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Developing reduced SNP assays from whole-genome sequence data to estimate introgression

Developing reduced SNP assays from whole-genome
sequence data to estimate introgression in an organism with  complex genetic patterns, the Iberian honeybee (Apis mellifera iberiensis)

Dora Henriques, Melanie Parejo, Alain Vignal, David Wragg,
Andreas Wallberg, Matthew T. Webster, M. Alice Pinto

 

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-scaleintroductions of commercial st rains (C-lineageancestry), which is leading to
introgressive hybridization and even the local extinction of native honeybee populations (M-lineageancestry). 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 arepresentative 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.

Evolutionary Applications. 2018;1–13.

https://doi.org/10.1111/eva.12623