Population genetic diversity and dynamics of the honey bee brood pathogen Melissococcus plutonius in a region with high prevalence.

European foulbrood (EFB) is a honey bee brood disease caused by the bacterium Melissococcus plutonius. Large-scale EFB outbreaks have been reported in several countries in recent decades, which entail costly sanitation measures of affected apiaries to restrict the spread of this contagious pathogen. To mitigate its impact, a better understanding of the population dynamics of the etiological agent is required. We here used multi-locus sequence typing (MLST) to infer the genetic diversity and geographical distribution of 160 M. plutonius isolates collected from EFB symptomatic honey bee colonies seven years apart. Isolates belonged to three clonal complexes (CCs) known worldwide and to 12 sequence types (STs), of which five were novel. Phylogenetic and clustering analyses showed that some of these novel sequence types have likely evolved locally during a period of outbreak, but most disappeared again. We further screened the isolates for melissotoxin A (mtxA), a putative virulence gene. The prevalence of STs in which mtxA was frequent increased over time, suggesting that this gene promotes spread. Despite the increased frequency of this gene in the population, the total number of cases decreased, which could be due to stricter control measures implemented before the second sampling period. Our results provide a better understanding of M. plutonius population dynamics and help identify knowledge gaps that limit efficient control of this emerging disease.

A short exposure to a semi-natural habitat alleviates the honey bee hive microbial imbalance caused by agricultural stress.

Honeybee health and the species' gut microbiota are interconnected. Also noteworthy are the multiple niches present within hives, each with distinct microbiotas and all coexisting, which we termed "apibiome". External stressors (e.g. anthropization) can compromise microbial balance and bee resilience. We hypothesised that (1) the bacterial communities of hives located in areas with different degrees of anthropization differ in composition, and (2) due to interactions between the multiple microbiomes within the apibiome, changes in the community of a niche would impact the bacteria present in other hive sections. We characterised the bacterial consortia of different niches (bee gut, bee bread, hive entrance and internal hive air) of 43 hives from 3 different environments (agricultural, semi-natural and natural) through 16S rRNA amplicon sequencing. Agricultural samples presented lower community evenness, depletion of beneficial bacteria, and increased recruitment of stress related pathways (predicted via PICRUSt2). The taxonomic and functional composition of gut and hive entrance followed an environmental gradient. Arsenophonus emerged as a possible indicator of anthropization, gradually decreasing in abundance from agriculture to the natural environment in multiple niches. Importantly, after 16 days of exposure to a semi-natural landscape hives showed intermediate profiles, suggesting alleviation of microbial dysbiosis through reduction of anthropization.

Virus Prevalence in Egg Samples Collected from Naturally Selected and Traditionally Managed Honey Bee Colonies across Europe.

Monitoring virus infections can be an important selection tool in honey bee breeding. A recent study pointed towards an association between the virus-free status of eggs and an increased virus resistance to deformed wing virus (DWV) at the colony level. In this study, eggs from both naturally surviving and traditionally managed colonies from across Europe were screened for the prevalence of different viruses. Screenings were performed using the phenotyping protocol of the 'suppressed in ovo virus infection' trait but with qPCR instead of end-point PCR and a primer set that covers all DWV genotypes. Of the 213 screened samples, 109 were infected with DWV, 54 were infected with black queen cell virus (BQCV), 3 were infected with the sacbrood virus, and 2 were infected with the acute bee paralyses virus. It was demonstrated that incidences of the vertical transmission of DWV were more frequent in naturally surviving than in traditionally managed colonies, although the virus loads in the eggs remained the same. When comparing virus infections with queen age, older queens showed significantly lower infection loads of DWV in both traditionally managed and naturally surviving colonies, as well as reduced DWV infection frequencies in traditionally managed colonies. We determined that the detection frequencies of DWV and BQCV in honey bee eggs were lower in samples obtained in the spring than in those collected in the summer, indicating that vertical transmission may be lower in spring. Together, these patterns in vertical transmission show that honey bee queens have the potential to reduce the degree of vertical transmission over time.

Complex population structure and haplotype patterns in the Western European honey bee from sequencing a large panel of haploid drones.

Honey bee subspecies originate from specific geographical areas in Africa, Europe and the Middle East, and beekeepers interested in specific phenotypes have imported genetic material to regions outside of the bees' original range for use either in pure lines or controlled crosses. Moreover, imported drones are present in the environment and mate naturally with queens from the local subspecies. The resulting admixture complicates population genetics analyses, and population stratification can be a major problem for association studies. To better understand Western European honey bee populations, we produced a whole genome sequence and single nucleotide polymorphism (SNP) genotype data set from 870 haploid drones and demonstrate its utility for the identification of nine genetic backgrounds and various degrees of admixture in a subset of 629 samples. Five backgrounds identified correspond to subspecies, two to isolated populations on islands and two to managed populations. We also highlight several large haplotype blocks, some of which coincide with the position of centromeres. The largest is 3.6 Mb long and represents 21% of chromosome 11, with two major haplotypes corresponding to the two dominant genetic backgrounds identified. This large naturally phased data set is available as a single vcf file that can now serve as a reference for subsequent populations genomics studies in the honey bee, such as (i) selecting individuals of verified homogeneous genetic backgrounds as references, (ii) imputing genotypes from a lower-density data set generated by an SNP-chip or by low-pass sequencing, or (iii) selecting SNPs compatible with the requirements of genotyping chips.

Population Structure and Diversity in European Honey Bees (Apismellifera L.)-An Empirical Comparison of Pool and Individual Whole-Genome Sequencing.

BACKGROUND: Whole-genome sequencing has become routine for population genetic studies. Sequencing of individuals provides maximal data but is rather expensive and fewer samples can be studied. In contrast, sequencing a pool of samples (pool-seq) can provide sufficient data, while presenting less of an economic challenge. Few studies have compared the two approaches to infer population genetic structure and diversity in real datasets. Here, we apply individual sequencing (ind-seq) and pool-seq to the study of Western honey bees (Apis mellifera). METHODS: We collected honey bee workers that belonged to 14 populations, including 13 subspecies, totaling 1347 colonies, who were individually (139 individuals) and pool-sequenced (14 pools). We compared allele frequencies, genetic diversity estimates, and population structure as inferred by the two approaches. RESULTS: Pool-seq and ind-seq revealed near identical population structure and genetic diversities, albeit at different costs. While pool-seq provides genome-wide polymorphism data at considerably lower costs, ind-seq can provide additional information, including the identification of population substructures, hybridization, or individual outliers. CONCLUSIONS: If costs are not the limiting factor, we recommend using ind-seq, as population genetic structure can be inferred similarly well, with the advantage gained from individual genetic information. Not least, it also significantly reduces the effort required for the collection of numerous samples and their further processing in the laboratory.

Recovering High-Quality Host Genomes from Gut Metagenomic Data through Genotype Imputation.

Metagenomic datasets of host-associated microbial communities often contain host DNA that is usually discarded because the amount of data is too low for accurate host genetic analyses. However, genotype imputation can be employed to reconstruct host genotypes if a reference panel is available. Here, the performance of a two-step strategy is tested to impute genotypes from four types of reference panels built using different strategies to low-depth host genome data (≈2× coverage) recovered from intestinal samples of two chicken genetic lines. First, imputation accuracy is evaluated in 12 samples for which both low- and high-depth sequencing data are available, obtaining high imputation accuracies for all tested panels (>0.90). Second, the impact of reference panel choice in population genetics statistics on 100 chickens is assessed, all four panels yielding comparable results. In light of the observations, the feasibility and application of the applied imputation strategy are discussed for different species with regard to the host DNA proportion, genomic diversity, and availability of a reference panel. This method enables leveraging insofar discarded host DNA to get insights into the genetic structure of host populations, and in doing so, facilitates the implementation of hologenomic approaches that jointly analyze host and microbial genomic data.

Authoritative subspecies diagnosis tool for European honey bees based on ancestry informative SNPs.

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 FST) 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.

Digging into the Genomic Past of Swiss Honey Bees by Whole-Genome Sequencing Museum Specimens.

Historical specimens in museum collections provide opportunities to gain insights into the genomic past. For the Western honey bee, Apis mellifera L., this is particularly important because its populations are currently under threat worldwide and have experienced many changes in management and environment over the last century. Using Swiss Apis mellifera mellifera as a case study, our research provides important insights into the genetic diversity of native honey bees prior to the industrial-scale introductions and trade of non-native stocks during the 20th century-the onset of intensive commercial breeding and the decline of wild honey bees following the arrival of Varroa destructor. We sequenced whole-genomes of 22 honey bees from the Natural History Museum in Bern collected in Switzerland, including the oldest A. mellifera sample ever sequenced. We identify both, a historic and a recent migrant, natural or human-mediated, which corroborates with the population history of honey bees in Switzerland. Contrary to what we expected, we find no evidence for a significant genetic bottleneck in Swiss honey bees, and find that genetic diversity is not only maintained, but even slightly increased, most probably due to modern apicultural practices. Finally, we identify signals of selection between historic and modern honey bee populations associated with genes enriched in functions linked to xenobiotics, suggesting a possible selective pressure from the increasing use and diversity of chemicals used in agriculture and apiculture over the last century.

Evaluation of Suppressed Mite Reproduction (SMR) Reveals Potential for Varroa Resistance in European Honey Bees (Apis mellifera L.).

In the fight against the Varroa destructor mite, selective breeding of honey bee (Apis mellifera L.) populations that are resistant to the parasitic mite stands as a sustainable solution. Selection initiatives indicate that using the suppressed mite reproduction (SMR) trait as a selection criterion is a suitable tool to breed such resistant bee populations. We conducted a large European experiment to evaluate the SMR trait in different populations of honey bees spread over 13 different countries, and representing different honey bee genotypes with their local mite parasites. The first goal was to standardize and validate the SMR evaluation method, and then to compare the SMR trait between the different populations. Simulation results indicate that it is necessary to examine at least 35 single-infested cells to reliably estimate the SMR score of any given colony. Several colonies from our dataset display high SMR scores indicating that this trait is present within the European honey bee populations. The trait is highly variable between colonies and some countries, but no major differences could be identified between countries for a given genotype, or between genotypes in different countries. This study shows the potential to increase selective breeding efforts of V. destructor resistant populations.

Developing reduced SNP assays from whole-genome sequence data to estimate introgression in an organism with complex genetic patterns, the Iberian honeybee (Apis mellifera iberiensis).

The most important managed pollinator, the honeybee (Apis mellifera L.), has been subject to a growing number of threats. In western Europe, one such threat is large-scale introductions of commercial strains (C-lineage ancestry), which is leading to introgressive hybridization and even the local extinction of native honeybee populations (M-lineage ancestry). Here, we developed reduced assays of highly informative SNPs from 176 whole genomes to estimate C-lineage introgression in the most diverse and evolutionarily complex subspecies in Europe, the Iberian honeybee (Apis mellifera iberiensis). We started by evaluating the effects of sample size and sampling a geographically restricted area on the number of highly informative SNPs. We demonstrated that a bias in the number of fixed SNPs (FST = 1) is introduced when the sample size is small (N ≤ 10) and when sampling only captures a small fraction of a population's genetic diversity. These results underscore the importance of having a representative sample when developing reliable reduced SNP assays for organisms with complex genetic patterns. We used a training data set to design four independent SNP assays selected from pairwise FST between the Iberian and C-lineage honeybees. The designed assays, which were validated in holdout and simulated hybrid data sets, proved to be highly accurate and can be readily used for monitoring populations not only in the native range of A. m. iberiensis in Iberia but also in the introduced range in the Balearic islands, Macaronesia and South America, in a time- and cost-effective manner. While our approach used the Iberian honeybee as model system, it has a high value in a wide range of scenarios for the monitoring and conservation of potentially hybridized domestic and wildlife populations.

High sample throughput genotyping for estimating C-lineage introgression in the dark honeybee: an accurate and cost-effective SNP-based tool.

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.