Overview of tomato (Solanum lycopersicum) candidate pathogen recognition genes reveals important Solanum R locus dynamics.
To investigate the genome-wide spatial arrangement of R loci, a complete catalogue of tomato (Solanum lycopersicum) and potato (Solanum tuberosum) nucleotide-binding site (NBS) NBS, receptor-like protein (RLP) and receptor-like kinase (RLK) gene repertories was generated. Candidate pathogen recognition genes were characterized with respect to structural diversity, phylogenetic relationships and chromosomal distribution. NBS genes frequently occur in clusters of related gene copies that also include RLP or RLK genes. This scenario is compatible with the existence of selective pressures optimizing coordinated transcription. A number of duplication events associated with lineage-specific evolution were discovered. These findings suggest that different evolutionary mechanisms shaped pathogen recognition gene cluster architecture to expand and to modulate the defence repertoire. Analysis of pathogen recognition gene clusters associated with documented resistance function allowed the identification of adaptive divergence events and the reconstruction of the evolution history of these loci. Differences in candidate pathogen recognition gene number and organization were found between tomato and potato. Most candidate pathogen recognition gene orthologues were distributed at less than perfectly matching positions, suggesting an ongoing lineage-specific rearrangement. Indeed, a local expansion of Toll/Interleukin-1 receptor (TIR)-NBS-leucine-rich repeat (LRR) (TNL) genes in the potato genome was evident. Taken together, these findings have implications for improved understanding of the mechanisms of molecular adaptive selection at Solanum R loci.
Andolfo, G., Sanseverino, W., Rombauts, S., Van de Peer, Y., Bradeen, J. M., Carputo, D., Frusciante, L., Ercolano, M. (2012) Overview of tomato (Solanum lycopersicum) candidate pathogen recognition genes reveals important Solanum R locus dynamics. New Phytol. 197(1):223-37.
VIB / UGent
Bioinformatics & Evolutionary Genomics
+32 (0) 9 33 13807 (phone)
+32 (0) 9 33 13809 (fax)