Cargando…
The Tomato Interspecific NB-LRR Gene Arsenal and Its Impact on Breeding Strategies
Tomato (Solanum lycopersicum L.) is a model system for studying the molecular basis of resistance in plants. The investigation of evolutionary dynamics of tomato resistance (R)-loci provides unique opportunities for identifying factors that promote or constrain genome evolution. Nucleotide-binding d...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7911644/ https://www.ncbi.nlm.nih.gov/pubmed/33514027 http://dx.doi.org/10.3390/genes12020184 |
Sumario: | Tomato (Solanum lycopersicum L.) is a model system for studying the molecular basis of resistance in plants. The investigation of evolutionary dynamics of tomato resistance (R)-loci provides unique opportunities for identifying factors that promote or constrain genome evolution. Nucleotide-binding domain and leucine-rich repeat (NB-LRR) receptors belong to one of the most plastic and diversified families. The vast amount of genomic data available for Solanaceae and wild tomato relatives provides unprecedented insights into the patterns and mechanisms of evolution of NB-LRR genes. Comparative analysis remarked a reshuffling of R-islands on chromosomes and a high degree of adaptive diversification in key R-loci induced by species-specific pathogen pressure. Unveiling NB-LRR natural variation in tomato and in other Solanaceae species offers the opportunity to effectively exploit genetic diversity in genomic-driven breeding programs with the aim of identifying and introducing new resistances in tomato cultivars. Within this motivating context, we reviewed the repertoire of NB-LRR genes available for tomato improvement with a special focus on signatures of adaptive processes. This issue is still relevant and not thoroughly investigated. We believe that the discovery of mechanisms involved in the generation of a gene with new resistance functions will bring great benefits to future breeding strategies. |
---|