Authoritative subspecies diagnosis tool for European honey bees based on ancestryinformative 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 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.The SmartBees project was funded by the European Commission under its FP7 KBBE programme (2013.1.3-02, SmartBees Grant Agreement number 613960) https://ec.europa.eu/research/fp7.MP was supported by a Basque Government grant (IT1233-19). The funders provided the financial support to the research, but had no role in the design of the study, analysis, interpretations of data and in writing the manuscript

Bee Queen Breeding Methods - Review

The biological potential of a bee family is mainly generated by the biological value of the queen. Whether we grow queens widely or just for our own apiaries, we must consider the acquisition of high-quality biological material, and also the creation of optimal feeding and caring conditions, in order to obtain high genetic value queens. Queen breeding technology starts with the setting of hoeing families, nurse families, drone-breeding families – necessary for the pairing of young queens, and also of the families which will provide the bees used to populate the nuclei where the next queens will hatch. The complex of requirements for the breeding of good, high-production queens is sometimes hard to met, under the application of artificial methods. The selection of breeding method must rely on all these requirements and on the beekeeper’s level of training

Bee Queen Breeding Methods - Review

The biological potential of a bee family is mainly generated by the biological value of the queen. Whether we grow queens widely or just for our own apiaries, we must consider the acquisition of high-quality biological material, and also the creation of optimal feeding and caring conditions, in order to obtain high genetic value queens. Queen breeding technology starts with the setting of hoeing families, nurse families, drone-breeding families – necessary for the pairing of young queens, and also of the families which will provide the bees used to populate the nuclei where the next queens will hatch. The complex of requirements for the breeding of good, high-production queens is sometimes hard to met, under the application of artificial methods. The selection of breeding method must rely on all these requirements and on the beekeeper’s level of training

Historical Changes in Honey Bee Wing Venation in Romania

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

Cloud computing based bushfire prediction for cyber-physical emergency applications

Here, scientists from 19 European countries, most of them collaborating in Working Group 4: “Diversity and Vitality” of COST Action FA 0803 “Prevention of honey bee COlony LOSSes” (COLOSS), review the methodology applied in each country for discriminating between honey bee populations. Morphometric analyses (classical and geometric) and different molecular markers have been applied. Even if the approach has been similar, however, different methodologies regarding measurements, landmarks or molecular markers may have been used, as well as different statistical procedures. There is therefore the necessity to establish common methods in all countries in order to have results that can be directly compared. This is one of the goals of WG4 of the COLOSS project