Abstract

The most important managed pollinator, the honeybee (Apis mellifera L.), has been subject to a growing number of threats. In western Europe, one such threat is large‐scale introductions of commercial strains (C‐lineage ancestry), which is leading to introgressive hybridization and even the local extinction of native honeybee populations (M‐lineage ancestry). Here, we developed reduced assays of highly informative SNPs from 176 whole genomes to estimate C‐lineage introgression in the most diverse and evolutionarily complex subspecies in Europe, the Iberian honeybee (Apis mellifera iberiensis). We started by evaluating the effects of sample size and sampling a geographically restricted area on the number of highly informative SNPs. We demonstrated that a bias in the number of fixed SNPs (FST = 1) is introduced when the sample size is small (N ≤ 10) and when sampling only captures a small fraction of a population's genetic diversity. These results underscore the importance of having a representative sample when developing reliable reduced SNP assays for organisms with complex genetic patterns. We used a training data set to design four independent SNP assays selected from pairwise FST between the Iberian and C‐lineage honeybees. The designed assays, which were validated in holdout and simulated hybrid data sets, proved to be highly accurate and can be readily used for monitoring populations not only in the native range of A. m. iberiensis in Iberia but also in the introduced range in the Balearic islands, Macaronesia and South America, in a time‐ and cost‐effective manner. While our approach used the Iberian honeybee as model system, it has a high value in a wide range of scenarios for the monitoring and conservation of potentially hybridized domestic and wildlife populations.

Highlights

  • Biodiversity, including the genetic diversity within and between populations, is a unique heritage whose conservation is imperative for the benefit of future generations (Frankham, Ballou, & Briscoe, 2002)

  • Developing cost-­effective molecular tools for accurate estimation of introgression in A. mellifera is increasingly important as commercial strains are threatening native genetic diversity in many regions throughout Europe (Bertrand et al, 2015; De la Rúa et al, 2009; Jensen et al, 2005; Parejo et al, 2016; Pinto et al, 2014; Soland-­Reckeweg et al, 2009)

  • The processing of the large amounts of data generated by whole-­ genome sequencing requires bioinformatics expertise and powerful computational resources typically not available to state entities or conservation centres

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Summary

| INTRODUCTION

Biodiversity, including the genetic diversity within and between populations, is a unique heritage whose conservation is imperative for the benefit of future generations (Frankham, Ballou, & Briscoe, 2002). Such complexity has been shaped by recurrent cycles of interacting selective and demographic processes, typical of long-­term glacial refugia organisms (Chávez-­Galarza et al, 2013, 2015, 2017) This genetic legacy might be at risk if Iberian beekeepers adopt a strategy of importing commercial strains belonging to the highly divergent lineage C, as is occurring at large-­scale throughout western and northern Europe north of the Pyrenees. Following the last glacial maximum, honeybees dispersed from the Iberian refugium to colonize a broad territory, extending from the Pyrenees to the Urals (Franck, Garnery, Solignac, & Cornuet, 1998; Ruttner, 1988) This important Iberian reservoir of genetic diversity has not yet been seriously threatened by C-­lineage introgression (Chávez-­Galarza et al, 2015, 2017; Miguel, Iriondo, Garnery, Sheppard, & Estonba, 2007), this scenario might change as many young beekeepers are attracted by the advertised benefits of commercial strains—being more prolific and docile. The constructed SNP assays were revealed to be very powerful for accurately estimating C-­lineage introgression and can be applied to support conservation efforts in the Iberian honeybee

| MATERIALS AND METHODS
Findings
| DISCUSSION
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