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Desiccating and germinating seeds are particularly prone to oxidative stress. Glutathione (GSH) is one of the most abundant and ubiquitous antioxidants in plants. To better understand GSH's role in developing and germinating seeds, wildtype (WT) and a line of seed antisense for glutathione reductase 2 (anGR2), one of two glutathione reductase (GR) genes characterized in the genetic model plant Arabidopsis thaliana, were compared. GSH levels in maturing and germinating seeds were measured by high performance liquid chromatography (HPLC) and GR activity by native Polyacrylamide gel electrophoresis (PAGE). Natural and accelerated aging and germination at high temperature and under water stress were compared for WT and anGR2 seeds. Total GSH pools were two-fold less in anGR2 than in WT after three hours of imbibition. Under high temperature and osmotic stress, germination percentages were lower in anGR2, suggesting a specific relationship between GSH metabolism and stress defense mechanisms early in germination. Germination of anGR2 seeds declined while that of WT seeds increased slightly, during nine months of conventional storage. The relationship between GR2 transcript and activity levels during early imbibition and total GSH pools suggest a key role for GR2 in protection against environmental stress. This study shows that GSH metabolism is one factor that determines the stress tolerance of germinating Arabidopsis seeds. [ABSTRACT FROM AUTHOR]

Abstract Background Modeling of cis-elements or regulatory motifs in promoter (upstream) regions of genes is a challenging computational problem. In this work, set of regulatory motifs simultaneously present in the promoters of a set of genes is modeled as a biclique in a suitably defined bipartite graph. A biologically meaningful co-occurrence of multiple cis-elements in a gene promoter is assessed by the combined analysis of genomic and gene expression data. Greater statistical significance is associated with a set of genes that shares a common set of regulatory motifs, while simultaneously exhibiting highly correlated gene expression under given experimental conditions. Methods XcisClique, the system developed in this work, is a comprehensive infrastructure that associates annotated genome and gene expression data, models known cis-elements as regular expressions, identifies maximal bicliques in a bipartite gene-motif graph; and ranks bicliques based on their computed statistical significance. Significance is a function of the probability of occurrence of those motifs in a biclique (a hypergeometric distribution), and on the new sum of absolute values statistic (SAV) that uses Spearman correlations of gene expression vectors. SAV is a statistic well-suited for this purpose as described in the discussion. Results XcisClique identifies new motif and gene combinations that might indicate as yet unidentified involvement of sets of genes in biological functions and processes. It currently supports Arabidopsis thaliana and can be adapted to other organisms, assuming the existence of annotated genomic sequences, suitable gene expression data, and identified regulatory motifs. A subset of Xcis Clique functionalities, including the motif visualization component MotifSee, source code, and supplementary material are available at https://bioinformatics.cs.vt.edu/xcisclique/.

Abstract Background Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, together with a statistical significance assessment. This process typically consists of two steps: data normalization and identification of differentially expressed genes through statistical analysis. The Expresso microarray experiment management system implements these steps with a two-stage, log-linear ANOVA mixed model technique, tailored to individual experimental designs. The complement of tools in TM4, on the other hand, is based on a number of preset design choices that limit its flexibility. In the TM4 microarray analysis suite, normalization, filter, and analysis methods form an analysis pipeline. TM4 computes integrated intensity values (IIV) from the average intensities and spot pixel counts returned by the scanner software as input to its normalization steps. By contrast, Expresso can use either IIV data or median intensity values (MIV). Here, we compare Expresso and TM4 analysis of two experiments and assess the results against qRT-PCR data. Results The Expresso analysis using MIV data consistently identifies more genes as differentially expressed, when compared to Expresso analysis with IIV data. The typical TM4 normalization and filtering pipeline corrects systematic intensity-specific bias on a per microarray basis. Subsequent statistical analysis with Expresso or a TM4 t-test can effectively identify differentially expressed genes. The best agreement with qRT-PCR data is obtained through the use of Expresso analysis and MIV data. Conclusion The results of this research are of practical value to biologists who analyze microarray data sets. The TM4 normalization and filtering pipeline corrects microarray-specific systematic bias and complements the normalization stage in Expresso analysis. The results of Expresso using MIV data have the best agreement with qRT-PCR results. In one experiment, MIV is a better choice than IIV as input to data normalization and statistical analysis methods, as it yields as greater number of statistically significant differentially expressed genes; TM4 does not support the choice of MIV input data. Overall, the more flexible and extensive statistical models of Expresso achieve more accurate analytical results, when judged by the yardstick of qRT-PCR data, in the context of an experimental design of modest complexity.

Recent advances in genomic technologies have generated data on large-scale protein-DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has become a major challenge in genomic research. To solve this problem, we have developed a method called ConSReg, which provides a novel approach to integrate regulatory genomic data into predictive machine learning models of key regulatory genes. Using Arabidopsis as a model system, we tested our approach to identify regulatory genes in data sets from single cell gene expression and from abiotic stress treatments. Our results showed that ConSReg accurately predicted transcription factors that regulate differentially expressed genes with an average auROC of 0.84, which is 23.5-25% better than enrichment-based approaches. To further validate the performance of ConSReg, we analyzed an independent data set related to plant nitrogen responses. ConSReg provided better rankings of the correct transcription factors in 61.7% of cases, which is three times better than other plant tools. We applied ConSReg to Arabidopsis single cell RNA-seq data, successfully identifying candidate regulatory genes that control cell wall formation. Our methods provide a new approach to define candidate regulatory genes using integrated genomic data in plants., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: Comparative transcriptome analysis is the comparison of expression patterns between homologous genes in different species. Since most molecular mechanistic studies in plants have been performed in model species, including Arabidopsis and rice, comparative transcriptome analysis is particularly important for functional annotation of genes in diverse plant species. Many biological processes, such as embryo development, are highly conserved between different plant species. The challenge is to establish one-to-one mapping of the developmental stages between two species., Results: In this manuscript, we solve this problem by converting the gene expression patterns into co-expression networks and then apply network module finding algorithms to the cross-species co-expression network. We describe how such analyses are carried out using bash scripts for preliminary data processing followed by using the R programming language for module finding with a simulated annealing method. We also provide instructions on how to visualize the resulting co-expression networks across species., Conclusions: We provide a comprehensive pipeline from installing software and downloading raw transcriptome data to predicting homologous genes and finding orthologous co-expression networks. From the example provided, we demonstrate the application of our method to reveal functional conservation and divergence of genes in two plant species., Competing Interests: Competing interestsThe authors declare no competing interests.

Determining the complete Arabidopsis ( Arabidopsis thaliana ) protein-protein interaction network is essential for understanding the functional organization of the proteome. Numerous small-scale studies and a couple of large-scale ones have elucidated a fraction of the estimated 300,000 binary protein-protein interactions in Arabidopsis. In this study, we provide evidence that a docking algorithm has the ability to identify real interactions using both experimentally determined and predicted protein structures. We ranked 0.91 million interactions generated by all possible pairwise combinations of 1,346 predicted structure models from an Arabidopsis predicted "structure-ome" and found a significant enrichment of real interactions for the top-ranking predicted interactions, as shown by cosubcellular enrichment analysis and yeast two-hybrid validation. Our success rate for computationally predicted, structure-based interactions was 63% of the success rate for published interactions naively tested using the yeast two-hybrid system and 2.7 times better than for randomly picked pairs of proteins. This study provides another perspective in interactome exploration and biological network reconstruction using protein structural information. We have made these interactions freely accessible through an improved Arabidopsis Interactions Viewer and have created community tools for accessing these and ∼2.8 million other protein-protein and protein-DNA interactions for hypothesis generation by researchers worldwide. The Arabidopsis Interactions Viewer is freely available at http://bar.utoronto.ca/interactions2/., (© 2019 American Society of Plant Biologists. All Rights Reserved.)

Background: In gene regulatory networks, transcription factors often function as co-regulators to synergistically induce or inhibit expression of their target genes. However, most existing module-finding algorithms can only identify densely connected genes but not co-regulators in regulatory networks., Methods: We have developed a new computational method, CoReg, to identify transcription co-regulators in large-scale regulatory networks. CoReg calculates gene similarities based on number of common neighbors of any two genes. Using simulated and real networks, we compared the performance of different similarity indices and existing module-finding algorithms and we found CoReg outperforms other published methods in identifying co-regulatory genes. We applied CoReg to a large-scale network of Arabidopsis with more than 2.8 million edges and we analyzed more than 2,300 published gene expression profiles to charaterize co-expression patterns of gene moduled identified by CoReg., Results: We identified three types of modules in the Arabidopsis network: regulator modules, target modules and intermediate modules. Regulator modules include genes with more than 90% edges as out-going edges; Target modules include genes with more than 90% edges as incoming edges. Other modules are classified as intermediate modules. We found that genes in target modules tend to be highly co-expressed under abiotic stress conditions, suggesting this network struture is robust against perturbation., Conclusions: Our analysis shows that the CoReg is an accurate method in identifying co-regulatory genes in large-scale networks. We provide CoReg as an R package, which can be applied in finding co-regulators in any organisms with genome-scale regulatory network data.

The Beacon Editor is a cross-platform desktop application for the creation and modification of signal transduction pathways using the Systems Biology Graphical Notation Activity Flow (SBGN-AF) language. Prompted by biologists' requests for enhancements, the Beacon Editor includes numerous powerful features for the benefit of creation and presentation.

The sessile lifestyle of plants requires them to cope with stresses in situ . Plants overcome abiotic stresses by altering structure/morphology, and in some extreme conditions, by compressing the life cycle to survive the stresses in the form of seeds. Genetic and molecular studies have uncovered complex regulatory processes that coordinate stress adaptation and tolerance in plants, which are integrated at various levels. Investigating natural variation in stress responses has provided important insights into the evolutionary processes that shape the integrated regulation of adaptation and tolerance. This review primarily focuses on the current understanding of how transcriptional, post-transcriptional, post-translational, and epigenetic processes along with genetic variation orchestrate stress responses in plants. We also discuss the current and future development of computational tools to identify biologically meaningful factors from high dimensional, genome-scale data and construct the signaling networks consisting of these components.

Motivation: The increasing availability of chromatin immunoprecipitation sequencing (ChIP-Seq) data enables us to learn more about the action of transcription factors in the regulation of gene expression. Even though in vivo transcriptional regulation often involves the concerted action of more than one transcription factor, the format of each individual ChIP-Seq dataset usually represents the action of a single transcription factor. Therefore, a relational database in which available ChIP-Seq datasets are curated is essential. Results: We present Expresso (database and webserver) as a tool for the collection and integration of available Arabidopsis ChIP-Seq peak data, which in turn can be linked to a user's gene expression data. Known target genes of transcription factors were identified by motif analysis of publicly available GEO ChIP-Seq data sets. Expresso currently provides three services: 1) Identification of target genes of a given transcription factor; 2) Identification of transcription factors that regulate a gene of interest; 3) Computation of correlation between the gene expression of transcription factors and their target genes. Availability : Expresso is freely available at http://bioinformatics.cs.vt.edu/expresso/., Competing Interests: Competing interests: No competing interests were disclosed.

Gene regulatory networks (GRNs) provide a representation of relationships between regulators and their target genes. Several methods for GRN inference, both unsupervised and supervised, have been developed to date. Because regulatory relationships consistently reprogram in diverse tissues or under different conditions, GRNs inferred without specific biological contexts are of limited applicability. In this report, a machine learning approach is presented to predict GRNs specific to developing Arabidopsis thaliana embryos. We developed the Beacon GRN inference tool to predict GRNs occurring during seed development in Arabidopsis based on a support vector machine (SVM) model. We developed both global and local inference models and compared their performance, demonstrating that local models are generally superior for our application. Using both the expression levels of the genes expressed in developing embryos and prior known regulatory relationships, GRNs were predicted for specific embryonic developmental stages. The targets that are strongly positively correlated with their regulators are mostly expressed at the beginning of seed development. Potential direct targets were identified based on a match between the promoter regions of these inferred targets and the cis elements recognized by specific regulators. Our analysis also provides evidence for previously unknown inhibitory effects of three positive regulators of gene expression. The Beacon GRN inference tool provides a valuable model system for context-specific GRN inference and is freely available at https://github.com/BeaconProjectAtVirginiaTech/beacon_network_inference.git.

Background: Alternative splicing has been proposed to increase transcript diversity and protein plasticity in eukaryotic organisms, but the extent to which this is the case is currently unclear, especially with regard to the diversification of molecular function. Eukaryotic splicing involves complex interactions of splicing factors and their targets. Inference of co-splicing networks capturing these types of interactions is important for understanding this crucial, highly regulated post-transcriptional process at the systems level., Results: First, several transcript and protein attributes, including coding potential of transcripts and differences in functional domains of proteins, were compared between splice variants and protein isoforms to assess transcript and protein diversity in a biological system. Alternative splicing was shown to increase transcript and function-related protein diversity in developing Arabidopsis embryos. Second, CoSpliceNet, which integrates co-expression and motif discovery at splicing regulatory regions to infer co-splicing networks, was developed. CoSpliceNet was applied to temporal RNA sequencing data to identify candidate regulators of splicing events and predict RNA-binding motifs, some of which are supported by prior experimental evidence. Analysis of inferred splicing factor targets revealed an unexpected role for the unfolded protein response in embryo development., Conclusions: The methods presented here can be used in any biological system to assess transcript diversity and protein plasticity and to predict candidate regulators, their targets, and RNA-binding motifs for splicing factors. CoSpliceNet is freely available at http://delasa.github.io/co-spliceNet/ .

Developing Arabidopsis seeds accumulate oils and seed storage proteins synthesized by the pathways of primary metabolism. Seed development and metabolism are positively regulated by transcription factors belonging to the LAFL (LEC1, AB13, FUSCA3 and LEC2) regulatory network. The VAL gene family encodes repressors of the seed maturation program in germinating seeds, although they are also expressed during seed maturation. The possible regulatory role of VAL1 in seed development has not been studied to date. Reverse genetics revealed that val1 mutant seeds accumulated elevated levels of proteins compared with the wild type, suggesting that VAL1 functions as a repressor of seed metabolism; however, in the absence of VAL1, the levels of metabolites, ABA, auxin and jasmonate derivatives did not change significantly in developing embryos. Two VAL1 splice variants were identified through RNA sequencing analysis: a full-length form and a truncated form lacking the plant homeodomain-like domain associated with epigenetic repression. None of the transcripts encoding the core LAFL network transcription factors were affected in val1 embryos. Instead, activation of VAL1 by FUSCA3 appears to result in the repression of a subset of seed maturation genes downstream of core LAFL regulators, as 39% of transcripts in the FUSCA3 regulon were derepressed in the val1 mutant. The LEC1 and LEC2 regulons also responded, but to a lesser extent. Additional 832 transcripts that were not LAFL targets were derepressed in val1 mutant embryos. These transcripts are candidate targets of VAL1, acting through epigenetic and/or transcriptional repression., (© 2015 The Authors The Plant Journal © 2015 John Wiley & Sons Ltd.)

Background: Transcriptomics reveals the existence of transcripts of different coding potential and strand orientation. Alternative splicing (AS) can yield proteins with altered number and types of functional domains, suggesting the global occurrence of transcriptional and post-transcriptional events. Many biological processes, including seed maturation and desiccation, are regulated post-transcriptionally (e.g., by AS), leading to the production of more than one coding or noncoding sense transcript from a single locus., Results: We present an integrated computational framework to predict isoform-specific functions of plant transcripts. This framework includes a novel plant-specific weighted support vector machine classifier called CodeWise, which predicts the coding potential of transcripts with over 96 % accuracy, and several other tools enabling global sequence similarity, functional domain, and co-expression network analyses. First, this framework was applied to all detected transcripts (103,106), out of which 13 % was predicted by CodeWise to be noncoding RNAs in developing soybean embryos. Second, to investigate the role of AS during soybean embryo development, a population of 2,938 alternatively spliced and differentially expressed splice variants was analyzed and mined with respect to timing of expression. Conserved domain analyses revealed that AS resulted in global changes in the number, types, and extent of truncation of functional domains in protein variants. Isoform-specific co-expression network analysis using ArrayMining and clustering analyses revealed specific sub-networks and potential interactions among the components of selected signaling pathways related to seed maturation and the acquisition of desiccation tolerance. These signaling pathways involved abscisic acid- and FUSCA3-related transcripts, several of which were classified as noncoding and/or antisense transcripts and were co-expressed with corresponding coding transcripts. Noncoding and antisense transcripts likely play important regulatory roles in seed maturation- and desiccation-related signaling in soybean., Conclusions: This work demonstrates how our integrated framework can be implemented to make experimentally testable predictions regarding the coding potential, co-expression, co-regulation, and function of transcripts and proteins related to a biological process of interest.

The development of water stress resistant lines of commercial tomato by breeding or genetic engineering is possible, but will take considerable time before commercial varieties are available for production. However, grafting commercial tomato lines on drought resistant rootstock may produce drought tolerant commercial tomato lines much more rapidly. Due to changing climates and the need for commercial production of vegetables in low quality fields there is an urgent need for stress tolerant commercial lines of vegetables such as tomato. In previous observations we identified a scion root stock combination ('BHN 602' scion grafted onto 'Jjak Kkung' rootstock hereafter identified as 602/Jjak) that had a qualitative drought-tolerance phenotype when compared to the non-grafted line. Based on this initial observation, we studied photosynthesis and vegetative above-ground growth during mild-drought for the 602/Jjak compared with another scion-rootstock combination ('BHN 602' scion grafted onto 'Cheong Gang' rootstock hereafter identified as 602/Cheong) and a non-grafted control. Overall above ground vegetative growth was significantly lower for 602/Jjak in comparison to the other plant lines. Moreover, water potential reduction in response to mild drought was significantly less for 602/Jjak, yet stomatal conductance of all plant-lines were equally inhibited by mild-drought. Light saturated photosynthesis of 602/Jjak was less affected by low water potential than the other two lines as was the % reduction in mesophyll conductance. Therefore, the Jjak Kkung rootstock caused aboveground growth reduction, water conservation and increased photosynthetic tolerance of mild drought. These data show that different rootstocks can change the photosynthetic responses to drought of a high yielding, commercial tomato line. Also, this rapid discovery of one scion-rootstock combination that provided mild-drought tolerance suggests that screening more scion-rootstock combination for stress tolerance may rapidly yield commercially viable, stress tolerant lines of tomato.

Developing soybean seeds accumulate oils, proteins, and carbohydrates that are used as oxidizable substrates providing metabolic precursors and energy during seed germination. The accumulation of these storage compounds in developing seeds is highly regulated at multiple levels, including at transcriptional and post-transcriptional regulation. RNA sequencing was used to provide comprehensive information about transcriptional and post-transcriptional events that take place in developing soybean embryos. Bioinformatics analyses lead to the identification of different classes of alternatively spliced isoforms and corresponding changes in their levels on a global scale during soybean embryo development. Alternative splicing was associated with transcripts involved in various metabolic and developmental processes, including central carbon and nitrogen metabolism, induction of maturation and dormancy, and splicing itself. Detailed examination of selected RNA isoforms revealed alterations in individual domains that could result in changes in subcellular localization of the resulting proteins, protein-protein and enzyme-substrate interactions, and regulation of protein activities. Different isoforms may play an important role in regulating developmental and metabolic processes occurring at different stages in developing oilseed embryos.

Soybean (Glycine max) seeds are an important source of seed storage compounds, including protein, oil, and sugar used for food, feed, chemical, and biofuel production. We assessed detailed temporal transcriptional and metabolic changes in developing soybean embryos to gain a systems biology view of developmental and metabolic changes and to identify potential targets for metabolic engineering. Two major developmental and metabolic transitions were captured enabling identification of potential metabolic engineering targets specific to seed filling and to desiccation. The first transition involved a switch between different types of metabolism in dividing and elongating cells. The second transition involved the onset of maturation and desiccation tolerance during seed filling and a switch from photoheterotrophic to heterotrophic metabolism. Clustering analyses of metabolite and transcript data revealed clusters of functionally related metabolites and transcripts active in these different developmental and metabolic programs. The gene clusters provide a resource to generate predictions about the associations and interactions of unknown regulators with their targets based on "guilt-by-association" relationships. The inferred regulators also represent potential targets for future metabolic engineering of relevant pathways and steps in central carbon and nitrogen metabolism in soybean embryos and drought and desiccation tolerance in plants.

Background: Cold acclimation in woody perennials is a metabolically intensive process, but coincides with environmental conditions that are not conducive to the generation of energy through photosynthesis. While the negative effects of low temperatures on the photosynthetic apparatus during winter have been well studied, less is known about how this is reflected at the level of gene and metabolite expression, nor how the plant generates primary metabolites needed for adaptive processes during autumn., Results: The MapMan tool revealed enrichment of the expression of genes related to mitochondrial function, antioxidant and associated regulatory activity, while changes in metabolite levels over the time course were consistent with the gene expression patterns observed. Genes related to thylakoid function were down-regulated as expected, with the exception of plastid targeted specific antioxidant gene products such as thylakoid-bound ascorbate peroxidase, components of the reactive oxygen species scavenging cycle, and the plastid terminal oxidase. In contrast, the conventional and alternative mitochondrial electron transport chains, the tricarboxylic acid cycle, and redox-associated proteins providing reactive oxygen species scavenging generated by electron transport chains functioning at low temperatures were all active., Conclusions: A regulatory mechanism linking thylakoid-bound ascorbate peroxidase action with "chloroplast dormancy" is proposed. Most importantly, the energy and substrates required for the substantial metabolic remodeling that is a hallmark of freezing acclimation could be provided by heterotrophic metabolism.

Microarray gene expression profiling is a powerful technique to understand complex developmental processes, but making biologically meaningful inferences from such studies has always been challenging. We previously reported a microarray study of the freezing acclimation period in Sitka spruce (Picea sitchensis) in which a large number of candidate genes for climatic adaptation were identified. In the current paper, we apply additional systems biology tools to these data to further probe changes in the levels of genes and metabolites and activities of associated pathways that regulate this complex developmental transition. One aspect of this adaptive process that is not well understood is the role of the cell wall. Our data suggest coordinated metabolic and signaling responses leading to cell wall remodeling. Co-expression of genes encoding proteins associated with biosynthesis of structural and non-structural cell wall carbohydrates was observed, which may be regulated by ethylene signaling components. At the same time, numerous genes, whose products are putatively localized to the endomembrane system and involved in both the synthesis and trafficking of cell wall carbohydrates, were up-regulated. Taken together, these results suggest a link between ethylene signaling and biosynthesis, and targeting of cell wall related gene products during the period of winter hardening. Automated Layout Pipeline for Inferred NEtworks (ALPINE), an in-house plugin for the Cytoscape visualization environment that utilizes the existing GeneMANIA and Mosaic plugins, together with the use of visualization tools, provided images of proposed signaling processes that became active over the time course of winter hardening, particularly at later time points in the process. The resulting visualizations have the potential to reveal novel, hypothesis-generating, gene association patterns in the context of targeted subcellular location.

Drought stress affects cereals especially during the reproductive stage. The maize (Zea mays) drought transcriptome was studied using RNA-Seq analysis to compare drought-treated and well-watered fertilized ovary and basal leaf meristem tissue. More drought-responsive genes responded in the ovary compared with the leaf meristem. Gene Ontology enrichment analysis revealed a massive decrease in transcript abundance of cell division and cell cycle genes in the drought-stressed ovary only. Among Gene Ontology categories related to carbohydrate metabolism, changes in starch and Suc metabolism-related genes occurred in the ovary, consistent with a decrease in starch levels, and in Suc transporter function, with no comparable changes occurring in the leaf meristem. Abscisic acid (ABA)-related processes responded positively, but only in the ovaries. Related responses suggested the operation of low glucose sensing in drought-stressed ovaries. The data are discussed in the context of the susceptibility of maize kernel to drought stress leading to embryo abortion and the relative robustness of dividing vegetative tissue taken at the same time from the same plant subjected to the same conditions. Our working hypothesis involves signaling events associated with increased ABA levels, decreased glucose levels, disruption of ABA/sugar signaling, activation of programmed cell death/senescence through repression of a phospholipase C-mediated signaling pathway, and arrest of the cell cycle in the stressed ovary at 1 d after pollination. Increased invertase levels in the stressed leaf meristem, on the other hand, resulted in that tissue maintaining hexose levels at an "unstressed" level, and at lower ABA levels, which was correlated with successful resistance to drought stress.

Massive amounts of transcriptomic data documenting plant responses to changes in environment continue to accumulate in online databases. Unfortunately, many of these data sets have not been analyzed in full detail, especially those that involve time course experiments. To gain more knowledge of the successive gene expression events that occur when stress is initiated in one organ and then relayed to another, we have chosen stress response data for Arabidopsis shoots and roots from the detailed time course study of Killian et al. as a promising source to mine. Using refined statistical analysis, modified vector analysis, and a GO enrichment algorithm, more information was revealed concerning the effects of salt and UVB on gene expression events in shoots and roots over a 24-h time period. GeneMania, with in-house modifications, was used to further analyze abscisic acid (ABA) and jasmonic acid-related (JA) gene expression events in salt-stressed roots and shoots. JA effects appeared to be quite distinct in roots when compared to shoots, especially with respect to the expression of members of the negative regulatory JAZ gene family. In contrast, ABA-related gene expression events were more similar in the two organs. Instances of crosstalk between hormones were observed, as were early responses of regulatory genes involved in both auxin and cytokinin signaling. In the case of each hormone class examined, hormone biosynthesis genes were coexpressed with the genes encoding negative regulators of the corresponding signaling pathway. Hypotheses to explain this finding and future experiments to further explore these nonlinear phenomena are proposed.

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services.

Heat shock proteins (HSPs) are induced not only under heat stress conditions but also under other environmental stresses such as water stress. In plants, HSPs families are larger than those of other eukaryotes. In order to elucidate a possible connection between HSP expression and photosynthetic acclimation or conditioning, we conducted a water stress experiment in loblolly pine (Pinus taeda L.) seedlings involving progressive treatment consisting of one cycle of mild stress (-1 MPa) followed by two cycles of severe stress (-1.7 MPa). Net photosynthesis was measured at each stress level. Photosynthetic acclimation occurred in the progressive treatment after the first cycle, but not in the severe treatment, suggesting that a cycle of mild stress conditioned the trees to adapt to a more severe stress. Real time results indicated specific patterns in needles in the expression of HSP70, HSP90 and sHSP genes for each treatment, both at maximum stress and at recovery. We identified a pine homolog to GRP94 (ER resident HSP90) that was induced after rehydration coincident with acclimation. Further analysis of the promoter region of the pine GRP94 showed putative cis-elements associated with water stress and rehydration, corresponding to the expression pattern observed in our experiment., (Copyright 2010 Elsevier Masson SAS. All rights reserved.)

Responses to prolonged drought and recovery from drought of two South American potato (Solanum tuberosum L. ssp. andigena (Juz & Buk) Hawkes) landraces, Sullu and Ccompis were compared under field conditions. Physiological and biomass measurements, yield analysis, the results of hybridisation to a potato microarray platform (44 000 probes) and metabolite profiling were used to characterise responses to water deficit. Drought affected shoot and root biomass negatively in Ccompis but not in Sullu, whereas both genotypes maintained tuber yield under water stress. Ccompis showed stronger reduction in maximum quantum yield under stress than Sullu, and less decrease in stomatal resistance. Genes associated with PSII functions were activated during recovery in Sullu only. Evidence for sucrose accumulation in Sullu only during maximum stress and recovery was observed, in addition to increases in cell wall biosynthesis. A depression in the abundance of plastid superoxide dismutase transcripts was observed under maximum stress in Ccompis. Both sucrose and the regulatory molecule trehalose accumulated in the leaves of Sullu only. In contrast, in Ccompis, the raffinose oligosaccharide family pathway was activated, whereas low levels of sucrose and minor stress-mediated changes in trehalose were observed. Proline, and expression of the associated genes, rose in both genotypes under drought, with a 3-fold higher increase in Sullu than in Ccompis. The results demonstrate the presence of distinct molecular and biochemical drought responses in the two potato landraces leading to yield maintenance but differential biomass accumulation in vegetative tissues.

The drought stress tolerance of two Solanum tuberosum subsp. andigena landraces, one hybrid (adgxtbr) and Atlantic (S. tuberosum subsp. tuberosum) has been evaluated. Photosynthesis in the Andigena landraces during prolonged drought was maintained significantly longer than in the Tuberosum (Atlantic) line. Among the Andigena landraces, 'Sullu' (SUL) was more drought resistant than 'Negra Ojosa' (NOJ). Microarray analysis and metabolite data from leaf samples taken at the point of maximum stress suggested higher mitochondrial metabolic activity in SUL than in NOJ. A greater induction of chloroplast-localized antioxidant and chaperone genes in SUL compared with NOJ was evident. ABA-responsive TFs were more induced in NOJ compared with SUL, including WRKY1, mediating a response in SA signalling that may give rise to increased ROS. NOJ may be experiencing higher ROS levels than SUL. Metabolite profiles of NOJ were characterized by compounds indicative of stress, for example, proline, trehalose, and GABA, which accumulated to a higher degree than in SUL. The differences between the Andigena lines were not explained by protective roles of compatible solutes; hexoses and complex sugars were similar in both landraces. Instead, lower levels of ROS accumulation, greater mitochondrial activity and active chloroplast defences contributed to a lower stress load in SUL than in NOJ during drought.

A drought screen identified accessions of Solanum tuberosum ssp. andigena that showed varying degrees of physiological acclimation or adaptation to repeated drought stress. The accessions also showed variable tuber phenotypes from small tubers that failed to develop in an accession that showed photosynthetic adaptation to normal tubers in an accession with a phenotype showing some degree of photosynthetic adaptation and acclimation. Using microarray data, we correlated the expression of genes associated with carbon metabolism with the tuber development phenotypes under drought. Genes associated with sucrose and starch metabolism showed responses consistent with starch deficiency in the adapted accession and normal starch deposition in the intermediate accession. Starch phosphorylase and glycogen bound starch synthase were induced in the adapted accession, which had abnormal tuber development. Genes associated with trehalose were induced in the intermediate accession with normal tuber development. Genes associated with respiration were also induced in the intermediate accession, and a pattern compatible with the existence of a 3PGA recovery pathway was revealed. Expression of thioredoxin genes also correlated with tuber development phenotypes under drought stress. The data suggest differential regulation of starch deposition in accessions of Andigena with different abilities to respond to drought stress.

Phospholipase D (PLD) has been implicated in a variety of stresses including osmotic stress and wounding. PLDalpha1-derived phosphatidic acid interacts with ABI1 phosphatase 2C and promotes abscisic acid signalling. It has also been shown to regulate proline biosynthesis negatively. Plants with abrogated PLDalpha show insensitivity to abscisic acid (ABA) and impaired stomatal conductance. The goal in the present study was to identify early PLDalpha-mediated events in response to progressive drought stress in Arabidopsis. Water was withheld from 7-week-old Arabidopsis thaliana (Col-0) and antisense-PLDalpha1 (anti-PLDalpha) in a controlled environment chamber. Diurnal leaf water potential (LWP) and photosynthesis measurements were recorded five and three times a day, respectively. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and microarray analyses were conducted using RNA from shoots collected at the fourth LWP time point on the ninth day after stress imposition. Anti-PLDalpha experienced severe water stress (-1.28 MPa) at the same time period that Col-0 experienced less water stress (-0.31 MPa). Diurnal LWP measurements showed that anti-PLDalpha had a lower LWP than Col-0 in both control and drought-stress conditions. Photosynthesis was also more affected in anti-PLDalpha than in Col-0. Anti-PLDalpha plants recovered fully following rehydration after 10 d of stress. qRT-PCR revealed up to 18-fold lower values for PLDalpha transcripts in stressed anti-PLDalpha plants when compared with stressed Col-0. Microarray expression profiles revealed distinct gene expression patterns in Col-0 and anti-PLDalpha. No differences in gene expression were detected between the two genotypes in the absence of drought stress. ROP8, PLDdelta, and lipid transfer proteins were among the differentially expressed genes between the two genotypes.

Free Air [CO(2)] Enrichment (FACE) allows for plant growth under fully open-air conditions of elevated [CO(2)] at concentrations expected to be reached by mid-century. We used Arabidopsis thaliana ecotypes Col-0, Cvi-0, and WS to analyze changes in gene expression and metabolite profiles of plants grown in "SoyFACE" (http://www.soyface.uiuc.edu/), a system of open-air rings within which [CO(2)] is elevated to approximately 550 ppm. Data from multiple rings, comparing plants in ambient air and elevated [CO(2)], were analyzed by mixed model ANOVA, linear discriminant analysis (LDA) and data-mining tools. In elevated [CO(2)], decreases in the expression of genes related to chloroplast functions characterized all lines but individual members of distinct multi-gene families were regulated differently between lines. Also, different strategies distinguished the lines with respect to the regulation of genes related to carbohydrate biosynthesis and partitioning, N-allocation and amino acid metabolism, cell wall biosynthesis, and hormone responses, irrespective of the plants' developmental status. Metabolite results paralleled reactions seen at the level of transcript expression. Evolutionary adaptation of species to their habitat and intrinsic genetic plasticity seem to determine the nature of responses to elevated [CO(2)]. Irrespective of their underlying genetic diversity, and evolutionary adaptation to different habitats, a small number of common, predominantly stress-responsive, signature transcripts appear to characterize responses of the Arabidopsis ecotypes in FACE.