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Plants produce diverse metabolites to cope with the challenges presented by complex and ever-changing environments. These challenges drive the diversification of specialized metabolites within and between plant species. However, we are just beginning to understand how frequently new alleles arise controlling specialized metabolite diversity and how the geographic distribution of these alleles may be structured by ecological and demographic pressures. Here, we measure the variation in specialized metabolites across a population of 797 natural Arabidopsis thaliana accessions. We show that a combination of geography, environmental parameters, demography and different genetic processes all combine to influence the specific chemotypes and their distribution. This showed that causal loci in specialized metabolism contain frequent independently generated alleles with patterns suggesting potential within-species convergence. This provides a new perspective about the complexity of the selective forces and mechanisms that shape the generation and distribution of allelic variation that may influence local adaptation., eLife digest Since plants cannot move, they have evolved chemical defenses to help them respond to changes in their surroundings. For example, where animals run from predators, plants may produce toxins to put predators off. This approach is why plants are such a rich source of drugs, poisons, dyes and other useful substances. The chemicals plants produce are known as specialized metabolites, and they can change a lot between, and even within, plant species. The variety of specialized metabolites is a result of genetic changes and evolution over millions of years. Evolution is a slow process, yet plants are able to rapidly develop new specialized metabolites to protect them from new threats. Even different populations of the same species produce many distinct metabolites that help them survive in their surroundings. However, the factors that lead plants to produce new metabolites are not well understood, and it is not known how this affects genetic variation. To gain a better understanding of this process, Katz et al. studied 797 European variants of a common weed species called Arabidopsis thaliana, which is widely studied. The investigation found that many factors affect the range of specialized metabolites in each variant. These included local geography and environment, as well as genetics and population history (demography). Katz et al. revealed a pattern of relationships between the variants that could mirror their evolutionary history as the species spread and adapted to new locations. These results highlight the complex network of factors that affect plant evolution. Rapid diversification is key to plant survival in new and changing environments and has resulted in a wide range of specialized metabolites. As such they are of interest both for studying plant evolution and for understanding their ecology. Expanding similar work to more populations and other species will broaden the scope of our ability to understand how plants adapt to their surroundings.

Plant species have evolved myriads of solutions to adapt to dynamic environments, including complex cell type development and regulation. To understand this diversity, we profiled tomato root cell type translatomes and chromatin accessibility. Using xylem differentiation in tomato, relative to Arabidopsis, examples of functional innovation, repurposing and conservation of transcription factors are described. Repurposing and innovation of genes are further observed within an exodermis regulatory network and illustrate its function. Translatome analyses of rice, tomato and Arabidopsis tissues suggest that root meristems are more conserved, and that the functions of constitutively expressed genes are more conserved than those of cell type/tissue-enriched genes. These observations suggest that higher-order properties of cell type and pan-cell type regulation are conserved between plants and animals.One Sentence SummaryPan-species cell type translatome and chromatin accessibility data reveal novelty, conservation and repurposing of gene function.

The sessile lifestyle of plants requires accurate physiology adjustments to be able to thrive in a changing environment. Plants integrate environmental timing signals to control developmental and stress responses. Here, we identified Far1 Related Sequence (FRS) 7 and FRS12, two transcriptional repressors that accumulate in short-day conditions, as regulators of Arabidopsis glucosinolate (GSL) biosynthesis. Loss of function of FRS7 and FRS12 results in plants with increased amplitudes of diurnal expression of GSL pathway genes. Protein interaction analyses revealed that FRS7 and FRS12 recruit the NOVEL INTERACTOR OF JAZ (NINJA) to assemble a transcriptional repressor complex. Genetic and molecular evidence demonstrated that FRS7, FRS12 and NINJA jointly regulate the expression of GSL biosynthetic genes, and thus constitute a molecular mechanism that modulates specialized metabolite accumulation.

Genetic diversity provides the raw material for species to adapt and persist in the face of climate change. Yet, the extent to which these genetic effects scale at the level of ecological communities remains unclear. Here we experimentally test the effect of plant genetic diversity on the persistence of an insect food web under a current and future warming scenario. We found that plant genetic diversity increased food-web persistence by increasing the intrinsic growth rates of species across multiple trophic levels. This positive effect was robust to a 3°C warming scenario and resulted from allelic variation at two genes that control the biosynthesis of chemical defenses. Our results suggest that the ongoing loss of genetic diversity may undermine the persistence and functioning of ecosystems in a changing world.One Sentence SummaryThe loss of genetic diversity accelerates the extinction of inter-connected species from an experimental food web.

The theoretical ability of epigenetic variation to influence the heritable variation of complex traits is gaining traction in the study of adaptation. This theory posits that epigenetic marks can control adaptive phenotypes but the relative potential of epigenetic variation in comparison to genetic variation in these traits is not presently understood. To compare the potential of epigenetic and genetic variation in adaptive traits, we analyzed the influence of DNA methylation variation on the accumulation of chemical defense compounds glucosinolates from the order Brassicales. Several decades of work on glucosinolates has generated extensive knowledge about their synthesis, regulation, genetic variation and contribution to fitness establishing this pathway as a model pathway for complex adaptive traits. Using high-throughput phenotyping with a randomized block design of ddm1 derived Arabidopsis thaliana epigenetic Recombinant Inbred Lines, we measured the correlation between DNA methylation variation and mean glucosinolate variation and within line stochastic variation. Using this information, we identified epigenetic Quantitative Trait Loci that contained specific Differentially Methylated Regions associated with glucosinolate traits. This showed that variation in DNA methylation correlates both with levels and variance of glucosinolates and flowering time with trait-specific loci. By conducting a meta-analysis comparing the results to different genetically variable populations, we conclude that the influence of DNA methylation variation on these adaptive traits is much lower than the corresponding impact of standing genetic variation. As such, selective pressure on these traits should mainly affect standing genetic variation to lead to adaptation.

How a plant regulates the relationship between plant growth and plant defense is critical for understanding plant fitness or yield. Yet, little about the required complex underlying interactions are understood.... Plants integrate internal and external signals to finely coordinate growth and defense for maximal fitness within a complex environment. A common model suggests that growth and defense show a trade-offs relationship driven by energy costs. However, recent studies suggest that the coordination of growth and defense likely involves more conditional and intricate connections than implied by the trade-off model. To explore how a transcription factor (TF) network may coordinate growth and defense, we used a high-throughput phenotyping approach to measure growth and flowering in a set of single and pairwise mutants previously linked to the aliphatic glucosinolate (GLS) defense pathway. Supporting a link between growth and defense, 17 of the 20 tested defense-associated TFs significantly influenced plant growth and/or flowering time. The TFs’ effects were conditional upon the environment and age of the plant, and more critically varied across the growth and defense phenotypes for a given genotype. In support of the coordination model of growth and defense, the TF mutant’s effects on short-chain aliphatic GLS and growth did not display a simple correlation. We propose that large TF networks integrate internal and external signals and separately modulate growth and the accumulation of the defensive aliphatic GLS.

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., eLife digest Infections are complex interactions between two organisms. When a disease-causing microbe and a potential host engage, molecules continuously flow in both directions. This creates an inter-connected loop of messages and counter-messages, attacks, counter-attacks and resistance. This communication determines the final winner and the outcome of the disease. Yet it is technically difficult to measure it from both organisms at the same time, mostly because it is often impossible to tell whether a given molecule came from the microbe or the host. As such, little is known about how most infections play out at the molecular level. Now, rather than looking directly at the communication molecules, Zhang et al. have measured the active genes in samples of a plant infected with a fungus. While a molecule released by the plant may be indistinguishable from one from the fungus, the genes needed to make those molecules will be different in each species. The experiments involved two species where databases of gene sequences already exist: Arabidopsis thaliana, a plant often used in laboratory studies, and a fungus known as Botrytis cinerea, which infects many plants. Zhang et al. showed that the interactions between the two organisms are diverse and, rather than single genes, they largely involve sets of genes that are all switched on together as so-called gene co-expression networks (or GCNs for short). Ten of these networks encoded mechanisms that allow the fungus to attack plant hosts. Further analysis identified potential connections between networks of genes in the plant and fungus. These connections may reveal some of the targets of the fungus’s toxins or counter mechanisms that plants can use to attempt to defend themselves. These findings show that it is possible to listen to the molecular communication between two organisms during an infection. In the future, a similar approach may make it possible to ask if a host plant communicates with all of its possible disease-causing microbes with a few distinct pathways, or if instead, hosts have the flexibility to uniquely communicate with each microbe in a different way.

Biology relies on the central thesis that the genes in an organism encode molecular mechanisms that combine with stimuli and raw materials from the environment to create a final phenotypic expression representative of the genomic programming. While conceptually simple, the genotype-to-phenotype linkage in a eukaryotic organism relies on the interactions of thousands of genes and an environment with a potentially unknowable level of complexity. Modern biology has moved to the use of networks in systems biology to try to simplify this complexity to decode how an organism's genome works. Previously, biological networks were basic ways to organize, simplify, and analyze data. However, recent advances are allowing networks to move beyond description and become phenotypes or hypotheses in their own right. This review discusses these efforts, like mapping responses across biological scales, including relationships among cellular entities, and the direct use of networks as traits or hypotheses.

We performed whole genome resequencing of 84 field isolates of Botrytis cinerea, largely collected from a local set of plant species. Combined with 13 previously resequenced isolates sampled from diverse locations, this gave a collection of 97 isolates for studies of natural variation. Alignment to the reference sequence T4 and SNP detection provided further data for population genetics analysis including a mapping population for association studies. Although much of the genomic diversity was captured in the original 13 isolates, the additional genomes increased total diversity in the population by a third. Surprisingly, the same additional genomes increase mitochondrial diversity 2-fold. Across the population, LD was limited and decayed rapidly, reflecting frequent outcrossings. Effectively, this sampling strategy increased the level of genetic diversity available, whilst limiting the problem of population stratification and enabling GWAS of several phenotypes on common Arabidopsis plants affected in disease pathways. Overlap of results using all GWAS methods revealed numerous candidate genes / pathways that potentially contribute to its broad host range and offer conceivable pathogen decrease targets.

The Golgi lumen is the site of many different glycosylation events, including cell wall polysaccharide biosynthesis and lipid glycosylation. Transporters are necessary for the import of the substrates required for glycosylation (nucleotide sugars) from the cytosol where they are synthesized. Plants use four GDP-linked sugars to glycosylate macromolecules: GDP-L-Fucose, GDP-D-Mannose, GDP-L-Galactose and GDP-D-Glucose. Of the predicted fifty-one members of the nucleotide sugar transporter/triose phosphate transporter family in Arabidopsis, only four appear to contain the conserved motif needed for the transport of GDP-linked sugars, GOLGI LOCALIZED NUCLEOTIDE SUGAR TRANSPORTER (GONST) 1-4. Previously, we have demonstrated that GONST1 provides GDP-D-Mannose for glycosylation of a class of sphingolipids, the glycosylinositolphosphorylceramides (GIPCs). Here, we characterize its closest homologue, GONST2, and conclude that it also specifically provides substrate for GIPC glycosylation. Expression ofGONST2driven by theGONST1promoter is able to rescue the severe growth phenotype ofgonst1. Loss of GONST2 exacerbates thegonst1constitutive hypersensitive response, as well as the reduced cell wall cellulose content. Thegonst2mutant grows normally under standard conditions, but has enhanced resistance to the powdery mildew-causing fungusGolovinomyces orontii.

SummaryRhizosphere microbes affect plant performance, including plant resistance against insect herbivores; yet, the relative influence of rhizosphere microbes vs. plant genotype on herbivory levels and on metabolites related to defense remains unclear.In Boechera stricta, we tested the effects of rhizosphere microbes and plant genotype on herbivore resistance, the primary metabolome, and select secondary metabolites.Plant populations differed significantly in the concentrations of 6 glucosinolates (GLS), secondary metabolites known to provide herbivore resistance in the Brassicaceae, and the population with lower GLS levels experienced ~60% higher levels of aphid (Aphis spp.) attack; no effect was observed of GLS on damage by a second herbivore, flea beetles (Altica spp.). Rhizosphere microbiome (intact vs. disrupted) had no effect on plant GLS concentrations. However, aphid number and flea beetle damage were respectively ~3-fold and 7-fold higher among plants grown in the disrupted rhizosphere microbiome treatment, and distinct (as estimated from 16s rRNA amplicon sequencing) intact native microbiomes also differed in their effects on herbivore damage. These differences may be attributable to shifts in primary metabolic pathways.The findings suggest that rhizosphere microbes can play a greater role than plant genotype in defense against insect herbivores, and act through mechanisms independent of plant genotype.

Human selection during crop domestication alters numerous traits, including disease resistance. Studies of qualitative resistance to specialist pathogens typically find decreased resistance in domesticated crops in comparison to their wild relatives. However, less is known about how crop domestication affects quantitative interactions with generalist pathogens. To study how crop domestication impacts plant resistance to generalist pathogens, and correspondingly how this interacts with the pathogen’s genetics, we infected a collection of wild and domesticated tomato accessions with a genetically diverse population of the generalist pathogenBotrytis cinerea. We quantified variation in lesion size of 97B. cinereagenotypes (isolates) on 6 domesticatedSolanum lycopersicumand 6 wildS. pimpinellifoliumgenotypes. This showed that lesion size was significantly controlled by plant domestication, plant genetic variation, and the pathogen’s genotype. Overall, resistance was slightly elevated in the wild germplasm in comparison to domesticated tomato accessions. Genome-wide association (GWA) mapping inB. cinereaidentified a highly polygenic collection of genes. This suggests that breeding against this pathogen would need to utilize a diversity of isolates to capture all possible mechanisms. Critically, we identified a discrete subset ofB. cinereagenes where the allelic variation was linked to altered virulence against the wild versus domesticated tomato accessions. This indicates that this generalist pathogen already has the necessary allelic variation in place to handle the introgression of wild resistance mechanisms into the domesticated crop. Future studies are needed to assess how these observations extend to other domesticated crops and other generalist pathogens.

To optimize fitness a plant should monitor its metabolism to appropriately control growth and defense. Primary metabolism can be measured by the universally conserved TOR (Target of Rapamycin) pathway to balance growth and development with the available energy and nutrients. Recent work suggests that plants may measure defense metabolites to potentially provide a strategy ensuring fast reallocation of resources to coordinate plant growth and defense. There is little understanding of mechanisms enabling defense metabolite signaling. To identify mechanisms of defense metabolite signaling, we used glucosinolates, an important class of plant defense metabolites. We report novel signaling properties specific to one distinct glucosinolate, 3-hydroxypropylglucosinolate across plants and fungi. This defense metabolite, or derived compounds, reversibly inhibits root growth and development. 3-hydroxypropylglucosinolate signaling functions via genes in the ancient TOR pathway. If this event is not unique, this raises the possibility that other evolutionarily new plant metabolites may link to ancient signaling pathways., eLife digest Plants, like all organisms, must invest their resources carefully. Growing new roots or shoots may allow a plant to better exploit its environment. But a plant should never leave itself vulnerable to disease. As such, there must be a balance between allocating resources to growth or to defense. Brassicas like cabbage, Brussels sprouts and wasabi use unique compounds called glucosinolates to protect themselves against pests and disease-causing microbes. These same compounds give these vegetables their distinctive flavors, and they are the source of many of the health benefits linked to eating these vegetables. Yet it was not known if glucosinolates could also affect a plant’s growth and development. Malinovsky et al. tested a number of purified glucosinolates with the model plant Arabidopsis thaliana, and found that one (called 3-hydroxypropylglucosinolate) caused the plants to grow with stunted roots. When 10 other species of plant were grown with this glucosinolate, almost all had shorter-than-normal roots. The effect was not limited to plants; baker’s yeast also grew less when its liquid media contained the plant-derived compound. The reason glucosinolates can protect plants against insect pests, provide us with health benefits, and widely inhibit growth is most likely because they have evolved to interact with proteins that are found in many different organisms.Indeed, through experiments with mutant Arabidopsis plants, Malinovsky et al. revealed that their glucosinolate influences the TOR complex. This complex of proteins works in an ancient and widespread signaling pathway that balances growth and development with the available energy and nutrients in organisms ranging from humans to yeast to plants. The TOR complex plays such a vital role in living cells that problems with this complex have been linked to diseases such as cancer and heart disease. Importantly, the chemical structure of this glucosinolate is unlike other compounds that have already been tested against the TOR complex. As such, it is possible that this glucosinolate might lead to new drugs for a range of human diseases. Further, as this compound affects plant growth, it could also act as a starting point for new herbicides. Together these findings show how studying molecules made in model organisms and understanding how they function can lead to the identification of new compounds and targets with an unexpectedly wide range of potential uses.

Plants produce a tremendous diversity of specialized metabolites (SMs) to interact with and manage their environment. A major challenge hindering efforts to tap this seemingly boundless source of pharmacopeia is the identification of SM pathways and their constituent genes. Given the well-established observation that the genes comprising a SM pathway are co-regulated in response to specific environmental conditions, we hypothesized that genes from a given SM pathway would form tight associations (modules) with each other in gene co-expression networks, facilitating their identification. To evaluate this hypothesis, we used 10 global co-expression datasets—each a meta-analysis of hundreds to thousands of expression experiments—across eight plant model organisms to identify hundreds of modules of co-expressed genes for each species. In support of our hypothesis, 15.3-52.6% of modules contained two or more known SM biosynthetic genes (e.g., cytochrome P450s, terpene synthases, and chalcone synthases), and module genes were enriched in SM functions (e.g., glucoside and flavonoid biosynthesis). Moreover, modules recovered many experimentally validated SM pathways in these plants, including all six known to form biosynthetic gene clusters (BGCs). In contrast, genes predicted based on physical proximity on a chromosome to form plant BGCs were no more co-expressed than the null distribution for neighboring genes. These results not only suggest that most predicted plant BGCs do not represent genuine SM pathways but also argue that BGCs are unlikely to be a hallmark of plant specialized metabolism. We submit that global gene co-expression is a rich, but largely untapped, data source for discovering the genetic basis and architecture of plant natural products, which can be applied even without knowledge of the genome sequence.

© 2017 Douglas et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. BREVIPEDICELLUS (BP) encodes a class-I KNOTTED1-like homeobox (KNOX) transcription factor that plays a critical role in conditioning a replication competent state in the apical meristem, and it also governs growth and cellular differentiation in internodes and pedicels. To search for factors that modify BP signaling, we conducted a suppressor screen on bp er (erecta) plants and identified a mutant that ameliorates many of the pleiotropic defects of the parent line. Map based cloning and complementation studies revealed that the defect lies in the FILAMENTOUS FLOWER (FIL) gene, a member of the YABBY family of transcriptional regulators that contribute to meristem organization and function, phyllotaxy, leaf and floral organ growth and polarity, and are also known to repress KNOX gene expression. Genetic and cytological analyses of the fil-10 suppressor line indicate that the role of FIL in promoting growth is independent of its previously characterized influences on meristem identity and lateral organ polarity, and likely occurs non-cellautonomously from superior floral organs. Transcription profiling of inflorescences revealed that FIL downregulates numerous transcription factors which in turn may subordinately regulate inflorescence architecture. In addition, FIL, directly or indirectly, activates over a dozen genes involved in glucosinolate production in part by activating MYB28, a known activator of many aliphatic glucosinolate biosynthesis genes. In the bp er fil-10 suppressor mutant background, enhanced expression of CYP71A13, AMIDASE1 (AMI) and NITRILASE genes suggest that auxin levels can be modulated by shunting glucosinolate metabolites into the IAA biosynthetic pathway, and increased IAA levels in the bp er fil-10 suppressor accompany enhanced internode and pedicel elongation. We propose that FIL acts to oppose KNOX1 gene function through a complex regulatory network that involves changes in secondary metabolites and auxin.

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.

© 2016 American Society of Plant Biologists. All rights reserved. Understanding whether the functionality of a biological system can be characterized by measuring few selected components is key to targeted phenotyping techniques in systems biology. Methods from observability theory have proven useful in identifying sensor components that have to be measured to obtain information about the entire system. Yet, the extent to which the data profiles reflect the role of components in the observability of the system remains unexplored. Here we first identify the sensor metabolites in the model plant Arabidopsis (Arabidopsis thaliana) by employing state-of-the-art genome-scale metabolic networks. By using metabolic data profiles from a set of seven environmental perturbations as well as from natural variability, we demonstrate that the data profiles of sensor metabolites are more correlated than those of nonsensor metabolites. This pattern was confirmed with in silico generated metabolic profiles from a medium-size kinetic model of plant central carbon metabolism. Altogether, due to the small number of identified sensors, our study implies that targeted metabolite analyses may provide the vast majority of relevant information about plant metabolic systems.

14 páginas, 8 figuras y 3 tablas., 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., This work was funded by a Marie Curie International Outgoing Fellowship within the 7th European Community Framework Programme (PIOF-GA-2010-275286), the NSF DBI grant 820580 to DK, the NSF MCB grant 1330337 to DK, the USDA National Institute of Food and Agriculture, Hatch project number CA-D-PLS-7033-H to DK and by the Danish National Research Foundation (DNRF99) grant to DK and MB.

© 2016, Zhang, Kwon, Chen and Kliebenstein. Generalist necrotrophic pathogens including Botrytis cinerea cause significant yield and financial losses on Brassica crops. However, there is little knowledge about the mechanisms underlying the complex interactions encoded by both host and pathogen genomes in this interaction. This potentially includes multiple layers of plant defense and pathogen virulence mechanisms that could complicate in breeding broad spectrum resistance within Brassica species. Glucosinolates (GSLs) are a diverse group of defense metabolites that play a key role in interaction between Brassica and biotic attackers. In this study, we utilized a collection of diverse B. cinerea isolates to investigate resistance within the Brassica rapa R500 × IMB211 recombinant inbred line population. We tested variation on lesion development and glucosinolate accumulation in parental lines and all population lines. We then mapped quantitative trait loci (QTL) for both resistances to B. cinerea and defense metabolites in this population. Phenotypic analysis and QTL mapping demonstrate that the genetic basis of resistance to B. cinerea in B. rapa is isolate specific and polygenic with transgressive segregation that both parents contribute resistance alleles. QTLs controlling defensive GSLs are highly dependent on pathogen infection. An overlap of two QTLs identified between resistance to B. cinerea and defense metabolites also showed isolate specific effects. This work suggests that directly searching for resistance loci may not be the best approach at improving resistance in B. rapa to necrotrophic pathogen.

© 2016 American Society of Plant Biologists. All rights reserved. Plant cell walls are important barriers against microbial pathogens. Cell walls of Arabidopsis thaliana leaves contain three major types of polysaccharides: cellulose, various hemicelluloses, and pectins. UDP-D-galacturonic acid, the key building block of pectins, is produced from the precursor UDP-D-glucuronic acid by the action of glucuronate 4-epimerases (GAEs). Pseudomonas syringae pv maculicola ES4326 (Pma ES4326) repressed expression of GAE1 and GAE6 in Arabidopsis, and immunity to Pma ES4326 was compromised in gae6 and gae1 gae6 mutant plants. These plants had brittle leaves and cell walls of leaves had less galacturonic acid. Resistance to specific Botrytis cinerea isolates was also compromised in gae1 gae6 double mutant plants. Although oligogalacturonide (OG)-induced immune signaling was unaltered in gae1 gae6 mutant plants, immune signaling induced by a commercial pectinase, macerozyme, was reduced. Macerozyme treatment or infection with B. cinerea released less soluble uronic acid, likely reflecting fewer OGs, from gae1 gae6 cell walls than from wild-type Col-0. Although both OGs and macerozyme-induced immunity to B. cinerea in Col-0, only OGs also induced immunity in gae1 gae6. Pectin is thus an important contributor to plant immunity, and this is due at least in part to the induction of immune responses by soluble pectin, likely OGs, that are released during plant-pathogen interactions.

Bacteria in a long-term evolution experiment evolved a new metabolic trait via two separate mutations with opposite effects.

© 2015 Jensen, Kliebenstein and Burow. Quantitative trait loci (QTL) mapping studies enable identification of loci that are part of regulatory networks controlling various phenotypes. Detailed investigations of genes within these loci are required to ultimately understand the function of individual genes and how they interact with other players in the network. In this study, we use transgenic plants in combination with natural variation to investigate the regulatory role of the AOP3 gene found in GS-AOP locus previously suggested to contribute to the regulation of glucosinolate defense compounds. Phenotypic analysis and QTL mapping in F2 populations with different AOP3 transgenes support that the enzymatic function and the AOP3 RNA both play a significant role in controlling glucosinolate accumulation. Furthermore, we find different loci interacting with either the enzymatic activity or the RNA of AOP3 and thereby extend the regulatory network controlling glucosinolate accumulation.

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., Danish National Research Foundation DNRF grant 99 (B.A.H., M.B., D.J.K.), IEE Marie Curie stipend PIEF-GA-2008-221236 (M.B.)

The plant cell wall is an important factor for determining cell shape, function and response to the environment. Secondary cell walls, such as those found in xylem, are composed of cellulose, hemicelluloses and lignin and account for the bulk of plant biomass. The coordination between transcriptional regulation of synthesis for each polymer is complex and vital to cell function. A regulatory hierarchy of developmental switches has been proposed, although the full complement of regulators remains unknown. Here we present a protein-DNA network between Arabidopsis thaliana transcription factors and secondary cell wall metabolic genes with gene expression regulated by a series of feed-forward loops. This model allowed us to develop and validate new hypotheses about secondary wall gene regulation under abiotic stress. Distinct stresses are able to perturb targeted genes to potentially promote functional adaptation. These interactions will serve as a foundation for understanding the regulation of a complex, integral plant component.

The Plant Cell is introducing a new category of research article, which we call Breakthrough Reports, to provide a home for exploratory articles on mechanistic and conceptual aspects of plant biology. Breakthrough Reports will showcase studies with conceptual novelty, whether in pointing the way to

© 2015 Zhang et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in anymedium, provided the original author and source are credited. Sclerotinia sclerotiorum and Botrytis cinerea are notorious plant pathogenic fungi with an extensive host range including Brassica crops. Glucosinolates (GSLs) are an important group of secondary metabolites characteristic of the Brassicales order, whose degradation products are proving to be increasingly important in plant protection. Enhancing the defense effect of GSL and their associated degradation products is an attractive strategy to strengthen the resistance of plants by transgenic approaches. We generated the lines of Brassica napus with three biosynthesis genes involved in GSL metabolic pathway (BnMAM1, BnCYP83A1 and BnUGT74B1), respectively.We then measured the foliar GSLs of each transgenic lines and inoculated them with S. sclerotiorum and B. cinerea. Compared with the wild type control, over-expressing BnUGT74B1 in B. napus increased the aliphatic and indolic GSL levels by 1.7 and 1.5 folds in leaves respectively; while over-expressing BnMAM1 or BnCYP83A1 resulted in an approximate 1.5-fold higher only in the aliphatic GSL level in leaves. The results of plant inoculation demonstrated that BnUGT74B1-overexpressing lines showed less severe disease symptoms and tissue damage compared with the wild type control, but BnMAM1 or BnCYP83A1-overexpressing lines showed no significant difference in comparison to the controls. These results suggest that the resistance to S. sclerotiorum and B. cinerea in B. napus could be enhanced through tailoring the GSL profiles by transgenic approaches or molecular breeding, which provides useful information to assist plant breeders to design improved breeding strategies.

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., Author Summary Systems biology is largely based on the principal that the link between genotype and phenotype is deterministic, and, if we know enough, can be predicted with high accuracy. In contrast, recent work studying transcription within single celled organisms has shown that the genotype to phenotype link is stochastic, i.e. a single genotype actually makes a range of phenotypes even in a single environment. Further, natural variation within genes can lead to each allele displaying a different phenotypic distribution. To test if multi-cellular organisms also display natural genetic variation in the stochastic link between genotype and phenotype, we measured the metabolome, growth and defense metabolism within an Arabidopsis RIL population and mapped quantitative trait loci. We show that genetic variation in the nuclear and organeller genomes influence the stochastic variation in all measured traits. Further, each trait class has distinct genetics underlying the stochastic variance, showing that there are different mechanisms controlling the stochastic genotype to phenotype link for each trait. Further work is necessary to identify the mechanisms underpinning the stochastic nature of the genotype to phenotype link.

© 2014 Joseph, Atwell, Corwin, Li and Kliebenstein. 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.

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, eLife digest The vast majority of genes in plant and animal cells are located on chromosomes within the nucleus. However, cells also contain a small number of genes outside the nucleus in cellular organelles such as the mitochondria, which generate energy, and the chloroplasts, which carry out photosynthesis. All these non-nuclear genes comprise the organellar genome. When trying to explain how variation in genes leads to differences in the characteristics of animals and plants, geneticists have historically paid most attention to the genes inside the nucleus. However, more recent work has shown that variation in the organellar genome can also contribute to differences between individuals, although the relative contribution of organellar genes versus nuclear genes remains unclear. Now, Joseph et al. have performed the first large-scale analysis of how variation in the organellar genome affects the characteristics (or phenotype) of the plant model organism, Arabidopsis. The study examined the degree to which variation in each of roughly 13,000 nuclear genes and 200 organellar genes affected the levels of thousands of metabolites inside cells. This metabolomics analysis revealed that variation in the organellar genome contributed to variation in the levels of more than 80% of the metabolites studied. Organellar genes also helped to regulate the effect of nuclear genes. This combination of direct and indirect influences helps to explain how a small number of organellar genes can have a disproportionately large effect on phenotype. The work of Joseph et al. suggests that the role of the organellar genome has been significantly underestimated to date, and that geneticists should consider variation in both the nuclear and organellar genome when attempting to determine how genes affect phenotype. DOI: http://dx.doi.org/10.7554/eLife.00776.002

The modular design of plants enables individual plant organs to manifest autonomous functions [1] and continue aspects of metabolism, such as respiration, even after separation from the parent plant [2]. Therefore, we hypothesized that harvested vegetables and fruits may retain capacity to perceive and respond to external stimuli. For example, the fitness advantage of plant circadian clock function is recognized [3 and 4]; however, whether the clock continues to influence postharvest physiology is unclear. Here we demonstrate that the circadian clock of postharvest cabbage (Brassica oleracea) is entrainable by light-dark cycles and results in enhanced herbivore resistance. In addition, entrainment of Arabidopsis plants and postharvest cabbage causes cyclical accumulation of metabolites that function in plant defense; in edible crops, these metabolites also have potent anticancer properties [5]. Finally, we show that the phenomena of postharvest entrainment and enhanced herbivore resistance are widespread among diverse crops. Therefore, sustained clock entrainment of postharvest crops may be a simple mechanism to promote pest resistance and nutritional value of plant-derived food., This material is based upon work supported by the National Science Foundation under grant number MCB 0817976 and a Rice University Institute of Biosciences and Bioengineering Medical Innovations Award to J.B. We also acknowledge support from National Science Foundation grant number DBI 0820580 (D.J.K.). M.F. is supported by the Misión Biológica de Galicia (CSIC) of Spain and a Marie Curie Fellowship (PIOF-GA-2010-275286).

Transcriptional reprogramming forms a major part of a plant's response to pathogen infection. Many individual components and pathways operating during plant defense have been identified, but our knowledge of how these different components interact is still rudimentary. We generated a high-resolution time series of gene expression profiles from a single Arabidopsis thaliana leaf during infection by the necrotrophic fungal pathogen Botrytis cinerea. Approximately one-third of the Arabidopsis genome is differentially expressed during the first 48 h after infection, with the majority of changes in gene expression occurring before significant lesion development. We used computational tools to obtain a detailed chronology of the defense response against B. cinerea, highlighting the times at which signaling and metabolic processes change, and identify transcription factor families operating at different times after infection. Motif enrichment and network inference predicted regulatory interactions, and testing of one such prediction identified a role for TGA3 in defense against necrotrophic pathogens. These data provide an unprecedented level of detail about transcriptional changes during a defense response and are suited to systems biology analyses to generate predictive models of the gene regulatory networks mediating the Arabidopsis response to B. cinerea.

Transcriptomics is a major platform to study organismal biology. The advent of new parallel sequencing technologies has opened up a new avenue of transcriptomics with ever deeper and deeper sequencing to identify and quantify each and every transcript in a sample. However, this may not be the best usage of the parallel sequencing technology for all transcriptomics experiments. I utilized the Shannon Entropy approach to estimate the information contained within a transcriptomics experiment and tested the ability of shallow RNAseq to capture the majority of this information. This analysis showed that it was possible to capture nearly all of the network or genomic information present in a variety of transcriptomics experiments using a subset of the most abundant 5000 transcripts or less within any given sample. Thus, it appears that it should be possible and affordable to conduct large scale factorial analysis with a high degree of replication using parallel sequencing technologies.

Plant Anti-Insect Armaments Because individual plants are unable to relocate, they are subject to extreme selection by the insects feeding upon them. One means by which plants suppress herbivory is to produce toxic compounds to deter feeding (see the Perspective by Hare ). Agrawal et al. (p. 113 ) compared pesticide–treated or untreated evening primroses. Over 5 years of pesticide treatment, the production of defensive chemicals in the fruit reduced and flowering times shifted, and the primrose's competitive ability against dandelions improved. Züst et al. (p. 116 ) examined large-scale geographic patterns in a polymorphic chemical defense locus in the model plant Arabidopsis thaliana and found that it is matched by changes in the relative abundance of two specialist aphids. Thus, herbivory has strong and immediate effects on the local genotypic composition of plants and traits associated with herbivore resistance.

Models of myriad forms are rapidly becoming central to biology. These range from statistical models that are fundamental to the interpretation of experimental results to ordinary differential equation models that attempt to describe the results in a mechanistic format. Models will be more and more essential to biologists but this growing importance requires all model users to become more sophisticated about what is in a model and how that limits the usability of the model. This review attempts to relay the potential pitfalls that can lie within a model.

Models of myriad forms are rapidly becoming central to biology. This ranges from statistical models that are fundamental to the interpretation of experimental results to ODE models that attempt to describe the results in a mechanistic format. Models will be more and more essential to biologists but this growing importance requires all model users to become more sophisticated about what is in a model and how that limits the usability of the model. This review attempts to relay the potential pitfalls that can lay within a model

Genome-wide association mapping is highly sensitive to environmental changes, but network analysis allows rapid causal gene identification., Background 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. Methodology/Principal Findings 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. Conclusions/Significance 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., Author Summary Understanding how genetic variation can control phenotypic variation is a fundamental goal of modern biology. A major push has been made using genome-wide association mapping in all organisms to attempt and rapidly identify the genes contributing to phenotypes such as disease and nutritional disorders. But a number of fundamental questions have not been answered about the use of genome-wide association: for example, how does the internal or external environment influence the genes found? Furthermore, the simple question of how many genes may influence a trait is unknown. Finally, a number of studies have identified significant false-positive and -negative issues within genome-wide association studies that are not solvable by direct statistical approaches. We have used genome-wide association mapping in the plant Arabidopsis thaliana to begin exploring these questions. We show that both external and internal environments significantly alter the identified genes, such that using different tissues can lead to the identification of nearly completely different gene sets. Given the large number of potential false-positives, we developed an orthogonal approach to filtering the possible genes, by identifying co-functioning networks using the nominal candidate gene list derived from genome-wide association studies. This allowed us to rapidly identify and validate a large number of novel and unexpected genes that affect Arabidopsis thaliana defense metabolism within phenotypic ranges that have been shown to be selectable within the field. These genes and the associated networks suggest that Arabidopsis thaliana defense metabolism is more readily similar to the infinite gene hypothesis, according to which there is a vast number of causative genes controlling natural variation in this phenotype. It remains to be seen how frequently this is true for other organisms and other phenotypes.

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.