two reads with the alternative base, but did not require reads in both directions. Polymorphisms meeting these parameters occurred at a rate of 6.2 × 10-5 per base pair. Given a median per-contig coverage of 5.0× in the final assembly (Table 1), our ability to detect low frequency polymorphisms is of course limited, but such polymorphisms contribute much less ambiguity to genome assembly.
To further investigate the potential for sequence polymorphism within a V. destructor population, we identified trinucleotide microsatellite loci in the genomic sequence and obtained amplification products for ten of these (see Methods). Consistent with our estimate of SNP frequency, we found no polymorphism at these loci in 65 individual mites collected from research apiaries at the USDA-ARS facility in Beltsville, Maryland, the source of the genome survey pool.
V. destructor is considered the most damaging honey-bee pest and has become widespread since its host shift from A. cerana less than a century ago. Resistance to common acaricides has already appeared , and the development of new control strategies are hampered by our limited knowledge of the V. destructor - A. mellifera interaction, particularly at the genetic level. The present genome survey makes available a large number of genic sequences for analysis and manipulation by the community of researchers. The contigs we obtained from low-coverage shotgun sequencing were short, as expected, such that few complete gene models are likely to be annotated from this data set. Nonetheless, our assembly enables the identification of genes of interest and the cloning of complete transcripts as they are needed. The assembly will also greatly assist the validation and annotation of transcriptome surveys and can support proteomic initiatives. We hope the resources provided here will aid investigators already tackling the problem of mite control with molecular methods as well as encourage the involvement of others.
Genetic approaches to the study of mite control are promising for a number of reasons. Successful reproduction of Varroa mites requires precise coordination with the care of honey bee brood and a sophisticated evasion of honey bee defences. Chemosensory genes are among those likely to play crucial roles in this process. At the phenotypic level, there is known variation among Varroa haplotype groups and species in their ability to successfully parasitize A. mellifera[16, 17], as well as known variation in the resistance of honey bee strains [14, 15, 54, 55]. While Varroa mites are not tractable to controlled crosses, associative mapping of traits such as reproductive success on different hosts remains an attractive possibility, as is the mapping of resistance traits in honey bee. Resequencing efforts are needed to uncover genetic variation that can be exploited for these purposes. Those efforts would also contribute to a better understanding of the demographic history of V. destructor and to species relationships within the genus. Polymorphic markers within haplotype groups would aid investigations of the population biology of the species, particularly in light of the difficulty of observing or manipulating Varroa mites in their habitat. For example, estimates of outcrossing and migration might be relevant to the design of new mitigation strategies, particularly if the evolution of resistance traits is expected. While consistent with previous work  that found low genetic polymorphism within the predominant V. destructor lineage, our analysis nonetheless enables genome-scale mining of markers for population-genetic studies.
Our analysis of conserved peptide blocks showed a higher rate of protein evolution within the Varroa lineage relative to Ixodes. It remains to be clarified whether this level of sequence divergence is characteristic of mites or peculiar to the Varroa lineage. Similarly, whether this result correlates with divergence in other aspects of genome evolution, such as exon structure and regulatory features, will be an important question to pursue as annotations improve for both species. As genomic resources for V. destructor continue to improve, opportunities for evolutionary comparisons with other arthropods will be enriched. Such comparisons are of tremendous value because they can expose conserved elements that might otherwise elude detection by direct experiment, and they reveal the relative rates at which various classes of homologous sequence diverge. Varroa mites and others in the Parasitiformes comprise a lineage that diverged from ixodid ticks over 300 million years ago , while the chelicerates as a whole branched from the insects and crustacea 725 million years ago . Consequently, as a representative of the Parasitiformes, Varroa provides a key evolutionary landmark for comparative studies across arthropods currently targeted for genomic analyses.
An accessory goal of genome projects targeting arthropod pests is the identification of novel microbes and viruses that may be relevant to the epidemiology of vectored diseases, or that lend themselves to biocontrol programs. A significant finding of this study was the discovery of an actinomycete bacterium that infects V. destructor at intermediate frequencies (albeit presumably at high titer given its abundance in the genome sequence) but apparently does not infect A. mellifera at appreciable levels. However, these findings are preliminary and await a more systematic survey of infection among mites and bees. Future research should also be directed toward isolating this bacterium and assessing the fitness consequences of infection. Further characterization of the putative baculovirus identified in this survey is similarly a priority.
This work contributes to the relatively small body of genomic studies to date that have applied next-generation sequencing to a complex eukaryotic genome phylogenetically distant from other reference genomes. As the costs and technical requirements for genome sequencing continue to decline, such studies will undoubtedly become commonplace. In many cases, the sequencing of a single genotype or inbred group will not be feasible, and there may also be a significant metagenomic contribution from associated microbes. While these factors introduce new challenges, our results underscore the utility of these methods for rapidly advancing the study of non-model organisms.
Our results have provided general tools for the research community and novel directions for investigating the biology and control of Varroa mites. Ongoing development of Varroa genomic resources will be a boon for comparative genomics of under-represented arthropods, and will further enhance the honey bee and its associated pathogens as a model system for studying host-pathogen interactions.
Samples were prepared for flow cytometry as previously described . For each replicate, the synganglion of a mature female V. destructor was placed along with the head of a mature female D. virilis into a 2 ml tissue grinder (Kimble-Kontes) containing 1 ml of cold Galbraith buffer, and stroked 15 times with the A pestle to release nuclei. The preparation was filtered through 20 μm nylon and stained with prodidium iodide to a final concentration of 50 ppm. Stained samples were held on ice in the dark for 1-2 hr prior to analysis. The mean fluorescence of stained nuclei in replicate preparations of Varroa and D. virilis standard was quantified using a Coulter Epics Elite flow cytometer (Coulter Electronic), with excitation provided by a laser tuned at 488 nm and 25 mW. PI fluorescence at > 615 nm was detected by a photomultiplier screened by a long pass filter. To ensure that scoring included only intact nuclei free from cytoplasmic tags, counting was activated by red fluorescence (discrimination), and only (gated) nuclei with low forward and side scatter were included in the analysis. The positions of sample peaks relative to the D. virilis peak were verified by running samples without a standard. DNA content was determined from co-preparations as the ratio of the 2C Varroa peak to the 2C D. virilis peak times the 1C genome size of D. virilis (333 Mb, after ).
Sample preparation and sequencing
V. destructor mites were collected on two occasions for sequencing from infested colonies of the USDA-ARS Bee Research Laboratory apiaries in Beltsville, MD, USA in October, 2008. For each collection, 300 bees were placed into a 0.5 liter glass jar containing 40 g confectioner's sugar. The sugar and bees were thoroughly mixed by shaking the jar for 30 s. The sugar and phoretic mites were then separated from their bee hosts by shaking the jar contents through a 1 mm wire mesh placed at the jar opening. Mites were shaken into a small water bath, which was then poured through a cheesecloth filter and rinsed twice with sterile water to remove residual sugar. Live mites were then picked onto sterile tissue paper and frozen at -80°C until nucleic acid extraction.
To obtain sufficient high-quality DNA for six pyrosequencing runs, three separate DNA extractions were made from the collected mites. DNA from one sample of ~400 mites was extracted with DNAzol (Invitrogen) following the manufacturer's instructions. A second sample of ~400 mites was homogenized in 800 μl proteinase K buffer (10 mM NaCl, 10 mM Tris, 50 mM ethylenediamenetetracetic acid (EDTA), and 10 μg/ul proteinase K) and incubated 60 min at 55°C, vortexing every 20 min. Afterwards, 180 μl of 8 M potassium acetate was added and the sample incubated on ice for 30 min. After high-speed centrifugation, DNA was precipitated from the supernatant with ethanol and re-suspended in distilled, deionized water. A third sample of ~200 mites was homogenized in 500 μl hexadecyltrimethylammonuim bromide (CTAB) buffer (100 mM Tris-HCl at pH 8.0, 20 mM EDTA, 1.4 M NaCl, 2% CTAB, and 0.2% β-mercaptoethanol) and incubated 60 min at 65°C, vortexing every 20 min. An equal volume of 24:1 chloroform:isoamyl alcohol was then added and the sample centrifuged at high speed. DNA was precipitated from the supernatant with isopropanol and re-suspended in distilled, deionized water. For all extractions, DNA concentration and quality were evaluated with a Nanodrop ND-8000 spectrophotometer and were found to be comparable. DNA quality was also checked by gel electrophoresis.
Pyrosequencing was performed at the Institute for Genome Sciences, University of Maryland School of Medicine, on a Genome Sequencer FLX instrument (454 LifeSciences) using GS-FLX titanium reagents. DNA was prepared for emulsion PCR according to the manufacturer's protocols.
Assembly and analysis
Contigs were assembled with the CABOG package of Celera Assembler version 5.2 . The sequences were assembled iteratively, adjusting the assumed error rate incrementally between 0% and 6%. The assembly selected for analysis used a 1.5% error rate because this value maximized the length of the longest contig (18.7 Kbp). The weighted median N50 contig size was relatively stable across iterations at ~2.1 Kbp, meaning that half of the assembled bases were consistently contained in contigs of this size or larger across the different assemblies.
Contigs were screened to identify sequences of organisms that were considered potential contaminants a priori. For example, a number of contigs were found to be nearly identical to the honey bee reference genome . These fragments included low-copy genic sequences as well as ribosomal, nongenic, and mitochondrial sequence. PCR primers specific to A. mellifera sequences amplified genomic DNA extracted from adult female mites but not from embryos (data not shown), implying that the source of A. mellifera contamination is bee hemolymph consumed by mites. In contrast, searches against the genome sequences  of chalkbrood (Ascosphaera apis), a fungal pathogen of honey bees, and American foulbrood (Paenibacillus larvae), a bacterial pathogen, did not reveal the presence of these spore-dispersed microbes in the sample.
Distribution of contigs that were designated bacterial by BLAST analysis, sorted by phylum
Number of contigs
Because many organisms show distinct patterns of codon usage , we compared codon usage for ORFs from unfiltered contigs (putatively V. destructor) with those from putatively bacterial contigs. Only ORFs with BLAST-supported homology to GenBank sequences were used for this comparison. We used the program INCA  to plot the codon-usage statistic 'B' of  as a function of third-position G+C (GC3) content (Additional file 6). The value of B for a given ORF is a measure of how similar its codon usage is to the overall codon usage in the data set. GC3 is considered here because third positions are much less constrained by protein function than first and second positions, and thus more indicative of background composition biases. The distinct patterns observed for the two groups of ORFs provide complementary evidence that these sequences do in fact derive from different organisms. The plot also shows that a few ORFs from contigs considered to be Varroa by our filtering methods may in fact be bacterial in nature and merit further evaluation. Of course, BLAST-supported ORFs are only proxies for transcripts and thus individual points may be highly inaccurate. In general, however, genic sequences that are putatively from V. destructor have a cohesive pattern of codon usage that can be distinguished form at least some bacterial contaminants, regardless of detectable homology.
To confirm the presence in mites of the actinomycete bacterium and DNA virus identified in the assembly, individual eggs, nymphs, female adults, and male adults were collected from parasitized honey bee pupae. DNA for PCR was extracted from individual samples by grinding them in 200 μl of 5% Chelex-100 solution (Bio-Rad), incubating at 65°C for 30 min, pelleting the mixture by high-speed centrifugation, and taking a 1:10 dilution in water of the resulting supernatant. Primers for the putative actinomycete TIF3 locus were CCGATCTCGACCTTGTGGAA (forward) and CTCGGAACATGATCGTCACC (reverse), and for the ABC locus were GAGGTCCTCGTCTCCGAATG (forward) and CGATGTCCTGGATCCTCTGG (reverse). The amplified TIF3 product was confirmed by Sanger sequencing (GenBank:GU365869). Primers designed to amplify the putative Baculovirus targeted a ribonucleotide reductase small subunit gene (forward ACGAACGACTATCTAGCCATGAAC and reverse GTCCGTTTCGGAGTGCATGAC) and a thymidylate synthase gene (forward CGCATGTACCAACAACTCGTAC and reverse CACAGTTGGTGTAGCGCAGT). The identities of these products were also confirmed by Sanger sequencing (GenBank:GU980896 and GenBank:GU980897, respectively). All PCR reactions were performed using standard reagents and thermocycler protocols, with an annealing temperature of 54°C.
To identify conserved peptide blocks, we first identified V. destructor ORFs that were reciprocal best BLASTP matches with I. scapularis predicted peptides. These were then used to identify the closest homologs in Da. pulex, Dr. melanogaster, and P. humanus. Sequences were aligned by ClustalW and then trimmed to include only blocks of well conserved, unambiguously aligned sequence for which we could have reasonable confidence of orthology. Genetic-distance matrices were calculated for each block with the protdist program of the PHYLIP package , weighted by alignment length and summed, then normalized to a maximum distance of one. Unrooted dendrograms were constructed with the fitch and neighbor programs of the PHYLIP package, giving virtually identical branch lengths; the neighbor-joining dendrogram is shown in Figure 5.
Microsatellite loci used to assess polymorphism levels in V. destructor are characterized in Additional file 7. PCR amplifications consisted of 1 U Taq DNA polymerase with appropriate buffer, 1 mM dNTP, 2 mM MgCl2, 0.2 μM of each forward and reverse primer in a final reaction volume of 5 μl. Fluorescently labeled primers were mixed with unlabeled primers at a 12:20 ratio. Thermocycling was performed as follows: 96°C for 2 min., then 3 cycles of 96°C for 30 sec., 60°C for 30 sec. (-1°C/Cycle), 65°C for 1 min., followed by 35 cycles of 96°C for 30 sec., 56°C for 30 sec., 65°C for 1 min, and a final extension at 65°C for 2 min. PCR products were diluted 1:20 and 1 μl of this dilution was added to 10 μL formamide containing the LIZ size standard. Products were analyzed by capillary electrophoresis using an Applied Biosystems 3730XL instrument. Allele sizes were scored using ABI GeneMapper version 3.7 (Applied Biosystems).
Financial support for this survey and an ongoing full genome sequencing project provided by USDA-ARS and the USDA National Institute of Food and Agriculture (grant 2009-05254 to JDE, GH, CE and LB). Additional support was provided by NIH grant R01-LM006845 and NSF grant NSF IIS-084494 to the University of Maryland (Steven Salzberg) and the University of Florida Department of Agriculture (JDE). We thank Antoinette Betschart and Kevin Hackett, USDA-ARS, for logistical support, Dawn Lopez for technical support, and the Institute for Genomic Sciences, University of Maryland, Baltimore, for sequencing. The helpful critique of three anonymous reviewers greatly improved the manuscript.
- Morse RA, Calderone NW: The value of honey bees as pollinators of U.S. crops in 2000. Bee Culture. 2000, 128: 1-15.Google Scholar
- Gallai N, Salles JM, Settele J, Vaissiere BE: Economic valuation of the vulnerability of world agriculture confronted with pollinator decline. Ecological Economics. 2009, 68: 810-821. 10.1016/j.ecolecon.2008.06.014.View ArticleGoogle Scholar
- Aizen MA, Harder LD: The global stock of domesticated honey bees is growing slower than agricultural demand for pollination. Current Biology. 2009, 19: 915-918. 10.1016/j.cub.2009.03.071.PubMedView ArticleGoogle Scholar
- Cox-Foster DL, Conlan S, Holmes EC, Palacios G, Evans JD, Moran NA, Quan PL, Briese T, Hornig M, Geiser DM, et al: A metagenomic survey of microbes in honey bee colony collapse disorder. Science. 2007, 318: 283-287. 10.1126/science.1146498.PubMedView ArticleGoogle Scholar
- Rosenkranz P, Aumeier P, Ziegelmann B: Biology and control of Varroa destructor. J Invertebr Pathol. 103 (Suppl 1): S96-119.Google Scholar
- Anderson DL, Trueman JWH: Varroa jacobsoni (Acari: Varroidae) is more than one species. Experimental and Applied Acarology. 2000, 24: 165-189. 10.1023/A:1006456720416.PubMedView ArticleGoogle Scholar
- Johnson RM, Evans JD, Robinson GE, Berenbaum MR: Changes in transcript abundance relating to colony collapse disorder in honey bees (Apis mellifera). Proc Natl Acad Sci USA. 2009, 106: 14790-14795. 10.1073/pnas.0906970106.PubMed CentralPubMedView ArticleGoogle Scholar
- Highfield AC, El Nagar A, Mackinder LC, Noel LM, Hall MJ, Martin SJ, Schroeder DC: Deformed wing virus implicated in overwintering honeybee colony losses. Appl Environ Microbiol. 2009, 75: 7212-7220. 10.1128/AEM.02227-09.PubMed CentralPubMedView ArticleGoogle Scholar
- Yang X, Cox-Foster D: Effects of parasitization by Varroa destructor on survivorship and physiological traits of Apis mellifera in correlation with viral incidence and microbial challenge. Parasitology. 2007, 134: 405-412. 10.1017/S0031182006000710.PubMedView ArticleGoogle Scholar
- Boecking O, Genersch E: Varroosis - The ongoing crisis in bee keeping. Journal fur Verbraucherschutz und Lebensmittelsicherheit. 2008, 3: 221-228. 10.1007/s00003-008-0331-y.View ArticleGoogle Scholar
- Sammataro D, Gerson U, Needham G: Parasitic mites of honey bees: life history, implications, and impact. Annu Rev Entomol. 2000, 45: 519-548. 10.1146/annurev.ento.45.1.519.PubMedView ArticleGoogle Scholar
- Kuenen LPS, Calderone NW: Transfers of Varroa mites from newly emerged bees: Preferences for age- and function-specific adult bees (Hymenoptera: Apidae). Journal of Insect Behavior. 1997, 10: 213-228. 10.1007/BF02765554.View ArticleGoogle Scholar
- Kraus B: Factors influencing host choice of the honey bee parasite Varroa jacobsoni Oud. Experimental and Applied Acarology. 1994, 18: 435-443. 10.1007/BF00051525.View ArticleGoogle Scholar
- De Guzman LI, Rinderer TE, Frake AM: Comparative reproduction of Varroa destructor in different types of Russian and Italian honey bee combs. Experimental and Applied Acarology. 2008, 44: 227-238. 10.1007/s10493-008-9142-1.PubMedView ArticleGoogle Scholar
- Rinderer TE, De Guzman LI, Delatte GT, Harper C: An evaluation of ARS Russian honey bees in combination with other methods for the control of Varroa mites. American Bee Journal. 2003, 143: 410-413.Google Scholar
- Anderson DL: Non-reproduction of Varroa jacobsoni in Apis mellifera colonies in Papua New Guinea and Indonesia. Apidologie. 1994, 25: 412-421. 10.1051/apido:19940408.View ArticleGoogle Scholar
- Anderson DL, Fuchs S: Two genetically distinct populations of Varroa jacobsoni with contrasting reproductive abilities on Apis mellifera. Journal of Apicultural Research. 1998, 37: 69-78.Google Scholar
- Navajas M, Anderson DL, De Guzman LI, Huang ZY, Clement J, Zhou T, Le Conte Y: New Asian types of Varroa destructor: a potential new threat for world apiculture. Apidologie. 2010Google Scholar
- NCBI Genome Project ID 33467. [http://www.ncbi.nlm.nih.gov/genomeprj?term=Varroa%20destructor]
- Cornman RS, Chen YP, Schatz MC, Street C, Zhao Y, Desany B, Egholm M, Hutchison S, Pettis JS, Lipkin WI, et al: Genomic analyses of the microsporidian Nosema ceranae, an emergent pathogen of honey bees. PLoS Pathog. 2009, 5: e1000466-10.1371/journal.ppat.1000466.PubMed CentralPubMedView ArticleGoogle Scholar
- Qin X, Evans JD, Aronstein KA, Murray KD, Weinstock GM: Genome sequences of the honey bee pathogens Paenibacillus larvae and Ascosphaera apis. Insect Molecular Biology. 2006, 15: 715-718. 10.1111/j.1365-2583.2006.00694.x.PubMed CentralPubMedView ArticleGoogle Scholar
- De Guzman LI, Rinderer TE, Stelzer JA: Occurrence of two genotypes of Varroa jacobsoni oud. in North America. Apidologie. 1999, 30: 31-36. 10.1051/apido:19990104.View ArticleGoogle Scholar
- Solignac M, Cornuet J-M, Vautrin D, Le Conte Y, Anderson D, Evans J, Cros-Arteil S, Navajas M: The invasive Korea and Japan types of Varroa destructor, ectoparasitic mites of the Western honeybee (Apis mellifera), are two partly isolated clones. Proceedings of the Royal Society - Biological Sciences (Series B). 2005, 272: 411-419. 10.1098/rspb.2004.2853.View ArticleGoogle Scholar
- Anderson DL: Variation in the parasitic bee mite Varroa jacobsoni Oud. Apidologie. 2000, 31: 281-292. 10.1051/apido:2000122.View ArticleGoogle Scholar
- Steiner J, Grasas Pompolo S, Takahashi CS, Gonsalves LS: Cytogenetics of the acarid Varroa jacobsoni. Brazilian Journal of Genetics. 1982, 4: 841-844.Google Scholar
- Pagel Van Zee J, Geraci NS, Guerrero FD, Wikel SK, Stuart JJ, Nene VM, Hill CA: Tick genomics: the Ixodes genome project and beyond. Int J Parasitol. 2007, 37: 1297-1305. 10.1016/j.ijpara.2007.05.011.PubMedView ArticleGoogle Scholar
- Geraci NS, Johnston JS, Robinson JP, Wikel SK, Hill CA: Variation in genome size of argasid and ixodid ticks. Insect Biochemistry and Molecular Biology. 2007, 37: 399-408. 10.1016/j.ibmb.2006.12.007.PubMedView ArticleGoogle Scholar
- Grbic M, Khila A, Lee KZ, Bjelica A, Grbic V, Whistlecraft J, Verdon L, Navajas M, Nagy L: Mity model: Tetranychus urticae, a candidate for chelicerate model organism. Bioessays. 2007, 29: 489-496. 10.1002/bies.20564.PubMedView ArticleGoogle Scholar
- wFleaBase. [http://wfleabase.org/]
- The International Aphid Genomics Consortium: Genome sequence of the pea aphid Acyrthosiphon pisum. PLoS Biol. 2010, 8: e1000313-10.1371/journal.pbio.1000313.PubMed CentralView ArticleGoogle Scholar
- Miller JR, Delcher AL, Koren S, Venter E, Walenz BP, Brownley A, Johnson J, Li K, Mobarry C, Sutton G: Aggressive assembly of pyrosequencing reads with mates. Bioinformatics. 2008, 24: 2818-2824. 10.1093/bioinformatics/btn548.PubMed CentralPubMedView ArticleGoogle Scholar
- Lander ES, Waterman MS: Genomic mapping by fingerprinting random clones: a mathematical analysis. Genomics. 1988, 2: 231-329. 10.1016/0888-7543(88)90007-9.PubMedView ArticleGoogle Scholar
- Tyson GW, Chapman J, Hugenholtz P, Allen EE, Ram RJ, Richardson PM, Solovyev VV, Rubin EM, Rokhsar DS, Banfield JF: Community structure and metabolism through reconstruction of microbial genomes from the environment. Nature. 2004, 428: 37-43. 10.1038/nature02340.PubMedView ArticleGoogle Scholar
- Gotz S, Garcia-Gomez JM, Terol J, Williams TD, Nagaraj SH, Nueda MJ, Robles M, Talon M, Dopazo J, Conesa A: High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res. 2008, 36: 3420-3435. 10.1093/nar/gkn176.PubMed CentralPubMedView ArticleGoogle Scholar
- Klepzig KD, Adams AS, Handelsman J, Raffa KF: Symbioses: a key driver of insect physiological processes, ecological interactions, evolutionary diversification, and impacts on humans. Environ Entomol. 2009, 38: 67-77. 10.1603/022.038.0109.PubMedView ArticleGoogle Scholar
- Finn RD, Tate J, Mistry J, Coggill PC, Sammut SJ, Hotz HR, Ceric G, Forslund K, Eddy SR, Sonnhammer EL, et al: The Pfam protein families database. Nucleic Acids Res. 2008, 36: D281-288. 10.1093/nar/gkm960.PubMed CentralPubMedView ArticleGoogle Scholar
- Baculovirus Molecular Biology. [http://www.ncbi.nlm.nih.gov/bookshelf/br.fcgi?book=bacvir]
- Rosell G, Quero C, Coll J, Guerrero A: Biorational insecticides in pest management. Journal of Pesticide Science. 2008, 33: 103-121. 10.1584/jpestics.R08-01.View ArticleGoogle Scholar
- Herniou EA, Olszewski JA, Cory JS, O'Reilly DR: The genome sequence and evolution of baculoviruses. Annu Rev Entomol. 2003, 48: 211-234. 10.1146/annurev.ento.48.091801.112756.PubMedView ArticleGoogle Scholar
- Ogata H, Goto S, Sato K, Fujibuchi W, Bono H, Kanehisa M: KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 1999, 27: 29-34. 10.1093/nar/27.1.29.PubMed CentralPubMedView ArticleGoogle Scholar
- Vectorbase. [http://www.vectorbase.org]
- Parra G, Bradnam K, Ning Z, Keane T, Korf I: Assessing the gene space in draft genomes. Nucleic Acids Res. 2009, 37: 289-297. 10.1093/nar/gkn916.PubMed CentralPubMedView ArticleGoogle Scholar
- HMMER3: a new generation of sequence homology search software. [http://hmmer.janelia.org]
- RepeatMasker Open-3.0. [http://www.repeatmasker.org]
- Volff JN: Turning junk into gold: domestication of transposable elements and the creation of new genes in eukaryotes. Bioessays. 2006, 28: 913-922. 10.1002/bies.20452.PubMedView ArticleGoogle Scholar
- Atkinson PW, Pinkerton AC, O'Brochta DA: Genetic transformation systems in insects. Annu Rev Entomol. 2001, 46: 317-346. 10.1146/annurev.ento.46.1.317.PubMedView ArticleGoogle Scholar
- Jeyaprakash A, Hoy MA: First divergence time estimate of spiders, scorpions, mites and ticks (subphylum: Chelicerata) inferred from mitochondrial phylogeny. Exp Appl Acarol. 2009, 47: 1-18. 10.1007/s10493-008-9203-5.PubMedView ArticleGoogle Scholar
- Jones DT, Taylor WR, Thornton JM: The rapid generation of mutation data matrices from protein sequences. Computer Applications in the Biosciences. 1992, 8: 275-282.PubMedGoogle Scholar
- Felsenstein J: Inferring phylogenies. 2004, Sunderland, Mass.: SinauerGoogle Scholar
- Regier JC, Shultz JW, Zwick A, Hussey A, Ball B, Wetzer R, Martin JW, Cunningham CW: Arthropod relationships revealed by phylogenomic analysis of nuclear protein-coding sequences. Nature. 463: 1079-1083. 10.1038/nature08742.Google Scholar
- Wheeler WC, Whiting M, Wheeler QD, Carpenter JM: The phylogeny of the extant hexapod orders. Cladistics. 2005, 17: 113-169. 10.1111/j.1096-0031.2001.tb00115.x.View ArticleGoogle Scholar
- Brockman W, Alvarez P, Young S, Garber M, Giannoukos G, Lee WL, Russ C, Lander ES, Nusbaum C, Jaffe DB: Quality scores and SNP detection in sequencing-by-synthesis systems. Genome Res. 2008, 18: 763-770. 10.1101/gr.070227.107.PubMed CentralPubMedView ArticleGoogle Scholar
- Pettis JS: A scientific note on Varroa destructor resistance to coumaphos in the United States. Apidologie. 2004, 35: 91-92. 10.1051/apido:2003060.View ArticleGoogle Scholar
- Guzman-Novoa E, Vandame R, Arechavaleta ME: Susceptibility of European and Africanized honey bees (Apis mellifera L.) to Varroa jacobsoni Oud. in Mexico. Apidologie. 1999, 30: 173-182. 10.1051/apido:19990207.View ArticleGoogle Scholar
- Moretto G, Mello LJd: Varroa jacobsoni infestation of adult Africanized and Italian honey bees (Apis mellifera) in mixed colonies in Brazil. Genetics and Molecular Biology. 1999, 22: 321-323. 10.1590/S1415-47571999000300006.View ArticleGoogle Scholar
- Jeyaprakash A, Hoy MA: First divergence time estimate of spiders, scorpions, mites and ticks (subphylum: Chelicerata) inferred from mitochondrial phylogeny. Experimental and Applied Acarology. 2009, 47: 1-18. 10.1007/s10493-008-9203-5.PubMedView ArticleGoogle Scholar
- Pisani D, Poling LL, Lyons-Weiler M, Hedges SB: The colonization of land by animals: molecular phylogeny and divergence times among arthropods. BMC Biology. 2004, 2: 1-10.1186/1741-7007-2-1.PubMed CentralPubMedView ArticleGoogle Scholar
- Gregory TR, Johnston JS: Genome size diversity in the family Drosophilidae. Heredity. 2008, 101: 228-238. 10.1038/hdy.2008.49.PubMedView ArticleGoogle Scholar
- Honey Bee Genome Sequencing Consortium: Insights into social insects from the genome of the honeybee Apis mellifera. Nature. 2006, 443: 931-949. 10.1038/nature05260.View ArticleGoogle Scholar
- Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, Formsma K, Gerdes S, Glass EM, Kubal M, et al: The RAST Server: rapid annotations using subsystems technology. BMC Genomics. 2008, 9: 75-10.1186/1471-2164-9-75.PubMed CentralPubMedView ArticleGoogle Scholar
- Rice P, Longden I, Bleasby A: EMBOSS: the European Molecular Biology Open Software Suite. Trends Genet. 2000, 16: 276-277. 10.1016/S0168-9525(00)02024-2.PubMedView ArticleGoogle Scholar
- Karlin S, Mrazek J, Campbell AM: Codon usages in different gene classes of the Escherichia coli genome. Mol Microbiol. 1998, 29: 1341-1355. 10.1046/j.1365-2958.1998.01008.x.PubMedView ArticleGoogle Scholar
- Supek F, Vlahovicek K: INCA: synonymous codon usage analysis and clustering by means of self-organizing map. Bioinformatics. 2004, 20: 2329-2330. 10.1093/bioinformatics/bth238.PubMedView ArticleGoogle Scholar
- Felsenstein J: PHYLIP - Phylogeny Inference Package (Version 3.2). Cladistics. 1989, 5: 164-166.Google Scholar
- Page RD: TreeView: an application to display phylogenetic trees on personal computers. Comput Appl Biosci. 1996, 12: 357-358.PubMedGoogle Scholar
- Interpro. [http://www.ebi.ac.uk/interpro/]
- Uniprot. [http://www.uniprot.org]
- Jurka J, Kapitonov VV, Pavlicek A, Klonowski P, Kohany O, Walichiewicz J: Repbase Update, a database of eukaryotic repetitive elements. Cytogenet Genome Res. 2005, 110: 462-467. 10.1159/000084979.PubMedView ArticleGoogle Scholar
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