A metabolomic approach to the identification of health based consumer traits in tomato

We want to eat nice, tasty fruit and vegetables that are safe and good for us. Antioxidants are compounds found in fruits and vegetables that when obtained in the diet can help combat diseases. This is why it is important to eat fruits and vegetables regularly. In order to create improved, nutritional fruit and vegetables breeding programmes must be carried out to incorporate the desired improvements from one variety into another, which already has other worthwhile qualities. This approach utilises natural diversity and is a non-GM approach, thus avoiding the incorporation of foreign DNA. It is the composition of the molecules (chemicals) in the fruit that yield the characteristic properties we want. In order to identify improved health features and other characteristics that we want the molecules of interest have to be analysed. Modern methods enable us to identify many molecules simultaneously. We will use these chemical approaches to identify tomato varieties with improved features, especially those that will improve our health. To do this tomato collections that have had diversity crossed into a parent will be used. The amounts and types of compounds identified will be large and using computational approaches, these molecules can be linked to the desired characteristics we need to have in the final variety. In our case, this will be an enhanced level of antioxidants.

The consumers' demand for improved food quality has made nutritional content an important aspect of plant breeding. Although GM technology can introduce some of these traits into crops it is presently unacceptable to the public. The introduction of new diversity into breeding programs offers an alternative approach. The Solanum pennellii and S. habrochaites introgression line (IL) populations of tomato are a genomic resource from which quality traits of interest can be identified and subsequently transferred into elite lines. In the proposed project the two existing IL populations will be cultivated over two seasons under glasshouse conditions for the first time, in a manner that will facilitate accurate elucidation of metabolic diversity. In order to chemotype each IL genotype the NMR chemical fingerprinting approach available through the MeT-RO, Rothamsted facility will be used. The overview of the metabolite composition in each IL will provide a valuable community resource, from which traits and metabolites underlying QTLs can be identified. In addition, tomato represents a model system for all soft fruit crops and the Solanaceae taxa. A sub-set of ILs, relating to enhanced antioxidant (health) and colour traits, will be identified within the populations by targeted metabolite profiling for health-related phytochemicals (carotenoids, tocopherols, vitamin C, phenylpropanoids and flavonoids). This sub-set of ILs will be subjected to metabolomic analysis using NMR-MS on non-polar and polar fractions, GC-MS profiling and targeted metabolite analysis, creating large data sets. The data sets will be analysed and mined using the expertise at MeT-RO (Aberystwyth). Such an experimental approach will elucidate the metabolites and shifts in metabolism associated with health (antioxidant) and colour traits as well as enabling further annotation of the physical map of the IL chromosome segments with metabolite composition and associated traits. A clear route to the underlying gene(s) responsible will be defined and direction for future breeding programs determined. The datasets and related information will be curated and deposited using ArMet (http://www.armet.org) and Met-Ro databases enabling future access and utilisation by the scientific community. In addition the data outputs will be disseminated via the Solanaceae genome network (http;//www.sgn.cornell.edu/) and SRC-UK website (www.srcuk.org).