In order to enable exploitation of the tomato genome sequence, the protein coding genes on the raw DNA sequence will be identified and putative functions assigned. To this end, so-called gene-calling software will be applied to predict and model gene structures. To provide and disseminate the gene models to the SOL-community, a database for storing all gene structure-based information is available from TomDB or BOGAS (with browser). Apart from the protein-coding genes, other genetic elements need to be identified and annotated as well, such as transposable elements and repeats, microRNA etc. Due to their specific characteristics, the identification of these elements requires different approaches and techniques than those used for finding and predicting protein-coding genes. A fully automated screening of the predicted proteins for functional annotation will be performed. Comparative genomics approaches will be used to unveil conserved as well as novel biological features in different plant species. A well-known example is the identification of conserved elements - such as cis-acting regulatory elements - between different genomes that, because of their conservation over longer periods of time, must have an important functional meaning.  Genome assembly pipelines, will also be further developed specifically in the areas of automated repeat resolution and quality assessment.



Summary
•    To provide a remotely accessible annotation platform, and standardized Solanaceae predictions for protein-encoding genes, non-protein coding genes and transposable elements across all tomato genome sequences, and ensure consistent availability of the data for the IP.
•    To apply quality checks, including evaluation of results from other prediction platforms.
•    To provide improved tools to all tomato sequencers, aiming at having an optimal tomato sequence assembly of consistent quality   across all chromosomes, and within the EU-SOL.
•    To provide detailed automated functional annotation for all predicted genes with AFAWE
•    Provide the one-stop-shop database for data generated in T6.1.1, T6.1.3, T6.1.4
•    Provide assistance to the design of micro-array, link probes to predicted gene models