Supervisors: Beverley Glover and John Carr
Plant-eating insects are important because they cause around half of all crop losses. Additionally, some of these insects also transmit microorganisms that cause plant disease and this results in further crop losses. Trichomes (microscopic plant hairs) are important physical and/or chemical barriers against insect herbivory and represent potential targets for enhancing crop resistance to herbivores and the diseases they vector. For example, tomato plants possess five different types of hair that act as physical barriers, sticky traps or as booby-traps that release natural chemical insecticides and other protective substances when they are touched by insects. Tomato is a high value crop grown throughout the world, under conditions ranging from intensive large-scale cultivation to smallholder and subsistence farming. Both commercial and small-scale agriculture would benefit greatly through better understanding of how plant hairs develop and how they deter or kill insects.
Until the recent advent of high-throughput DNA sequencing, identification of genes controlling trichome development from crop species was technically difficult due to the complexity of the traits and the multiple trichome types present on many species. In this project you will use novel high throughput sequencing approaches to identify genes controlling trichome development and morphology in tomato, applying the SHOREmap technique only used so far in Arabidopsis and rice to identify trichome regulating loci from classical tomato trichome mutants. You will use misexpression of these genes in transgenic plants to determine their effects on feeding preferences, growth and behaviour of sap-sucking aphids. In combination this project will provide training in molecular genetic and bioinformatics techniques, as well as in herbivore behavioural studies.
- Schneeberger, K., Ossowski, S., Lanz, C., Juul, T., Petersen, A.H., Nielsen, K.L., Jorgensen, J., Weigel, D., and Andersen, S.U. 2009. SHOREmap: simultaneous mapping and mutation identification by deep sequencing. Nature Methods, 6, 550-551.