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ABSTRACT: Plants defend themselves against attack by natural enemies, and these defenses vary widely across populations. However, whether communities of natural enemies are a sufficiently potent force to maintain polymorphisms in defensive traits is largely unknown. Here, we exploit the genetic resources of Arabidopsis thaliana, coupled with 39 years of field data on aphid abundance, to (i) demonstrate that geographic patterns in a polymorphic defense locus (GS-ELONG) are strongly correlated with changes in the relative abundance of two specialist aphids; and (ii) demonstrate differential selection by the two aphids on GS-ELONG, using a multigeneration selection experiment. We thereby show a causal link between variation in abundance of the two specialist aphids and the geographic pattern at GS-ELONG, which highlights the potency of natural enemies as selective forces.
Science 10/2012; 338(6103):116-9. · 31.20 Impact Factor
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ABSTRACT: Plastid-derived signals are known to coordinate expression of nuclear genes encoding plastid-localized proteins in a process termed retrograde signaling. To date, the identity of retrograde-signaling molecules has remained elusive. Here, we show that methylerythritol cyclodiphosphate (MEcPP), a precursor of isoprenoids produced by the plastidial methylerythritol phosphate (MEP) pathway, elicits the expression of selected stress-responsive nuclear-encoded plastidial proteins. Genetic and pharmacological manipulations of the individual MEP pathway metabolite levels demonstrate the high specificity of MEcPP as an inducer of these targeted stress-responsive genes. We further demonstrate that abiotic stresses elevate MEcPP levels, eliciting the expression of the aforementioned genes. We propose that the MEP pathway, in addition to producing isoprenoids, functions as a stress sensor and a coordinator of expression of targeted stress-responsive nuclear genes via modulation of the levels of MEcPP, a specific and critical retrograde-signaling metabolite.
Cell 06/2012; 149(7):1525-35. · 32.40 Impact Factor
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ABSTRACT: Since research on plant interactions with herbivores and pathogens is often constrained by the analysis of already known compounds, there is a need to identify new defense-related plant metabolites. The uncommon nonprotein amino acid N(δ)-acetylornithine was discovered in a targeted search for Arabidopsis thaliana metabolites that are strongly induced by the phytohormone methyl jasmonate (MeJA). Stable isotope labeling experiments show that, after MeJA elicitation, Arg, Pro, and Glu are converted to Orn, which is acetylated by NATA1 to produce N(δ)-acetylornithine. MeJA-induced N(δ)-acetylornithine accumulation occurs in all tested Arabidopsis accessions, other Arabidopsis species, Capsella rubella, and Boechera stricta, but not in less closely related Brassicaceae. Both insect feeding and Pseudomonas syringae infection increase NATA1 expression and N(δ)-acetylornithine accumulation. NATA1 transient expression in Nicotiana tabacum and the addition of N(δ)-acetylornithine to an artificial diet both decrease Myzus persicae (green peach aphid) reproduction, suggesting a direct toxic or deterrent effect. However, since broad metabolic changes that are induced by MeJA in wild-type Arabidopsis are attenuated in a nata1 mutant strain, there may also be indirect effects on herbivores and pathogens. In the case of P. syringae, growth on a nata1 mutant is reduced compared with wild-type Arabidopsis, but growth in vitro is unaffected by N(δ)-acetylornithine addition.
The Plant Cell 09/2011; 23(9):3303-18. · 8.99 Impact Factor
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ABSTRACT: 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.
PLoS Genetics 09/2011; 7(9):e1002295. · 8.69 Impact Factor
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ABSTRACT: Genome-wide association (GWA) is gaining popularity as a means to study the architecture of complex quantitative traits, partially due to the improvement of high-throughput low-cost genotyping and phenotyping technologies. Glucosinolate (GSL) secondary metabolites within Arabidopsis spp. can serve as a model system to understand the genomic architecture of adaptive quantitative traits. GSL are key anti-herbivory defenses that impart adaptive advantages within field trials. While little is known about how variation in the external or internal environment of an organism may influence the efficiency of GWA, GSL variation is known to be highly dependent upon the external stresses and developmental processes of the plant lending it to be an excellent model for studying conditional GWA.
To understand how development and environment can influence GWA, we conducted a study using 96 Arabidopsis thaliana accessions, >40 GSL phenotypes across three conditions (one developmental comparison and one environmental comparison) and ∼230,000 SNPs. Developmental stage had dramatic effects on the outcome of GWA, with each stage identifying different loci associated with GSL traits. Further, while the molecular bases of numerous quantitative trait loci (QTL) controlling GSL traits have been identified, there is currently no estimate of how many additional genes may control natural variation in these traits. We developed a novel co-expression network approach to prioritize the thousands of GWA candidates and successfully validated a large number of these genes as influencing GSL accumulation within A. thaliana using single gene isogenic lines.
Together, these results suggest that complex traits imparting environmentally contingent adaptive advantages are likely influenced by up to thousands of loci that are sensitive to fluctuations in the environment or developmental state of the organism. Additionally, while GWA is highly conditional upon genetics, the use of additional genomic information can rapidly identify causal loci en masse.
PLoS Biology 08/2011; 9(8):e1001125. · 11.45 Impact Factor
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ABSTRACT: To identify the underlying molecular basis of carbon partitioning between starch and oil we conducted 454 pyrosequencing, followed by custom microarrays to profile gene expression throughout endosperm development, of two closely related oat cultivars that differ in oil content at the expense of starch as determined by several approaches including non-invasive magnetic resonance imaging. Comparative transcriptome analysis in conjunction with metabolic profiling displays a close coordination between energy metabolism and carbon partitioning pathways, with increased demands for energy and reducing equivalents in kernels with a higher oil content. These studies further expand the repertoire of networks regulating carbon partitioning to those involved in metabolism of cofactors, suggesting that an elevated supply of cofactors, here called cofactomes, contribute to the allocation of higher carbon pools for production of oils and storage proteins. These data highlight a close association between cofactomes and carbon partitioning, thereby providing a biotechnological target for conversion of starch to oil.
The Plant Journal 05/2011; 67(6):1018-28. · 6.16 Impact Factor
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ABSTRACT: Modern systems biology permits the study of complex networks, such as circadian clocks, and the use of complex methodologies, such as quantitative genetics. However, it is difficult to combine these approaches due to factorial expansion in experiments when networks are examined using complex methods. We developed a genomic quantitative genetic approach to overcome this problem, allowing us to examine the function(s) of the plant circadian clock in different populations derived from natural accessions. Using existing microarray data, we defined 24 circadian time phase groups (i.e., groups of genes with peak phases of expression at particular times of day). These groups were used to examine natural variation in circadian clock function using existing single time point microarray experiments from a recombinant inbred line population. We identified naturally variable loci that altered circadian clock outputs and linked these circadian quantitative trait loci to preexisting metabolomics quantitative trait loci, thereby identifying possible links between clock function and metabolism. Using single-gene isogenic lines, we found that circadian clock output was altered by natural variation in Arabidopsis thaliana secondary metabolism. Specifically, genetic manipulation of a secondary metabolic enzyme led to altered free-running rhythms. This represents a unique and valuable approach to the study of complex networks using quantitative genetics.
The Plant Cell 02/2011; 23(2):471-85. · 8.99 Impact Factor
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ABSTRACT: Intra- and interspecific variation in flower color is a hallmark of angiosperm diversity. The evolutionary forces underlying the variety of flower colors can be nearly as diverse as the colors themselves. In addition to pollinator preferences, non-pollinator agents of selection can have a major influence on the evolution of flower color polymorphisms, especially when the pigments in question are also expressed in vegetative tissues. In such cases, identifying the target(s) of selection starts with determining the biochemical and molecular basis for the flower color variation and examining any pleiotropic effects manifested in vegetative tissues. Herein, we describe a widespread purple-white flower color polymorphism in the mustard Parrya nudicaulis spanning Alaska. The frequency of white-flowered individuals increases with increasing growing-season temperature, consistent with the role of anthocyanin pigments in stress tolerance. White petals fail to produce the stress responsive flavonoid intermediates in the anthocyanin biosynthetic pathway (ABP), suggesting an early pathway blockage. Petal cDNA sequences did not reveal blockages in any of the eight enzyme-coding genes in white-flowered individuals, nor any color differentiating SNPs. A qRT-PCR analysis of white petals identified a 24-fold reduction in chalcone synthase (CHS) at the threshold of the ABP, but no change in CHS expression in leaves and sepals. This arctic species has avoided the deleterious effects associated with the loss of flavonoid intermediates in vegetative tissues by decoupling CHS expression in petals and leaves, yet the correlation of flower color and climate suggests that the loss of flavonoids in the petals alone may affect the tolerance of white-flowered individuals to colder environments.
PLoS ONE 01/2011; 6(4):e18230. · 4.09 Impact Factor
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ABSTRACT: We used a selection of Arabidopsis thaliana mutants with knockouts in defence genes to demonstrate growth costs of trichome development and glucosinolate production. Four of the seven defence mutants had significantly higher size-standardized growth rates (SGRs) than the wild-type in early life, although this benefit declined as plants grew larger. SGR is known to be a good predictor of success under high-density conditions, and we confirmed that mutants with higher growth rates had a large advantage when grown in competition. Despite the lack of differences in flowering-time genes, the mutants differed in flowering time, a trait that strongly correlated with early growth rate. Aphid herbivory decreased plant growth rate and increased flowering time, and aphid population growth rate was closely coupled to the growth rate of the host plant. Small differences in early SGR thus had cascading effects on both flowering time and herbivore populations.
Proceedings of the Royal Society B: Biological Sciences 01/2011; 278(1718):2598-603. · 5.41 Impact Factor
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ABSTRACT: *Most plants suffer some degree of herbivore attack and many actively defend themselves against such an event. However, while such defence is generally assumed to be costly, it has sometimes proved difficult to demonstrate the costs of defensive compounds. *Here, we present a method for analysing growth rates which allows the effects of variation in initial plant size to be properly accounted for and apply it to 30 lines from a recombinant inbred population of Arabidopsis thaliana. We then relate different measures of relative growth rate (RGR) to damage caused by a specialist lepidopteran insect and to levels of putative defensive compounds measured on the same lines. *We show that seed size variation within the recombinant inbred population is large enough to generate differences in RGR, even when no other physiological differences exist. However, once size-standardized, RGR was positively correlated with herbivore damage (fast-growing lines suffered more damage) and was negatively correlated with the concentration of several glucosinolate compounds. *We conclude that defensive compounds do have a growth cost and that the production of such compounds results in reduced herbivore damage. However, size standardization of RGR was essential to uncovering the growth costs of defensive compounds.
New Phytologist 09/2010; 187(4):1102-11. · 6.64 Impact Factor
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ABSTRACT: Systems biology approaches address higher levels of complex, but dynamic metabolic regulatory networks utilizing single accessions of a species. This contrasts with the likelihood that plants utilize genetic diversity of both individual genes and regulatory networks as a solution to surviving in a complex environment. This would require systems biology to begin a more inclusive search for 'all' networks within a species. In this review, we will highlight how natural genetic diversity within particularly aliphatic glucosinolates in Arabidopsis thaliana and related species has resulted in highly complex, dynamic regulatory networks enabling the plant to adapt to a highly changing environment. We will discuss how this diversity is essential for the fitness performance of A. thaliana.
Current opinion in plant biology 03/2010; 13(3):348-53. · 10.33 Impact Factor
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ABSTRACT: While R2R3 MYB transcription factors are a large gene family of transcription factors within plants, comprehensive functional data in planta are still scarce. A model for studying R2R3 MYB control of metabolic networks is the glucosinolates (GLSs), secondary metabolites that control plant resistance against insects and pathogens and carry cancer-preventive properties. Three related members of the R2R3 MYB transcription factor family within Arabidopsis (Arabidopsis thaliana), MYB28, MYB29, and MYB76, are the commonly defined regulators of aliphatic GLS biosynthesis. We utilized new genotypes and systems analysis techniques to test the existing regulatory model in which MYB28 is the dominant regulator, MYB29 plays a minor rheostat role, and MYB76 is largely uninvolved. We unequivocally show that MYB76 is not dependent on MYB28 and MYB29 for induction of aliphatic GLSs and that MYB76 plays a role in determining the spatial distribution of aliphatic GLSs within the leaf, pointing at a potential role of MYB76 in transport regulation. Transcriptional profiling of knockout mutants revealed that GLS metabolite levels are uncoupled from the level of transcript accumulation for aliphatic GLS biosynthetic genes. This uncoupling of chemotypes from biosynthetic transcripts suggests revising our view of the regulation of GLS metabolism from a simple linear transcription factor-promoter model to a more modular system in which transcription factors cause similar chemotypes via nonoverlapping regulatory patterns. Similar regulatory networks might exist in other secondary pathways.
Plant physiology 03/2010; 153(1):348-63. · 6.53 Impact Factor
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PLoS Pathogens 01/2010; 6(3):e1000759. · 9.13 Impact Factor
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ABSTRACT: 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.
PLoS Genetics 01/2010; 6(11):e1001198. · 8.69 Impact Factor
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ABSTRACT: Despite the described central role of jasmonate signaling in plant defense against necrotrophic pathogens, the existence of intraspecific variation in pathogen capacity to activate or evade plant jasmonate-mediated defenses is rarely considered. Experimental infection of jasmonate-deficient and jasmonate-insensitive Arabidopsis thaliana with diverse isolates of the necrotrophic fungal pathogen Botrytis cinerea revealed pathogen variation for virulence inhibition by jasmonate-mediated plant defenses and induction of plant defense metabolites. Comparison of the transcriptional effects of infection by two distinct B. cinerea isolates showed only minor differences in transcriptional responses of wild-type plants, but notable isolate-specific transcript differences in jasmonate-insensitive plants. These transcriptional differences suggest B. cinerea activation of plant defenses that require plant jasmonate signaling for activity in response to only one of the two B. cinerea isolates tested. Thus, similar infection phenotypes observed in wild-type plants result from different signaling interactions with the plant that are likely integrated by jasmonate signaling.
PLoS Pathogens 01/2010; 6(4):e1000861. · 9.13 Impact Factor
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Daniel J Kliebenstein
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ABSTRACT: The vast majority of measurable phenotypes within species are not fixed and populations contain significant levels of natural genetic variation among individuals affecting phenotypes from development to metabolism to abiotic resistance. All of which are of interest to both basic and applied biologists from a myriad of fields. Despite the ubiquity of this variation there is very little known about the molecular underpinnings of natural genetic variation or the forces behind its maintenance or generation. Recent advances in both genomics and systems biology are beginning to allow some of the first direct empirical tests of a suite of parameters that while being a foundation of natural variation were largely left to the theoreticians. These include the following basic questions: what is Pleiotropy?; how many genes control a given quantitative trait?; where is the heritability? and how is conditional genetic variation generated. This review highlights progress made towards addressing these questions via the use of systems biological inquiries into natural variation.
Plant physiology 11/2009; 152(2):480-6. · 6.53 Impact Factor
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ABSTRACT: With the improvement and decline in cost of high-throughput genotyping and phenotyping technologies, genome-wide association (GWA) studies are fast becoming a preferred approach for dissecting complex quantitative traits. Glucosinolate (GSL) secondary metabolites within Arabidopsis spp. can serve as a model system to understand the genomic architecture of quantitative traits. GSLs are key defenses against insects in the wild and the relatively large number of cloned quantitative trait locus (QTL) controlling GSL traits allows comparison of GWA to previous QTL analyses. To better understand the specieswide genomic architecture controlling plant-insect interactions and the relative strengths of GWA and QTL studies, we conducted a GWA mapping study using 96 A. thaliana accessions, 43 GSL phenotypes, and approximately 230,000 SNPs. Our GWA analysis identified the two major polymorphic loci controlling GSL variation (AOP and MAM) in natural populations within large blocks of positive associations encompassing dozens of genes. These blocks of positive associations showed extended linkage disequilibrium (LD) that we hypothesize to have arisen from balancing or fluctuating selective sweeps at both the AOP and MAM loci. These potential sweep blocks are likely linked with the formation of new defensive chemistries that alter plant fitness in natural environments. Interestingly, this GWA analysis did not identify the majority of previously identified QTL even though these polymorphisms were present in the GWA population. This may be partly explained by a nonrandom distribution of phenotypic variation across population subgroups that links population structure and GSL variation, suggesting that natural selection can hinder the detection of phenotype-genotype associations in natural populations.
Genetics 10/2009; 185(3):991-1007. · 4.01 Impact Factor
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April E Agee,
Marci Surpin,
Eun Ju Sohn,
Thomas Girke,
Abel Rosado,
Brian W Kram,
Clay Carter,
Adam M Wentzell, Daniel J Kliebenstein,
Hak Chul Jin,
Ohkmae K Park,
Hailing Jin,
Glenn R Hicks,
Natasha V Raikhel
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ABSTRACT: We identified an Arabidopsis (Arabidopsis thaliana) ethyl methanesulfonate mutant, modified vacuole phenotype1-1 (mvp1-1), in a fluorescent confocal microscopy screen for plants with mislocalization of a green fluorescent protein-delta tonoplast intrinsic protein fusion. The mvp1-1 mutant displayed static perinuclear aggregates of the reporter protein. mvp1 mutants also exhibited a number of vacuole-related phenotypes, as demonstrated by defects in growth, utilization of stored carbon, gravitropic response, salt sensitivity, and specific susceptibility to the fungal necrotroph Alternaria brassicicola. Similarly, crosses with other endomembrane marker fusions identified mislocalization to aggregate structures, indicating a general defect in protein trafficking. Map-based cloning showed that the mvp1-1 mutation altered a gene encoding a putative myrosinase-associated protein, and glutathione S-transferase pull-down assays demonstrated that MVP1 interacted specifically with the Arabidopsis myrosinase protein, THIOGLUCOSIDE GLUCOHYDROLASE2 (TGG2), but not TGG1. Moreover, the mvp1-1 mutant showed increased nitrile production during glucosinolate hydrolysis, suggesting that MVP1 may play a role in modulation of myrosinase activity. We propose that MVP1 is a myrosinase-associated protein that functions, in part, to correctly localize the myrosinase TGG2 and prevent inappropriate glucosinolate hydrolysis that could generate cytotoxic molecules.
Plant physiology 10/2009; 152(1):120-32. · 6.53 Impact Factor
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ABSTRACT: The identification of genes that confer durable, multipathogen resistance may help breeders overcome devastating wheat fungal
diseases.
Science 04/2009; 323(5919):1301-2. · 31.20 Impact Factor
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Daniel J Kliebenstein
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ABSTRACT: Gene expression microarrays allow rapid and easy quantification of transcript accumulation for almost transcripts present in a genome. This technology has been utilized for diverse investigations from studying gene regulation in response to genetic or environmental fluctuation to global expression QTL (eQTL) analyses of natural variation. Typical analysis techniques focus on responses of individual genes in isolation of other genes. However, emerging evidence indicates that genes are organized into regulons, i.e., they respond as groups due to individual transcription factors binding multiple promoters, creating what is commonly called a network. We have developed a set of statistical approaches that allow researchers to test specific network hypothesis using a priori-defined gene networks. When applied to Arabidopsis thaliana this approach has been able to identify natural genetic variation that controls networks. In this chapter we describe approaches to develop and test specific network hypothesis utilizing natural genetic variation. This approach can be expanded to facilitate direct tests of the relationship between phenotypic trait and transcript genetic architecture. Finally, the use of a priori network definitions can be applied to any microarray experiment to directly conduct hypothesis testing at a genomics level.
Methods in molecular biology (Clifton, N.J.) 02/2009; 553:227-45.
