The regulatory network controlling tomato ripening

The global tomato industry is worth in excess of $10 billion. More than 100 million metric tonnes of tomatoes are produced each year, and in the United States and Western Europe it is the most important fruit in the human diet in terms of quantity consumed. A diet rich in fruits and vegetables is known to be essential for human health providing protection from heart disease, stroke, high blood pressure and certain cancers. This project focuses on understanding the molecular basis of fruit quality attributes in partnership with Syngenta, a company with a world wide tomato business. The strategy will be to compare the molecular events occurring in the fruits of wild type and naturally occurring non-ripening mutants of tomato. The regulatory genes underlying these mutations have recently been identified. The challenge is to connect the emerging network of regulatory factors with their down-stream effectors and thereby identify control points for the various ripening pathways, for example, colour development and fruit softening. We will achieve this aim by profiling the gene expression and metabolite pools of wild type and mutant tomato fruit at a wide range of stages of fruit development. Mathematical modelling techniques will then be used to associate regulators with down-stream effects and metabolites, to produce an initial regulatory framework. These models can then be tested experimentally by silencing selected transcription factors in transgenic plants and determining how this affects the patterns of gene expression, metabolite pools and ripening. This will allow us to build dynamic models to describe this important developmental process. Our industrial partner will use the information to breed improved tomato varieties.

Tomato is probably the most important fruit in the western diet and is also a model for understanding the development and ripening of fleshy fruits. In partnership with Syngenta, we want to understand the molecular basis of fruit ripening and use this information to breed improve tomato varieties. In tomato, there are a small number of distinct single gene mutants where ripening is almost completely abolished. The genes underlying these mutations have been cloned by us and others. In this application we will analyse the transcriptome and metabolome of wild type and non-mutant tomato fruit at 8 stages of fruit development and ripening, and use the information to build dynamic models that describe the ripening process. To achieve this aim we will draw on a range of unique and public genomics resources. The transcriptomics data will be obtained using the Syngenta GeneChip array containing sequences that represent 22000 genes. Syngenta will undertake the metabolomics assays and will capture information on at least 60 compounds in an untargeted screen, as well as targeted quantitative analysis for carotenoids, polyphenols and flavonoids. The data analysis will then be undertaken within the Centre for Plant Integrative Biology (CPIB), but with additional inputs from Syngenta using their proprietary tomato-specific metabolic-network. Time-Series Network Identification and Bayesian Network Reconstruction will be used to build initial network models connecting transcription factors to down-stream genes and metabolites. These and subsequent dynamic models will provide hypotheses for testing in tomato using virus induced gene silencing (VIGS). The models will then be refined from the array and metabolite profiles of the fruit where transcription factor expression has been modulated. A final refined model will be used to select targets for the development of novel varieties.