Genome-wide characterization of the NLR gene family in tomato (Solanum lycopersicum) and their relatedness to disease resistance

A physical model links structure and function in the plant immune system

Effector-Triggered Immunity (ETI) is an important part of the plant immune system, allowing plants to sense and respond to harmful pathogen proteins known as "effectors." Effectors can be sensed directly or indirectly by NLR (Nucleotide-binding Leucine-rich Repeat) proteins, many of which "guard" the plant proteins targeted by effectors. Although a few effector-target-NLR interactions have been characterized, a general understanding of how these molecular interactions give rise to a functioning immune system is lacking. Here, we present a physics-based model of ETI based on protein-protein interactions. We show that the simplest physical model consistent with the biology gives rise to a robust immune sensor and explains the empirical phenomenon of effector interference as a generic consequence of molecules competing for binding partners. Using the evolutionarily conserved ZAR1 defense gene as a model, we explain how more complex interaction networks integrate multiple pathogen signals into a single response. We then examine alternatives to a guarding architecture, including direct sensing, decoys, and blended "integrated decoy" strategies, and reveal that these sensing architectures obey functional trade-offs between their sensitivity, target protection, and proteomic cost. This allows a quantitative analysis of the trade-offs between different forms of ETI. We discuss these findings in the context of the evolutionary forces shaping the plant immune system.

The resistance awakens: Diversity at the DNA, RNA, and protein levels informs engineering of plant immune receptors from Arabidopsis to crops

Plants rely on germline-encoded, innate immune receptors to sense pathogens and initiate the defense response. The exponential increase in quality and quantity of genomes, RNA-seq datasets, and protein structures has underscored the incredible biodiversity of plant immunity. Arabidopsis continues to serve as a valuable model and theoretical foundation of our understanding of wild plant diversity of immune receptors, while expansion of study into agricultural crops has also revealed distinct evolutionary trajectories and challenges. Here, we provide the classical context for study of both intracellular nucleotide-binding, leucine-rich repeat receptors and surface-localized pattern recognition receptors at the levels of DNA sequences, transcriptional regulation, and protein structures. We then examine how recent technology has shaped our understanding of immune receptor evolution and informed our ability to efficiently engineer resistance. We summarize current literature and provide an outlook on how researchers take inspiration from natural diversity in bioengineering efforts for disease resistance from Arabidopsis and other model systems to crops.

Graft incompatibility between pepper and tomato elicits an immune response and triggers localized cell death

Graft compatibility is the capacity of two plants to form cohesive vascular connections. Tomato and pepper are incompatible graft partners; however, the underlying cause of graft rejection between these two species remains unknown. We diagnosed graft incompatibility between tomato and diverse pepper varieties based on weakened biophysical stability, decreased growth, and persistent cell death using viability stains. Transcriptomic analysis of the junction was performed using RNA sequencing, and molecular signatures for incompatible graft response were characterized based on meta-transcriptomic comparisons with other biotic processes. We show that tomato is broadly incompatible with diverse pepper cultivars. These incompatible graft partners activate prolonged transcriptional changes that are highly enriched for defense processes. Amongst these processes was broad nucleotide-binding and leucine-rich repeat receptors (NLR) upregulation and genetic signatures indicative of an immune response. Using transcriptomic datasets for a variety of biotic stress treatments, we identified a significant overlap in the genetic profile of incompatible grafting and plant parasitism. In addition, we found over 1000 genes that are uniquely upregulated in incompatible grafts. Based on NLR overactivity, DNA damage, and prolonged cell death, we hypothesize that tomato and pepper graft incompatibility is characterized by an immune response that triggers cell death which interferes with junction formation.

Unraveling the genetic basis of quantitative resistance to diseases in tomato: a meta-QTL analysis and mining of transcript profiles

KEY MESSAGE

Whole-genome QTL mining and meta-analysis in tomato for resistance to bacterial and fungal diseases identified 73 meta-QTL regions with significantly refined/reduced confidence intervals. Tomato production is affected by a range of biotic stressors, causing yield losses and quality reductions. While sources of genetic resistance to many tomato diseases have been identified and characterized, stability of the resistance genes or quantitative trait loci (QTLs) across the resources has not been determined. Here, we examined 491 QTLs previously reported for resistance to tomato diseases in 40 independent studies and 54 unique mapping populations. We identified 29 meta-QTLs (MQTLs) for resistance to bacterial pathogens and 44 MQTLs for resistance to fungal pathogens, and were able to reduce the average confidence interval (CI) of the QTLs by 4.1-fold and 6.7-fold, respectively, compared to the average CI of the original QTLs. The corresponding physical length of the CIs of MQTLs ranged from 56 kb to 6.37 Mb, with a median of 921 kb, of which 27% had a CI lower than 500 kb and 53% had a CI lower than 1 Mb. Comparison of defense responses between tomato and Arabidopsis highlighted 73 orthologous genes in the MQTL regions, which were putatively determined to be involved in defense against bacterial and fungal diseases. Intriguingly, multiple genes were identified in some MQTL regions that are implicated in plant defense responses, including PR-P2, NDR1, PDF1.2, Pip1, SNI1, PTI5, NSL1, DND1, CAD1, SlACO, DAD1, SlPAL, Ph-3, EDS5/SID1, CHI-B/PR-3, Ph-5, ETR1, WRKY29, and WRKY25. Further, we identified a number of candidate resistance genes in the MQTL regions that can be useful for both marker/gene-assisted breeding as well as cloning and genetic transformation.

Graft incompatibility between pepper and tomato can be attributed to genetic incompatibility between diverged immune systems

Graft compatibility is the capacity of two plants to form cohesive vascular connections. Tomato and pepper are incompatible graft partners; however, the underlying cause of graft rejection between these two species remains unknown.We diagnosed graft incompatibility between tomato and diverse pepper varieties based on weakened biophysical stability, decreased growth, and persistent cell death using trypan blue and TUNEL assays. Transcriptomic analysis of cell death in the junction was performed using RNA-sequencing, and molecular signatures for incompatible graft response were characterized based on meta-transcriptomic comparisons with other biotic processes.We show that tomato is broadly incompatible with diverse pepper cultivars. These incompatible graft partners activate prolonged transcriptional changes that are highly enriched for defense processes. Amongst these processes was broad NLR upregulation and hypersensitive response. Using transcriptomic datasets for a variety of biotic stress treatments, we identified a significant overlap in the genetic profile of incompatible grafting and plant parasitism. In addition, we found over 1000 genes that are uniquely upregulated in incompatible grafts.Based on NLR overactivity, DNA damage, and prolonged cell death we have determined that tomato and pepper graft incompatibility is likely caused by a form of genetic incompatibility, which triggers a hyperimmune-response.

NLR- and mlo-Based Resistance Mechanisms against Powdery Mildew in Cannabis sativa

Powdery mildew (PM) is one of the most common Cannabis sativa diseases. In spite of this, very few documented studies have characterized the resistance genes involved in PM defense mechanisms, or sources of natural genetic resistance in cannabis. The focus of the present work is on the two primary mechanisms for qualitative resistance against PM. The first is based on resistance (R) genes characterized by conserved nucleotide-binding site and/or leucine-rich repeat domains (NLRs). The second one involves susceptibility (S) genes, and particularly mildew resistance locus o (MLO) genes, whose loss-of-function mutations seem to be a reliable way to protect plants from PM infection. Cannabis defenses against PM are thus discussed, mainly detailing the strategies based on these two mechanisms. Emerging studies about this research topic are also reported and, based on the most significant results, a potential PM resistance model in cannabis plant-pathogen interactions is proposed. Finally, innovative approaches, based on the pyramiding of multiple R genes, as well as on genetic engineering and genome editing methods knocking out S genes, are discussed, to obtain durable PM-resistant cannabis cultivars with a broad-spectrum resistance range.

Integrated Molecular and Bioinformatics Approaches for Disease-Related Genes in Plants

Modern plant pathology relies on bioinformatics approaches to create novel plant disease diagnostic tools. In recent years, a significant amount of biological data has been generated due to rapid developments in genomics and molecular biology techniques. The progress in the sequencing of agriculturally important crops has made it possible to develop a better understanding of plant-pathogen interactions and plant resistance. The availability of host-pathogen genome data offers effective assistance in retrieving, annotating, analyzing, and identifying the functional aspects for characterization at the gene and genome levels. Physical mapping facilitates the identification and isolation of several candidate resistance (R) genes from diverse plant species. A large number of genetic variations, such as disease-causing mutations in the genome, have been identified and characterized using bioinformatics tools, and these desirable mutations were exploited to develop disease resistance. Moreover, crop genome editing tools, namely the CRISPR (clustered regulatory interspaced short palindromic repeats)/Cas9 (CRISPR-associated) system, offer novel and efficient strategies for developing durable resistance. This review paper describes some aspects concerning the databases, tools, and techniques used to characterize resistance (R) genes for plant disease management.