Plant nucleotide-binding leucine-rich repeat (NLR) immune receptors are pivotal components of plant innate immunity. They act as intracellular molecular sensors that recognize pathogen effectors or their activity to confer host-specific resistance in plants. These NLR immune receptors undergo extensive sequence diversification to keep pace with rapidly evolving pathogens. In the plant genome, this is reflected by extensive NLR repertoires characterized by gene clusters of closely related homologs with different recognition specificities, but often similar defense signaling properties.
Genome sequencing efforts in model and crop plant species now provide a wealth of information on the natural variation of NLR-encoding genes in plant genomes, including intra- and interspecific sequence variation. However, the extent to which sequence variation contributes to pathogen detection and NLR immune receptor activation at the molecular level is still poorly understood. Combining recent developments in the field of NLR structural biology, computational biology and machine learning will revolutionize our understanding of how natural sequence variation contributes to shaping a functionally diverse NLR immune receptor repertoire in plants. This knowledge will also provide a framework for the development of novel functional NLR immune receptors to improve crops, by highlighting functional constraints and opportunities to expand NLR diversity through genetic engineering.
This Research Topic covers a wide range of approaches and perspectives that will generate a large collection of articles highlighting current developments and advances in the field. The focus is, but is not limited to, plant NLR immune receptors and their matching effectors and/or co-factors. Contributions should emphasize developments on subtopics or combinations as diverse as:
• Molecular and functional diversity in NLR proteins across plant species;
• Evolutionary diversity, dynamics and adaptation of NLRs - integrated decoys, networks, etc;
• Biochemical insights into the plant immune signaling pathways;
• Structure-informed analysis of NLR helper/sensor functions: activation and recognition mechanisms in vitro and in vivo;
• Experimental and computational investigation of NLR complexes pre/post activation;
• New experimental tools in plant immune system research;
• Bioinformatic tools and resources aiding plant immunity research;
• Artificial Intelligence techniques in revealing molecular & evolutionary patterns and assessing the NLR diversity landscape;
• Artificial evolution to expand NLR diversity by biotechnological tools.
Plant nucleotide-binding leucine-rich repeat (NLR) immune receptors are pivotal components of plant innate immunity. They act as intracellular molecular sensors that recognize pathogen effectors or their activity to confer host-specific resistance in plants. These NLR immune receptors undergo extensive sequence diversification to keep pace with rapidly evolving pathogens. In the plant genome, this is reflected by extensive NLR repertoires characterized by gene clusters of closely related homologs with different recognition specificities, but often similar defense signaling properties.
Genome sequencing efforts in model and crop plant species now provide a wealth of information on the natural variation of NLR-encoding genes in plant genomes, including intra- and interspecific sequence variation. However, the extent to which sequence variation contributes to pathogen detection and NLR immune receptor activation at the molecular level is still poorly understood. Combining recent developments in the field of NLR structural biology, computational biology and machine learning will revolutionize our understanding of how natural sequence variation contributes to shaping a functionally diverse NLR immune receptor repertoire in plants. This knowledge will also provide a framework for the development of novel functional NLR immune receptors to improve crops, by highlighting functional constraints and opportunities to expand NLR diversity through genetic engineering.
This Research Topic covers a wide range of approaches and perspectives that will generate a large collection of articles highlighting current developments and advances in the field. The focus is, but is not limited to, plant NLR immune receptors and their matching effectors and/or co-factors. Contributions should emphasize developments on subtopics or combinations as diverse as:
• Molecular and functional diversity in NLR proteins across plant species;
• Evolutionary diversity, dynamics and adaptation of NLRs - integrated decoys, networks, etc;
• Biochemical insights into the plant immune signaling pathways;
• Structure-informed analysis of NLR helper/sensor functions: activation and recognition mechanisms in vitro and in vivo;
• Experimental and computational investigation of NLR complexes pre/post activation;
• New experimental tools in plant immune system research;
• Bioinformatic tools and resources aiding plant immunity research;
• Artificial Intelligence techniques in revealing molecular & evolutionary patterns and assessing the NLR diversity landscape;
• Artificial evolution to expand NLR diversity by biotechnological tools.