261 research outputs found

    A Systems Biology Approach Identifies a R2R3 MYB Gene Subfamily with Distinct and Overlapping Functions in Regulation of Aliphatic Glucosinolates

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    BACKGROUND: Glucosinolates are natural metabolites in the order Brassicales that defend plants against both herbivores and pathogens and can attract specialized insects. Knowledge about the genes controlling glucosinolate regulation is limited. Here, we identify three R2R3 MYB transcription factors regulating aliphatic glucosinolate biosynthesis in Arabidopsis by combining several systems biology tools. METHODOLOGY/PRINCIPAL FINDINGS: MYB28 was identified as a candidate regulator of aliphatic glucosinolates based on its co-localization within a genomic region controlling variation both in aliphatic glucosinolate content (metabolite QTL) and in transcript level for genes involved in the biosynthesis of aliphatic glucosinolates (expression QTL), as well as its co-expression with genes in aliphatic glucosinolate biosynthesis. A phylogenetic analysis with the R2R3 motif of MYB28 showed that it and two homologues, MYB29 and MYB76, were members of an Arabidopsis-specific clade that included three characterized regulators of indole glucosinolates. Over-expression of the individual MYB genes showed that they all had the capacity to increase the production of aliphatic glucosinolates in leaves and seeds and induce gene expression of aliphatic biosynthetic genes within leaves. Analysis of leaves and seeds of single knockout mutants showed that mutants of MYB29 and MYB76 have reductions in only short-chained aliphatic glucosinolates whereas a mutant in MYB28 has reductions in both short- and long-chained aliphatic glucosinolates. Furthermore, analysis of a double knockout in MYB28 and MYB29 identified an emergent property of the system since the absence of aliphatic glucosinolates in these plants could not be predicted by the chemotype of the single knockouts. CONCLUSIONS/SIGNIFICANCE: It seems that these cruciferous-specific MYB regulatory genes have evolved both overlapping and specific regulatory capacities. This provides a unique system within which to study the evolution of MYB regulatory factors and their downstream targets

    Identification of QTLs controlling gene expression networks defined a priori

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    BACKGROUND: Gene expression microarrays allow the quantification of transcript accumulation for many or all genes in a genome. This technology has been utilized for a range of investigations, from assessments of gene regulation in response to genetic or environmental fluctuation to global expression QTL (eQTL) analyses of natural variation. Current analysis techniques facilitate the statistical querying of individual genes to evaluate the significance of a change in response, also known as differential expression. Since genes are also known to respond as groups due to their membership in networks, effective approaches are needed to investigate transcriptome variation as related to gene network responses. RESULTS: We describe a statistical approach that is capable of assessing higher-order a priori defined gene network response, as measured by microarrays. This analysis detected significant network variation between two Arabidopsis thaliana accessions, Bay-0 and Shahdara. By extending this approach, we were able to identify eQTLs controlling network responses for 18 out of 20 a priori-defined gene networks in a recombinant inbred line population derived from accessions Bay-0 and Shahdara. CONCLUSION: This approach has the potential to be expanded to facilitate direct tests of the relationship between phenotypic trait and transcript genetic architecture. The use of a priori definitions for network eQTL identification has enormous potential for providing direction toward future eQTL analyses

    Mapping of QTL for Resistance against the Crucifer Specialist Herbivore Pieris brassicae in a New Arabidopsis Inbred Line Population, Da(1)-12×Ei-2

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    In Arabidopsis thaliana and other crucifers, the glucosinolate-myrosinase system contributes to resistance against herbivory by generalist insects. As yet, it is unclear how crucifers defend themselves against crucifer-specialist insect herbivores.We analyzed natural variation for resistance against two crucifer specialist lepidopteran herbivores, Pieris brassicae and Plutella xylostella, among Arabidopsis thaliana accessions and in a new Arabidopsis recombinant inbred line (RIL) population generated from the parental accessions Da(1)-12 and Ei-2. This RIL population consists of 201 individual F(8) lines genotyped with 84 PCR-based markers. We identified six QTL for resistance against Pieris herbivory, but found only one weak QTL for Plutella resistance. To elucidate potential factors causing these resistance QTL, we investigated leaf hair (trichome) density, glucosinolates and myrosinase activity, traits known to influence herbivory by generalist insects. We identified several previously unknown QTL for these traits, some of which display a complex pattern of epistatic interactions.Although some trichome, glucosinolate or myrosinase QTL co-localize with Pieris QTL, none of these traits explained the resistance QTL convincingly, indicating that resistance against specialist insect herbivores is influenced by other traits than resistance against generalists

    Genomic Analysis of QTLs and Genes Altering Natural Variation in Stochastic Noise

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    Quantitative genetic analysis has long been used to study how natural variation of genotype can influence an organism's phenotype. While most studies have focused on genetic determinants of phenotypic average, it is rapidly becoming understood that stochastic noise is genetically determined. However, it is not known how many traits display genetic control of stochastic noise nor how broadly these stochastic loci are distributed within the genome. Understanding these questions is critical to our understanding of quantitative traits and how they relate to the underlying causal loci, especially since stochastic noise may be directly influenced by underlying changes in the wiring of regulatory networks. We identified QTLs controlling natural variation in stochastic noise of glucosinolates, plant defense metabolites, as well as QTLs for stochastic noise of related transcripts. These loci included stochastic noise QTLs unique for either transcript or metabolite variation. Validation of these loci showed that genetic polymorphism within the regulatory network alters stochastic noise independent of effects on corresponding average levels. We examined this phenomenon more globally, using transcriptomic datasets, and found that the Arabidopsis transcriptome exhibits significant, heritable differences in stochastic noise. Further analysis allowed us to identify QTLs that control genomic stochastic noise. Some genomic QTL were in common with those altering average transcript abundance, while others were unique to stochastic noise. Using a single isogenic population, we confirmed that natural variation at ELF3 alters stochastic noise in the circadian clock and metabolism. Since polymorphisms controlling stochastic noise in genomic phenotypes exist within wild germplasm for naturally selected phenotypes, this suggests that analysis of Arabidopsis evolution should account for genetic control of stochastic variance and average phenotypes. It remains to be determined if natural genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes

    The Chromatin Remodeler SPLAYED Regulates Specific Stress Signaling Pathways

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    Organisms are continuously exposed to a myriad of environmental stresses. Central to an organism's survival is the ability to mount a robust transcriptional response to the imposed stress. An emerging mechanism of transcriptional control involves dynamic changes in chromatin structure. Alterations in chromatin structure are brought about by a number of different mechanisms, including chromatin modifications, which covalently modify histone proteins; incorporation of histone variants; and chromatin remodeling, which utilizes ATP hydrolysis to alter histone-DNA contacts. While considerable insight into the mechanisms of chromatin remodeling has been gained, the biological role of chromatin remodeling complexes beyond their function as regulators of cellular differentiation and development has remained poorly understood. Here, we provide genetic, biochemical, and biological evidence for the critical role of chromatin remodeling in mediating plant defense against specific biotic stresses. We found that the Arabidopsis SWI/SNF class chromatin remodeling ATPase SPLAYED (SYD) is required for the expression of selected genes downstream of the jasmonate (JA) and ethylene (ET) signaling pathways. SYD is also directly recruited to the promoters of several of these genes. Furthermore, we show that SYD is required for resistance against the necrotrophic pathogen Botrytis cinerea but not the biotrophic pathogen Pseudomonas syringae. These findings demonstrate not only that chromatin remodeling is required for selective pathogen resistance, but also that chromatin remodelers such as SYD can regulate specific pathways within biotic stress signaling networks

    Genetic Networks Controlling Structural Outcome of Glucosinolate Activation across Development

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    Most phenotypic variation present in natural populations is under polygenic control, largely determined by genetic variation at quantitative trait loci (QTLs). These genetic loci frequently interact with the environment, development, and each other, yet the importance of these interactions on the underlying genetic architecture of quantitative traits is not well characterized. To better study how epistasis and development may influence quantitative traits, we studied genetic variation in Arabidopsis glucosinolate activation using the moderately sized Bayreuth×Shahdara recombinant inbred population, in terms of number of lines. We identified QTLs for glucosinolate activation at three different developmental stages. Numerous QTLs showed developmental dependency, as well as a large epistatic network, centered on the previously cloned large-effect glucosinolate activation QTL, ESP. Analysis of Heterogeneous Inbred Families validated seven loci and all of the QTL×DPG (days post-germination) interactions tested, but was complicated by the extensive epistasis. A comparison of transcript accumulation data within 211 of these RILs showed an extensive overlap of gene expression QTLs for structural specifiers and their homologs with the identified glucosinolate activation loci. Finally, we were able to show that two of the QTLs are the result of whole-genome duplications of a glucosinolate activation gene cluster. These data reveal complex age-dependent regulation of structural outcomes and suggest that transcriptional regulation is associated with a significant portion of the underlying ontogenic variation and epistatic interactions in glucosinolate activation

    The Complex Genetic Architecture of the Metabolome

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    Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype–metabolite associations distributed non-randomly within the genome. These clusters of genotype–metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype–metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable

    Characterization of the natural variation in Arabidopsis thaliana metabolome by the analysis of metabolic distance

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    Metabolite fingerprinting is widely used to unravel the chemical characteristics of biological samples. Multivariate data analysis and other statistical tools are subsequently used to analyze and visualize the plasticity of the metabolome and/or the relationship between those samples. However, there are limitations to these approaches for example because of the multi-dimensionality of the data that makes interpretation of the data obtained from untargeted analysis almost impossible for an average human being. These limitations make the biological information that is of prime importance in untargeted studies be partially exploited. Even in the case of full exploitation, current methods for relationship elucidation focus mainly on between groups variation and differences. Therefore, a measure that is capable of exploiting both between- and within-group biological variation would be of great value. Here, we examined the natural variation in the metabolome of nine Arabidopsis thaliana accessions grown under various environmental conditions and established a measure for the metabolic distance between accessions and across environments. This data analysis approach shows that there is just a minor correlation between genetic and metabolic diversity of the nine accessions. On the other hand, it delivers so far in Arabidopsis unexplored chemical information and is shown to be biologically relevant for resistance studies

    Distinct Roles of Jasmonates and Aldehydes in Plant-Defense Responses

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    BACKGROUND: Many inducible plant-defense responses are activated by jasmonates (JAs), C(6)-aldehydes, and their corresponding derivatives, produced by the two main competing branches of the oxylipin pathway, the allene oxide synthase (AOS) and hydroperoxide lyase (HPL) branches, respectively. In addition to competition for substrates, these branch-pathway-derived metabolites have substantial overlap in regulation of gene expression. Past experiments to define the role of C(6)-aldehydes in plant defense responses were biased towards the exogenous application of the synthetic metabolites or the use of genetic manipulation of HPL expression levels in plant genotypes with intact ability to produce the competing AOS-derived metabolites. To uncouple the roles of the C(6)-aldehydes and jasmonates in mediating direct and indirect plant-defense responses, we generated Arabidopsis genotypes lacking either one or both of these metabolites. These genotypes were subsequently challenged with a phloem-feeding insect (aphids: Myzus persicae), an insect herbivore (leafminers: Liriomyza trifolii), and two different necrotrophic fungal pathogens (Botrytis cinerea and Alternaria brassicicola). We also characterized the volatiles emitted by these plants upon aphid infestation or mechanical wounding and identified hexenyl acetate as the predominant compound in these volatile blends. Subsequently, we examined the signaling role of this compound in attracting the parasitoid wasp (Aphidius colemani), a natural enemy of aphids. PRINCIPAL FINDINGS: This study conclusively establishes that jasmonates and C(6)-aldehydes play distinct roles in plant defense responses. The jasmonates are indispensable metabolites in mediating the activation of direct plant-defense responses, whereas the C(6)-aldehyes are not. On the other hand, hexenyl acetate, an acetylated C(6)-aldehyde, is the predominant wound-inducible volatile signal that mediates indirect defense responses by directing tritrophic (plant-herbivore-natural enemy) interactions. SIGNIFICANCE: The data suggest that jasmonates and hexenyl acetate play distinct roles in mediating direct and indirect plant-defense responses. The potential advantage of this "division of labor" is to ensure the most effective defense strategy that minimizes incurred damages at a reduced metabolic cost
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