P0467 The Transcriptome of Tomato (S. lycopersicum)

Marco Pietrella , Italian Agency for New Technologies Energy & Sustainable Development, Rome, Italy
Gianfranco Diretto , Italian Agency for New Technologies Energy & Sustainable Development, Rome, Italy
Irina Mohorianu , University of East Anglia, School of Computing Sciences, Norwich, United Kingdom
Sara Lopez-Gomollon , University of East Anglia, School of Biological Sciences, Norwich, United Kingdom
Simon Moxon , Yale University, New Haven, CT
Clelia Peano , Institute of Biomedical Technologies, National Research Council, Milan, Italy
Fabio Fuligni , Institute of Biomedical Technologies, National Research Council, Milan, Italy
Ulrike Göbel , Max-Planck Institute for Plant Breeding Research, Koeln, Germany
Heiko Schoof , University of Bonn, Bonn, Germany
Gianluca De Bellis , Institute of Biomedical Technologies, National Research Council, Milan, Italy
Tamas Dalmay , University of East Anglia, School of Biological Sciences, Norwich, United Kingdom
Giovanni Giuliano , Italian Agency for New Technologies Energy & Sustainable Development, Rome, Italy
Tomato (S. lycopersicum) is one of the most important vegetable crops and a widely used model system for the study of fruit biology. Its genome has been recently sequenced and the corresponding gene annotation is of fundamental importance to get a deep insight into the biology of this plant. To get a better understanding of its transcriptome, we performed deep 454 and Illumina RNAseq and Illumina sRNA sequencing of several tissues of S. lycopersicum and its closest wild relative, S. pimpinellifolium. The sequencing data was used to identify and predict known and novel miRNAs and degradome libraries were used to predict targets for all the miRNAs. Using co-expression analysis, we built correlation networks and could identify miRNAs controlling several genes that could play a role in fruit ripening. Also, an analysis was conducted on nucleotide hexamers with putative regulatory functions, enriched in the promoters of tissue-specific genes.