Part 1: Understanding Drone Genetics

Study Description

Drone reproductive traits are essential for queen performance and colony success, yet we know very little about the role of genetics on these traits. The goal of this project is to identify genetic markers associated with drone reproductive traits. We will first screen important drone reproductive traits for 2 distinct genetic lineages and their offspring generation. Then, we will use genomic and transcriptomic sequencing techniques to associate genetic markers with measured drone phenotypic variation. Once we identify these genetic markers, we will develop a low-cost genetic screen for beekeepers to select breeder colonies for high-quality drones

BACKGROUND:

Pollinators improve the production of 87 of the leading global food products and provide over $215 billion worth of ecosystem services (1–4). Honey bees alone can increase yield for over 96% of pollinator-dependent crops. Though critical to food production, honey bee colonies—which are largely managed through commercial beekeeping operations—are expected to be reduced by over one third in number annually (5, 6). Despite these declines, the United States has increased both their demand and dependence on honey bees as pollinators (7). As a result, honey bee health is a matter of national concern.

The cause of honey bee declines is multifarious but among the largest threats is queen failure. Shockingly, as many as 50% of commercial queens fail within 6 months (8–10). The cause of failure and the production of poor queens is of deep importance to beekeepers and researchers alike (5, 6, 11). While much energy has focused on queens (12, 13), we are increasingly discovering that drones play a more important role in queen quality than originally expected. Indeed, queen reproductive potential has been linked to low sperm viability (14, 15) and poor drone quality (15, 16).

We have a detailed understanding of the traits necessary for drone reproduction: sperm morphology, seminal fluid composition (proteins and nucleic acids), and endophallus morphology to name only a few. However, we have little understanding of precisely how variation in these traits is generated. This is an important question because variation in reproductive phenotypes can lead to variation in drone reproductive success and ultimately, queen reproductive potential. Classically, phenotypic variation is generated through the effects of environmental and genetic variation (17). In the case of honey bee drone reproductive traits, we have substantial evidence of the role of environmental factors. For example, extreme temperatures (14, 18), miticides (19), insecticides (15), and poor nutrition (20) all deplete important reproductive traits.

We know comparatively little about the role genetics plays in shaping drone reproductive traits (16, 21, 22). This is a major gap in both our understanding of honey bee biology and in our ability to effectively manage colonies because there is substantial genetic variation in North American managed populations (23). This standing genetic variation may contribute to phenotypic variation in drone reproductive success observed among honey bee stocks in North America (16, 21, 22) and contribute to the success (or failure) of colonies (24).

 

Citations

1. Smith KM, et al. (2014) Ecohealth 10(4):434–445.2. Aizen MA, Garibaldi LA, Cunningham SA, Klein AM (2009) Ann Bot 103(9):1579–1588.3. Gallai N, Salles J-M, Settele J, Vaissière BE (2008) Ecol Econ 68(3):810–821.4. Klein A-M, et al. (2007) Proc R Soc B Biol Sci 274(1608):303–313.5. Kulhanek K, et al. (2017) J Apic Res 56(4):328–340.6. USDA-NASS (2017) 1–20.7. Brittain C, Williams N, Kremen C, Klein A (2013) Proc R Soc London B Biol Sci 280:20122767.8. vanEngelsdorp D, Tarpy DR, Lengerich EJ, Pettis JS (2013) Prev Vet Med 108(2–3):225–233.9. Sandrock C, et al. (2014) PLoS One 9(8):1–13.10. Pettis JS, Wilson W, Shimanuki H, Teel P (1991) Apidologie 22:1–7.11. Brodschneider R, et al. (2016) J Apic Res 55(5):375–378.12. Delaney D, et al. (2011) Apidologie 42(1): 1-13.13. Tarpy DR, Keller JJ, Caren JR, Delaney DA (2012). J Econ Entomol. doi:10.1603/EC11276.14. Pettis JS, Rice N, Joselow K (2016) 1–10.15. Kairo G, et al. (2016) Sci Rep 6. doi:10.1038/srep31904.16. Rousseau A, Fournier V, Giovenazzo P (2015) Can Entomol. doi:10.4039/tce.2015.12.17. Fischer E (1918) J für die reine und Angew Math 148:1–78.18. Bienkowska M, Panasiuk B, Wegrzynowicz P, Gerula D (2011) t J Apic Sci 55(2):161–168.19. Johnson RM, Dahlgren L, Siegfried BD, Ellis MD (2013) J Apic Res. doi:10.3896 /IBRA.1.52.2.18.20. Rousseau A, Giovenazzo P (2016) J Econ Entomol. doi:10.1093/jee/tow056.21. Woyke J, Jasinski Z (1978) Apidologie 9(3):203–212.22. LOCKE SJ, PENG Y ‐S (1993) Physiol Entomol 18(2):144–148.23. Harpur BA, Minaei S, Kent CF, Zayed A (2012) Mol Ecol. doi:10.1111/j.1365-294X.2012.05614.x.24. Hunt G, Given KJ, Tsuruda JM, Andino GK (2016) Bee Cult 8:41–47.

 

 

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