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International audience; Interactions among plants have been long recognized as a major force driving plant community dynamics and crop yield. Surprisingly, our knowledge of the ecological genetics associated with variation of plant-plant interactions remains limited. In this opinion article by scientists from complementary disciplines, the international PLANTCOM network identified four timely questions to foster a better understanding of the mechanisms mediating plant assemblages. We propose that by identifying the key relationships among phenotypic traits involved in plant-plant interactions and the underlying adaptive genetic and molecular pathways, while considering environmental fluctuations at diverse spatial and time scales, we can improve predictions of genotype-by-genotype-by-environment interactions and modeling of productive and stable plant assemblages in wild habitats and crop fields.

Although originally primarily a model for functional biology, the thale cress Arabidopsis thaliana has, owing to its broad geographical distribution and adaptation to diverse abiotic and biotic environments, developed into a powerful model in population genomics. Here, we present chromosome-level genome assemblies of 72 diverse accessions located across the global species range. We found that genomic co-linearity is remarkably conserved, even among geographically and genetically distant accessions. Along chromosome arms, megabase-scale rearrangements are rare, typically present only in a single accession. This indicates that the highly re-arranged karyotype of Arabidopsis thaliana (as compared to other Brassicaceae species), is quasi-fixed and that rearrangements in chromosome arms are counter-selected. In contrast, centromeric regions show much higher structural dynamics, and divergences in core centromeres account for most of the variation in genome size. Pan-genome analyses of the gene space uncovered 40,382 distinct genes, 52% being present in all accessions and 48% appearing to be dispensable, including 23% private to a single accession, indicating a vast unexplored genic diversity. The availability of 72 new Arabidopsis thaliana genome assemblies will empower future genetic research.

Understanding the role of host genome in modulating microbiota variation is a need to shed light into the holobiont theory and overcome the current limits on the description of host-microbiota interactions at the genomic and molecular levels. However, the host genetic architecture structuring microbiota is only partly described in plants. In addition, most association genetic studies on microbiota are often carried out outside the native habitats where the host evolve and the identification of signatures of local adaptation on the candidate genes has been overlooked. To fill these gaps and dissect the genetic architecture driving adaptive plant-microbiota interactions, we adopted a Genome-Environmental-Association (GEA) analysis on 141 whole-genome sequenced natural populations of Arabidopsis thaliana characterized in situ for their leaf and root bacterial communities and a large range of environmental descriptors (i.e. climate, soil and plant communities). Across 194 microbiota traits, a much higher fraction of among-population variance was explained by the host genetics than by ecology, with the plant neighborhood as the main ecological driver of microbiota variation. Importantly, the relative importance of host genetics and ecology expressed a phylogenetic signal at the family and genus level. In addition, the polygenic architecture of adaptation to bacterial communities was highly flexible between plant compartments and seasons. Relatedly, signatures of local adaptation were stronger on QTLs of the root microbiota in spring. Finally, we provide evidence that plant immunity, in particular the FLS2 gene, is a major source of adaptive genetic variation structuring bacterial assemblages in A. thaliana.

Disease emergence is accelerating in response to human activity-induced global changes. Understanding the mechanisms by which host populations can rapidly adapt to this threat will be crucial for developing future management practices. Pacific Oyster Mortality Syndrome (POMS) imposes a substantial and recurrent selective pressure on oyster populations (Crassostrea gigas). Rapid adaptation to this disease may arise through both genetic and epigenetic mechanisms. In this study, we used a combination of whole exome capture of bisulfite-converted DNA, next-generation sequencing, and (epi)genome-wide association mapping, to show that natural oyster populations differentially exposed to POMS displayed signatures of selection both in their genome (single nucleotide polymorphisms) and epigenome (CG-context DNA methylation). Consistent with higher resistance to POMS, the genes targeted by genetic and epigenetic variations were mainly related to host immunity. By combining correlation analyses, DNA methylation quantitative trait loci, and variance partitioning, we revealed that a third of the observed phenotypic variation was explained by interactions between the genetic sequence and epigenetic information, ∼14% by the genetic sequence, and up to 25% by the epigenome alone. Thus, as well as genetic adaptation, epigenetic mechanisms governing immune responses contribute significantly to the rapid adaptation of hosts to emerging infectious diseases.

Dissecting the genetic components of Genotype-by-Environment interactions is of key importance in the context of increasing instability and plant competition due to climate change and phytosanitary treatment limitations. It is widely addressed in plants using Multi-Environment Trials (MET), in which statistical modelling for genome-wide association studies (GWAS) is promising but significantly more complex than for single-environment studies. In this context, we introduce metaGE, a flexible and computationally efficient meta-analysis approach for the joint analysis of any MET GWAS experiment. To cope with the specific requirements of the MET context, metaGE accounts for both the heterogeneity of QTL effects across environments and the correlation between GWAS summary statistics acquired on the same or related set(s) of genotypes. Compared to previous GWAS in 3 plant species and a multi-parent population, metaGE identified known and new QTLs. It provided valuable insight into the genetic architecture of several complex traits and the variation of QTL effects conditional to environmental conditions.

Phytopathogens are a continuous threat for global food production and security. Emergence or re-emergence of plant pathogens is highly dependent on the environmental conditions affecting pathogen spread and survival. Under climate change, a geographic expansion of pathogen distribution poleward has been observed, potentially resulting in disease outbreaks on crops and wild plants. Therefore, estimating the adaptive potential of plants to novel epidemics and describing its underlying genetic architecture, is a primary need to propose agricultural management strategies reducing pathogen outbreaks and to breed novel plant cultivars adapted to pathogens that might spread in novel habitats under climate change. To address this challenge, we inoculated Pseudomonas syringae strains isolated from Arabidopsis thaliana populations located in south-west of France on the highly genetically polymorphic TOU-A A. thaliana population located east-central France. While no adaptive potential was identified in response to most P. syringae strains, the TOU-A population displays a variable disease response to the P. syringae strain JACO-CL belonging to the phylogroup 7 (PG7). This strain carried a reduced T3SS characteristic of the PG7 as well as flexible genomic traits and potential novel effectors. GWA mapping on 192 TOU-A accessions inoculated with JACO-CL revealed a polygenic architecture. The main QTL region encompasses two R genes and the AT5G18310 gene encoding for ubiquitin hydrolase, a target of the AvrRpt2 P. syringae effector. Altogether, our results pave the way for a better understanding of the genetic and molecular basis of the adaptive potential in an ecologically relevant A. thaliana – P. syringae pathosystem.

Non-pathogenic bacteria can largely contribute to plant health by mobilizing and supplying nutrients and by providing protection against pathogens and resistance to abiotic stresses. Yet, the number of GWAS reporting the genetic architecture of the response to individual members of the beneficial microbiota remains limited. In this study, we established a GWAS under field conditions to estimate the level of genetic variation and the underlying genetic architecture, among 162 accessions ofArabidopsis thalianaoriginating from 54 natural populations located south-west of France, in response to 13 strains of seven of the most abundant and prevalent non-pathogenic bacterial species isolated from the leaf compartment ofA. thalianain the same geographical region. Using a high-throughput phenotyping methodology to score vegetative growth-related traits, extensive genetic variation was detected within our local set ofA. thalianaaccessions in response to these leaf bacteria, both at the species and strain levels. The presence of crossing reaction norms among strains indicates that declaring a strain as a plant-growth promoting bacterium is highly dependent on the host genotype tested. In line with the strong genotype-by-genotype interactions, we detected a complex and highly flexible genetic architecture between the 13 strains. Finally, the candidate genes underlying the QTLs revealed a significant enrichment in several biological pathways, including cell, secondary metabolism, signalling and transport. Altogether, plant innate immunity appears as a significant source of natural genetic variation in plant-microbiota interactions and opens new avenues for better understanding the ecologically relevant molecular dialog during plant-microbiota interactions.

A paradoxical finding from genome-wide association studies (GWAS) in plants is that variation in metabolite profiles typically maps to a small number of loci, despite the complexity of underlying biosynthetic pathways. This discrepancy may partially arise from limitations presented by geographically diverse mapping panels. Properties of metabolic pathways that impede GWAS by diluting the additive effect of a causal variant, such as allelic and genetic heterogeneity and epistasis, would be expected to increase in severity with the geographical range of the mapping panel. We hypothesized that a population from a single locality would reveal an expanded set of associated loci. We tested this in a French

International audience; In their natural environment, plants are exposed to biotic or abiotic stresses that occur sequentially or simultaneously. Plant responses to these stresses have been studied widely and have been well characterised in simplified systems involving single plant species facing individual stress. Temperature elevation is a major abiotic driver of climate change and scenarios have predicted an increase in the number and severity of epidemics. In this context, here we review the available data on the effect of heat stress on plant-pathogen interactions. Considering 45 studies performed on model or crop species, we discuss the possible implications of the optimum growth temperature of plant hosts and pathogens, mode of stress application and temperature variation on resistance modulations. Alarmingly, most identified resistances are altered under temperature elevation, regardless of the plant and pathogen species. Therefore, we have listed current knowledge on heat-dependent plant immune mechanisms and pathogen thermosensory processes, mainly studied in animals and human pathogens, that could help to understand the outcome of plant-pathogen interactions under elevated temperatures. Based on a general overview of the mechanisms involved in plant responses to pathogens, and integrating multiple interactions with the biotic environment, we provide recommendations to optimise plant disease resistance under heat stress and to identify thermotolerant resistance mechanisms.

International audience; Harnessing natural genetic variation is an established alternative to artificial genetic variation for investigating the molecular dialog between partners in plant pathosystems. Herein, we review the successes of genome-wide association studies (GWAS) in both plants and pathogens. While GWAS in plants confirmed that the genetic architecture of disease resistance is polygenic, dynamic during the infection kinetics, and dependent on the environment, GWAS shortened the time of identification of quantitative trait loci (QTLs) and revealed both complex epistatic networks and a genetic architecture dependent upon the geographical scale. A similar picture emerges from the few GWAS in pathogens. In addition, the ever-increasing number of functionally validated QTLs has revealed new molecular plant defense mechanisms and pathogenicity determinants. Finally, we propose recommendations to better decode the disease triangle.

International audience; The Gram-negative bacterium Ralstonia solanacearum, the causal agent of bacterial wilt, is a worldwide major crop pathogen whose virulence strongly relies on a type III secretion system (T3SS). This extracellular apparatus allows the translocation of proteins, called type III effectors (T3Es), directly into the host cells. To date, very few data are available in plant-pathogenic bacteria concerning the role played by type III secretion (T3S) regulators at the posttranslational level. We have demonstrated that HpaP, a putative T3S substrate specificity switch protein of R. solanacearum, controls T3E secretion. To better understand the role of HpaP on T3S control, we analyzed the secretomes of the GMI1000 wild-type strain as well as the hpaP mutant using a mass spectrometry experiment (liquid chromatography tandem mass spectrometry). The secretomes of both strains appeared to be very similar and highlighted the modulation of the secretion of few type III substrates. Interestingly, only one type III-associated protein, HrpJ, was identified as specifically secreted by the hpaP mutant. HrpJ appeared to be an essential component of the T3SS, essential for T3S and pathogenicity. We further showed that HrpJ is specifically translocated in planta by the hpaP mutant and that HrpJ can physically interact with HpaP. Moreover, confocal microscopy experiments demonstrated a cytoplasmic localization for HrpJ once in planta. When injected into Arabidopsis thaliana leaves, HrpJ is able to trigger a necrosis on 16 natural accessions. A genome-wide association mapping revealed a major association peak with 12 highly significant single-nucleotide polymorphisms located on a plant acyl-transferase.

Here, we report the genome sequence of the P. syringae strain RAYR-BL, isolated from natural accessions of Arabidopsis plants. The draft genome sequence consists of 5.85 Mbp assembled in 110 contigs. The study of P. syringae RAYR-BL is a valuable tool to investigate molecular features of plant-pathogen interaction under environmental conditions.

A paradoxical finding from genome-wide association studies (GWAS) in plants is that variation in metabolite profiles typically maps to a small number of loci, despite the complexity of underlying biosynthetic pathways. This discrepancy may partially arise from limitations presented by geographically diverse mapping panels. Properties of metabolic pathways that impede GWAS by diluting the additive effect of a causal variant, such as allelic and genic heterogeneity and epistasis, would be expected to increase in severity with the geographic range of the mapping panel. We hypothesized that a population from a single locality would reveal an expanded set of associated loci. We tested this in a French Arabidopsis thaliana population (< 1 km transect) by profiling and conducting GWAS for glucosinolates, a suite of defensive metabolites that have been studied in depth through functional and genetic mapping approaches. For two distinct classes of glucosinolates, we discovered more associations at biosynthetic loci than previous GWAS with continental-scale mapping panels. Candidate genes underlying novel associations were supported by concordance between their observed effects in the TOU-A population and previous functional genetic and biochemical characterization. Local populations complement geographically diverse mapping panels to reveal a more complete genetic architecture for metabolic traits.

The principles of heredity state that the two alleles carried by a heterozygote are equally transmitted to the progeny. However, genomic regions that escape this rule have been reported in many organisms. It is notably the case of genetic loci referred to as gamete killers, where one allele enhances its transmission by causing the death of the gametes that do not carry it. Gamete killers are of great interest, particularly to understand mechanisms of evolution and speciation. Although being common in plants, only a few, all in rice, have so far been deciphered to the causal genes. Here, we studied a pollen killer found in hybrids between two accessions of Arabidopsis thaliana. Exploring natural variation, we observed this pollen killer in many crosses within the species. Genetic analyses revealed that three genetically linked elements are necessary for pollen killer activity. Using mutants, we showed that this pollen killer works according to a poison-antidote model, where the poison kills pollen grains not producing the antidote. We identified the gene encoding the antidote, a chimeric protein addressed to mitochondria. De novo genomic sequencing in 12 natural variants with different behaviors regarding the pollen killer revealed a hyper variable locus, with important structural variations particularly in killer genotypes, where the antidote gene recently underwent duplications. Our results strongly suggest that the gene has newly evolved within A. thaliana. Finally, we identified in the protein sequence polymorphisms related to its antidote activity.

International audience; Microbial communities are influenced by a complex system of host effects, including traits involved in physical barriers, immunity, hormones, metabolisms and nutrient homeostasis. Variation of host control within species is governed by many genes of small effect and is sensitive to biotic and abiotic environments. On the flip side, these host impacts seem targeted on particular microbial species, with that impact percolating through the microbial community. There is not yet evidence that the nature and strength of these interactions differs between fungal and bacterial communities, or among different compartments of the plant. The challenge of deciphering how systems of host traits impact systems of microbial associates is vast but holds promise for developing novel strategies to improve plant health.

SummaryAs obligatory parasites, plant viruses alter host cellular metabolism. There is a lack of information on the variability of virus-induced metabolic responses among genetically diverse plants in a natural context with daily changing conditions. To decipher the metabolic landscape of plant-virus interactions in a natural setting, one hundred and thirty-two and twenty-six accessions of Arabidopsis thaliana were inoculated with Turnip mosaic virus (TuMV), in two field experiments over 2 years. The accessions were phenotyped for viral accumulation, above-ground biomass, targeted and untargeted metabolic profiles. The accessions revealed quantitative response to the virus, from susceptibility to resistance. Susceptible accessions accumulate primary and secondary metabolites upon infection, at the cost of hindered growth. Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) revealed that the primary metabolites sucrose, glucose and glutamate discriminate susceptible and resistant accessions. Twenty-one metabolic signatures were found to significantly accumulate in resistant accessions whereas they maintained their growth at the same level as mock-inoculated plants without biomass penalty.Metabolic content was demonstrated to discriminate and to be highly predictive of the susceptibility of inoculated Arabidopsis. The PLS coefficient estimated in the training data set reveals, after cross-validation, a correlation of 0.61 between predicted and true viral accumulation. This study is the first to describe the metabolic landscape of plant-virus interactions in a natural setting and its predictive link to susceptibility. It reveals that, in this undomesticated species and in ecologically realistic conditions, growth and resistance are in a permanent conversation and provides new insights on plant-virus interactions.

International audience; 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 geno-mics, network reconstruction, and mutational analysis to identify and validate molecular networks that control QDR in Arabidopsis thaliana in response to the bacterial pathogen Xanthomonas cam-pestris. To tackle this challenge, we first performed a transcrip-tomic 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 re-sistance to X. campestris. RKS1-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 A. thaliana. 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 par-ticipate partially in RKS1-mediated resistance. However, these func-tional modules exhibit differential robustness to genetic mutations, indicating that, within the decentralized structure of the QDR net-work, some modules are more resilient than others. In conclusion, our work sheds light on the complexity of QDR and provides com-prehensive understanding of a QDR immune network.

International audience; The study of model organisms on islands may shed light on rare long-range dispersal events, uncover signatures of local evolutionary processes, and inform demographic inference on the mainland. Here, we sequenced the genomes of Arabidopsis thaliana samples from the oceanic island of Madeira. These samples include the most diverged worldwide, likely a result of long isolation on the island. We infer that colonization of Madeira happened between 70 and 85 ka, consistent with a propagule dispersalmodel (of size >= 10), or with an ecological window of opportunity. This represents a clear example of a natural long-range dispersal event in A. thaliana. Long-term effective population size on the island, rather than the founder effect, had the greatest impact on levels of diversity, and rates of coalescence. Our results uncover a selective sweep signature on the ancestral haplotype of a known translocation in Eurasia, as well as the possible importance of the low phosphorous availability in volcanic soils, and altitude, in shaping early adaptations to the island conditions. Madeiran genomes, sheltered from the complexities of continental demography, help illuminate ancient demographic events in Eurasia. Our data support a model in which two separate lineages of A. thaliana, one originating in Africa and the other from the Caucasus expanded and met in Iberia, resulting in a secondary contact zone there. Although previous studies inferred that the westward expansion of A. thaliana coincided with the spread of human agriculture, our results suggest that it happened much earlier (20-40 ka).

The Gram-negative bacterium

International audience

SummaryFactors that drive continental-scale variation in root microbiota and plant adaptation are poorly understood. We monitored root-associated microbial communities in Arabidopsis thaliana and co-occurring grasses at 17 European sites across three years. Analysis of 5,625 microbial community profiles demonstrated strong geographic structuring of the soil biome, but not of the root microbiota. Remarkable similarity in bacterial community composition in roots of A. thaliana and grasses was explained by the presence of a few diverse and geographically widespread taxa that disproportionately colonize roots across sites. In a reciprocal transplant between two A. thaliana populations in Sweden and Italy, we uncoupled soil from location effects and tested their respective contributions to root microbiota variation and plant adaptation. The composition of the root microbiota was affected by location and soil origin, and to a lesser degree by host genotype. The filamentous eukaryotes were particularly strongly affected by location. Strong local adaptation between the two A. thaliana populations was observed, with difference in soil properties and microbes of little importance for the observed magnitude of adaptive differentiation. Our results suggest that, across large spatial scales, climate is more important than are soil conditions for plant adaptation and variation in root-associated filamentous eukaryotic communities.

UMR BFP - Equipe Virologie; International audience; The genetic architecture of plant response to viruses has often been studied in model nonnatural pathosystems under controlled conditions. There is an urgent need to elucidate the genetic architecture of the response to viruses in a natural setting. A field experiment was performed in each of two years. In total, 317 Arabidopsis thaliana accessions were inoculated with its natural Turnip mosaic virus (TuMV). The accessions were phenotyped for viral accumulation, frequency of infected plants, stem length and symptoms. Genome-wide association mapping was performed. Arabidopsis thaliana exhibits extensive natural variation in its response to TuMV in the field. The underlying genetic architecture reveals a more quantitative picture than in controlled conditions. Ten genomic regions were consistently identified across the two years. RTM3 (Restricted TEV Movement 3) is a major candidate for the response to TuMV in the field. New candidate genes include Dead box helicase 1, a Tim Barrel domain protein and the eukaryotic translation initiation factor eIF3b. To our knowledge, this study is the first to report the genetic architecture of quantitative response of A. thaliana to a naturally occurring virus in a field environment, thereby highlighting relevant candidate genes involved in plant virus interactions in nature.

Associate Editor: Stephen Wright; International audience; Despite the importance of plant-plant interactions on plant community dynamics and crop yield, our understanding of the adaptive genetics underlying these interactions is still limited and deserves to be investigated in the context of complex and diffuse interactions occurring in plant assemblages. Here, based on 145 natural populations of Arabidopsis thaliana located in south-west of France and characterized for plant communities, we conducted a Genome-Environment Association analysis to finely map adaptive genomic regions of A. thaliana associated with plant community descriptors. To control for correlated abiotic environment effects, we also characterized the populations for a set of biologically meaningful climate and soil variables. A nonnegligible fraction of top single nucleotide polymorphisms was associated with both plant community descriptors and abiotic variables, highlighting the importance of considering the actual abiotic drivers of plant communities to disentangle genetic variants for biotic adaptation from genetic variants for abiotic adaptation. The adaptive loci associated with species abundance were highly dependent on the identity of the neighboring species suggesting a high degree of biotic specialization of A. thaliana to members of its plant interaction network. Moreover, the identification of adaptive loci associated with a-diversity and composition of plant communities supports the ability of A. thaliana to interact simultaneously with multiple plant neighbors, which in turn can help to understand the role of community-wide selection. Altogether, our study highlights that dissecting the genetic basis underlying plant-plant interactions at a regional scale while controlling for abiotic confounding factors can help understanding the adaptive mechanisms modulating natural plant assemblages.

International audience; As obligatory parasites, plant viruses alter host cellular metabolism. There is a lack of information on the variability of virus-induced metabolic responses among genetically diverse plants in a natural context with daily changing conditions. To decipher the metabolic landscape of plant-virus interactions in a natural setting, twenty-six and ten accessions of Arabidopsis thaliana were inoculated with Turnip mosaic virus (TuMV), in two field experiments over 2 years. The accessions were measured for viral accumulation, above-ground biomass, targeted and untargeted metabolic profiles. The phenotypes of the accessions ranged from susceptibility to resistance. Susceptible and resistant accessions were shown to have different metabolic routes after inoculation. Susceptible genotypes accumulate primary and secondary metabolites upon infection, at the cost of hindered growth. Twenty-one metabolic signatures significantly accumulated in resistant accessions whereas they maintained their growth as mock-inoculated plants without biomass penalty. Metabolic content was demonstrated to discriminate and be highly predictive of the susceptibility of inoculated Arabidopsis. This study is the first to describe the metabolic landscape of plant-virus interactions in a natural setting and its predictive link to susceptibility. It provides new insights on plant-virus interactions. In this undomesticated species and in ecologically realistic conditions, growth and resistance are in a permanent conversation.

International audience; Although the contribution of cytonuclear interactions to plant fitness variation is relatively well documented at the interspecific level, the prevalence of cytonuclear interactions at the intraspecific level remains poorly investigated. In this study, we set up a field experiment to explore the range of effects that cytonuclear interactions have on fitness-related traits in Arabidopsis thaliana. To do so, we created a unique series of 56 cytolines resulting from cytoplasmic substitutions among eight natural accessions reflecting within-species genetic diversity. An assessment of these cytolines and their parental lines scored for 28 adaptive whole-organism phenotypes showed that a large proportion of phenotypic traits (23 of 28) were affected by cytonuclear interactions. The effects of these interactions varied from slight but frequent across cytolines to strong in some specific parental pairs. Two parental pairs accounted for half of the significant pairwise interactions. In one parental pair, Ct-1/Sha, we observed symmetrical phenotypic responses between the two nuclear backgrounds when combined with specific cytoplasms, suggesting nuclear differentiation at loci involved in cytonuclear epistasis. In contrast, asymmetrical phenotypic responses were observed in another parental pair, Cvi-0/Sha. In the Cvi-0 nuclear background, fecundity and phenology-related traits were strongly affected by the Sha cytoplasm, leading to a modified reproductive strategy without penalizing total seed production. These results indicate that natural variation in cytoplasmic and nuclear genomes interact to shape integrative traits that contribute to adaptation, thereby suggesting that cytonuclear interactions can play a major role in the evolutionary dynamics of A. thaliana.

Whilst there are many examples of contemporary directional selection, evidence for responses to selection that match predictions are often missing in quantitative genetic studies of wild populations. This is despite genetic variation and selection pressures - theoretical prerequisites for the response to selection - being present. This conundrum can be explained by statistical issues with accurate parameter estimation, and by biological mechanisms that interfere with the response to selection. These biological mechanisms can accelerate or constrain this response. These mechanisms are generally studied independently but might act simultaneously. We therefore integrated these mechanisms to explore their potential combined effect. This has implications for explaining the apparent evolutionary stasis of wild populations and the conservation of wildlife.

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 and leaf associated bacterial communities of 163 ecologically contrasted Arabidopsis thaliana populations sampled across two seasons in South-West 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 OTUs. This result suggests that the potential biomarkers controlling pathogen’s invasion are highly dynamic.

BGPI : équipe 4 Interactions Céréales Agents Pathogènes (ICAP); International audience; Despite the importance of plant-plant interactions on crop yield and plant community dynamics, our understanding of the genetic and molecular bases underlying natural variation of plant-plant interactions is largely limited in comparison with other types of biotic interactions. By listing 63 quantitative trait loci (QTL) mapping and global gene expression studies based on plants directly challenged by other plants, we explored whether the genetic architecture and the function of the candidate genes underlying natural plant-plant interactions depend on the type of interactions between two plants (competition versus commensalism versus reciprocal helping versus asymmetry). The 16 transcriptomic studies are unevenly distributed between competitive interactions (n = 12) and asymmetric interactions (n = 4, all focusing on response to parasitic plants). By contrast, 17 and 30 QTL studies were identified for competitive interactions and asymmetric interactions (either weed suppressive ability or response to parasitic plants), respectively. Surprisingly, no studies have been carried out on the identification of genetic and molecular bases underlying natural variation in positive interactions. The candidate genes underlying natural plant-plant interactions can be classified into seven categories of plant function that have been identified in artificial environments simulating plant-plant interactions either frequently (photosynthesis, hormones), only recently (cell wall modification and degradation, defense pathways against pathogens) or rarely (ABC transporters, histone modification and meristem identity/life history traits). Finally, we introduce several avenues that need to be explored in the future to obtain a thorough understanding of the genetic and molecular bases underlying plant-plant interactions within the context of realistic community complexity.

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.