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Authoritative subspecies diagnosis tool for European honey bees based on ancestry informative SNPs.


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.

SUBMITTER: Momeni J 

PROVIDER: S-EPMC7860026 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Authoritative subspecies diagnosis tool for European honey bees based on ancestry informative SNPs.

Momeni Jamal J   Parejo Melanie M   Nielsen Rasmus O RO   Langa Jorge J   Montes Iratxe I   Papoutsis Laetitia L   Farajzadeh Leila L   Bendixen Christian C   Căuia Eliza E   Charrière Jean-Daniel JD   Coffey Mary F MF   Costa Cecilia C   Dall'Olio Raffaele R   De la Rúa Pilar P   Drazic M Maja MM   Filipi Janja J   Galea Thomas T   Golubovski Miroljub M   Gregorc Ales A   Grigoryan Karina K   Hatjina Fani F   Ilyasov Rustem R   Ivanova Evgeniya E   Janashia Irakli I   Kandemir Irfan I   Karatasou Aikaterini A   Kekecoglu Meral M   Kezic Nikola N   Matray Enikö Sz ES   Mifsud David D   Moosbeckhofer Rudolf R   Nikolenko Alexei G AG   Papachristoforou Alexandros A   Petrov Plamen P   Pinto M Alice MA   Poskryakov Aleksandr V AV   Sharipov Aglyam Y AY   Siceanu Adrian A   Soysal M Ihsan MI   Uzunov Aleksandar A   Zammit-Mangion Marion M   Vingborg Rikke R   Bouga Maria M   Kryger Per P   Meixner Marina D MD   Estonba Andone A  

BMC genomics 20210203 1


<h4>Background</h4>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 high  ...[more]

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