Explore the vast range of titles available.

The worldwide dispersal of the ectoparasitic mite Varroa destructor from its Asian origins has fundamentally transformed the relationship of the honey bee ( Apis mellifera ) with several of its viruses, via changes in transmission and/or host immunosuppression. The extent to which honey bee-virus relationships change after Varroa invasion is poorly understood for most viruses, in part because there are few places in the world with several geographically close but completely isolated honey bee populations that either have, or have not, been exposed long-term to Varroa , allowing for separate ecological, epidemiological, and adaptive relationships to develop between honey bees and their viruses, in relation to the mite’s presence or absence. The Azores is one such place, as it contains islands with and without the mite. Here, we combined qPCR with meta-amplicon deep sequencing to uncover the relationship between Varroa presence, and the prevalence, load, diversity, and phylogeographic structure of eight honey bee viruses screened across the archipelago. Four viruses were not detected on any island (ABPV-Acute bee paralysis virus, KBV-Kashmir bee virus, IAPV-Israeli acute bee paralysis virus, BeeMLV-Bee macula-like virus); one (SBV-Sacbrood virus) was detected only on mite-infested islands; one (CBPV-Chronic bee paralysis virus) occurred on some islands, and two (BQCV-Black queen cell virus, LSV-Lake Sinai virus,) were present on every single island. This multi-virus screening builds upon a parallel survey of Deformed wing virus (DWV) strains that uncovered a remarkably heterogeneous viral landscape featuring Varroa -infested islands dominated by DWV-A and -B, Varroa -free islands naïve to DWV, and a refuge of the rare DWV-C dominating the easternmost Varroa -free islands. While all four detected viruses investigated here were affected by Varroa for one or two parameters (usually prevalence and/or the Richness component of ASV diversity), the strongest effect was observed for the multi-strain LSV. Varroa unambiguously led to elevated prevalence, load, and diversity (Richness and Shannon Index) of LSV, with these results largely shaped by LSV-2, a major LSV strain. Unprecedented insights into the mite-virus relationship were further gained from implementing a phylogeographic approach. In addition to enabling the identification of a novel LSV strain that dominated the unique viral landscape of the easternmost islands, this approach, in combination with the recovered diversity patterns, strongly suggests that Varroa is driving the evolutionary change of LSV in the Azores. This study greatly advances the current understanding of the effect of Varroa on the epidemiology and adaptive evolution of these less-studied viruses, whose relationship with Varroa has thus far been poorly defined.

With a growing number of parasites and pathogens experiencing large-scale range expansions, monitoring diversity in immune genes of host populations has never been so important because it can inform on the adaptive potential to resist the invaders. Population surveys of immune genes are becoming common in many organisms, yet they are missing in the honey bee ( Apis mellifera L.), a key managed pollinator species that has been severely affected by biological invasions. To fill the gap, here we identified single nucleotide polymorphisms (SNPs) in a wide range of honey bee immune genes and developed a medium-density assay targeting a subset of these genes. Using a discovery panel of 123 whole-genomes, representing seven A. mellifera subspecies and three evolutionary lineages, 180 immune genes were scanned for SNPs in exons, introns (< 4 bp from exons), 3’ and 5´UTR, and < 1 kb upstream of the transcription start site. After application of multiple filtering criteria and validation, the final medium-density assay combines 91 quality-proved functional SNPs marking 89 innate immune genes and these can be readily typed using the high-sample-throughput iPLEX MassARRAY system. This medium-density-SNP assay was applied to 156 samples from four countries and the admixture analysis clustered the samples according to their lineage and subspecies, suggesting that honey bee ancestry can be delineated from functional variation. In addition to allowing analysis of immunogenetic variation, this newly-developed SNP assay can be used for inferring genetic structure and admixture in the honey bee.

The evolutionary trajectory of island populations can be rapidly altered by human-mediated migration, a process further exacerbated when immigrants introduce invasive parasites, creating new selective pressures. Using customised SNP panels constructed with genome-wide diagnostic loci, we describe the genetic changes in honey bee populations inhabiting the Azores archipelago. As part of a breeding initiative in the 1980s, these populations were recurrently exposed to beekeeper-mediated gene flow from a highly divergent commercial line (C lineage) until the arrival of the Varroa mite to the Azores in 2000, which prompted a honey bee importation ban. Admixture analysis revealed a spatially heterogeneous introgression landscape in the Azores. Four of the five mite-free islands (Santa Maria, São Miguel, Terceira, and São Jorge) presented negligible levels of C-lineage introgression (mean Q-value: 0.004–0.091) despite repeated C-lineage importations in the past. In contrast, the three mite-infested islands (Pico, Faial, and Flores) presented high levels of introgression (mean Q-value: 0.156–0.261). The mite-free island of Graciosa harboured the most admixed population (mean Q-value: 0.392), which is consistent with efforts to eradicate the historical population and replace it with C-lineage honey bees during the implementation of the breeding program. Bayesian inference modelling indicated that the presence of a C-lineage maternal origin and Varroa were associated with increased introgression proportions (100% posterior probability), increasing the mean Q-value by 0.049 and 0.118, respectively. Our findings indicate that these anthropogenic processes altered the historically introduced gene pool and provide a foundation for developing effective conservation strategies to protect honey bees in the Azores.

The availability of powerful high-throughput genomic tools, combined with genome scans, has helped identifying genes and genetic changes responsible for environmental adaptation in many organisms, including the honeybee. Here, we resequenced 87 whole genomes of the honeybee native to Iberia and used conceptually different selection methods (Samβada, LFMM, PCAdapt, iHs) together with in sillico protein modelling to search for selection footprints along environmental gradients. We found 670 outlier SNPs, most of which associated with precipitation, longitude and latitude. Over 88.7% SNPs laid outside exons and there was a significant enrichment in regions adjacent to exons and UTRs. Enrichment was also detected in exonic regions. Furthermore, in silico protein modelling suggests that several non-synonymous SNPs are likely direct targets of selection, as they lead to amino acid replacements in functionally important sites of proteins. We identified genomic signatures of local adaptation in 140 genes, many of which are putatively implicated in fitness-related functions such as reproduction, immunity, olfaction, lipid biosynthesis and circadian clock. Our genome scan suggests that local adaptation in the Iberian honeybee involves variations in regions that might alter patterns of gene expression and in protein-coding genes, which are promising candidates to underpin adaptive change in the honeybee.

Background With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and F ST ) to select the most informative SNPs for ancestry inference. Results Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% ± 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof. Conclusions The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees.

Beekeeping activities, especially queen trading, have shaped the distribution of honey bee (Apis mellifera) subspecies in Europe, and have resulted in extensive introductions of two eastern European C-lineage subspecies (A. m. ligustica and A. m. carnica) into the native range of the M-lineage A. m. mellifera subspecies in Western Europe. As a consequence, replacement and gene flow between native and commercial populations have occurred at varying levels across western European populations. Genetic identification and introgression analysis using molecular markers is an important tool for management and conservation of honey bee subspecies. Previous studies have monitored introgression by using microsatellite, PCR-RFLP markers and most recently, high density assays using single nucleotide polymorphism (SNP) markers. While the latter are almost prohibitively expensive, the information gained to date can be exploited to create a reduced panel containing the most ancestry-informative markers (AIMs) for those purposes with very little loss of information. The objective of this study was to design reduced panels of AIMs to verify the origin of A. m. mellifera individuals and to provide accurate estimates of the level of C-lineage introgression into their genome. The discriminant power of the SNPs using a variety of metrics and approaches including the Weir & Cockerham's FST, an FST-based outlier test, Delta, informativeness (In), and PCA was evaluated. This study shows that reduced AIMs panels assign individuals to the correct origin and calculates the admixture level with a high degree of accuracy. These panels provide an essential tool in Europe for genetic stock identification and estimation of admixture levels which can assist management strategies and monitor honey bee conservation programs.

The main biological threat to the western honeybee ( Apis mellifera ) is the parasitic mite Varroa destructor , largely because it vectors lethal epidemics of honeybee viruses that, in the absence of this mite, are relatively innocuous. The severe pathology is a direct consequence of excessive virus titres caused by this novel transmission route. However, little is known about how the virus adapts genetically during transmission and whether this influences the pathology. Here, we show that upon injection into honeybee pupae, the deformed wing virus type-A (DWV-A) quasispecies undergoes a rapid, extensive expansion of its sequence space, followed by strong negative selection towards a uniform, common shape by the time the pupae have completed their development, with no difference between symptomatic and asymptomatic adults in either DWV titre or genetic composition. This suggests that the physiological and molecular environment during pupal development has a strong, conservative influence on shaping the DWV-A quasispecies in emerging adults. There was furthermore no evidence of any progressive adaptation of the DWV-A quasispecies to serial intra-abdominal injection, simulating mite transmission, despite the generation of ample variation immediately following each transmission, suggesting that the virus either had already adapted to transmission by injection, or was unaffected by it.

The natural distribution of the honeybee ( Apis mellifera L.) has been changed by humans in recent decades to such an extent that the formerly widest-spread European subspecies, Apis mellifera mellifera , is threatened by extinction through introgression from highly divergent commercial strains in large tracts of its range. Conservation efforts for A . m . mellifera are underway in multiple European countries requiring reliable and cost-efficient molecular tools to identify purebred colonies. Here, we developed four ancestry-informative SNP assays for high sample throughput genotyping using the iPLEX Mass Array system. Our customized assays were tested on DNA from individual and pooled, haploid and diploid honeybee samples extracted from different tissues using a diverse range of protocols. The assays had a high genotyping success rate and yielded accurate genotypes. Performance assessed against whole-genome data showed that individual assays behaved well, although the most accurate introgression estimates were obtained for the four assays combined (117 SNPs). The best compromise between accuracy and genotyping costs was achieved when combining two assays (62 SNPs). We provide a ready-to-use cost-effective tool for accurate molecular identification and estimation of introgression levels to more effectively monitor and manage A . m . mellifera conservatories.

Sociality has brought many advantages to various hymenoptera species, including their ability of regulating physical factors in their nest (e.g., temperature). Although less studied, humidity is known to be important for egg, larval and pupal development, and also for nectar concentration. Two subspecies of Apis mellifera of the M evolutionary lineage were used as models to test the ability of a superorganism (i.e. honeybee colony) to regulate the humidity in its nest (i.e. “hygroregulation hypothesis”) in four conservation centers: two in France (A. m. mellifera) and two in Portugal (A. m. iberiensis). We investigated the ability of both subspecies to regulate the humidity in hives daily, but also during the seasons for one complete year. Our data and statistical analysis demonstrated the capacity of the bees to regulate humidity in their hive, regardless of the day, season or subspecies. Furthermore, the study showed that humidity in beehives is stable even during winter, when brood is absent, and when temperature is known to be less stable in the beehives. These results suggest that humidity is important for honeybees at every life stage, maybe because of the ‘imprint’ of the evolutionary history of this hymenopteran lineage.

Genetic diversity is an important biological trait for a successful invasion. During the expansion across a new territory, an invasive species may face unprecedented ecological conditions that will determine its demography and genetic diversity. The first record of the yellow‐legged hornet (Vespa velutina) in Europe dates back to 2004 in France, from where it has successfully spread through a large territory in the continent, including Italy, Spain and Portugal. Integrative approaches offer a powerful strategy to detect and understand patterns of genetic variation in central and marginal populations. Here, we have analysed the relationship between genetic diversity parameters inferred from 15 V. velutina nuclear DNA microsatellite loci, and geographical and environmental drivers, such as the distance to the introduction focus, environmental suitability and distance to native and invasive niche centroids. Our results revealed a central–marginal dynamic, where allelic richness decreased towards the edge of the expansion range. The low environmental suitability of the territories invaded by marginal populations could prevent a diverse population from establishing and reducing the genetic diversity in populations at the expansion edge. Moreover, Markov chain Monte Carlo analysis showed both geographical and environmental distances were influencing population genetic differentiation. This study highlights the importance of combining genetic analysis with geographical and environmental drivers to understand genetic trends of invasive species to new environment. We tested central–marginal population dynamics on the yellow‐legged hornet in Europe. Allelic richness decreased towards the edge of the expansion range to low environmental suitability areas. Both geographical and environmental distances were influencing population genetic differentiation.