PERKing up our understanding of the proline-rich extensin-like receptor kinases, a forgotten plant receptor kinase family.

Proline-rich extensin-like receptor kinases (PERKs) are an important class of receptor-like kinases (RLKs) containing an extracellular proline-rich domain. While they are thought to be putative sensors of the cell wall integrity, there are very few reports on their biological functions in the plant, as compared with other RLKs. Several studies support a role for PERKs in plant growth and development, but their effect on the cell wall composition to regulate cell expansion is still lacking. Gene expression data suggest that they may intervene in response to environmental changes, in agreement with their subcellular localization. And there is growing evidence for PERKs as novel sensors of environmental stresses such as insects and viruses. However, little is known about their precise role in plant immunity and in the extracellular network of RLKs, as no PERK-interacting RLK or any coreceptor has been identified as yet. Similarly, their signaling activities and downstream signaling components are just beginning to be deciphered, including Ca2+ fluxes, reactive oxygen species accumulation and phosphorylation events. Here we outline emerging roles for PERKs as novel sensors of environmental stresses, and we discuss how to better understand this overlooked class of receptor kinases via several avenues of research.

Network organization of the plant immune system: from pathogen perception to robust defense induction.

The plant immune system has been explored essentially through the study of qualitative resistance, a simple form of immunity, and from a reductionist point of view. The recent identification of genes conferring quantitative disease resistance revealed a large array of functions, suggesting more complex mechanisms. In addition, thanks to the advent of high-throughput analyses and system approaches, our view of the immune system has become more integrative, revealing that plant immunity should rather be seen as a distributed and highly connected molecular network including diverse functions to optimize expression of plant defenses to pathogens. Here, we review the recent progress made to understand the network complexity of regulatory pathways leading to plant immunity, from pathogen perception, through signaling pathways and finally to immune responses. We also analyze the topological organization of these networks and their emergent properties, crucial to predict novel immune functions and test them experimentally. Finally, we report how these networks might be regulated by environmental clues. Although system approaches remain extremely scarce in this area of research, a growing body of evidence indicates that the plant response to combined biotic and abiotic stresses cannot be inferred from responses to individual stresses. A view of possible research avenues in this nascent biology domain is finally proposed.

The Genomic Architecture of Competitive Response of Arabidopsis thaliana Is Highly Flexible Among Plurispecific Neighborhoods.

Plants are daily challenged by multiple abiotic and biotic stresses. A major biotic constraint corresponds to competition with other plant species. Although plants simultaneously interact with multiple neighboring species throughout their life cycle, there is still very limited information about the genetics of the competitive response in the context of plurispecific interactions. Using a local mapping population of Arabidopsis thaliana, we set up a genome wide association study (GWAS) to estimate the extent of genetic variation of competitive response in 12 plant species assemblages, based on three competitor species (Poa annua, Stellaria media, and Veronica arvensis). Based on five phenotypic traits, we detected strong crossing reaction norms not only between the three bispecific neighborhoods but also among the plurispecific neighborhoods. The genetic architecture of competitive response was highly dependent on the identity and the relative abundance of the neighboring species. In addition, most of the enriched biological processes underlying competitive responses largely differ among neighborhoods. While the RNA related processes might confer a broad range response toolkit for multiple traits in diverse neighborhoods, some processes, such as signaling and transport, might play a specific role in particular assemblages. Altogether, our results suggest that plants can integrate and respond to different species assemblages depending on the identity and number of each neighboring species, through a large range of candidate genes associated with diverse and unexpected processes leading to developmental and stress responses.

Toward Unifying Evolutionary Ecology and Genomics to Understand Positive Plant-Plant Interactions Within Wild Species.

In a local environment, plant networks include interactions among individuals of different species and among genotypes of the same species. While interspecific interactions are recognized as main drivers of plant community patterns, intraspecific interactions have recently gained attention in explaining plant community dynamics. However, an overview of intraspecific genotype-by-genotype interaction patterns within wild plant species is still missing. From the literature, we identified 91 experiments that were mainly designed to investigate the presence of positive interactions based on two contrasting hypotheses. Kin selection theory predicts partisan help given to a genealogical relative. The rationale behind this hypothesis relies on kin/non-kin recognition, with the positive outcome of kin cooperation substantiating it. On the other hand, the elbow-room hypothesis supports intraspecific niche partitioning leading to positive outcome when genetically distant genotypes interact. Positive diversity-productivity relationship rationalizes this hypothesis, notably with the outcome of overyielding. We found that both these hypotheses have been highly supported in experimental studies despite their opposite predictions between the extent of genetic relatedness among neighbors and the level of positive interactions. Interestingly, we identified a highly significant effect of breeding system, with a high proportion of selfing species associated with the presence of kin cooperation. Nonetheless, we identified several shortcomings regardless of the species considered, such as the lack of a reliable estimate of genetic relatedness among genotypes and ecological characterization of the natural habitats from which genotypes were collected, thereby impeding the identification of selective drivers of positive interactions. We therefore propose a framework combining evolutionary ecology and genomics to establish the eco-genomic landscape of positive GxG interactions in wild plant species.

Robustness of plant quantitative disease resistance is provided by a decentralized immune network.

Quantitative disease resistance (QDR) represents the predominant form of resistance in natural populations and crops. Surprisingly, very limited information exists on the biomolecular network of the signaling machineries underlying this form of plant immunity. This lack of information may result from its complex and quantitative nature. Here, we used an integrative approach including genomics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in Arabidopsis thaliana in response to the bacterial pathogen Xanthomonas campestris To tackle this challenge, we first performed a transcriptomic analysis focused on the early stages of infection and using transgenic lines deregulated for the expression of RKS1, a gene underlying a QTL conferring quantitative and broad-spectrum resistance to XcampestrisRKS1-dependent gene expression was shown to involve multiple cellular activities (signaling, transport, and metabolism processes), mainly distinct from effector-triggered immunity (ETI) and pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) responses already characterized in Athaliana Protein-protein interaction network reconstitution then revealed a highly interconnected and distributed RKS1-dependent network, organized in five gene modules. Finally, knockout mutants for 41 genes belonging to the different functional modules of the network revealed that 76% of the genes and all gene modules participate partially in RKS1-mediated resistance. However, these functional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR network, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides comprehensive understanding of a QDR immune network.

Expression polymorphism at the ARPC4 locus links the actin cytoskeleton with quantitative disease resistance to Sclerotinia sclerotiorum in Arabidopsis thaliana.

Quantitative disease resistance (QDR) is a form of plant immunity widespread in nature, and the only one active against broad host range fungal pathogens. The genetic determinants of QDR are complex and largely unknown, and are thought to rely partly on genes controlling plant morphology and development. We used genome-wide association mapping in Arabidopsis thaliana to identify ARPC4 as associated with QDR against the necrotrophic fungal pathogen Sclerotinia sclerotiorum. Mutants impaired in ARPC4 showed enhanced susceptibility to S. sclerotiorum, defects in the structure of the actin filaments and in their responsiveness to S. sclerotiorum. Disruption of ARPC4 also alters callose deposition and the expression of defense-related genes upon S. sclerotiorum infection. Analysis of ARPC4 diversity in A. thaliana identified one haplotype (ARPC4R ) showing a c. 1 kbp insertion in ARPC4 regulatory region and associated with higher level of QDR. Accessions from the ARPC4R haplotype showed enhanced ARPC4 expression upon S. sclerotiorum challenge, indicating that polymorphisms in ARPC4 regulatory region are associated with enhanced QDR. This work identifies a novel actor of plant QDR against a fungal pathogen and provides a prime example of genetic mechanisms leading to the recruitment of cell morphology processes in plant immunity.

A Genomic Map of Climate Adaptation in Arabidopsis thaliana at a Micro-Geographic Scale.

Understanding the genetic bases underlying climate adaptation is a key element to predict the potential of species to face climate warming. Although substantial climate variation is observed at a micro-geographic scale, most genomic maps of climate adaptation have been established at broader geographical scales. Here, by using a Pool-Seq approach combined with a Bayesian hierarchical model that control for confounding by population structure, we performed a genome-environment association (GEA) analysis to investigate the genetic basis of adaptation to six climate variables in 168 natural populations of Arabidopsis thaliana distributed in south-west of France. Climate variation among the 168 populations represented up to 24% of climate variation among 521 European locations where A. thaliana inhabits. We identified neat and strong peaks of association, with most of the associated SNPs being significantly enriched in likely functional variants and/or in the extreme tail of genetic differentiation among populations. Furthermore, genes involved in transcriptional mechanisms appear predominant in plant functions associated with local climate adaptation. Globally, our results suggest that climate adaptation is an important driver of genomic variation in A. thaliana at a small spatial scale and mainly involves genome-wide changes in fundamental mechanisms of gene regulation. The identification of climate-adaptive genetic loci at a micro-geographic scale also highlights the importance to include within-species genetic diversity in ecological niche models for projecting potential species distributional shifts over short geographic distances.

Two-way mixed-effects methods for joint association analysis using both host and pathogen genomes.

Infectious diseases are often affected by specific pairings of hosts and pathogens and therefore by both of their genomes. The integration of a pair of genomes into genome-wide association mapping can provide an exquisitely detailed view of the genetic landscape of complex traits. We present a statistical method, ATOMM (Analysis with a Two-Organism Mixed Model), that maps a trait of interest to a pair of genomes simultaneously; this method makes use of whole-genome sequence data for both host and pathogen organisms. ATOMM uses a two-way mixed-effect model to test for genetic associations and cross-species genetic interactions while accounting for sample structure including interactions between the genetic backgrounds of the two organisms. We demonstrate the applicability of ATOMM to a joint association study of quantitative disease resistance (QDR) in the Arabidopsis thaliana-Xanthomonas arboricola pathosystem. Our method uncovers a clear host-strain specificity in QDR and provides a powerful approach to identify genetic variants on both genomes that contribute to phenotypic variation.

In situ relationships between microbiota and potential pathobiota in Arabidopsis thaliana.

A current challenge in microbial pathogenesis is to identify biological control agents that may prevent and/or limit host invasion by microbial pathogens. In natura, hosts are often infected by multiple pathogens. However, most of the current studies have been performed under laboratory controlled conditions and by taking into account the interaction between a single commensal species and a single pathogenic species. The next step is therefore to explore the relationships between host-microbial communities (microbiota) and microbial members with potential pathogenic behavior (pathobiota) in a realistic ecological context. In the present study, we investigated such relationships within root-associated and leaf-associated bacterial communities of 163 ecologically contrasted Arabidopsis thaliana populations sampled across two seasons in southwest of France. In agreement with the theory of the invasion paradox, we observed a significant humped-back relationship between microbiota and pathobiota α-diversity that was robust between both seasons and plant organs. In most populations, we also observed a strong dynamics of microbiota composition between seasons. Accordingly, the potential pathobiota composition was explained by combinations of season-specific microbiota operational taxonomic units. This result suggests that the potential biomarkers controlling pathogen's invasion are highly dynamic.

Author Correction: Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time.

In the version of this Article previously published, there was a typographical error ('4' instead of '2') in the equations relating F ST and effective population size (N e) in the Methods section 'Genome-wide scan for selection based on temporal differentiation'. The correct equations are given below.[Formula: see text] [Formula: see text].

Parallel evolution of the POQR prolyl oligo peptidase gene conferring plant quantitative disease resistance.

Plant pathogens with a broad host range are able to infect plant lineages that diverged over 100 million years ago. They exert similar and recurring constraints on the evolution of unrelated plant populations. Plants generally respond with quantitative disease resistance (QDR), a form of immunity relying on complex genetic determinants. In most cases, the molecular determinants of QDR and how they evolve is unknown. Here we identify in Arabidopsis thaliana a gene mediating QDR against Sclerotinia sclerotiorum, agent of the white mold disease, and provide evidence of its convergent evolution in multiple plant species. Using genome wide association mapping in A. thaliana, we associated the gene encoding the POQR prolyl-oligopeptidase with QDR against S. sclerotiorum. Loss of this gene compromised QDR against S. sclerotiorum but not against a bacterial pathogen. Natural diversity analysis associated POQR sequence with QDR. Remarkably, the same amino acid changes occurred after independent duplications of POQR in ancestors of multiple plant species, including A. thaliana and tomato. Genome-scale expression analyses revealed that parallel divergence in gene expression upon S. sclerotiorum infection is a frequent pattern in genes, such as POQR, that duplicated both in A. thaliana and tomato. Our study identifies a previously uncharacterized gene mediating QDR against S. sclerotiorum. It shows that some QDR determinants are conserved in distantly related plants and have emerged through the repeated use of similar genetic polymorphisms at different evolutionary time scales.

Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time.

Rapid phenotypic evolution of quantitative traits can occur within years, but its underlying genetic architecture remains uncharacterized. Here we test the theoretical prediction that genes with intermediate pleiotropy drive adaptive evolution in nature. Through a resurrection experiment, we grew Arabidopsis thaliana accessions collected across an 8-year period in six micro-habitats representative of that local population. We then used genome-wide association mapping to identify the single-nucleotide polymorphisms (SNPs) associated with evolved and unevolved traits in each micro-habitat. Finally, we performed a selection scan by testing for temporal differentiation in these SNPs. Phenotypic evolution was consistent across micro-habitats, but its associated genetic bases were largely distinct. Adaptive evolutionary change was most strongly driven by a small number of quantitative trait loci (QTLs) with intermediate degrees of pleiotropy; this pleiotropy was synergistic with the per-trait effect size of the SNPs, increasing with the degree of pleiotropy. In addition, weak selection was detected for frequent micro-habitat-specific QTLs that shape single traits. In this population, A. thaliana probably responded to local warming and increased competition, in part mediated by central regulators of flowering time. This genetic architecture, which includes both synergistic pleiotropic QTLs and distinct QTLs within particular micro-habitats, enables rapid phenotypic evolution while still maintaining genetic variation in wild populations.

An essential role for the VASt domain of the Arabidopsis VAD1 protein in the regulation of defense and cell death in response to pathogens.

Several regulators of programmed cell death (PCD) have been identified in plants which encode proteins with putative lipid-binding domains. Among them, VAD1 (Vascular Associated Death) contains a novel protein domain called VASt (VAD1 analog StAR-related lipid transfer) still uncharacterized. The Arabidopsis mutant vad1-1 has been shown to exhibit a lesion mimic phenotype with light-conditional appearance of propagative hypersensitive response-like lesions along the vascular system, associated with defense gene expression and increased resistance to Pseudomonas strains. To test the potential of ectopic expression of VAD1 to influence HR cell death and to elucidate the role of the VASt domain in this function, we performed a structure-function analysis of VAD1 by transient over-expression in Nicotiana benthamiana and by complementation of the mutant vad1-1. We found that (i) overexpression of VAD1 controls negatively the HR cell death and defense expression either transiently in Nicotiana benthamania or in Arabidopsis plants in response to avirulent strains of Pseudomonas syringae, (ii) VAD1 is expressed in multiple subcellular compartments, including the nucleus, and (iii) while the GRAM domain does not modify neither the subcellular localization of VAD1 nor its immunorepressor activity, the domain VASt plays an essential role in both processes. In conclusion, VAD1 acts as a negative regulator of cell death associated with the plant immune response and the VASt domain of this unknown protein plays an essential role in this function, opening the way for the functional analysis of VASt-containing proteins and the characterization of novel mechanisms regulating PCD.

Advances on plant-pathogen interactions from molecular toward systems biology perspectives.

In the past 2 decades, progress in molecular analyses of the plant immune system has revealed key elements of a complex response network. Current paradigms depict the interaction of pathogen-secreted molecules with host target molecules leading to the activation of multiple plant response pathways. Further research will be required to fully understand how these responses are integrated in space and time, and exploit this knowledge in agriculture. In this review, we highlight systems biology as a promising approach to reveal properties of molecular plant-pathogen interactions and predict the outcome of such interactions. We first illustrate a few key concepts in plant immunity with a network and systems biology perspective. Next, we present some basic principles of systems biology and show how they allow integrating multiomics data and predict cell phenotypes. We identify challenges for systems biology of plant-pathogen interactions, including the reconstruction of multiscale mechanistic models and the connection of host and pathogen models. Finally, we outline studies on resistance durability through the robustness of immune system networks, the identification of trade-offs between immunity and growth and in silico plant-pathogen co-evolution as exciting perspectives in the field. We conclude that the development of sophisticated models of plant diseases incorporating plant, pathogen and climate properties represent a major challenge for agriculture in the future.

The Arabidopsis thaliana lectin receptor kinase LecRK-I.9 is required for full resistance to Pseudomonas syringae and affects jasmonate signalling.

On microbial attack, plants can detect invaders and activate plant innate immunity. For the detection of pathogen molecules or cell wall damage, plants employ receptors that trigger the activation of defence responses. Cell surface proteins that belong to large families of lectin receptor kinases are candidates to function as immune receptors. Here, the function of LecRK-I.9 (At5g60300), a legume-type lectin receptor kinase involved in cell wall-plasma membrane contacts and in extracellular ATP (eATP) perception, was studied through biochemical, gene expression and reverse genetics approaches. In Arabidopsis thaliana, LecRK-I.9 expression is rapidly, highly and locally induced on inoculation with avirulent strains of Pseudomonas syringae pv. tomato (Pst). Two allelic lecrk-I.9 knock-out mutants showed decreased resistance to Pst. Conversely, over-expression of LecRK-I.9 led to increased resistance to Pst. The analysis of defence gene expression suggests an alteration of both the salicylic acid (SA) and jasmonic acid (JA) signalling pathways. In particular, LecRK-I.9 expression during plant-pathogen interaction was dependent on COI1 (CORONATINE INSENSITIVE 1) and JAR1 (JASMONATE RESISTANT 1) components, and JA-responsive transcription factors (TFs) showed altered levels of expression in plants over-expressing LecRK-I.9. A similar misregulation of these TFs was obtained by JA treatment. This study identified LecRK-I.9 as necessary for full resistance to Pst and demonstrated its involvement in the control of defence against pathogens through a regulation of JA signalling components. The role of LecRK-I.9 is discussed with regard to the potential molecular mechanisms linking JA signalling to cell wall damage and/or eATP perception.

Quantitative disease resistance to the bacterial pathogen Xanthomonas campestris involves an Arabidopsis immune receptor pair and a gene of unknown function.

Although quantitative disease resistance (QDR) is a durable and broad-spectrum form of resistance in plants, the identification of the genes underlying QDR is still in its infancy. RKS1 (Resistance related KinaSe1) has been reported recently to confer QDR in Arabidopsis thaliana to most but not all races of the bacterial pathogen Xanthomonas campestris pv. campestris (Xcc). We therefore explored the genetic bases of QDR in A. thaliana to diverse races of X. campestris (Xc). A nested genome-wide association mapping approach was used to finely map the genomic regions associated with QDR to Xcc12824 (race 2) and XccCFBP6943 (race 6). To identify the gene(s) implicated in QDR, insertional mutants (T-DNA) were selected for the candidate genes and phenotyped in response to Xc. We identified two major QTLs that confer resistance specifically to Xcc12824 and XccCFBP6943. Although QDR to Xcc12824 is conferred by At5g22540 encoding for a protein of unknown function, QDR to XccCFBP6943 involves the well-known immune receptor pair RRS1/RPS4. In addition to RKS1, this study reveals that three genes are involved in resistance to Xc with strikingly different ranges of specificity, suggesting that QDR to Xc involves a complex network integrating multiple response pathways triggered by distinct pathogen molecular determinants.

The hnRNP-Q protein LIF2 participates in the plant immune response.

Eukaryotes have evolved complex defense pathways to combat invading pathogens. Here, we investigated the role of the Arabidopsis thaliana heterogeneous nuclear ribonucleoprotein (hnRNP-Q) LIF2 in the plant innate immune response. We show that LIF2 loss-of-function in A. thaliana leads to changes in the basal expression of the salicylic acid (SA)- and jasmonic acid (JA)- dependent defense marker genes PR1 and PDF1.2, respectively. Whereas the expression of genes involved in SA and JA biosynthesis and signaling was also affected in the lif2-1 mutant, no change in SA and JA hormonal contents was detected. In addition, the composition of glucosinolates, a class of defense-related secondary metabolites, was altered in the lif2-1 mutant in the absence of pathogen challenge. The lif2-1 mutant exhibited reduced susceptibility to the hemi-biotrophic pathogen Pseudomonas syringae and the necrotrophic ascomycete Botrytis cinerea. Furthermore, the lif2-1 sid2-2 double mutant was less susceptible than the wild type to P. syringae infection, suggesting that the lif2 response to pathogens was independent of SA accumulation. Together, our data suggest that lif2-1 exhibits a basal primed defense state, resulting from complex deregulation of gene expression, which leads to increased resistance to pathogens with various infection strategies. Therefore, LIF2 may function as a suppressor of cell-autonomous immunity. Similar to its human homolog, NSAP1/SYNCRIP, a trans-acting factor involved in both cellular processes and the viral life cycle, LIF2 may regulate the conflicting aspects of development and defense programs, suggesting that a conserved evolutionary trade-off between growth and defense pathways exists in eukaryotes.