Project No. 2466

STANDARD PROJECT

Primary Supervisor

Dr Daniel Stabler – University of Southampton

Co-Supervisor(s)

Dr Maria Clara Castellanos – University of Sussex

Dr Lorraine Williams – University of Southampton

Summary

Food security is at the forefront of important topics in bioscience and in developing biotechnology.

Animal pollination of crops improves yield, providing larger, more nutritious yields per unit of land than unpollinated crops – even self-pollinating species have improved seed set when visited by pollinators. To improve our insurance on securing food we must understand how plants allocate nutrients to nectar to maintain high pollination rates.

Nectar is a unique plant exudate, used florally to reward pollinating animals, and extra-florally to reward animals that facilitate herbivore defence. It is a highly variable liquid composed of sugars, amino acids, proteins, lipids, minerals, and secondary metabolites. Volume, viscosity, and time that nectar is produced also vary greatly between species.

Carbohydrate exchange is essential currency for animals in engaging with plants. Plants synthesise, transport, and store their sugars to support their own growth and somatic maintenance. However, transport of sugars to nectaries and into nectar is a critical function of supplying an energetic reward to visiting pollinators. Previous work has identified the necessity of SWEET9 for the transport of sucrose into nectar. However, to date, we do not understand how cultivars of crop plants vary in their expression of sugar transporters (SWEET family) and how they respond to the broad environmental conditions that crop plants are exposed to.

The student will pair analytical (HPLC) and molecular techniques (qPCR) with field level data to understand how crops vary in their expression of the family of SWEET genes and how their expression relates to current and predicted agricultural conditions. This project has scope to have real impact in how crop plants are bred and engineered and to understand how species might be suitable for predicted climates in an uncertain world. The candidate would benefit from experience with analytical techniques including qPCR, HPLC, LC-MS or GC-MS.