Plants have developed a complex defense system against diverse pests and pathogens. Once pathogens overcome mechanical barriers to infection, plant receptors initiate signaling pathways driving the expression of defense response genes. Plant immune systems rely on their ability to recognize enemy molecules, carry out signal transduction, and respond defensively through pathways involving many genes and their products. Pathogens actively attempt to evade and interfere with response pathways, selecting for a decentralized, multicomponent immune system. Recent advances in molecular techniques have greatly expanded our understanding of plant immunity, largely driven by potential application to agricultural systems. Here, we review the major plant immune system components, state of the art knowledge, and future direction of research on plant–pathogen interactions. In our review, we will discuss how the decentralization of plant immune systems have provided both increased evolutionary opportunity for pathogen resistance, as well as additional mechanisms for pathogen inhibition of such defense responses. We conclude that the rapid advances in bioinformatics and molecular biology are driving an explosion of information that will advance agricultural production and illustrate how complex molecular interactions evolve.

Nucleotide Binding Site—Leucine-Rich Repeat (NBS-LRR) genes encode disease resistance proteins involved in plants’ defense against their pathogens. Although sunflower is affected by many diseases, only a few molecular details have been uncovered regarding pathogenesis and resistance mechanisms. Recent availability of sunflower whole genome sequences in publicly accessible databases allowed us to accomplish a genome-wide identification of Toll-interleukin-1 receptor-like Nucleotide-binding site Leucine-rich repeat (TNL), Coiled Coil (CC)-NBS-LRR (CNL), Resistance to powdery mildew8 (RPW8)-NBS-LRR (RNL) and NBS-LRR (NL) protein encoding genes. Hidden Markov Model (HMM) profiling of 52,243 putative protein sequences from sunflower resulted in 352 NBS-encoding genes, among which 100 genes belong to CNL group including 64 genes with RX_CC like domain, 77 to TNL, 13 to RNL, and 162 belong to NL group. We also identified signal peptides and nuclear localization signals present in the identified genes and their homologs. We found that NBS genes were located on all chromosomes and formed 75 gene clusters, one-third of which were located on chromosome 13. Phylogenetic analyses between sunflower and Arabidopsis NBS genes revealed a clade-specific nesting pattern in CNLs, with RNLs nested in the CNL-A clade, and species-specific nesting pattern for TNLs. Surprisingly, we found a moderate bootstrap support (BS = 50%) for CNL-A clade being nested within TNL clade making both the CNL and TNL clades paraphyletic. Arabidopsis and sunflower showed 87 syntenic blocks with 1049 high synteny hits between chromosome 5 of Arabidopsis and chromosome 6 of sunflower. Expression data revealed functional divergence of the NBS genes with basal level tissue-specific expression. This study represents the first genome-wide identification of NBS genes in sunflower paving avenues for functional characterization and potential crop improvement.

Disease resistance genes (R genes), as part of the plant defense system, have coevolved with corresponding pathogen molecules. The main objectives of this project were to identify non-Toll interleukin receptor, nucleotide-binding site, leucine-rich repeat (nTNL) genes and elucidate their evolutionary divergence across six plant genomes. Using reference sequences from Arabidopsis, we investigated nTNL orthologs in the genomes of common bean, Medicago, soybean, poplar, and rice. We used Hidden Markov Models for sequence identification, performed model-based phylogenetic analyses, visualized chromosomal positioning, inferred gene clustering, and assessed gene expression profiles. We analyzed 908 nTNL R genes in the genomes of the six plant species, and classified them into 12 subgroups based on the presence of coiled-coil (CC), nucleotide binding site (NBS), leucine rich repeat (LRR), resistance to Powdery mildew 8 (RPW8), and BED type zinc finger domains. Traditionally classified CC-NBS-LRR (CNL) genes were nested into four clades (CNL A-D) often with abundant, well-supported homogeneous subclades of Type-II R genes. CNL-D members were absent in rice, indicating a unique R gene retention pattern in the rice genome. Genomes from Arabidopsis, common bean, poplar and soybean had one chromosome without any CNL R genes. Medicago and Arabidopsis had the highest and lowest number of gene clusters, respectively. Gene expression analyses suggested unique patterns of expression for each of the CNL clades. Differential gene expression patterns of the nTNL genes were often found to correlate with number of introns and GC content, suggesting structural and functional divergence.

Mitogen-Activated Protein Kinase (MAPK) genes encode proteins that regulate biotic and abiotic stresses in plants through signaling cascades comprised of three major subfamilies: MAP Kinase (MPK), MAPK Kinase (MKK), and MAPKK Kinase (MKKK). The main objectives of this research were to conduct genome-wide identification of MAPK genes in Helianthus annuus and examine functional divergence of these genes in relation to those in nine other plant species (Amborella trichopoda, Aquilegia coerulea, Arabidopsis thaliana, Daucus carota, Glycine max, Oryza sativa, Solanum lycopersicum, Sphagnum fallax, and Vitis vinifera), representing diverse taxonomic groups of the Plant Kingdom. A Hidden Markov Model (HMM) profile of the MAPK genes utilized reference sequences from A. thaliana and G. max, yielding a total of 96 MPKs and 37 MKKs in the genomes of A. trichopoda, A. coerulea, C. reinhardtii, D. carota, H. annuus, S. lycopersicum, and S. fallax. Among them, 28 MPKs and eight MKKs were confirmed in H. annuus. Phylogenetic analyses revealed four clades within each subfamily. Transcriptomic analyses showed that at least 19 HaMPK and seven HaMKK genes were induced in response to salicylic acid (SA), sodium chloride (NaCl), and polyethylene glycol (Peg) in leaves and roots. Of the seven published sunflower microRNAs, five microRNA families are involved in targeting eight MPKs. Additionally, we discussed the need for using MAP Kinase nomenclature guidelines across plant species. Our identification and characterization of MAP Kinase genes would have implications in sunflower crop improvement, and in advancing our knowledge of the diversity and evolution of MAPK genes in the Plant Kingdom.

Pathogenic effectors inhibit plant resistance responses by interfering with intracellular signaling mechanisms. Plant Nucleotide-binding, Leucine-rich repeat Receptors (NLRs) have evolved highly variable effector-recognition sites to detect these effectors. While many NLRs utilize variable Leucine-Rich Repeats (LRRs) to bind to effectors, some have gained Integrated Domains (IDs) necessary for receptor activation or downstream signaling. While a few studies have identified IDs within NLRs, the homology and regulation of these genes have yet to be elucidated. We identified a diverse set of wheat NLR-ID fusion proteins as candidates for NLR functional diversification through ID effector recognition or signal transduction. NLR-ID diversity corresponds directly with the various signaling components essential to defense responses, expanding the potential functions for immune receptors and removing the need for intermediate signaling factors that are often targeted by effectors. ID homologs (>80% similarity) in other grasses indicate that these domains originated as functional, non-NLR-encoding genes and were incorporated into NLR-encoding genes through duplication. Multiple NLR-ID genes encode experimentally verified alternative transcripts that include or exclude IDs. This indicates that plants employ alternative splicing to regulate IDs, possibly using them as baits, decoys, and functional signaling components. Future studies should aim to elucidate differential expression of NLR-ID alternative transcripts.