Evaluating the performance of a variable number of SNPs for genetic identification and introgression analysis in the dark honey bee

Abstract

Genetic identification and introgression analysis using molecular markers is an important tool for management and conservation of honey bee subspecies. High density assays featuring Single Nucleotide Polymorphism (SNP) markers can be exploited to create a reduced panel containing the most informative markers for these purposes. The objective of this study was to determine the minimum number of SNP loci required to verify the origin of dark honey bee individuals and to provide accurate estimates of the level of C-lineage introgression into their genome. We estimated allele frequencies of ll83 SNPs from ll3 drone honey bee individuals sampled in the natural ranges of A. m. melliféra, A. m. carnica and A. m. ligustica, and evaluated the discriminant power of the SNPs using a variety of metrics and approaches including the Weir & Cockerham’s FST, Delta, informativeness (In), PCA and an FST-based outlier test. Taking into account the less expensive multiplex assays made available by Illumina®, we created 5 panels of 48-, 96-, 144-, 192- and 384-SNPs with the average top-ranked loci and tested them to obtain the probability of assigning individuals to the correct origin and to calculate the admixture level using each panel. The analyses showed no significant differences in the introgression proportions produced by the different SNP panels, suggesting that a low number of loci is sufficient to produce accurate estimates. This study was financed by the Project PTDC/BIA-BEC/099640/2008 and I. Muñoz was supported by a Postdoctoral fellowship from the Fundacion Séneca (Murcia, Spain).