Tracing the genealogy origin of geographic populations based on genomic variation and deep learning

Assigning a query individual animal or plant to its derived population is a prime task in diverse applications related to organismal genealogy. Such endeavors have conventionally relied on short DNA sequences under a phylogenetic framework. These methods naturally show constraints when the inferred population sources are ambiguously phylogenetically structured, a scenario demanding substantially more informative genetic signals. Recent advances in cost-effective production of whole-genome sequences and artificial intelligence have created an unprecedented opportunity to trace the population origin for essentially any given individual, as long as the genome reference data are comprehensive and standardized. Here, we developed a convolutional neural network method to identify population origins using genomic SNPs. Three empirical datasets (an Asian honeybee, a red fire ant, and a chicken datasets) and two simulated populations are used for the proof of concepts. The performance tests indicate that our method can accurately identify the genealogy origin of query individuals, with success rates ranging from  93 % to 100 %. We further showed that the accuracy of the model can be significantly increased by refining the informative sites through FST filtering. Our method is robust to configurations related to batch sizes and epochs, whereas model learning benefits from the setting of a proper preset learning rate. Moreover, we explained the importance score of key sites for algorithm interpretability and credibility, which has been largely ignored. We anticipate that by coupling genomics and deep learning, our method will see broad potential in conservation and management applications that involve natural resources, invasive pests and weeds, and illegal trades of wildlife products.

A blood test to monitor bee health across a European network of agricultural sites of different land-use by MALDI BeeTyping mass spectrometry

There are substantial concerns about impaired honey bee health and colony losses due to several poorly understood factors. We used MALDI profiling (MALDI BeeTyping®) analysis to investigate how some environmental and management factors under field conditions across Europe affected the honey bee haemolymph peptidome (all peptides in the circulatory fluid), as a profile of molecular markers representing the immune status of Apis mellifera. Honey bees were exposed to a range of environmental stressors in 128 agricultural sites across eight European countries in four biogeographic zones, with each country contributing eight sites each for two different cropping systems: oilseed rape (OSR) and apple (APP). The full haemolymph peptide profiles, including the presence and levels of three key immunity markers, namely the antimicrobial peptides (AMPs) Apidaecin, Abaecin and Defensin-1, allowed the honey bee responses to environmental variables to be discriminated by country, crop type and site. When considering just the AMPs, it was not possible to distinguish between countries by the prevalence of each AMP in the samples. However, it was possible to discriminate between countries on the amounts of the AMPs, with the Swedish samples in particular expressing high amounts of all AMPs. A machine learning model was developed to discriminate the haemolymphs of bees from APP and OSR sites. The model was 90.6 % accurate in identifying the crop type from the samples used to build the model. Overall, MALDI BeeTyping® of bee haemolymph represents a promising and cost-effective "blood test" for simultaneously monitoring dozens of peptide markers affected by environmental stressors at the landscape scale, thus providing policymakers with new diagnostic and regulatory tools for monitoring bee health.

The nuclear and mitochondrial genome assemblies of Tetragonisca angustula (Apidae: Meliponini), a tiny yet remarkable pollinator in the Neotropics

BACKGROUND

The field of bee genomics has considerably advanced in recent years, however, the most diverse group of honey producers on the planet, the stingless bees, are still largely neglected. In fact, only eleven of the ~ 600 described stingless bee species have been sequenced, and only three using a long-read (LR) sequencing technology. Here, we sequenced the nuclear and mitochondrial genomes of the most common, widespread and broadly reared stingless bee in Brazil and other neotropical countries-Tetragonisca angustula (popularly known in Brazil as jataí).

RESULTS

A total of 48.01 Gb of DNA data were generated, including 2.31 Gb of Pacific Bioscience HiFi reads and 45.70 Gb of Illumina short reads (SRs). Our preferred assembly comprised 683 contigs encompassing 284.49 Mb, 62.84 Mb of which (22.09%) corresponded to 445,793 repetitive elements. N50, L50 and complete BUSCOs reached 1.02 Mb, 91 contigs and 97.1%, respectively. We predicted that the genome of T. angustula comprises 17,459 protein-coding genes and 4,108 non-coding RNAs. The mitogenome consisted of 17,410 bp, and all 37 genes were found to be on the positive strand, an unusual feature among bees. A phylogenomic analysis of 26 hymenopteran species revealed that six odorant receptor orthogroups of T. angustula were found to be experiencing rapid evolution, four of them undergoing significant contractions.

CONCLUSIONS

Here, we provided the first nuclear and mitochondrial genome assemblies for the ecologically and economically important T. angustula, the fourth stingless bee species to be sequenced with LR technology thus far. We demonstrated that even relatively small amounts of LR data in combination with sufficient SR data can yield high-quality genome assemblies for bees.

Haplotypes of the tRNAleu-COII mtDNA Region in Russian Apis mellifera Populations

Analysis of the mtDNA tRNAleu-COII locus is a widely used tool to establish belonging to a particular evolutionary lineage of Apis mellifera L. (lineages A, M, C, O, and Y). In Russia, most of the area was once inhabited by Apis mellifera mellifera from the M evolutionary lineage, but the introduction of bee subspecies from the southern regions of Russia (A. m. caucasica, A. m. carnica) and from abroad (A. m. carnica, A. m. ligustica) led to fragmentation of their native range. In this study, the results of assessing the haplotype number for the tRNAleu-COII locus of mtDNA in Russian Apis mellifera populations were presented. We analyzed 269 colonies from 19 regions of Russia. As a result, two evolutionary lineages were identified: the East European lineage C (26.4%) and the Northwestern European lineage M (73.6%). A total of 29 haplotypes were identified, 8 of them were already reported, and 21 were found to be novel. From the C lineage, haplotypes C1, C2, C2c, C2j, and C3 were predominant. All M lineage samples from Russia belong to the M17 and M4' haplogroups but have only minor variations in the form of nucleotide substitutions. An analysis of publications devoted to the tRNAleu-COII locus haplotypes, as well as an analysis of the available tRNAleu-COII sequences in GenBank, showed that there is still a problem with the haplotype nomenclature.

When One's Not Enough: Colony Pool-Seq Outperforms Individual-Based Methods for Assessing Introgression in Apis mellifera mellifera

The human management of honey bees (Apis mellifera) has resulted in the widespread introduction of subspecies outside of their native ranges. One well known example of this is Apis mellifera mellifera, native to Northern Europe, which has now been significantly introgressed by the introduction of C lineage honey bees. Introgression has consequences for species in terms of future adaptive potential and long-term viability. However, estimating introgression in colony-living haplodiploid species is challenging. Previous studies have estimated introgression using individual workers, individual drones, multiple drones, and pooled workers. Here, we compare introgression estimates via three genetic approaches: SNP array, individual RAD-seq, and pooled colony RAD-seq. We also compare two statistical approaches: a maximum likelihood cluster program (ADMIXTURE) and an incomplete lineage sorting model (ABBA BABA). Overall, individual approaches resulted in lower introgression estimates than pooled colonies when using ADMIXTURE. However, the pooled colony ABBA BABA approach resulted in generally lower introgression estimates than all three ADMIXTURE estimates. These results highlight that sometimes one individual is not enough to assess colony-level introgression, and future studies that do use colony pools should not be solely dependent on clustering programs for introgression estimates.

AmelHap: Leveraging drone whole-genome sequence data to create a honey bee HapMap

Honey bee, Apis mellifera, drones are typically haploid, developing from an unfertilized egg, inheriting only their queen's alleles and none from the many drones she mated with. Thus the ordered combination or 'phase' of alleles is known, making drones a valuable haplotype resource. We collated whole-genome sequence data for 1,407 drones, including 45 newly sequenced Scottish drones, collectively representing 19 countries, 8 subspecies and various hybrids. Following alignment to Amel_HAv3.1, variant calling and quality filtering, we retained 17.4 M high quality variants across 1,328 samples with a genotyping rate of 98.7%. We demonstrate the utility of this haplotype resource, AmelHap, for genotype imputation, returning >95% concordance when up to 61% of data is missing in haploids and up to 12% of data is missing in diploids. AmelHap will serve as a useful resource for the community for imputation from low-depth sequencing or SNP chip data, accurate phasing of diploids for association studies, and as a comprehensive reference panel for population genetic and evolutionary analyses.

Honey bee (Apis mellifera) wing images: a tool for identification and conservation

BACKGROUND

The honey bee (Apis mellifera) is an ecologically and economically important species that provides pollination services to natural and agricultural systems. The biodiversity of the honey bee in parts of its native range is endangered by migratory beekeeping and commercial breeding. In consequence, some honey bee populations that are well adapted to the local environment are threatened with extinction. A crucial step for the protection of honey bee biodiversity is reliable differentiation between native and nonnative bees. One of the methods that can be used for this is the geometric morphometrics of wings. This method is fast, is low cost, and does not require expensive equipment. Therefore, it can be easily used by both scientists and beekeepers. However, wing geometric morphometrics is challenging due to the lack of reference data that can be reliably used for comparisons between different geographic regions.

FINDINGS

Here, we provide an unprecedented collection of 26,481 honey bee wing images representing 1,725 samples from 13 European countries. The wing images are accompanied by the coordinates of 19 landmarks and the geographic coordinates of the sampling locations. We present an R script that describes the workflow for analyzing the data and identifying an unknown sample. We compared the data with available reference samples for lineage and found general agreement with them.

CONCLUSIONS

The extensive collection of wing images available on the Zenodo website can be used to identify the geographic origin of unknown samples and therefore assist in the monitoring and conservation of honey bee biodiversity in Europe.

Prospects, challenges and perspectives in harnessing natural selection to solve the ‘varroa problem’ of honey bees

Honey bees, Apis mellifera, of European origin are major pollinators of crops and wild flora. Their endemic and exported populations are threatened by a variety of abiotic and biotic factors. Among the latter, the ectoparasitic mite Varroa destructor is the most important single cause behind colony mortality. The selection of mite resistance in honey bee populations has been deemed a more sustainable solution to its control than varroacidal treatments. Because natural selection has led to the survival of some European and African honey bee populations to V. destructor infestations, harnessing its principles has recently been highlighted as a more efficient way to provide honey bee lineages that survive infestations when compared with conventional selection on resistance traits against the parasite. However, the challenges and drawbacks of harnessing natural selection to solve the varroa problem have only been minimally addressed. We argue that failing to consider these issues could lead to counterproductive results, such as increased mite virulence, loss of genetic diversity reducing host resilience, population collapses or poor acceptance by beekeepers. Therefore, it appears timely to evaluate the prospects for the success of such programmes and the qualities of the populations obtained. After reviewing the approaches proposed in the literature and their outcomes, we consider their advantages and drawbacks and propose perspectives to overcome their limitations. In these considerations, we not only reflect on the theoretical aspects of host-parasite relationships but also on the currently largely neglected practical constraints, that is, the requirements for productive beekeeping, conservation or rewilding objectives. To optimize natural selection-based programmes towards these objectives, we suggest designs based on a combination of nature-driven phenotypic differentiation and human-directed selection of traits. Such a dual strategy aims at allowing field-realistic evolutionary approaches towards the survival of V. destructor infestations and the improvement of honey bee health.

Identification of runs of homozygosity in Western honey bees (Apis mellifera) using whole-genome sequencing data

Runs of homozygosity (ROH) are continuous homozygous segments that arise through the transmission of haplotypes that are identical by descent. The length and distribution of ROH segments provide insights into the genetic diversity of populations and can be associated with selection signatures. Here, we analyzed reconstructed whole-genome queen genotypes, from a pool-seq data experiment including 265 Western honeybee colonies from Apis mellifera mellifera and Apis mellifera carnica. Integrating individual ROH patterns and admixture levels in a dynamic population network visualization allowed us to ascertain major differences between the two subspecies. Within A. m. mellifera, we identified well-defined substructures according to the genetic origin of the queens. Despite the current applied conservation efforts, we pinpointed 79 admixed queens. Genomic inbreeding (F ROH) strongly varied within and between the identified subpopulations. Conserved A. m. mellifera from Switzerland had the highest mean F ROH (3.39%), while queens originating from a conservation area in France, which were also highly admixed, showed significantly lower F ROH (0.45%). The majority of A. m. carnica queens were also highly admixed, except 12 purebred queens with a mean F ROH of 2.33%. Within the breed-specific ROH islands, we identified 14 coding genes for A. m. mellifera and five for A. m. carnica, respectively. Local adaption of A. m. mellifera could be suggested by the identification of genes involved in the response to ultraviolet light (Crh-BP, Uvop) and body size (Hex70a, Hex70b), while the A. m. carnica specific genes Cpr3 and Cpr4 are most likely associated with the lighter striping pattern, a morphological phenotype expected in this subspecies. We demonstrated that queen genotypes derived from pooled workers are useful tool to unravel the population dynamics in A. mellifera and provide fundamental information to conserve native honey bees.

Using the Software DeepWings© to Classify Honey Bees across Europe through Wing Geometric Morphometrics

DeepWings© is a software that uses machine learning to automatically classify honey bee subspecies by wing geometric morphometrics. Here, we tested the five subspecies classifier (A. m. carnica, Apis mellifera caucasia, A. m. iberiensis, Apis mellifera ligustica, and A. m. mellifera) of DeepWings© on 14,816 wing images with variable quality and acquired by different beekeepers and researchers. These images represented 2601 colonies from the native ranges of the M-lineage A. m. iberiensis and A. m. mellifera, and the C-lineage A. m. carnica. In the A. m. iberiensis range, 92.6% of the colonies matched this subspecies, with a high median probability (0.919). In the Azores, where the Iberian subspecies was historically introduced, a lower proportion (85.7%) and probability (0.842) were observed. In the A. m mellifera range, only 41.1 % of the colonies matched this subspecies, which is compatible with a history of C-derived introgression. Yet, these colonies were classified with the highest probability (0.994) of the three subspecies. In the A. m. carnica range, 88.3% of the colonies matched this subspecies, with a probability of 0.984. The association between wing and molecular markers, assessed for 1214 colonies from the M-lineage range, was highly significant but not strong (r = 0.31, p < 0.0001). The agreement between the markers was influenced by C-derived introgression, with the best results obtained for colonies with high genetic integrity. This study indicates the good performance of DeepWings© on a realistic wing image dataset.

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.

Thrice out of Asia and the adaptive radiation of the western honey bee

The origin of the western honey bee Apis mellifera has been intensely debated. Addressing this knowledge gap is essential for understanding the evolution and genetics of one of the world’s most important pollinators. By analyzing 251 genomes from 18 native subspecies, we found support for an Asian origin of honey bees with at least three expansions leading to African and European lineages. The adaptive radiation of honey bees involved selection on a few genomic “hotspots.” We found 145 genes with independent signatures of selection across all bee lineages, and these genes were highly associated with worker traits. Our results indicate that a core set of genes associated with worker and colony traits facilitated the adaptive radiation of honey bees across their vast distribution.

Practical Applications of Genomics in Managing Honey bee Health

The honey bee Apis mellifera is a model organism for sociogenomics and one of the most important managed pollinators. High mortalities experienced by honey bee colonies over the past several decades are expected to have a substantive effect on crop pollination and global food security. These threats and the availability of a growing number of genomic resources for the honey bee have motivated research on how genetics and genomics can be practically applied to manage bee health. The authors review 3 such applications: (1) Certification of bee lineages using single-polymorphism markers; (2) breeding bees using marker-assisted selection; (3) diagnosing honey bee stressors using biomarkers.

The Current State of the Protected Apis mellifera mellifera Population in Russia: Hybridization and Nosematosis

The Southern Urals of Russia are the habitat of one of the surviving populations of the dark forest bee-the Burzyan population of Apis mellifera mellifera. In this study, we present the results of the subspecies identification of bee colonies in the Altyn-Solok Nature Reserve in the Southern Ural Mountains using the intergenic mtDNA COI-COII locus and the assessment of the prevalence of nosematosis. Analysis of the mtDNA COI-COII intergenic locus in the studied sample showed that 30.4% of the colonies belong to the lineage C. The PCR diagnostics of nosematosis in 92 colonies selected from different sectors of the Altyn-Solok Nature Reserve showed that about half of the analyzed colonies were infected with Nosema apis. Nosema ceranae was found in eight colonies. Both of these factors can lead to the extinction of this population of the dark forest bee.

Historical Changes in Honey Bee Wing Venation in Romania

Simple Summary

Honey bees, in addition to producing honey, are important pollinators of wild and cultivated plants. Unfortunately, in some places, the population of honey bees is declining. One of the factors that affect their survival is adaptation to the local environment. Bees native to a particular area survive better than those imported. Despite this fact, some beekeepers import non-native bees and use them in their apiaries. Imported bees produce hybrids with bees from surrounding colonies because beekeepers do not control their mating. In consequence, the whole population can change. In this study, we verified how the population of Romanian bees has changed over the last four decades. We found significant temporal changes in wing venation. Despite these changes, the two major subpopulations of bees separated by mountains remain distinct. We provide a tool for the easy identification of native bees from Romania, which can help to protect them.

Abstract

The honey bee (Apis mellifera) is an ecologically and economically important species that provides pollination services to natural and agricultural systems. The biodiversity of the honey bee is being endangered by the mass import of non-native queens. In many locations, it is not clear how the local populations have been affected by hybridisation between native and non-native bees. There is especially little information about temporal changes in hybridisation. In Romania, A. m. carpatica naturally occurs, and earlier studies show that there are two subpopulations separated by the Carpathian Mountains. In this study, we investigated how the arrangement of veins in bees’ wings (venation) has changed in Romanian honey bees in the last four decades. We found that in the contemporary population of Romanian bees, there are still clear differences between the intra- and extra-Carpathian subpopulations, which indicates that natural variation among honey bees is still being preserved. We also found significant differences between bees collected before and after 2000. The observed temporal changes in wing venation are most likely caused by hybridisation between native bees and non-native bees sporadically introduced by beekeepers. In order to facilitate conservation and the monitoring of native Romanian bees, we developed a method facilitating their identification.

Whole-Genome Sequence Analysis of Italian Honeybees (Apis mellifera)

Simple Summary

The purpose of this study was to (i) explore the population structure of the A.m. ligustica which is widely distributed along the entire Italian peninsula, (ii) quantify the introgression of A.m. carnica, Buckfast, and A.m. mellifera bees in the two autochthonous Italian subspecies A.m. ligustica and A.m. sicula, and to (iii) to propose conservation strategies for the two autochthonous subspecies. Whole-genome sequencing was performed by Illumina technology obtaining a total of 4,380,004 single nucleotide polymorphisms (SNPs). Results of the analysis of the patterns of genetic variation allowed us to identify and subgroup bees according to their type. Morphometric analysis of 5800 worker bees was in agreement with genomic data. The investigation revealed the genetic originality of the Sicula, and in A.m. ligustica limited genetic introgression from the other breeds.

Abstract

At the end of the last glaciation, Apis mellifera was established in northern Europe. In Italy, Apis melliferaligustica adapted to the mild climate and to the rich floristic biodiversity. Today, with the spread of Varroa destructor and with the increasing use of pesticides in agriculture, the Ligustica subspecies is increasingly dependent on human action for its survival. In addition, the effects of globalization of bee keeping favored the spread in Italy of other honeybee stocks of A. mellifera, in particular the Buckfast bee. The purpose of this study was to characterize the Italian honeybee’s population by sequencing the whole genome of 124 honeybees. Whole genome sequencing was performed by Illumina technology, obtaining a total coverage of 3720.89X, with a mean sample coverage of 29.77X. A total of 4,380,004 SNP variants, mapping on Amel_HAv3.1 chromosomes, were detected. Results of the analysis of the patterns of genetic variation allowed us to identify and subgroup bees according to their type. The investigation revealed the genetic originality of the Sicula, and in A.m. ligustica limited genetic introgression from the other breeds. Morphometric analysis of 5800 worker bees was in agreement with genomic data.

Mitochondrial DNA Suggests the Introduction of Honeybees of African Ancestry to East-Central Europe

Simple Summary

In Europe, a well-known threat to the conservation of honeybee diversity is the loss of genetic uniqueness of local populations due to beekeepers’ preference for a few genetic lineages. However, due to climate change and large-scale ongoing movement of breeding individuals, the expansion of bees of African origin could represent another threat. This issue has not yet been recognised in detail, although bees bearing African mitochondrial DNA occur in South-West and South Europe due to natural gene flow. Here, we determine the diversity of mitochondrial DNA in honey bees from East-Central Europe. We sequenced the COI-COII region in 427 bees sampled along two 900 km transects (17.5° N and 23° E). We found that 1.64% of bees (95% CI: 0.66–3.35%) had African mitochondrial DNA. It is unlikely that their presence in the area resulted from natural migration but instead human-driven introductions of hybrids of African ancestry. This expansion deserves more attention, as it may contribute to the dissemination of undesirable traits, parasites and diseases.

Abstract

In Europe, protecting the genetic diversity of Apis mellifera is usually perceived in the context of limiting the spread of the evolutionary C-lineage within the original range of the M-lineage. However, due to climate change and large-scale ongoing movement of breeding individuals, the expansion of bees from the African A-lineage could represent another threat. This issue has not yet been investigated in detail, although A-mitotypes occur in South-West and South Europe due to natural gene flow. Here, we determine the diversity of mtDNA in honey bees from East-Central Europe. We sequenced the COI-COII region in 427 bees sampled along two 900 km transects (17.5° N and 23° E). We found that 1.64% of bees (95% CI: 0.66–3.35 %) had A-mitotypes. It is unlikely that their presence in the area resulted from natural migration but instead human driven introductions of hybrids of African ancestry. This expansion deserves more attention, as it may contribute to the dissemination of undesirable traits, parasites and diseases.

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.

Recent advances in population and quantitative genomics of honey bees

The increase in the availability of individual Apis mellifera genomes has resulted in significant progress toward understanding the evolution and adaptation of the honey bee. These efforts have identified new subspecies, evolutionary lineages, and a significant number of genes involved with adaptations and colony-level quantitative traits. Many studies have also developed genetic assays that are being used to monitor the movement and admixture of honey bee populations. These resources are valuable for conservation and breeding programs that seek to improve the economic value of colonies or preserve locally adapted populations and subspecies. This review provides a brief discussion on how population and quantitative genomic studies has improved our understanding of the honey bee.

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.

Whole-genome sequencing approaches for conservation biology: Advantages, limitations and practical recommendations

Whole-genome resequencing (WGR) is a powerful method for addressing fundamental evolutionary biology questions that have not been fully resolved using traditional methods. WGR includes four approaches: the sequencing of individuals to a high depth of coverage with either unresolved or resolved haplotypes, the sequencing of population genomes to a high depth by mixing equimolar amounts of unlabelled-individual DNA (Pool-seq) and the sequencing of multiple individuals from a population to a low depth (lcWGR). These techniques require the availability of a reference genome. This, along with the still high cost of shotgun sequencing and the large demand for computing resources and storage, has limited their implementation in nonmodel species with scarce genomic resources and in fields such as conservation biology. Our goal here is to describe the various WGR methods, their pros and cons and potential applications in conservation biology. WGR offers an unprecedented marker density and surveys a wide diversity of genetic variations not limited to single nucleotide polymorphisms (e.g., structural variants and mutations in regulatory elements), increasing their power for the detection of signatures of selection and local adaptation as well as for the identification of the genetic basis of phenotypic traits and diseases. Currently, though, no single WGR approach fulfils all requirements of conservation genetics, and each method has its own limitations and sources of potential bias. We discuss proposed ways to minimize such biases. We envision a not distant future where the analysis of whole genomes becomes a routine task in many nonmodel species and fields including conservation biology.

Genome-wide scans between two honeybee populations reveal putative signatures of human-mediated selection

Human‐mediated selection has left signatures in the genomes of many domesticated animals, including the European dark honeybee, Apis mellifera mellifera, which has been selected by apiculturists for centuries. Using whole‐genome sequence information, we investigated selection signatures in spatially separated honeybee subpopulations (Switzerland, n = 39 and France, n = 17). Three different test statistics were calculated in windows of 2 kb (fixation index, cross‐population extended haplotype homozygosity and cross‐population composite likelihood ratio) and combined into a recently developed composite selection score. Applying a stringent false discovery rate of 0.01, we identified six significant selective sweeps distributed across five chromosomes covering eight genes. These genes are associated with multiple molecular and biological functions, including regulation of transcription, receptor binding and signal transduction. Of particular interest is a selection signature on chromosome 1, which corresponds to the WNT4 gene, the family of which is conserved across the animal kingdom with a variety of functions. In Drosophila melanogaster, WNT4 alleles have been associated with differential wing, cross vein and abdominal phenotypes. Defining phenotypic characteristics of different Apis mellifera ssp., which are typically used as selection criteria, include colour and wing venation pattern. This signal is therefore likely to be a good candidate for human mediated‐selection arising from different applied breeding practices in the two managed populations.