Tomato (Solanum lycopersicum L.) has served as an important model system for studying the genetics and molecular basis of resistance mecha- nisms in plants. An unprecedented challenge is now to capitalize on the genetic and genomic achievements obtained in this species. In this study, we show that information on the tomato genome can be used predictively to link resistance function with specific sequences. An integrated genomic approach for identifying new resistance (R) gene candidates was developed. An R gene functional map was created by co-localization of candidate pathogen recognition genes and anchoring molecular markers associated with resistance phenotypes. In-depth characterization of the identified pathogen recognition genes was performed. Finally, in order to highlight expressed pathogen recognition genes and to provide a first step in validation, the tomato transcriptome was explored and basic molecular analyses were conducted. Such methodology can help to better direct positional cloning, reducing the amount of effort required to identify a functional gene. The resulting candidate loci selected are available for exploiting their specific function
