Extensive signal integration by the phytohormone protein network.

Plant hormones coordinate responses to environmental cues with developmental programs1, and are fundamental for stress resilience and agronomic yield2. The core signalling pathways underlying the effects of phytohormones have been elucidated by genetic screens and hypothesis-driven approaches, and extended by interactome studies of select pathways3. However, fundamental questions remain about how information from different pathways is integrated. Genetically, most phenotypes seem to be regulated by several hormones, but transcriptional profiling suggests that hormones trigger largely exclusive transcriptional programs4. We hypothesized that protein-protein interactions have an important role in phytohormone signal integration. Here, we experimentally generated a systems-level map of the Arabidopsis phytohormone signalling network, consisting of more than 2,000 binary protein-protein interactions. In the highly interconnected network, we identify pathway communities and hundreds of previously unknown pathway contacts that represent potential points of crosstalk. Functional validation of candidates in seven hormone pathways reveals new functions for 74% of tested proteins in 84% of candidate interactions, and indicates that a large majority of signalling proteins function pleiotropically in several pathways. Moreover, we identify several hundred largely small-molecule-dependent interactions of hormone receptors. Comparison with previous reports suggests that noncanonical and nontranscription-mediated receptor signalling is more common than hitherto appreciated.

Publisher Correction: Extensive signal integration by the phytohormone protein network.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genome sequence of the progenitor of the wheat D genome Aegilops tauschii.

Aegilops tauschii is the diploid progenitor of the D genome of hexaploid wheat (Triticum aestivum, genomes AABBDD) and an important genetic resource for wheat. The large size and highly repetitive nature of the Ae. tauschii genome has until now precluded the development of a reference-quality genome sequence. Here we use an array of advanced technologies, including ordered-clone genome sequencing, whole-genome shotgun sequencing, and BioNano optical genome mapping, to generate a reference-quality genome sequence for Ae. tauschii ssp. strangulata accession AL8/78, which is closely related to the wheat D genome. We show that compared to other sequenced plant genomes, including a much larger conifer genome, the Ae. tauschii genome contains unprecedented amounts of very similar repeated sequences. Our genome comparisons reveal that the Ae. tauschii genome has a greater number of dispersed duplicated genes than other sequenced genomes and its chromosomes have been structurally evolving an order of magnitude faster than those of other grass genomes. The decay of colinearity with other grass genomes correlates with recombination rates along chromosomes. We propose that the vast amounts of very similar repeated sequences cause frequent errors in recombination and lead to gene duplications and structural chromosome changes that drive fast genome evolution.

The Systems Architecture of Molecular Memory in Poplar after Abiotic Stress.

Throughout the temperate zones, plants face combined drought and heat spells in increasing frequency and intensity. Here, we compared periodic (intermittent, i.e., high-frequency) versus chronic (continuous, i.e., high-intensity) drought-heat stress scenarios in gray poplar (Populus× canescens) plants for phenotypic and transcriptomic effects during stress and after recovery. Photosynthetic productivity after stress recovery exceeded the performance of poplar trees without stress experience. We analyzed the molecular basis of this stress-related memory phenotype and investigated gene expression responses across five major tree compartments including organs and wood tissues. For each of these tissue samples, transcriptomic changes induced by the two stress scenarios were highly similar during the stress phase but strikingly divergent after recovery. Characteristic molecular response patterns were found across tissues but involved different genes in each tissue. Only a small fraction of genes showed similar stress and recovery expression profiles across all tissues, including type 2C protein phosphatases, the LATE EMBRYOGENESIS ABUNDANT PROTEIN4-5 genes, and homologs of the Arabidopsis (Arabidopsis thaliana) transcription factor HOMEOBOX7. Analysis of the predicted transcription factor regulatory networks for these genes suggested that a complex interplay of common and tissue-specific components contributes to the coordination of post-recovery responses to stress in woody plants.

Brassinosteroids participate in the control of basal and acquired freezing tolerance of plants.

Brassinosteroids (BRs) are growth-promoting plant hormones that play a role in abiotic stress responses, but molecular modes that enable this activity remain largely unknown. Here we show that BRs participate in the regulation of freezing tolerance. BR signaling-defective mutants of Arabidopsis thaliana were hypersensitive to freezing before and after cold acclimation. The constitutive activation of BR signaling, in contrast, enhanced freezing resistance. Evidence is provided that the BR-controlled basic helix-loop-helix transcription factor CESTA (CES) can contribute to the constitutive expression of the C-REPEAT/DEHYDRATION-RESPONSIVE ELEMENT BINDING FACTOR (CBF) transcriptional regulators that control cold responsive (COR) gene expression. In addition, CBF-independent classes of BR-regulated COR genes are identified that are regulated in a BR- and CES-dependent manner during cold acclimation. A model is presented in which BRs govern different cold-responsive transcriptional cascades through the posttranslational modification of CES and redundantly acting factors. This contributes to the basal resistance against freezing stress, but also to the further improvement of this resistance through cold acclimation.

Brassinosteroids Are Master Regulators of Gibberellin Biosynthesis in Arabidopsis.

Plant growth and development are highly regulated processes that are coordinated by hormones including the brassinosteroids (BRs), a group of steroids with structural similarity to steroid hormones of mammals. Although it is well understood how BRs are produced and how their signals are transduced, BR targets, which directly confer the hormone's growth-promoting effects, have remained largely elusive. Here, we show that BRs regulate the biosynthesis of gibberellins (GAs), another class of growth-promoting hormones, in Arabidopsis thaliana. We reveal that Arabidopsis mutants deficient in BR signaling are severely impaired in the production of bioactive GA, which is correlated with defective GA biosynthetic gene expression. Expression of the key GA biosynthesis gene GA20ox1 in the BR signaling mutant bri1-301 rescues many of its developmental defects. We provide evidence that supports a model in which the BR-regulated transcription factor BES1 binds to a regulatory element in promoters of GA biosynthesis genes in a BR-induced manner to control their expression. In summary, our study underscores a role of BRs as master regulators of GA biosynthesis and shows that this function is of major relevance for the growth and development of vascular plants.

PGSB PlantsDB: updates to the database framework for comparative plant genome research.

PGSB (Plant Genome and Systems Biology: formerly MIPS) PlantsDB (http://pgsb.helmholtz-muenchen.de/plant/index.jsp) is a database framework for the comparative analysis and visualization of plant genome data. The resource has been updated with new data sets and types as well as specialized tools and interfaces to address user demands for intuitive access to complex plant genome data. In its latest incarnation, we have re-worked both the layout and navigation structure and implemented new keyword search options and a new BLAST sequence search functionality. Actively involved in corresponding sequencing consortia, PlantsDB has dedicated special efforts to the integration and visualization of complex triticeae genome data, especially for barley, wheat and rye. We enhanced CrowsNest, a tool to visualize syntenic relationships between genomes, with data from the wheat sub-genome progenitor Aegilops tauschii and added functionality to the PGSB RNASeqExpressionBrowser. GenomeZipper results were integrated for the genomes of barley, rye, wheat and perennial ryegrass and interactive access is granted through PlantsDB interfaces. Data exchange and cross-linking between PlantsDB and other plant genome databases is stimulated by the transPLANT project (http://transplantdb.eu/).

Ribosome quality control is a central protection mechanism for yeast exposed to deoxynivalenol and trichothecin.

BACKGROUND: The trichothecene mycotoxins deoxynivalenol (DON) and trichothecin (TTC) are inhibitors of eukaryotic protein synthesis. Their effect on cellular homeostasis is poorly understood. We report a systematic functional investigation of the effect of DON and TTC on the yeast Saccharomyces cerevisiae using genetic array, network and microarray analysis. To focus the genetic analysis on intracellular consequences of toxin action we eliminated the PDR5 gene coding for a potent pleiotropic drug efflux protein potentially confounding results. We therefore used a knockout library with a pdr5Δ strain background. RESULTS: DON or TTC treatment creates a fitness bottleneck connected to ribosome efficiency. Genes isolated by systematic genetic array analysis as contributing to toxin resistance function in ribosome quality control, translation fidelity, and in transcription. Mutants in the E3 ligase Hel2, involved in ribosome quality control, and several members of the Rpd3 histone deacetylase complex were highly sensitive to DON. DON and TTC have similar genetic profiles despite their different toxic potency. Network analysis shows a coherent and tight network of genetic interactions among the DON and TTC resistance conferring gene products. The networks exhibited topological properties commonly associated with efficient processing of information. Many sensitive mutants have a "slow growth" gene expression signature. DON-exposed yeast cells increase transcripts of ribosomal protein and histone genes indicating an internal signal for growth enhancement. CONCLUSIONS: The combination of gene expression profiling and analysis of mutants reveals cellular pathways which become bottlenecks under DON and TTC stress. These are generally directly or indirectly connected to ribosome biosynthesis such as the general secretory pathway, cytoskeleton, cell cycle delay, ribosome synthesis and translation quality control. Gene expression profiling points to an increased demand of ribosomal components and does not reveal activation of stress pathways. Our analysis highlights ribosome quality control and a contribution of a histone deacetylase complex as main sources of resistance against DON and TTC.

Reticulate evolution of the rye genome.

Rye (Secale cereale) is closely related to wheat (Triticum aestivum) and barley (Hordeum vulgare). Due to its large genome (~8 Gb) and its regional importance, genome analysis of rye has lagged behind other cereals. Here, we established a virtual linear gene order model (genome zipper) comprising 22,426 or 72% of the detected set of 31,008 rye genes. This was achieved by high-throughput transcript mapping, chromosome survey sequencing, and integration of conserved synteny information of three sequenced model grass genomes (Brachypodium distachyon, rice [Oryza sativa], and sorghum [Sorghum bicolor]). This enabled a genome-wide high-density comparative analysis of rye/barley/model grass genome synteny. Seventeen conserved syntenic linkage blocks making up the rye and barley genomes were defined in comparison to model grass genomes. Six major translocations shaped the modern rye genome in comparison to a putative Triticeae ancestral genome. Strikingly dissimilar conserved syntenic gene content, gene sequence diversity signatures, and phylogenetic networks were found for individual rye syntenic blocks. This indicates that introgressive hybridizations (diploid or polyploidy hybrid speciation) and/or a series of whole-genome or chromosome duplications played a role in rye speciation and genome evolution.

TopKLists: a comprehensive R package for statistical inference, stochastic aggregation, and visualization of multiple omics ranked lists.

High-throughput sequencing techniques are increasingly affordable and produce massive amounts of data. Together with other high-throughput technologies, such as microarrays, there are an enormous amount of resources in databases. The collection of these valuable data has been routine for more than a decade. Despite different technologies, many experiments share the same goal. For instance, the aims of RNA-seq studies often coincide with those of differential gene expression experiments based on microarrays. As such, it would be logical to utilize all available data. However, there is a lack of biostatistical tools for the integration of results obtained from different technologies. Although diverse technological platforms produce different raw data, one commonality for experiments with the same goal is that all the outcomes can be transformed into a platform-independent data format - rankings - for the same set of items. Here we present the R package TopKLists, which allows for statistical inference on the lengths of informative (top-k) partial lists, for stochastic aggregation of full or partial lists, and for graphical exploration of the input and consolidated output. A graphical user interface has also been implemented for providing access to the underlying algorithms. To illustrate the applicability and usefulness of the package, we integrated microRNA data of non-small cell lung cancer across different measurement techniques and draw conclusions. The package can be obtained from CRAN under a LGPL-3 license.

RNASeqExpressionBrowser--a web interface to browse and visualize high-throughput expression data.

MOTIVATION: RNA-seq techniques generate massive amounts of expression data. Several pipelines (e.g. Tophat and Cufflinks) are broadly applied to analyse these datasets. However, accessing and handling the analytical output remain challenging for non-experts. RESULTS: We present the RNASeqExpressionBrowser, an open-source web interface that can be used to access the output from RNA-seq expression analysis packages in different ways, as it allows browsing for genes by identifiers, annotations or sequence similarity. Gene expression information can be loaded as long as it is represented in a matrix-like format. Additionally, data can be made available by setting up the tool on a public server. For demonstration purposes, we have set up a version providing expression information from the barley genome. AVAILABILITY AND IMPLEMENTATION: The source code and a show case are accessible at http://mips.helmholtz-muenchen.de/plant/RNASeqExpressionBrowser/.

Bacteria-triggered systemic immunity in barley is associated with WRKY and ETHYLENE RESPONSIVE FACTORs but not with salicylic acid.

Leaf-to-leaf systemic immune signaling known as systemic acquired resistance is poorly understood in monocotyledonous plants. Here, we characterize systemic immunity in barley (Hordeum vulgare) triggered after primary leaf infection with either Pseudomonas syringae pathovar japonica (Psj) or Xanthomonas translucens pathovar cerealis (Xtc). Both pathogens induced resistance in systemic, uninfected leaves against a subsequent challenge infection with Xtc. In contrast to systemic acquired resistance in Arabidopsis (Arabidopsis thaliana), systemic immunity in barley was not associated with NONEXPRESSOR OF PATHOGENESIS-RELATED GENES1 or the local or systemic accumulation of salicylic acid. Instead, we documented a moderate local but not systemic induction of abscisic acid after infection of leaves with Psj. In contrast to salicylic acid or its functional analog benzothiadiazole, local applications of the jasmonic acid methyl ester or abscisic acid triggered systemic immunity to Xtc. RNA sequencing analysis of local and systemic transcript accumulation revealed unique gene expression changes in response to both Psj and Xtc and a clear separation of local from systemic responses. The systemic response appeared relatively modest, and quantitative reverse transcription-polymerase chain reaction associated systemic immunity with the local and systemic induction of two WRKY and two ETHYLENE RESPONSIVE FACTOR (ERF)-like transcription factors. Systemic immunity against Xtc was further associated with transcriptional changes after a secondary/systemic Xtc challenge infection; these changes were dependent on the primary treatment. Taken together, bacteria-induced systemic immunity in barley may be mediated in part by WRKY and ERF-like transcription factors, possibly facilitating transcriptional reprogramming to potentiate immunity.

Genetic analysis of DEFECTIVE KERNEL1 loop function in three-dimensional body patterning in Physcomitrella patens.

DEFECTIVE KERNEL1 (DEK1) of higher plants plays an essential role in position-dependent signaling and consists of a large transmembrane domain (MEM) linked to a protease catalytic domain and a regulatory domain. Here, we show that the postulated sensory Loop of the MEM domain plays an important role in the developmental regulation of DEK1 activity in the moss Physcomitrella patens. Compared with P. patens lacking DEK1 (∆dek1), the dek1∆loop mutant correctly positions the division plane in the bud apical cell. In contrast with an early developmental arrest of ∆dek1 buds, dek1∆loop develops aberrant gametophores lacking expanded phyllids resulting from misregulation of mitotic activity. In contrast with the highly conserved sequence of the protease catalytic domain, the Loop is highly variable in land plants. Functionally, the sequence from Marchantia polymorpha fully complements the dek1∆loop phenotype, whereas sequences from maize (Zea mays) and Arabidopsis (Arabidopsis thaliana) give phenotypes with retarded growth and affected phyllid development. Bioinformatic analysis identifies MEM as a member of the Major Facilitator Superfamily, membrane transporters reacting to stimuli from the external environment. Transcriptome analysis comparing wild-type and ∆dek1 tissues identifies an effect on two groups of transcripts connected to dek1 mutant phenotypes: transcripts related to cell wall remodeling and regulation of the AINTEGUMENTA, PLETHORA, and BABY BOOM2 (APB2) and APB3 transcription factors known to regulate bud initiation. Finally, sequence data support the hypothesis that the advanced charophyte algae that evolved into ancestral land plants lost cytosolic calpains, retaining DEK1 as the sole calpain in the evolving land plant lineage.

chromoWIZ: a web tool to query and visualize chromosome-anchored genes from cereal and model genomes.

BACKGROUND: Over the last years reference genome sequences of several economically and scientifically important cereals and model plants became available. Despite the agricultural significance of these crops only a small number of tools exist that allow users to inspect and visualize the genomic position of genes of interest in an interactive manner. DESCRIPTION: We present chromoWIZ, a web tool that allows visualizing the genomic positions of relevant genes and comparing these data between different plant genomes. Genes can be queried using gene identifiers, functional annotations, or sequence homology in four grass species (Triticum aestivum, Hordeum vulgare, Brachypodium distachyon, Oryza sativa). The distribution of the anchored genes is visualized along the chromosomes by using heat maps. Custom gene expression measurements, differential expression information, and gene-to-group mappings can be uploaded and can be used for further filtering. CONCLUSIONS: This tool is mainly designed for breeders and plant researchers, who are interested in the location and the distribution of candidate genes as well as in the syntenic relationships between different grass species. chromoWIZ is freely available and online accessible at http://mips.helmholtz-muenchen.de/plant/chromoWIZ/index.jsp.

Quantitative trait loci-dependent analysis of a gene co-expression network associated with Fusarium head blight resistance in bread wheat (Triticum aestivum L.).

BACKGROUND: Fusarium head blight (FHB) caused by Fusarium graminearum Schwabe is one of the most prevalent diseases of wheat (Triticum aestivum L.) and other small grain cereals. Resistance against the fungus is quantitative and more than 100 quantitative trait loci (QTL) have been described. Two well-validated and highly reproducible QTL, Fhb1 and Qfhs.ifa-5A have been widely investigated, but to date the underlying genes have not been identified. RESULTS: We have investigated a gene co-expression network activated in response to F. graminearum using RNA-seq data from near-isogenic lines, harboring either the resistant or the susceptible allele for Fhb1 and Qfhs.ifa-5A. The network identified pathogen-responsive modules, which were enriched for differentially expressed genes between genotypes or different time points after inoculation with the pathogen. Central gene analysis identified transcripts associated with either QTL within the network. Moreover, we present a detailed gene expression analysis of four gene families (glucanases, NBS-LRR, WRKY transcription factors and UDP-glycosyltransferases), which take prominent roles in the pathogen response. CONCLUSIONS: A combination of a network-driven approach and differential gene expression analysis identified genes and pathways associated with Fhb1 and Qfhs.ifa-5A. We find G-protein coupled receptor kinases and biosynthesis genes for jasmonate and ethylene earlier induced for Fhb1. Similarly, we find genes involved in the biosynthesis and metabolism of riboflavin more abundant for Qfhs.ifa-5A.

Serum-autoantibodies for discovery of prostate cancer specific biomarkers.

BACKGROUND: The currently used prostate cancer serum marker has a low cancer specificity and improved diagnostics are needed. Here we evaluated whether autoantibodies are present in sera of prostate cancer patients and whether they are useful diagnostic markers for prostate cancer. METHODS: Sera from 20 prostate cancer patients and 20 healthy controls were incubated on expression clone arrays containing more than 37,000 recombinant human proteins. Functional annotation clustering of the identified autoantigens was performed using the DAVID database. Autoantigens identified in the prostate cancer group were validated on microarrays using sera of 40 prostate cancer patients, 40 patients with elevated PSA levels but prostate cancer negative biopsies (benign disease), and 40 healthy controls. RESULTS: We detected autoantibodies against 408 different antigens in sera of prostate cancer patients. One hundred seventy-four of these were exclusively detected in the cancer group compared to the healthy control group. Functional annotation clustering revealed an enrichment of RNA-associated, cytoskeleton, and nuclear proteins. The autoantibody panel was validated in serum samples of independent prostate cancer patients. Autoantibody profiles discriminated between prostate cancer patients and benign disease patients with an ROC curve AUC of 0.71. TTLL12, a protein recently described to be over-expressed in prostate cancer, was the highest ranked discrimination autoantigen. CONCLUSION: A variety of autoantibodies were identified in sera of prostate cancer patients and provide a first step towards autoantibody diagnostics. Serum autoantibodies reflect the disease and represent valuable tools not only for prostate cancer, but also for other diseases affecting the immune response.

QuACN: an R package for analyzing complex biological networks quantitatively.

MOTIVATION: Network-based representations of biological data have become an important way to analyze high-throughput data. To interpret the large amount of data that is produced by different high-throughput technologies, networks offer multifaceted aspects to analyze the data. As networks represent biological relationships within their structure, it turned out to be fruitful to analyze their topology. Therefore, we developed a freely available, open source R-package called Quantitative Analysis of Complex Networks (QuACN) to meet this challenge. QuACN contains different, information-theoretic and non-information-theoretic, topological network descriptors to analyze, classify and compare biological networks. AVAILABILITY: QuACN is freely available under LGPL via CRAN (http://cran.r-project.org/web/packages/QuACN/).

A network-based feature selection approach to identify metabolic signatures in disease.

The identification and interpretation of metabolic biomarkers is a challenging task. In this context, network-based approaches have become increasingly a key technology in systems biology allowing to capture complex interactions in biological systems. In this work, we introduce a novel network-based method to identify highly predictive biomarker candidates for disease. First, we infer two different types of networks: (i) correlation networks, and (ii) a new type of network called ratio networks. Based on these networks, we introduce scores to prioritize features using topological descriptors of the vertices. To evaluate our method we use an example dataset where quantitative targeted MS/MS analysis was applied to a total of 52 blood samples from 22 persons with obesity (BMI >30) and 30 healthy controls. Using our network-based feature selection approach we identified highly discriminating metabolites for obesity (F-score >0.85, accuracy >85%), some of which could be verified by the literature.

Structural measures for network biology using QuACN.

BACKGROUND: Structural measures for networks have been extensively developed, but many of them have not yet demonstrated their sustainably. That means, it remains often unclear whether a particular measure is useful and feasible to solve a particular problem in network biology. Exemplarily, the classification of complex biological networks can be named, for which structural measures are used leading to a minimal classification error. Hence, there is a strong need to provide freely available software packages to calculate and demonstrate the appropriate usage of structural graph measures in network biology. RESULTS: Here, we discuss topological network descriptors that are implemented in the R-package QuACN and demonstrate their behavior and characteristics by applying them to a set of example graphs. Moreover, we show a representative application to illustrate their capabilities for classifying biological networks. In particular, we infer gene regulatory networks from microarray data and classify them by methods provided by QuACN. Note that QuACN is the first freely available software written in R containing a large number of structural graph measures. CONCLUSION: The R package QuACN is under ongoing development and we add promising groups of topological network descriptors continuously. The package can be used to answer intriguing research questions in network biology, e.g., classifying biological data or identifying meaningful biological features, by analyzing the topology of biological networks.

The impact of storage effects in biobanks on biomarker discovery in systems biology studies.

Sample handling and storage conditions in specimens frozen over long periods of time can severely impact marker levels. If laboratory technologies, practices and related protocols change over time, biomarker studies are potentially biased and report erroneous results. These issues and pitfalls are often overlooked in system biology studies using previously collected and stored materials, and are likely to be one notable cause for biomarker candidates failing to be validated. We present results from simulation studies quantifying the loss in statistical power to detect true biomarkers, due to diminishing concentration of analytes in samples subject to poor handling and storage conditions.