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

Beneficial protective role of endogenous lactic acid bacteria against mycotic contamination of honeybee beebread

International audienceThe purpose of this article is to reveal the role of the lactic acid bacteria (LAB) in the beebread transformation/preservation, biochemical properties of 25 honeybee endogenous Lstrains, particularly: antifungal, proteolytic, and amylolytic activities putatively expressed in the beebread environment have been studied. Seventeen fungal strains isolated from beebread samples were identified and checked for their ability to grow on simulated beebread substrate (SBS) and then used to study mycotic propagation in the presence of LAB. Fungal strains identified as Aspergillus niger (Po1), Candida sp. (BB01), and Z. rouxii (BB02) were able to grow on SBS. Their growth was partly inhibited when co-cultured with the endogenous honeybee Lstrains studied. No proteolytic or amylolytic activities of the studied Lwere detected using pollen, casein starch based media as substrates. These findings suggest that some honeybee Lsymbionts are involved in maintaining a safe microbiological state in the host honeybee colonies by inhibiting beebread mycotic contaminations, starch, and protein predigestion in beebread by Lis less probable. Honeybee endogenous Luse pollen as a growth substrate and in the same time restricts fungal propagation, thus showing host beneficial action preserving larval food. This study also can have an impact on development of novel methods of pollen preservation and its processing as a food ingredient