High sample throughput genotyping for estimating C-lineage introgression in the dark honeybee: an accurate and cost-effective SNP-based tool

Abstract

The natural distribution of the honeybee (Apis mellifera L.) has been changed by humans in recent decades to such an extent that the formerly widest-spread European subspecies, Apis mellifera mellifera, is threatened by extinction through introgression from highly divergent commercial strains in large tracts of its range. Conservation efforts for A. m. mellifera are underway in multiple European countries requiring reliable and cost-efficient molecular tools to identify purebred colonies. Here, we developed four ancestry-informative SNP assays for high sample throughput genotyping using the iPLEX Mass Array system. Our customized assays were tested on DNA from individual and pooled, haploid and diploid honeybee samples extracted from different tissues using a diverse range of protocols. The assays had a high genotyping success rate and yielded accurate genotypes. Performance assessed against whole-genome data showed that individual assays behaved well, although the most accurate introgression estimates were obtained for the four assays combined (117 SNPs). The best compromise between accuracy and genotyping costs was achieved when combining two assays (62 SNPs). We provide a ready-to-use cost-effective tool for accurate molecular identification and estimation of introgression levels to more effectively monitor and manage A. m. mellifera conservatories.

Mitochondrial SNP markers to monitor evolutionary lineage ancestry in Apis melliferamellifera conservation programs

“…A number of studies have designed diagnostic tools with nuclear (nc) SNP markers capable of discriminating different honey bee lineages (Chapman et al 2015(Chapman et al , 2017Muñoz et al 2015;Parejo et al 2016). Recently, a set of highly informative ncSNPs for estimating C-derived introgression into A. m. mellifera (Muñoz et al 2015) were combined into four assays, which were tested and validated for genotyping in the Agena BioScience™ iPLEX MassARRAY platform (Henriques et al 2018a). The number of ncSNPs included in each of the four assays (M1 = 34, M2 = 32, M3 = 28, M4 = 23) is lower than the maximum capacity of the iPLEX protocol (40 SNPs) allowing additional markers, such as mitochondrial SNPs (mtSNPs).…”

“…The aim of this study was to improve the SNPs assays developed by Henriques et al (2018a) adding informative mitochondrial SNPs. To this end, we used whole mtDNA sequence data of 155 drones, each representing a single colony, collected across Europe (Table S1) (Henriques et al 2019;Parejo et al 2016).…”

“…F ST values between M-and C-derived individuals were inferred for each mtSNP from the training set using PLINK 1.9 (Chang et al 2015), and those showing F ST values > 0.75 were selected. Sequence information of the flanking regions (250 bp) of the selected mtSNPs was then used to supplement the four ncSNP assays (Henriques et al 2018a) using the Replex option of the software AssayDesign 4.0 (Agena BioScience™). The software searched for optimal areas within the flanking regions to design forward, reverse, and iPLEX extension primers compatible with those published in Henriques et al (2018a).…”

“…The five informative mtSNPs could only be added to the M4 ncSNP assay designed previously (Henriques et al 2018a), which contained the lowest number of ncSNPs (23). Henriques et al (2018a) showed that assay M1 (34 ncSNPs) has the best individual performance in estimating nuclear C-lineage introgression. Accordingly, a good approach for concurrent inference of nuclear and mitochondrial ancestry could be to combine M1 with the new 28-plex M4 (23 ncSNPs plus 5 mtSNPs).…”

“…Accordingly, a good approach for concurrent inference of nuclear and mitochondrial ancestry could be to combine M1 with the new 28-plex M4 (23 ncSNPs plus 5 mtSNPs). We therefore tested if the introgression proportions (Q values) estimated from the ncSNP assays M1 + M4 were similar to those obtainedfromthefourassaystogether (Henriques et al 2018a). From the 117 SNPs included in the four assays, we were able to extract 113 from the 155whole-genome (WG) sequences.…”