IBRA, the world's longest established apicultural research publishers, promotes the value of bees by providing information on bee science and beekeeping worldwide. A not-for-profit organisation founded in 1949

IBRA, the world's longest established apicultural research publishers, promotes the value of bees by providing information on bee science and beekeeping worldwide. A not-for-profit organisation founded in 1949

IBRA, the world's longest established apicultural research publishers, promotes the value of bees by providing information on bee science and beekeeping worldwide. A not-for-profit organisation founded in 1949

The expansion of Africanized honeybees from South America to the southwestern United States in <50 years is considered one of the most spectacular biological invasions yet documented. In the American tropics, it has been shown that during their expansion Africanized honeybees have low levels of introgressed alleles from resident European populations. In the United States, it has been speculated, but not shown, that Africanized honeybees would hybridize extensively with European honeybees. Here we report a continuous 11-year study investigating temporal changes in the genetic structure of a feral population from the southern United States undergoing Africanization. Our microsatellite data showed that (1) the process of Africanization involved both maternal and paternal bidirectional gene flow between European and Africanized honeybees and (2) the panmitic European population was replaced by panmitic mixtures of A. m. scutellata and European genes within 5 years after Africanization. The post-Africanization gene pool (1998–2001) was composed of a diverse array of recombinant classes with a substantial European genetic contribution (mean 25–37%). Therefore, the resulting feral honeybee population of south Texas was best viewed as a hybrid swarm.

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.