A SNP assay for assessing diversity in immune genes in the honey bee (Apis mellifera L.)

A genotyping by sequencing approach can disclose Apis mellifera population genomic information contained in honey environmental DNA

Awareness has been raised over the last years on the genetic integrity of autochthonous honey bee subspecies. Genomic tools available in Apis mellifera can make it possible to measure this information by targeting individual honey bee DNA. Honey contains DNA traces from all organisms that contributed or were involved in its production steps, including the honey bees of the colony. In this study, we designed and tested a genotyping by sequencing (GBS) assay to analyse single nucleotide polymorphisms (SNPs) of A. mellifera nuclear genome using environmental DNA extracted from honey. A total of 121 SNPs (97 SNPs informative for honey bee subspecies identification and 24 SNPs associated with relevant traits of the colonies) were used in the assay to genotype honey DNA, which derives from thousands of honey bees. Results were integrated with information derived from previous studies and whole genome resequencing datasets. This GBS method is highly reliable in estimating honey bee SNP allele frequencies of the whole colony from which the honey derived. This assay can be used to identify the honey bee subspecies of the colony that produced the honey and, in turn, to authenticate the entomological origin of the honey.

Age and Season Effect the Timing of Adult Worker Honeybee Infection by Nosema ceranae

The microsporidia Nosema ceranae is an intracellular parasite of honeybees’ midgut, highly prevalent in Apis mellifera colonies for which important epidemiological information is still unknown. Our research aimed at understanding how age and season influence the onset of infection in honeybees and its development in the colony environment. Adult worker honeybees of less than 24h were marked and introduced into 6 different colonies in assays carried out in spring and autumn. Bees of known age were individually analyzed by PCR for Nosema spp. infection and those resulting positive were studied to determine the load by Real Time-qPCR. The age of onset and development of infection in each season was studied on a total of 2401 bees and the probability and the load of infection for both periods was established with two statistical models. First N. ceranae infected honeybees were detected at day 5 post emergence (p.e.; spring) and at day 4 p.e. (autumn) and in-hive prevalence increased from that point onwards, reaching the highest mean infection on day 18 p.e. (spring). The probability of infection increased significantly with age in both periods although the age variable better correlated in spring. The N. ceranae load tended to increase with age in both periods, although the age-load relationship was clearer in spring than in autumn. Therefore, age and season play an important role on the probability and the development of N. ceranae infection in honeybees, bringing important information to understand how it spreads within a colony.