Authors: Jamal Momeni, Melanie Parejo, Rasmus O. Nielsen, Jorge Langa, Iratxe Montes, Laetitia Papoutsis, Leila Farajzadeh, Christian Bendixen, Eliza Căuia, Jean-Daniel Charrière, Mary F. Coffey, Cecilia Costa, Raffaele Dall’Olio, Pilar De la Rúa, M. Maja Drazic, Janja Filipi, Thomas Galea, Miroljub Golubovski, Ales Gregorc, Karina Grigoryan, Fani Hatjina, Rustem Ilyasov, Evgeniya Ivanova, Irakli Janashia, Irfan Kandemir, Aikaterini Karatasou, Meral Kekecoglu, Nikola Kezic, Enikö Sz. Matray, David Mifsud, Rudolf Moosbeckhofer, Alexei G. Nikolenko, Alexandros Papachristoforou, Plamen Petrov, M. Alice Pinto, Aleksandr V. Poskryakov, Aglyam Y. Sharipov, Adrian Siceanu, M. Ihsan Soysal, Aleksandar Uzunov, Marion Zammit-Mangion, Rikke Vingborg, Maria Bouga, Per Kryger, Marina D. Meixner, Andone Estonba

Venue: BMC Genomics

Type: Article

Abstract: 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 informa... (read more)

Concepts: Evolutionary biology, Genetics, Artificial intelligence, Machine learning, Computational biology

DOI: 10.1186/s12864-021-07379-7