1. Authoritative subspecies diagnosis tool for European honey bees based on ancestry informative SNPsJamal Momeni, Melanie Parejo, Rasmus O. Nielsen, Jorge Langa, Iratxe Montes, Laetitia Papoutsis, Leila Farajzadeh, Christian Brendixen, Eliza Cǎuia, Aleš Gregorc, 2021, original scientific article Abstract: 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.
Keywords: Apis mellifera, European suspecies, conservation, machine learning, prediction, biodiversity
Published in DKUM: 01.10.2024; Views: 0; Downloads: 2
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2. Complex population structure and haplotype patterns in the Western European honey bee from sequencing a large panel of haploid dronesDavid Wragg, Sonia E. Eynard, Benjamin Basso, Kamila Canale-Tabet, Emmanuelle Labarthe, Olivier Bouchez, Kaspar Bienefeld, Małgorzata Bieńkowska, Cecilia Costa, Aleš Gregorc, Per Kryger, Melanie Parejo, Alice M. Pinto, Jean-Pierre Bidanel, Bertrand Servin, Yves Le Conte, Alain Vignal, 2022, original scientific article Abstract: 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.
Keywords: genome, haplotype, honey bee, population genetics, SNP
Published in DKUM: 08.07.2024; Views: 109; Downloads: 15
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