Heritable differences in abundance of bacterial rhizosphere taxa are correlated with fungal necrotrophic pathogen resistance.

Host-microbe interactions are increasingly recognized as important drivers of organismal health, growth, longevity and community-scale ecological processes. However, less is known about how genetic variation affects hosts' associated microbiomes and downstream phenotypes. We demonstrate that sunflower (Helianthus annuus) harbours substantial, heritable variation in microbial communities under field conditions. We show that microbial communities co-vary with heritable variation in resistance to root infection caused by the necrotrophic pathogen Sclerotinia sclerotiorum and that plants grown in autoclaved soil showed almost complete elimination of pathogen resistance. Association mapping suggests at least 59 genetic locations with effects on both microbial relative abundance and Sclerotinia resistance. Although the genetic architecture appears quantitative, we have elucidated previously unexplained genetic variation for resistance to this pathogen. We identify new targets for plant breeding and demonstrate the potential for heritable microbial associations to play important roles in defence in natural and human-altered environments.

Quantitative interactions: the disease outcome of Botrytis cinerea across the plant kingdom.

Botrytis cinerea is a fungal pathogen that causes necrotic disease on more than a thousand known hosts widely spread across the plant kingdom. How B. cinerea interacts with such extensive host diversity remains largely unknown. To address this question, we generated an infectivity matrix of 98 strains of B. cinerea on 90 genotypes representing eight host plants. This experimental infectivity matrix revealed that the disease outcome is largely explained by variations in either the host resistance or pathogen virulence. However, the specific interactions between host and pathogen account for 16% of the disease outcome. Furthermore, the disease outcomes cluster among genotypes of a species but are independent of the relatedness between hosts. When analyzing the host specificity and virulence of B. cinerea, generalist strains are predominant. In this fungal necrotroph, specialization may happen by a loss in virulence on most hosts rather than an increase of virulence on a specific host. To uncover the genetic architecture of Botrytis host specificity and virulence, a genome-wide association study (GWAS) was performed and revealed up to 1492 genes of interest. The genetic architecture of these traits is widespread across the B. cinerea genome. The complexity of the disease outcome might be explained by hundreds of functionally diverse genes putatively involved in adjusting the infection to diverse hosts.

Pathogen Genetic Control of Transcriptome Variation in the Arabidopsis thaliana - Botrytis cinerea Pathosystem.

In plant-pathogen relations, disease symptoms arise from the interaction of the host and pathogen genomes. Host-pathogen functional gene interactions are well described, whereas little is known about how the pathogen genetic variation modulates both organisms' transcriptomes. To model and generate hypotheses on a generalist pathogen control of gene expression regulation, we used the Arabidopsis thaliana-Botrytis cinerea pathosystem and the genetic diversity of a collection of 96 B. cinerea isolates. We performed expression-based genome-wide association (eGWA) for each of 23,947 measurable transcripts in Arabidopsis (host), and 9267 measurable transcripts in B. cinerea (pathogen). Unlike other eGWA studies, we detected a relative absence of locally acting expression quantitative trait loci (cis-eQTL), partly caused by structural variants and allelic heterogeneity hindering their identification. This study identified several distantly acting trans-eQTL linked to eQTL hotspots dispersed across Botrytis genome that altered only Botrytis transcripts, only Arabidopsis transcripts, or transcripts from both species. Gene membership in the trans-eQTL hotspots suggests links between gene expression regulation and both known and novel virulence mechanisms in this pathosystem. Genes annotated to these hotspots provide potential targets for blocking manipulation of the host response by this ubiquitous generalist necrotrophic pathogen.

PMR5, an acetylation protein at the intersection of pectin biosynthesis and defense against fungal pathogens.

Powdery mildew (Golovinomyces cichoracearum), one of the most prolific obligate biotrophic fungal pathogens worldwide, infects its host by penetrating the plant cell wall without activating the plant's innate immune system. The Arabidopsis mutant powdery mildew resistant 5 (pmr5) carries a mutation in a putative pectin acetyltransferase gene that confers enhanced resistance to powdery mildew. Here, we show that heterologously expressed PMR5 protein transfers acetyl groups from [14 C]-acetyl-CoA to oligogalacturonides. Through site-directed mutagenesis, we show that three amino acids within a highly conserved esterase domain in putative PMR5 orthologs are necessary for PMR5 function. A suppressor screen of mutagenized pmr5 seed selecting for increased powdery mildew susceptibility identified two previously characterized genes affecting the acetylation of plant cell wall polysaccharides, RWA2 and TBR. The rwa2 and tbr mutants also suppress powdery mildew disease resistance in pmr6, a mutant defective in a putative pectate lyase gene. Cell wall analysis of pmr5 and pmr6, and their rwa2 and tbr suppressor mutants, demonstrates minor shifts in cellulose and pectin composition. In direct contrast to their increased powdery mildew resistance, both pmr5 and pmr6 plants are highly susceptibile to multiple strains of the generalist necrotroph Botrytis cinerea, and have decreased camalexin production upon infection with B. cinerea. These results illustrate that cell wall composition is intimately connected to fungal disease resistance and outline a potential route for engineering powdery mildew resistance into susceptible crop species.

Plant-necrotroph co-transcriptome networks illuminate a metabolic battlefield.

A central goal of studying host-pathogen interaction is to understand how host and pathogen manipulate each other to promote their own fitness in a pathosystem. Co-transcriptomic approaches can simultaneously analyze dual transcriptomes during infection and provide a systematic map of the cross-kingdom communication between two species. Here we used the Arabidopsis-B. cinerea pathosystem to test how plant host and fungal pathogen interact at the transcriptomic level. We assessed the impact of genetic diversity in pathogen and host by utilization of a collection of 96 isolates infection on Arabidopsis wild-type and two mutants with jasmonate or salicylic acid compromised immunities. We identified ten B. cinereagene co-expression networks (GCNs) that encode known or novel virulence mechanisms. Construction of a dual interaction network by combining four host- and ten pathogen-GCNs revealed potential connections between the fungal and plant GCNs. These co-transcriptome data shed lights on the potential mechanisms underlying host-pathogen interaction.

Digital Imaging Combined with Genome-Wide Association Mapping Links Loci to Plant-Pathogen Interaction Traits.

Plant resistance to generalist pathogens with broad host ranges, such as Botrytis cinerea (Botrytis), is typically quantitative and highly polygenic. Recent studies have begun to elucidate the molecular genetic basis of plant-pathogen interactions using commonly measured traits, including lesion size and/or pathogen biomass. However, with the advent of digital imaging and high-throughput phenomics, there are a large number of additional traits available to study quantitative resistance. In this study, we used high-throughput digital imaging analysis to investigate previously poorly characterized visual traits of plant-pathogen interactions related to disease resistance using the Arabidopsis (Arabidopsis thaliana)/Botrytis pathosystem. From a large collection of visual lesion trait measurements, we focused on color, shape, and size to test how these aspects of the Arabidopsis/Botrytis interaction are genetically related. Through genome-wide association mapping in Arabidopsis, we show that lesion color and shape are genetically separable traits associated with plant disease resistance. Moreover, by employing defined mutants in 23 candidate genes identified from the genome-wide association mapping, we demonstrate links between loci and each of the different plant-pathogen interaction traits. These results expand our understanding of the functional mechanisms driving plant disease resistance.

Plastic Transcriptomes Stabilize Immunity to Pathogen Diversity: The Jasmonic Acid and Salicylic Acid Networks within the Arabidopsis/Botrytis Pathosystem.

To respond to pathogen attack, selection and associated evolution has led to the creation of plant immune system that are a highly effective and inducible defense system. Central to this system are the plant defense hormones jasmonic acid (JA) and salicylic acid (SA) and crosstalk between the two, which may play an important role in defense responses to specific pathogens or even genotypes. Here, we used the Arabidopsis thaliana-Botrytis cinerea pathosystem to test how the host's defense system functions against genetic variation in a pathogen. We measured defense-related phenotypes and transcriptomic responses in Arabidopsis wild-type Col-0 and JA- and SA-signaling mutants, coi1-1 and npr1-1, individually challenged with 96 diverse B. cinerea isolates. Those data showed genetic variation in the pathogen influences on all components within the plant defense system at the transcriptional level. We identified four gene coexpression networks and two vectors of defense variation triggered by genetic variation in B. cinerea This showed that the JA and SA signaling pathways functioned to constrain/canalize the range of virulence in the pathogen population, but the underlying transcriptomic response was highly plastic. These data showed that plants utilize major defense hormone pathways to buffer disease resistance, but not the metabolic or transcriptional responses to genetic variation within a pathogen.

Epistasis × environment interactions among Arabidopsis thaliana glucosinolate genes impact complex traits and fitness in the field.

Despite the growing number of studies showing that genotype × environment and epistatic interactions control fitness, the influences of epistasis × environment interactions on adaptive trait evolution remain largely uncharacterized. Across three field trials, we quantified aliphatic glucosinolate (GSL) defense chemistry, leaf damage, and relative fitness using mutant lines of Arabidopsis thaliana varying at pairs of causal aliphatic GSL defense genes to test the impact of epistatic and epistasis × environment interactions on adaptive trait variation. We found that aliphatic GSL accumulation was primarily influenced by additive and epistatic genetic variation, leaf damage was primarily influenced by environmental variation and relative fitness was primarily influenced by epistasis and epistasis × environment interactions. Epistasis × environment interactions accounted for up to 48% of the relative fitness variation in the field. At a single field site, the impact of epistasis on relative fitness varied significantly over 2 yr, showing that epistasis × environment interactions within a location can be temporally dynamic. These results suggest that the environmental dependency of epistasis can profoundly influence the response to selection, shaping the adaptive trajectories of natural populations in complex ways, and deserves further consideration in future evolutionary studies.

Quantitative Resistance: More Than Just Perception of a Pathogen.

Molecular plant pathology has focused on studying large-effect qualitative resistance loci that predominantly function in detecting pathogens and/or transmitting signals resulting from pathogen detection. By contrast, less is known about quantitative resistance loci, particularly the molecular mechanisms controlling variation in quantitative resistance. Recent studies have provided insight into these mechanisms, showing that genetic variation at hundreds of causal genes may underpin quantitative resistance. Loci controlling quantitative resistance contain some of the same causal genes that mediate qualitative resistance, but the predominant mechanisms of quantitative resistance extend beyond pathogen recognition. Indeed, most causal genes for quantitative resistance encode specific defense-related outputs such as strengthening of the cell wall or defense compound biosynthesis. Extending previous work on qualitative resistance to focus on the mechanisms of quantitative resistance, such as the link between perception of microbe-associated molecular patterns and growth, has shown that the mechanisms underlying these defense outputs are also highly polygenic. Studies that include genetic variation in the pathogen have begun to highlight a potential need to rethink how the field considers broad-spectrum resistance and how it is affected by genetic variation within pathogen species and between pathogen species. These studies are broadening our understanding of quantitative resistance and highlighting the potentially vast scale of the genetic basis of quantitative resistance.

Genome Wide Association Mapping in Arabidopsis thaliana Identifies Novel Genes Involved in Linking Allyl Glucosinolate to Altered Biomass and Defense.

A key limitation in modern biology is the ability to rapidly identify genes underlying newly identified complex phenotypes. Genome wide association studies (GWAS) have become an increasingly important approach for dissecting natural variation by associating phenotypes with genotypes at a genome wide level. Recent work is showing that the Arabidopsis thaliana defense metabolite, allyl glucosinolate (GSL), may provide direct feedback regulation, linking defense metabolism outputs to the growth, and defense responses of the plant. However, there is still a need to identify genes that underlie this process. To start developing a deeper understanding of the mechanism(s) that modulate the ability of exogenous allyl GSL to alter growth and defense, we measured changes in plant biomass and defense metabolites in a collection of natural 96 A. thaliana accessions fed with 50 µM of allyl GSL. Exogenous allyl GSL was introduced exclusively to the roots and the compound transported to the leaf leading to a wide range of heritable effects upon plant biomass and endogenous GSL accumulation. Using natural variation we conducted GWAS to identify a number of new genes which potentially control allyl responses in various plant processes. This is one of the first instances in which this approach has been successfully utilized to begin dissecting a novel phenotype to the underlying molecular/polygenic basis.

Effector-Triggered Immune Response in Arabidopsis thaliana Is a Quantitative Trait.

We identified loci responsible for natural variation in Arabidopsis thaliana (Arabidopsis) responses to a bacterial pathogen virulence factor, HopAM1. HopAM1 is a type III effector protein secreted by the virulent Pseudomonas syringae strain Pto DC3000. Delivery of HopAM1 from disarmed Pseudomonas strains leads to local cell death, meristem chlorosis, or both, with varying intensities in different Arabidopsis accessions. These phenotypes are not associated with differences in bacterial growth restriction. We treated the two phenotypes as quantitative traits to identify host loci controlling responses to HopAM1. Genome-wide association (GWA) of 64 Arabidopsis accessions identified independent variants highly correlated with response to each phenotype. Quantitative trait locus (QTL) mapping in a recombinant inbred population between Bur-0 and Col-0 accessions revealed genetic linkage to regions distinct from the top GWA hits. Two major QTL associated with HopAM1-induced cell death were also associated with HopAM1-induced chlorosis. HopAM1-induced changes in Arabidopsis gene expression showed that rapid HopAM1-dependent cell death in Bur-0 is correlated with effector-triggered immune responses. Studies of the effect of mutations in known plant immune system genes showed, surprisingly, that both cell death and chlorosis phenotypes are enhanced by loss of EDS1, a regulatory hub in the plant immune-signaling network. Our results reveal complex genetic architecture for response to this particular type III virulence effector, in contrast to the typical monogenic control of cell death and disease resistance triggered by most type III effectors.

The Defense Metabolite, Allyl Glucosinolate, Modulates Arabidopsis thaliana Biomass Dependent upon the Endogenous Glucosinolate Pathway.

Glucosinolates (GSLs) play an important role in plants as direct mediators of biotic and abiotic stress responses. Recent work is beginning to show that the GSLs can also inducing complex defense and growth networks. However, the physiological significance of these GSL-induced responses and the molecular mechanisms by which GSLs are sensed and/or modulate these responses are not understood. To identify these potential mechanisms within the plant and how they may relate to the endogenous GSLs, we tested the regulatory effect of exogenous allyl GSL application on growth and defense metabolism across sample of Arabidopsis thaliana accessions. We found that application of exogenous allyl GSL had the ability to initiate changes in plant biomass and accumulation of defense metabolites that genetically varied across accessions. This growth effect was related to the allyl GSL side-chain structure. Utilizing this natural variation and mutants in genes within the GSL pathway we could show that the link between allyl GSL and altered growth responses are dependent upon the function of known genes controlling the aliphatic GSL pathway.

Expansive Phenotypic Landscape of Botrytis cinerea Shows Differential Contribution of Genetic Diversity and Plasticity.

The modern evolutionary synthesis suggests that both environmental variation and genetic diversity are critical determinants of pathogen success. However, the relative contribution of these two sources of variation is not routinely measured. To estimate the relative contribution of plasticity and genetic diversity for virulence-associated phenotypes in a generalist plant pathogen, we grew a population of 15 isolates of Botrytis cinerea from throughout the world, under a variety of in vitro and in planta conditions. Under in planta conditions, phenotypic differences between the isolates were determined by the combination of genotypic variation within the pathogen and environmental variation. In contrast, phenotypic differences between the isolates under in vitro conditions were predominantly determined by genetic variation in the pathogen. Using a correlation network approach, we link the phenotypic variation under in vitro experimental conditions to phenotypic variation during plant infection. This study indicates that there is a high level of phenotypic variation within B. cinerea that is controlled by a mixture of genetic variation, environment, and genotype × environment. This argues that future experiments into the pathogenicity of B. cinerea must account for the genetic and environmental variation within the pathogen to better sample the potential phenotypic space of the pathogen.

The Quantitative Basis of the Arabidopsis Innate Immune System to Endemic Pathogens Depends on Pathogen Genetics.

The most established model of the eukaryotic innate immune system is derived from examples of large effect monogenic quantitative resistance to pathogens. However, many host-pathogen interactions involve many genes of small to medium effect and exhibit quantitative resistance. We used the Arabidopsis-Botrytis pathosystem to explore the quantitative genetic architecture underlying host innate immune system in a population of Arabidopsis thaliana. By infecting a diverse panel of Arabidopsis accessions with four phenotypically and genotypically distinct isolates of the fungal necrotroph B. cinerea, we identified a total of 2,982 genes associated with quantitative resistance using lesion area and 3,354 genes associated with camalexin production as measures of the interaction. Most genes were associated with resistance to a specific Botrytis isolate, which demonstrates the influence of pathogen genetic variation in analyzing host quantitative resistance. While known resistance genes, such as receptor-like kinases (RLKs) and nucleotide-binding site leucine-rich repeat proteins (NLRs), were found to be enriched among associated genes, they only account for a small fraction of the total genes associated with quantitative resistance. Using publically available co-expression data, we condensed the quantitative resistance associated genes into co-expressed gene networks. GO analysis of these networks implicated several biological processes commonly connected to disease resistance, including defense hormone signaling and ROS production, as well as novel processes, such as leaf development. Validation of single gene T-DNA knockouts in a Col-0 background demonstrate a high success rate (60%) when accounting for differences in environmental and Botrytis genetic variation. This study shows that the genetic architecture underlying host innate immune system is extremely complex and is likely able to sense and respond to differential virulence among pathogen genotypes.

Whole genome resequencing of Botrytis cinerea isolates identifies high levels of standing diversity.

How standing genetic variation within a pathogen contributes to diversity in host/pathogen interactions is poorly understood, partly because most studied pathogens are host-specific, clonally reproducing organisms which complicates genetic analysis. In contrast, Botrytis cinerea is a sexually reproducing, true haploid ascomycete that can infect a wide range of diverse plant hosts. While previous work had shown significant genomic variation between two isolates, we proceeded to assess the level and frequency of standing variation in a population of B. cinerea. To begin measuring standing genetic variation in B. cinerea, we re-sequenced the genomes of 13 different isolates and aligned them to the previously sequenced T4 reference genome. In addition one of these isolates was resequenced from four independently repeated cultures. A high level of genetic diversity was found within the 13 isolates. Within this variation, we could identify clusters of genes with major effect polymorphisms, i.e., polymorphisms that lead to a predicted functional knockout, that surrounded genes involved in controlling vegetative incompatibility. The genotype at these loci was able to partially predict the interaction of these isolates in vegetative fusion assays showing that these loci control vegetative incompatibility. This suggests that the vegetative incompatibility loci within B. cinerea are associated with regions of increased genetic diversity. The genome re-sequencing of four clones from the one isolate (Grape) that had been independently propagated over 10 years showed no detectable spontaneous mutation. This suggests that B. cinerea does not display an elevated spontaneous mutation rate. Future work will allow us to test if, and how, this diversity may be contributing to the pathogen's broad host range.

Natural genetic variation in Arabidopsis thaliana defense metabolism genes modulates field fitness.

Natural populations persist in complex environments, where biotic stressors, such as pathogen and insect communities, fluctuate temporally and spatially. These shifting biotic pressures generate heterogeneous selective forces that can maintain standing natural variation within a species. To directly test if genes containing causal variation for the Arabidopsis thaliana defensive compounds, glucosinolates (GSL) control field fitness and are therefore subject to natural selection, we conducted a multi-year field trial using lines that vary in only specific causal genes. Interestingly, we found that variation in these naturally polymorphic GSL genes affected fitness in each of our environments but the pattern fluctuated such that highly fit genotypes in one trial displayed lower fitness in another and that no GSL genotype or genotypes consistently out-performed the others. This was true both across locations and within the same location across years. These results indicate that environmental heterogeneity may contribute to the maintenance of GSL variation observed within Arabidopsis thaliana.

Genetic variation in the nuclear and organellar genomes modulates stochastic variation in the metabolome, growth, and defense.

Recent studies are starting to show that genetic control over stochastic variation is a key evolutionary solution of single celled organisms in the face of unpredictable environments. This has been expanded to show that genetic variation can alter stochastic variation in transcriptional processes within multi-cellular eukaryotes. However, little is known about how genetic diversity can control stochastic variation within more non-cell autonomous phenotypes. Using an Arabidopsis reciprocal RIL population, we showed that there is significant genetic diversity influencing stochastic variation in the plant metabolome, defense chemistry, and growth. This genetic diversity included loci specific for the stochastic variation of each phenotypic class that did not affect the other phenotypic classes or the average phenotype. This suggests that the organism's networks are established so that noise can exist in one phenotypic level like metabolism and not permeate up or down to different phenotypic levels. Further, the genomic variation within the plastid and mitochondria also had significant effects on the stochastic variation of all phenotypic classes. The genetic influence over stochastic variation within the metabolome was highly metabolite specific, with neighboring metabolites in the same metabolic pathway frequently showing different levels of noise. As expected from bet-hedging theory, there was more genetic diversity and a wider range of stochastic variation for defense chemistry than found for primary metabolism. Thus, it is possible to begin dissecting the stochastic variation of whole organismal phenotypes in multi-cellular organisms. Further, there are loci that modulate stochastic variation at different phenotypic levels. Finding the identity of these genes will be key to developing complete models linking genotype to phenotype.

Meta-analysis of metabolome QTLs in Arabidopsis: trying to estimate the network size controlling genetic variation of the metabolome.

A central goal of systems biology is to develop models that are both predictive and accurately describe the biological system. One complexity to this endeavor is that it is possible to develop models that appear predictive even if they use far fewer components than the biological system itself uses for the same process. This problem also occurs in quantitative genetics where it is often possible to describe the variation in a system using fewer genes than are actually variable due to the complications of linkage between causal polymorphisms and population structure. Thus, there is a crucial need to begin an empirical investigation into the true number of components that are used by biological systems to determine a phenotypic outcome. In this study, we use a meta-analysis of directly comparable metabolomics quantitative studies using quantitative trait locus mapping and genome wide association mapping to show that it is currently not possible to estimate how many genetic loci are truly polymorphic within Arabidopsis thaliana. Our analysis shows that it would require the analysis of at least a 1000 line bi-parental population to begin to estimate how many polymorphic loci control metabolic variation within Arabidopsis. Understanding the base number of loci that are actually involved in determining variation in metabolic systems is fundamental to developing systems models that are truly reflective of how metabolism is modulated within a living organism.

A pair of receptor-like kinases is responsible for natural variation in shoot growth response to mannitol treatment in Arabidopsis thaliana.

Growth is a complex trait that adapts to the prevailing conditions by integrating many internal and external signals. Understanding the molecular origin of this variation remains a challenging issue. In this study, natural variation of shoot growth under mannitol-induced stress was analyzed by standard quantitative trait locus mapping methods in a recombinant inbred line population derived from a cross between the Col-0 and Cvi-0 Arabidopsis thaliana accessions. Cloning of a major QTL specific to mannitol-induced stress condition led to identification of EGM1 and EGM2, a pair of tandem-duplicated genes encoding receptor-like kinases that are potentially involved in signaling of mannitol-associated stress responses. Using various genetic approaches, we identified two non-synonymous mutations in the EGM2[Cvi] allele that are shared by at least ten accessions from various origins and are probably responsible for a specific tolerance to mannitol. We have shown that the enhanced shoot growth phenotype contributed by the Cvi allele is not linked to generic osmotic properties but instead to a specific chemical property of mannitol itself. This result raises the question of the function of such a gene in A. thaliana, a species that does not synthesize mannitol. Our findings suggest that the receptor-like kinases encoded by EGM genes may be activated by mannitol produced by pathogens such as fungi, and may contribute to plant defense responses whenever mannitol is present.

Cytoplasmic genetic variation and extensive cytonuclear interactions influence natural variation in the metabolome.

Understanding genome to phenotype linkages has been greatly enabled by genomic sequencing. However, most genome analysis is typically confined to the nuclear genome. We conducted a metabolomic QTL analysis on a reciprocal RIL population structured to examine how variation in the organelle genomes affects phenotypic variation. This showed that the cytoplasmic variation had effects similar to, if not larger than, the largest individual nuclear locus. Inclusion of cytoplasmic variation into the genetic model greatly increased the explained phenotypic variation. Cytoplasmic genetic variation was a central hub in the epistatic network controlling the plant metabolome. This epistatic influence manifested such that the cytoplasmic background could alter or hide pairwise epistasis between nuclear loci. Thus, cytoplasmic genetic variation plays a central role in controlling natural variation in metabolomic networks. This suggests that cytoplasmic genomes must be included in any future analysis of natural variation. DOI: http://dx.doi.org/10.7554/eLife.00776.001.