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.

Phenotypic and genotypic diversity among strains of Aureobasidium pullulans in comparison with related species.

Intra-specific diversity of 200 Aureobasidium pullulans strains isolated from different sources and their relatives Kabatiella lini CBS 125.21 T and Hormonema prunorum CBS 933.72 T were studied by assessment of macromorphological, and physiological tests, sodium dodecyl sulfate-polyacrylamide gel electrophoresis technique (SDS-PAGE) of whole-cell proteins as well as enterobacterial repetitive intergenic consensus (ERIC)-, repetitive extragenic palindromic (REP)- and BOX-PCR techniques (collectively known as rep-PCR). Rep-PCR is an efficient procedure for discrimination of A. pullulans in terms of simplicity and rapidity. RFLP-PCR technique was applied for the identification of A. pullulans isolates and distinction from related species. This technique was insufficient for investigation of intra-specific diversity. The tested strains of A. pullulans could be divided into two groups based on their macromorphological, protein patterns obtained after SDS-PAGE as well as rep-PCR patterns. The first group of strains shared similar characteristics and was very different from the second one, designated as "complex group", consisting of strains with very little similarities within the group. Phenetic analysis of ERIC banding patterns failed to group the isolates on the basis of their substrate or geographical origin. Using 18S rDNA gene sequence analysis of selected isolates, three strains: HoHe3 km, A. pullulans DSM 62074 and H. prunorum CBS 933.72 T were distinguished from all other analysed members of genera Aureobasidium and Kabatiella.

Genetic diversity among isolates of Paenibacillus larvae from Austria.

Genetic diversity of 214 Paenibacillus larvae strains from Austria was studied. Genotyping of isolates was performed by polymerase chain reaction (PCR) with primers corresponding to enterobacterial repetitive intergenic consensus (ERIC), BOX repetitive and extragenic palindromic (REP) elements (collectively known as rep-PCR) using ERIC primers, BOX A1R and MBO REP1 primers. Using ERIC-PCR technique two genotypes could be differentiated (ERIC I and II), whereas using combined typing by BOX- and REP-PCR, five different genotypes were detected (ab, aB, Ab, AB and alphab). Genotypes aB and alphab are new and have not been reported in other studies using the same techniques.

Health status of honey bee colonies (Apis mellifera) and disease-related risk factors for colony losses in Austria.

Austrian beekeepers frequently suffered severe colony losses during the last decade similar to trends all over Europe. This first surveillance study aimed to describe the health status of Austrian bee colonies and to analyze the reasons for losses for both the summer and winter season in Austria. In this study 189 apiaries all over Austria were selected using a stratified random sampling approach and inspected three times between July 2015 and spring 2016 by trained bee inspectors. The inspectors made interviews with the beekeepers about their beekeeping practice and the history of the involved colonies. They inspected a total of 1596 colonies for symptoms of nine bee pests and diseases (four of them notifiable diseases) and took bee samples for varroa mite infestation analysis. The most frequently detected diseases were three brood diseases: Varroosis, Chalkbrood and Sacbrood. The notifiable bee pests Aethina tumida and Tropilaelaps spp. were not detected. During the study period 10.8% of the 1596 observed colonies died. Winter proved to be the most critical season, in which 75% of the reported colony losses happened. Risks for suffering summer losses increased significantly, when colonies were weak in July, had queen problems or a high varroa mite infestation level on bees in July. Risks for suffering winter losses increased significantly, when the colonies had a high varroa mite infestation level on bees in September, were weak in September, had a queen older than one year or the beekeeper had few years of beekeeping experience. However, the effect of a high varroa mite infestation level in September had by far the greatest potential to raise the winter losses compared to the other significant factors.

A citizen science supported study on seasonal diversity and monoflorality of pollen collected by honey bees in Austria.

Austrian beekeepers participated in the "C.S.I. Pollen" study as citizen scientists and collected pollen from honey bee colonies in hive mounted traps every three weeks from April to September in 2014 and 2015 to uncover the seasonal availability of pollen sources for bees. 1622 pollen samples were collected and analysed using palynological light microscopy to the lowest taxonomic level possible. For 2014 and 2015 combined, 239 pollen types from more than 85 families were detected. 'Various unknown' species, Taraxacum-form and Plantago spp. were the pollen types collected by the majority of colonies (occurrence), whereas the most pollen grains collected were from Trifolium repens-form, Plantago spp. and Salix spp. (abundance). In spring, trees were found to be the most abundant pollen source, whereas in summer herbs dominated. On average, a colony collected pollen from 16.8 ± 4.7 (2014) and 15.0 ± 4.4 (2015) pollen types per sampling. Those numbers, however, vary between sampling dates and indicate a seasonal pattern. This is also supported by Simpson's diversity index, which was on median 0.668. In both years, 50.0% of analysed pollen samples were partially (>50%) and 4.2% were highly monofloral (i.e. containing >90% of one pollen type). Prevalence of monofloral pollen samples peaked at the beginning and the end of the season, when pollen diversity was the lowest.