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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.

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.

Survival in changing and challenging environments requires an organism to efficiently obtain and use its resources. Due to their sessile nature, it is particularly critical for plants to dynamically optimize their metabolism. In plant primary metabolism, metabolic fine-tuning involves feed-back mechanisms whereby the output of a pathway controls its input to generate a precise and robust response to environmental changes. By contrast, few studies have addressed the potential for feed-back regulation of secondary metabolism. In Arabidopsis, accumulation of the defense compounds glucosinolates has previously been linked to genetic variation in the glucosinolate biosynthetic gene AOP2. AOP2 expression can increase the transcript levels of two known regulators (MYB28 and MYB29) of the pathway, suggesting that AOP2 plays a role in positive feed-back regulation controlling glucosinolate biosynthesis. We generated mutants affecting AOP2, MYB28/29, or both. Transcriptome analysis of these mutants identified a so far unrecognized link between AOP2 and jasmonic acid (JA) signaling independent of MYB28 and MYB29. Thus, AOP2 is part of a regulatory feed-back loop linking glucosinolate biosynthesis and JA signaling and thereby allows the glucosinolate pathway to influence JA sensitivity. The discovery of this regulatory feed-back loop provides insight into how plants optimize the use of resources for defensive metabolites.

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.

The epidermis on leaves protects plants from pathogen invasion and provides a waterproof barrier. It consists of a layer of cells that is surrounded by thick cell walls, which are partially impregnated by highly hydrophobic cuticular components. We show that the Arabidopsis T-DNA insertion mutants of REDUCED WALL ACETYLATION 2 (rwa2), previously identified as having reduced O-acetylation of both pectins and hemicelluloses, exhibit pleiotrophic phenotype on the leaf surface. The cuticle layer appeared diffused and was significantly thicker and underneath cell wall layer was interspersed with electron-dense deposits. A large number of trichomes were collapsed and surface permeability of the leaves was enhanced in rwa2 as compared to the wild type. A massive reprogramming of the transcriptome was observed in rwa2 as compared to the wild type, including a coordinated up-regulation of genes involved in responses to abiotic stress, particularly detoxification of reactive oxygen species and defense against microbial pathogens (e.g., lipid transfer proteins, peroxidases). In accordance, peroxidase activities were found to be elevated in rwa2 as compared to the wild type. These results indicate that cell wall acetylation is essential for maintaining the structural integrity of leaf epidermis, and that reduction of cell wall acetylation leads to global stress responses in Arabidopsis.

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.

Although pioneered by human geneticists as a potential solution to the challenging problem of finding the genetic basis of common human diseases (1,2), genome-wide association (GWA) studies have, owing to advances in genotyping and sequencing technology, become an obvious general approach for studying the genetics of natural variation and traits of agricultural importance. They are particularly useful when inbred lines are available, because once these lines have been genotyped they can be phenotyped multiple times, making it possible (as well as extremely cost effective) to study many different traits in many different environments, while replicating the phenotypic measurements to reduce environmental noise. Here we demonstrate the power of this approach by carrying out a GWA study of (107 phenotypes in Arabidopsis thaliana, a widely distributed, predominantly self-fertilizing model plant known to harbour considerable genetic variation for many adaptively important traits (3). Our results are dramatically different from those of human GWA studies, in that we identify many common alleles of major effect, but they are also, in many cases, harder to interpret because confounding by complex genetics and population structure make it difficult to distinguish true associations from false. However, a-priori candidates are significantly over-represented among these associations as well, making many of them excellent candidates for follow-up experiments. Our study demonstrates the feasibility of GWA studies in A. thaliana and suggests that the approach will be appropriate for many other organisms., The genotyped sample (Supplementary Table 1) includes a core set of 95 lines (4) for which a wide variety of phenotypes were available, plus a second set of 96 lines [...]

The model plant Arabidopsis thaliana exhibits extensive natural variation in resistance to parasites. Immunity is often conferred by resistance (R) genes that permit recognition of specific races of a disease. The number of such R genes and their distribution are poorly understood. In this study, we investigated the basis for resistance to the downy mildew agent Hyaloperonospora arabidopsidis ex parasitica (Hpa) in a global sample of A. thaliana. We implemented a combined genome-wide mapping of resistance using populations of recombinant inbred lines and a collection of wild A. thaliana accessions. We tested the interaction between 96 host genotypes collected worldwide and five strains of Hpa. Then, a fraction of the species-wide resistance was genetically dissected using six recently constructed populations of recombinant inbred lines. We found that resistance is usually governed by single dominant R genes that are concentrated in four genomic regions only. We show that association genetics of resistance to diseases such as downy mildew enables increased mapping resolution from quantitative trait loci interval to candidate gene level. Association patterns in quantitative trait loci intervals indicate that the pool of A. thaliana resistance sources against the tested Hpa isolates may be predominantly confined to six RPP (Resistance to Hpa) loci isolated in previous studies. Our results suggest that combining association and linkage mapping could accelerate resistance gene discovery in plants. [ABSTRACT FROM AUTHOR]

Plant secondary metabolism is an active research area because of the unique and important roles the specialized metabolites have in the interaction of plants with their biotic and abiotic environment, the diversity and complexity of the compounds and their importance to human medicine. Thousands of natural accessions of Arabidopsis thaliana characterized with increasing genomic precision are available, providing new opportunities to explore the biochemical and genetic mechanisms affecting variation in secondary metabolism within this model species. In this study, we focused on four aromatic metabolites that were differentially accumulated among 96 Arabidopsis natural accessions as revealed by leaf metabolic profiling. Using UV, mass spectrometry, and NMR data, we identified these four compounds as different dihydroxybenzoic acid (DHBA) glycosides, namely 2,5-dihydroxybenzoic acid (gentisic acid) 5-O-b-D-glucoside, 2,3-dihydroxybenzoic acid 3-O-b-D-glucoside, 2,5-dihydroxybenzoic acid 5-O-b-D-xyloside, and 2,3-dihydroxybenzoic acid 3-O-b-D-xyloside. Quantitative trait locus (QTL) mapping using recombinant inbred lines generated from C24 and Col-0 revealed a major-effect QTL controlling the relative proportion of xylosides vs. glucosides. Association mapping identified markers linked to a gene encoding a UDP glycosyltransferase gene. Analysis of Transfer DNA (T-DNA) knockout lines verified that this gene is required for DHBA xylosylation in planta and recombinant protein was able to xylosylate DHBA in vitro. This study demonstrates that exploiting natural variation of secondary metabolism is a powerful approach for gene function discovery. [ABSTRACT FROM AUTHOR]