The Genetics Underlying Natural Variation in the Biotic Interactions of Arabidopsis thaliana: The Challenges of Linking Evolutionary Genetics and Community Ecology

Characterization of gene expression patterns in response to an orthotospovirus infection between two diploid peanut species and their hybrid

Tomato spotted wilt orthotospovirus (TSWV) transmitted by thrips causes significant yield loss in peanut (Arachis hypogaea L.) production. Use of peanut cultivars with moderate field resistance has been critical for TSWV management. However, current TSWV resistance is often not adequate, and the availability of sources of tetraploid resistance to TSWV is very limited. Allotetraploids derived by crossing wild diploid species could help introgress alleles that confer TSWV resistance into cultivated peanut. Thrips-mediated TSWV screening identified two diploids and their allotetraploid possessing the AA, BB, and AABB genomes Arachis stenosperma V10309, Arachis valida GK30011, and [A. stenosperma × A. valida]4x (ValSten1), respectively. These genotypes had reduced TSWV infection and accumulation in comparison with peanut of pure cultivated pedigree. Transcriptomes from TSWV-infected and non-infected samples from A. stenosperma, A. valida, and ValSten1 were assembled, and differentially expressed genes (DEGs) following TSWV infection were assessed. There were 3,196, 8,380, and 1,312 significant DEGs in A. stenosperma, A. valida, and ValSten1, respectively. A higher proportion of genes decreased in expression following TSWV infection for A. stenosperma and ValSten1, whereas a higher proportion of genes increased in expression following infection in A. valida. The number of DEGs previously annotated as defense-related in relation to abiotic and biotic stress was highest in A. valida followed by ValSten1 and A. stenosperma. Plant phytohormone and photosynthesis genes also were differentially expressed in greater numbers in A. valida followed by ValSten1 and A. stenosperma, with over half of those exhibiting decreases in expression.

Genetic architecture of the response of Arabidopsis thaliana to a native plant-growth-promoting bacterial strain

By improving plant nutrition and alleviating abiotic and biotic stresses, plant growth-promoting bacteria (PGPB) can help to develop eco-friendly and sustainable agricultural practices. Besides climatic conditions, soil conditions, and microbe-microbe interactions, the host genotype influences the effectiveness of PGPB. Yet, most GWAS conducted to characterize the genetic architecture of response to PGPB are based on non-native interactions between a host plant and PGPB strains isolated from the belowground compartment of other plants. In this study, a GWAS was set up under in vitro conditions to describe the genetic architecture of the response of Arabidopsis thaliana to the PGPB Pseudomonas siliginis, by inoculating seeds of 162 natural accessions from the southwest of France with one strain isolated from the leaf compartment in the same geographical region. Strong genetic variation of plant growth response to this native PGPB was observed at a regional scale, with the strain having a positive effect on the vegetative growth of small plants and a negative effect on the vegetative growth of large plants. The polygenic genetic architecture underlying this negative trade-off showed suggestive signatures of local adaptation. The main eco-evolutionary relevant candidate genes are involved in seed and root development.

Genome-wide association studies in plant pathosystems: success or failure?

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.

The ecologically relevant genetics of plant-plant interactions

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.

A Genome-Wide Association study in Arabidopsis thaliana to decipher the adaptive genetics of quantitative disease resistance in a native heterogeneous environment

Pathogens are often the main selective agents acting in plant communities, thereby influencing the distribution of polymorphism at loci affecting resistance within and among natural plant populations. In addition, the outcome of plant-pathogen interactions can be drastically affected by abiotic and biotic factors at different spatial and temporal grains. The characterization of the adaptive genetic architecture of disease resistance in native heterogeneous environments is however still missing. In this study, we conducted an in situ Genome-Wide Association study in the spatially heterogeneous native habitat of a highly genetically polymorphic local mapping population of Arabidopsis thaliana, to unravel the adaptive genetic architecture of quantitative disease resistance. Disease resistance largely differed among three native soils and was affected by the presence of the grass Poa annua. The observation of strong crossing reactions norms among the 195 A. thaliana genotypes for disease resistance among micro-habitats, combined with a negative fecundity-disease resistance relationship in each micro-habitat, suggest that alternative local genotypes of A. thaliana are favored under contrasting environmental conditions at the scale of few meters. A complex genetic architecture was detected for disease resistance and fecundity. However, only few QTLs were common between these two traits. Heterogeneous selection in this local population should therefore promote the maintenance of polymorphism at only few candidate resistance genes.

Investigating genetic diversity within the most abundant and prevalent non-pathogenic leaf-associated bacteria interacting with Arabidopsis thaliana in natural habitats

Microbiota modulates plant health and appears as a promising lever to develop innovative, sustainable and eco-friendly agro-ecosystems. Key patterns of microbiota assemblages in plants have been revealed by an extensive number of studies based on taxonomic profiling by metabarcoding. However, understanding the functionality of microbiota is still in its infancy and relies on reductionist approaches primarily based on the establishment of representative microbial collections. In Arabidopsis thaliana, most of these microbial collections include one strain per OTU isolated from a limited number of habitats, thereby neglecting the ecological potential of genetic diversity within microbial species. With this study, we aimed at estimating the extent of genetic variation between strains within the most abundant and prevalent leaf-associated non-pathogenic bacterial species in A. thaliana located south-west of France. By combining a culture-based collection approach consisting of the isolation of more than 7,000 bacterial colonies with an informative-driven approach, we isolated 35 pure strains from eight non-pathogenic bacterial species. We detected significant intra-specific genetic variation at the genomic level and for growth rate in synthetic media. In addition, significant host genetic variation was detected in response to most bacterial strains in in vitro conditions, albeit dependent on the developmental stage at which plants were inoculated, with the presence of both negative and positive responses on plant growth. Our study provides new genetic and genomic resources for a better understanding of the plant-microbe ecological interactions at the microbiota level. We also highlight the need of considering genetic variation in both non-pathogenic bacterial species and A. thaliana to decipher the genetic and molecular mechanisms involved in the ecologically relevant dialog between hosts and leaf microbiota.

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.

A complex network of additive and epistatic quantitative trait loci underlies natural variation of Arabidopsis thaliana quantitative disease resistance to Ralstonia solanacearum under heat stress

Plant immunity is often negatively impacted by heat stress. However, the underlying molecular mechanisms remain poorly characterized. Based on a genome-wide association mapping approach, this study aims to identify in Arabidopsis thaliana the genetic bases of robust resistance mechanisms to the devastating pathogen Ralstonia solanacearum under heat stress. A local mapping population was phenotyped against the R. solanacearum GMI1000 strain at 27 and 30 °C. To obtain a precise description of the genetic architecture underlying natural variation of quantitative disease resistance (QDR), we applied a genome-wide local score analysis. Alongside an extensive genetic variation found in this local population at both temperatures, we observed a playful dynamics of quantitative trait loci along the infection stages. In addition, a complex genetic network of interacting loci could be detected at 30 °C. As a first step to investigate the underlying molecular mechanisms, the atypical meiotic cyclin SOLO DANCERS gene was validated by a reverse genetic approach as involved in QDR to R. solanacearum at 30 °C. In the context of climate change, the complex genetic architecture underlying QDR under heat stress in a local mapping population revealed candidate genes with diverse molecular functions.

Plant-microbe Interactions for Sustainable Agriculture in the Post-genomic Era

Plant-microbe interactions are both symbiotic and antagonistic, and the knowledge of both these interactions is equally important for the progress of agricultural practice and produce. This review gives an insight into the recent advances that have been made in the plant-microbe interaction study in the post-genomic era and the application of those for enhancing agricultural production. Adoption of next-generation sequencing (NGS) and marker assisted selection of resistant genes in plants, equipped with cloning and recombination techniques, has progressed the techniques for the development of resistant plant varieties by leaps and bounds. Genome-wide association studies (GWAS) of both plants and microbes have made the selection of desirable traits in plants and manipulation of the genomes of both plants and microbes effortless and less time-consuming. Stress tolerance in plants has been shown to be accentuated by association of certain microorganisms with the plant, the study and application of the same have helped develop stress-resistant varieties of crops. Beneficial microbes associated with plants are being extensively used for the development of microbial consortia that can be applied directly to the plants or the soil. Next-generation sequencing approaches have made it possible to identify the function of microbes associated in the plant microbiome that are both culturable and non-culturable, thus opening up new doors and possibilities for the use of these huge resources of microbes that can have a potential impact on agriculture.

AthCNV: A Map of DNA Copy Number Variations in the Arabidopsis Genome

Copy number variations (CNVs) greatly contribute to intraspecies genetic polymorphism and phenotypic diversity. Recent analyses of sequencing data for >1000 Arabidopsis (Arabidopsis thaliana) accessions focused on small variations and did not include CNVs. Here, we performed genome-wide analysis and identified large indels (50 to 499 bp) and CNVs (500 bp and larger) in these accessions. The CNVs fully overlap with 18.3% of protein-coding genes, with enrichment for evolutionarily young genes and genes involved in stress and defense. By combining analysis of both genes and transposable elements (TEs) affected by CNVs, we revealed that the variation statuses of genes and TEs are tightly linked and jointly contribute to the unequal distribution of these elements in the genome. We also determined the gene copy numbers in a set of 1060 accessions and experimentally validated the accuracy of our predictions by multiplex ligation-dependent probe amplification assays. We then successfully used the CNVs as markers to analyze population structure and migration patterns. Finally, we examined the impact of gene dosage variation triggered by a CNV spanning the SEC10 gene on SEC10 expression at both the transcript and protein levels. The catalog of CNVs, CNV-overlapping genes, and their genotypes in a top model dicot will stimulate the exploration of the genetic basis of phenotypic variation.

Adaptation to Plant Communities across the Genome of Arabidopsis thaliana

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 α-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.

Plant trichomes and a single gene GLABRA1 contribute to insect community composition on field-grown Arabidopsis thaliana

BACKGROUND

Genetic variation in plants alters insect abundance and community structure in the field; however, little is known about the importance of a single gene among diverse plant genotypes. In this context, Arabidopsis trichomes provide an excellent system to discern the roles of natural variation and a key gene, GLABRA1, in shaping insect communities. In this study, we transplanted two independent glabrous mutants (gl1-1 and gl1-2) and 17 natural accessions of Arabidopsis thaliana to two localities in Switzerland and Japan.

RESULTS

Fifteen insect species inhabited the plant accessions, with the insect community composition significantly attributed to variations among plant accessions. The total abundance of leaf-chewing herbivores was negatively correlated with trichome density at both field sites, while glucosinolates had variable effects on leaf chewers between the sites. Interestingly, there was a parallel tendency for the abundance of leaf chewers to be higher on gl1-1 and gl1-2 than on their different parental accessions, Ler-1 and Col-0, respectively. Furthermore, the loss of function in the GLABRA1 gene significantly decreased the resistance of plants to the two predominant chewers; flea beetles and turnip sawflies.

CONCLUSIONS

Overall, our results indicate that insect community composition significantly varies among A. thaliana accessions across two distant field sites, with GLABRA1 playing a key role in altering the abundance of leaf-chewing herbivores. Given that such a trichome variation is widely observed in Brassicaceae plants, the present study exemplifies the community-wide effect of a single plant gene on crucifer-feeding insects in the field.

Rhizobacterial Community Assembly Patterns Vary Between Crop Species

Currently our limited understanding of crop rhizosphere community assembly hinders attempts to manipulate it beneficially. Variation in root communities has been attributed to plant host effects, soil type, and plant condition, but it is hard to disentangle the relative importance of soil and host without experimental manipulation. To examine the effects of soil origin and host plant on root associated bacterial communities we experimentally manipulated four crop species in split-plot mesocosms and surveyed variation in bacterial diversity by Illumina amplicon sequencing. Overall, plant species had a greater impact than soil type on community composition. While plant species associated with different Operational Taxonomic Units (OTUs) in different soils, plants tended to recruit bacteria from similar, higher order, taxonomic groups in different soils. However, the effect of soil on root-associated communities varied between crop species: Onion had a relatively invariant bacterial community while other species (maize and pea) had a more variable community structure. Dynamic communities could result from environment specific recruitment, differential bacterial colonization or reflect broader symbiont host range; while invariant community assembly implies tighter evolutionary or ecological interactions between plants and root-associated bacteria. Irrespective of mechanism, it appears both communities and community assembly rules vary between crop species.

Genome-wide association study reveals new loci involved in Arabidopsis thaliana and Turnip mosaic virus (TuMV) interactions in the field

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.

Dissecting quantitative resistance to Xanthomonas campestris pv. campestris in leaves of Brassica oleracea by QTL analysis

Black rot, caused by the bacterium Xanthomonas campestris pv. campestris (Xcc), produces important economic losses in crops of Brassica oleracea worldwide. Resistance to race 1, the most virulent and widespread in B. oleracea, is under quantitative control. Knowledge about the genetics of this resistance would help in designing strategies to control initial stages of invasion and development of the disease. QTL analysis of the resistance in the BolTBDH mapping population was performed. Resistance was measured with five traits related to initial stages of the invasion, success of infection and spread of the pathogen. Four single-trait QTLs of resistance were found, from which one represent novel variation. After performing multi-trait QTL, we concluded that spread of Xcc is related to the size of the leaf. Individuals from the mapping population follow two different strategies to cope with the spread of the disease: reducing lesion size or maintain more area of the leaf photosynthetically active, being more tolerant to Xcc invasion. Mechanisms underlying variation for resistance may be related to different aspects of plant immunity, including the synthesis of glucosinolates and phenolics.

Assortment of Flowering Time and Immunity Alleles in Natural Arabidopsis thaliana Populations Suggests Immunity and Vegetative Lifespan Strategies Coevolve

The selective impact of pathogen epidemics on host defenses can be strong but remains transient. By contrast, life-history shifts can durably and continuously modify the balance between costs and benefits of immunity, which arbitrates the evolution of host defenses. Their impact on the evolutionary dynamics of host immunity, however, has seldom been documented. Optimal investment into immunity is expected to decrease with shortening lifespan, because a shorter life decreases the probability to encounter pathogens or enemies. Here, we document that in natural populations of Arabidopsis thaliana, the expression levels of immunity genes correlate positively with flowering time, which in annual species is a proxy for lifespan. Using a novel genetic strategy based on bulk-segregants, we partitioned flowering time-dependent from -independent immunity genes and could demonstrate that this positive covariation can be genetically separated. It is therefore not explained by the pleiotropic action of some major regulatory genes controlling both immunity and lifespan. Moreover, we find that immunity genes containing variants reported to impact fitness in natural field conditions are among the genes whose expression covaries most strongly with flowering time. Taken together, these analyses reveal that natural selection has likely assorted alleles promoting lower expression of immunity genes with alleles that decrease the duration of vegetative lifespan in A. thaliana and vice versa. This is the first study documenting a pattern of variation consistent with the impact that selection on flowering time is predicted to have on diversity in host immunity.

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.

The genetics underlying natural variation of plant-plant interactions, a beloved but forgotten member of the family of biotic interactions

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.

Quantitative Disease Resistance under Elevated Temperature: Genetic Basis of New Resistance Mechanisms to Ralstonia solanacearum

In the context of climate warming, plants will be facing an increased risk of epidemics as well as the emergence of new highly aggressive pathogen species. Although a permanent increase of temperature strongly affects plant immunity, the underlying molecular mechanisms involved are still poorly characterized. In this study, we aimed to uncover the genetic bases of resistance mechanisms that are efficient at elevated temperature to the Ralstonia solanacearum species complex (RSSC), one of the most harmful phytobacteria causing bacterial wilt. To start the identification of quantitative trait loci (QTLs) associated with natural variation of response to R. solanacearum, we adopted a genome wide association (GWA) mapping approach using 176 worldwide natural accessions of Arabidopsis thaliana inoculated with the R. solanacearum GMI1000 strain. Following two different procedures of root-inoculation (root apparatus cut vs. uncut), plants were grown either at 27 or 30°C, with the latter temperature mimicking a permanent increase in temperature. At 27°C, the RPS4/RRS1-R locus was the main QTL of resistance detected regardless of the method of inoculation used. This highlights the power of GWA mapping to identify functionally important loci for resistance to the GMI1000 strain. At 30°C, although most of the accessions developed wilting symptoms, we identified several QTLs that were specific to the inoculation method used. We focused on a QTL region associated with response to the GMI1000 strain in the early stages of infection and, by adopting a reverse genetic approach, we functionally validated the involvement of a strictosidine synthase-like 4 (SSL4) protein that shares structural similarities with animal proteins known to play a role in animal immunity.

Temporal fitness fluctuations in experimental Arabidopsis thaliana populations

Understanding the genetics of lifetime fitness is crucial to understand a species’ ecological preferences and ultimately predict its ability to cope with novel environmental conditions. Yet, there is a dearth of information regarding the impact of the ecological variance experienced by natural populations on expressed phenotypic and fitness differences. Here, we follow the natural dynamics of experimental A. thaliana populations over 5 successive plantings whose timing was determined by the natural progression of the plant’s life cycle and disentangle the environmental and genetic factors that drive plant ecological performance at a given locality. We show that, at the temperate latitude where the experiment was conducted, a given genotype can experience winter-, spring- or summer-annual life cycles across successive seasons. Lifetime fitness across these seasons varied strongly, with a fall planting yielding 36-fold higher fitness compared to a spring planting. In addition, the actual life-stage at which plant overwinter oscillated across years, depending on the timing of the end of the summer season. We observed a rare but severe fitness differential coinciding with inadequate early flowering in one of the five planting. Substrate variation played a comparatively minor role, but also contributed to modulate the magnitude of fitness differentials between genotypes. Finally, reciprocal introgressions on chromosome 4 demonstrated that the fitness effect of a specific chromosomal region is strongly contingent on micro-geographic and seasonal fluctuations. Our study contributes to emphasize the extent to which the fitness impact of phenotypic traits and the genes that encode them in the genome can fluctuate. Experiments aiming at dissecting the molecular basis of local adaptation must apprehend the complexity introduced by temporal fluctuations because they massively affect the expression of phenotype and fitness differences.

Genome-Wide Association Studies In Plant Pathosystems: Toward an Ecological Genomics Approach

The emergence and re-emergence of plant pathogenic microorganisms are processes that imply perturbations in both host and pathogen ecological niches. Global change is largely assumed to drive the emergence of new etiological agents by altering the equilibrium of the ecological habitats which in turn places hosts more in contact with pathogen reservoirs. In this context, the number of epidemics is expected to increase dramatically in the next coming decades both in wild and crop plants. Under these considerations, the identification of the genetic variants underlying natural variation of resistance is a pre-requisite to estimate the adaptive potential of wild plant populations and to develop new breeding resistant cultivars. On the other hand, the prediction of pathogen's genetic determinants underlying disease emergence can help to identify plant resistance alleles. In the genomic era, whole genome sequencing combined with the development of statistical methods led to the emergence of Genome Wide Association (GWA) mapping, a powerful tool for detecting genomic regions associated with natural variation of disease resistance in both wild and cultivated plants. However, GWA mapping has been less employed for the detection of genetic variants associated with pathogenicity in microbes. Here, we reviewed GWA studies performed either in plants or in pathogenic microorganisms (bacteria, fungi and oomycetes). In addition, we highlighted the benefits and caveats of the emerging joint GWA mapping approach that allows for the simultaneous identification of genes interacting between genomes of both partners. Finally, based on co-evolutionary processes in wild populations, we highlighted a phenotyping-free joint GWA mapping approach as a promising tool for describing the molecular landscape underlying plant - microbe interactions.