Direct and indirect responses of the Arabidopsis transcriptome to an induced increase in trehalose 6-phosphate.

Trehalose 6-phosphate (Tre6P) is an essential signal metabolite that regulates the level of sucrose, linking growth and development to the metabolic status. We hypothesized that Tre6P plays a role in mediating the regulation of gene expression by sucrose. To test this, we performed transcriptomic profiling on Arabidopsis (Arabidopsis thaliana) plants that expressed a bacterial TREHALOSE 6-PHOSPHATE SYNTHASE (TPS) under the control of an ethanol-inducible promoter. Induction led to a 4-fold rise in Tre6P levels, a concomitant decrease in sucrose, significant changes (FDR ≤ 0.05) of over 13,000 transcripts, and two-fold or larger changes of over 5000 transcripts. Comparison with nine published responses to sugar availability allowed some of these changes to be linked to the rise in Tre6P, while others were probably due to lower sucrose or other indirect effects. Changes linked to Tre6P included repression of photosynthesis-related gene expression and induction of many growth-related processes including ribosome biogenesis. About 500 starvation-related genes are known to be induced by SUCROSE-NON-FERMENTING-1-RELATED KINASE 1 (SnRK1). They were largely repressed by Tre6P in a manner consistent with SnRK1 inhibition by Tre6P. SnRK1 also represses many genes that are involved in biosynthesis and growth. These responded to Tre6P in a more complex manner, pointing toward Tre6P interacting with other C-signaling pathways. Additionally, elevated Tre6P modified the expression of genes encoding regulatory subunits of the SnRK1 complex and TPS class II and FCS-LIKE ZINC FINGER proteins that are thought to modulate SnRK1 function and genes involved in circadian, TARGET OF RAPAMYCIN-, light, abscisic acid, and other hormone signaling.

Exploiting Natural Variation in Tomato to Define Pathway Structure and Metabolic Regulation of Fruit Polyphenolics in the Lycopersicum Complex.

While the structures of plant primary metabolic pathways are generally well defined and highly conserved across species, those defining specialized metabolism are less well characterized and more highly variable across species. In this study, we investigated polyphenolic metabolism in the lycopersicum complex by characterizing the underlying biosynthetic and decorative reactions that constitute the metabolic network of polyphenols across eight different species of tomato. For this purpose, GC-MS- and LC-MS-based metabolomics of different tissues of Solanum lycopersicum and wild tomato species were carried out, in concert with the evaluation of cross-hybridized microarray data for MapMan-based transcriptomic analysis, and publicly available RNA-sequencing data for annotation of biosynthetic genes. The combined data were used to compile species-specific metabolic networks of polyphenolic metabolism, allowing the establishment of an entire pan-species biosynthetic framework as well as annotation of the functions of decoration enzymes involved in the formation of metabolic diversity of the flavonoid pathway. The combined results are discussed in the context of the current understanding of tomato flavonol biosynthesis as well as a global view of metabolic shifts during fruit ripening. Our results provide an example as to how large-scale biology approaches can be used for the definition and refinement of large specialized metabolism pathways.

Aclonifen targets solanesyl diphosphate synthase, representing a novel mode of action for herbicides.

BACKGROUND: Aclonifen is a unique diphenyl ether herbicide. Despite its structural similarities to known inhibitors of the protoporphyrinogen oxidase (e.g. acifluorfen, bifenox or oxadiazon), which result in leaf necrosis, aclonifen causes a different phenotype that is described as bleaching. This also is reflected by the Herbicide Resistance Action Committee (HRAC) classification that categorizes aclonifen as an inhibitor of pigment biosynthesis with an unknown target. RESULTS: A comprehensive Arabidopsis thaliana RNAseq dataset comprising 49 different inhibitor treatments and covering 40 known target pathways was used to predict the aclonifen mode of action (MoA) by a random forest classifier. The classifier predicts for aclonifen a MoA within the carotenoid biosynthesis pathway similar to the reference compound norflurazon that inhibits the phytoene desaturase. Upon aclonifen treatment, the phytoene desaturation reaction is disturbed, resulting in a characteristic phytoene accumulation in vivo. However, direct enzyme inhibition by the herbicide was excluded for known herbicidal targets such as phytoene desaturase, 4-hydroxyphenylpyruvate dioxygenase and homogentisate solanesyltransferase. Eventually, the solanesyl diphosphate synthase (SPS), providing one of the two homogentisate solanesyltransferase substrate molecules, could be identified as the molecular target of aclonifen. Inhibition was confirmed using biochemical activity assays for the A. thaliana SPSs 1 and 2. Furthermore, a Chlamydomonas reinhardtii homolog was used for co-crystallization of the enzyme-inhibitor complex, showing that one inhibitor molecule binds at the interface between two protein monomers. CONCLUSION: Solanesyl diphosphate synthase was identified as the target of aclonifen, representing a novel mode of action for herbicides. © 2020 Society of Chemical Industry.

The Interplay between Carbon Availability and Growth in Different Zones of the Growing Maize Leaf.

Plants assimilate carbon in their photosynthetic tissues in the light. However, carbon is required during the night and in nonphotosynthetic organs. It is therefore essential that plants manage their carbon resources spatially and temporally and coordinate growth with carbon availability. In growing maize (Zea mays) leaf blades, a defined developmental gradient facilitates analyses in the cell division, elongation, and mature zones. We investigated the responses of the metabolome and transcriptome and polysome loading, as a qualitative proxy for protein synthesis, at dusk, dawn, and 6, 14, and 24 h into an extended night, and tracked whole-leaf elongation over this time course. Starch and sugars are depleted by dawn in the mature zone, but only after an extension of the night in the elongation and division zones. Sucrose (Suc) recovers partially between 14 and 24 h into the extended night in the growth zones, but not the mature zone. The global metabolome and transcriptome track these zone-specific changes in Suc. Leaf elongation and polysome loading in the growth zones also remain high at dawn, decrease between 6 and 14 h into the extended night, and then partially recover, indicating that growth processes are determined by local carbon status. The level of Suc-signaling metabolite trehalose-6-phosphate, and the trehalose-6-phosphate:Suc ratio are much higher in growth than mature zones at dusk and dawn but fall in the extended night. Candidate genes were identified by searching for transcripts that show characteristic temporal response patterns or contrasting responses to carbon starvation in growth and mature zones.

Systems approach for exploring the intricate associations between sweetness, color and aroma in melon fruits.

BACKGROUND: Melon (Cucumis melo) fruits exhibit phenotypic diversity in several key quality determinants such as taste, color and aroma. Sucrose, carotenoids and volatiles are recognized as the key compounds shaping the above corresponding traits yet the full network of biochemical events underlying their synthesis have not been comprehensively described. To delineate the cellular processes shaping fruit quality phenotypes, a population of recombinant inbred lines (RIL) was used as a source of phenotypic and genotypic variations. In parallel, ripe fruits were analyzed for both the quantified level of 77 metabolic traits directly associated with fruit quality and for RNA-seq based expression profiles generated for 27,000 unigenes. First, we explored inter-metabolite association patterns; then, we described metabolites versus gene association patterns; finally, we used the correlation-based associations for predicting uncharacterized synthesis pathways. RESULTS: Based on metabolite versus metabolite and metabolite versus gene association patterns, we divided metabolites into two key groups: a group including ethylene and aroma determining volatiles whose accumulation patterns are correlated with the expression of genes involved in the glycolysis and TCA cycle pathways; and a group including sucrose and color determining carotenoids whose accumulation levels are correlated with the expression of genes associated with plastid formation. CONCLUSIONS: The study integrates multiple processes into a genome scale perspective of cellular activity. This lays a foundation for deciphering the role of gene markers associated with the determination of fruit quality traits.

Systems Analysis of the Response of Photosynthesis, Metabolism, and Growth to an Increase in Irradiance in the Photosynthetic Model Organism Chlamydomonas reinhardtii.

We investigated the systems response of metabolism and growth after an increase in irradiance in the nonsaturating range in the algal model Chlamydomonas reinhardtii. In a three-step process, photosynthesis and the levels of metabolites increased immediately, growth increased after 10 to 15 min, and transcript and protein abundance responded by 40 and 120 to 240 min, respectively. In the first phase, starch and metabolites provided a transient buffer for carbon until growth increased. This uncouples photosynthesis from growth in a fluctuating light environment. In the first and second phases, rising metabolite levels and increased polysome loading drove an increase in fluxes. Most Calvin-Benson cycle (CBC) enzymes were substrate-limited in vivo, and strikingly, many were present at higher concentrations than their substrates, explaining how rising metabolite levels stimulate CBC flux. Rubisco, fructose-1,6-biosphosphatase, and seduheptulose-1,7-bisphosphatase were close to substrate saturation in vivo, and flux was increased by posttranslational activation. In the third phase, changes in abundance of particular proteins, including increases in plastidial ATP synthase and some CBC enzymes, relieved potential bottlenecks and readjusted protein allocation between different processes. Despite reasonable overall agreement between changes in transcript and protein abundance (R2 = 0.24), many proteins, including those in photosynthesis, changed independently of transcript abundance.

Trimmomatic: a flexible trimmer for Illumina sequence data.

MOTIVATION: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. RESULTS: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. AVAILABILITY AND IMPLEMENTATION: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic CONTACT: usadel@bio1.rwth-aachen.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mercator: a fast and simple web server for genome scale functional annotation of plant sequence data.

Next-generation technologies generate an overwhelming amount of gene sequence data. Efficient annotation tools are required to make these data amenable to functional genomics analyses. The Mercator pipeline automatically assigns functional terms to protein or nucleotide sequences. It uses the MapMan 'BIN' ontology, which is tailored for functional annotation of plant 'omics' data. The classification procedure performs parallel sequence searches against reference databases, compiles the results and computes the most likely MapMan BINs for each query. In the current version, the pipeline relies on manually curated reference classifications originating from the three reference organisms (Arabidopsis, Chlamydomonas, rice), various other plant species that have a reviewed SwissProt annotation, and more than 2000 protein domain and family profiles at InterPro, CDD and KOG. Functional annotations predicted by Mercator achieve accuracies above 90% when benchmarked against manual annotation. In addition to mapping files for direct use in the visualization software MapMan, Mercator provides graphical overview charts, detailed annotation information in a convenient web browser interface and a MapMan-to-GO translation table to export results as GO terms. Mercator is available free of charge via http://mapman.gabipd.org/web/guest/app/Mercator.

Transcriptome sequencing and microarray design for functional genomics in the extremophile Arabidopsis relative Thellungiella salsuginea (Eutrema salsugineum).

BACKGROUND: Most molecular studies of plant stress tolerance have been performed with Arabidopsis thaliana, although it is not particularly stress tolerant and may lack protective mechanisms required to survive extreme environmental conditions. Thellungiella salsuginea has attracted interest as an alternative plant model species with high tolerance of various abiotic stresses. While the T. salsuginea genome has recently been sequenced, its annotation is still incomplete and transcriptomic information is scarce. In addition, functional genomics investigations in this species are severely hampered by a lack of affordable tools for genome-wide gene expression studies. RESULTS: Here, we report the results of Thellungiella de novo transcriptome assembly and annotation based on 454 pyrosequencing and development and validation of a T. salsuginea microarray. ESTs were generated from a non-normalized and a normalized library synthesized from RNA pooled from samples covering different tissues and abiotic stress conditions. Both libraries yielded partially unique sequences, indicating their necessity to obtain comprehensive transcriptome coverage. More than 1 million sequence reads were assembled into 42,810 unigenes, approximately 50% of which could be functionally annotated. These unigenes were compared to all available Thellungiella genome sequence information. In addition, the groups of Late Embryogenesis Abundant (LEA) proteins, Mitogen Activated Protein (MAP) kinases and protein phosphatases were annotated in detail. We also predicted the target genes for 384 putative miRNAs. From the sequence information, we constructed a 44 k Agilent oligonucleotide microarray. Comparison of same-species and cross-species hybridization results showed superior performance of the newly designed array for T. salsuginea samples. The developed microarrays were used to investigate transcriptional responses of T. salsuginea and Arabidopsis during cold acclimation using the MapMan software. CONCLUSIONS: This study provides the first comprehensive transcriptome information for the extremophile Arabidopsis relative T. salsuginea. The data constitute a more than three-fold increase in the number of publicly available unigene sequences and will greatly facilitate genome annotation. In addition, we have designed and validated the first genome-wide microarray for T. salsuginea, which will be commercially available. Together with the publicly available MapMan software this will become an important tool for functional genomics of plant stress tolerance.

OrganellarGenomeDRAW--a suite of tools for generating physical maps of plastid and mitochondrial genomes and visualizing expression data sets.

Mitochondria and plastids (chloroplasts) are cell organelles of endosymbiotic origin that possess their own genetic information. Most organellar DNAs map as circular double-stranded genomes. Across the eukaryotic kingdom, organellar genomes display great size variation, ranging from ∼15 to 20 kb (the size of the mitochondrial genome in most animals) to >10 Mb (the size of the mitochondrial genome in some lineages of flowering plants). We have developed OrganellarGenomeDraw (OGDRAW), a suite of software tools that enable users to create high-quality visual representations of both circular and linear annotated genome sequences provided as GenBank files or accession numbers. Although all types of DNA sequences are accepted as input, the software has been specifically optimized to properly depict features of organellar genomes. A recent extension facilitates the plotting of quantitative gene expression data, such as transcript or protein abundance data, directly onto the genome map. OGDRAW has already become widely used and is available as a free web tool (http://ogdraw.mpimp-golm.mpg.de/). The core processing components can be downloaded as a Perl module, thus also allowing for convenient integration into custom processing pipelines.

UV-B irradiation changes specifically the secondary metabolite profile in broccoli sprouts: induced signaling overlaps with defense response to biotic stressors.

Only a few environmental factors have such a pronounced effect on plant growth and development as ultraviolet light (UV). Concerns have arisen due to increased UV-B radiation reaching the Earth's surface as a result of stratospheric ozone depletion. Ecologically relevant low to moderate UV-B doses (0.3-1 kJ m(-2) d(-1)) were applied to sprouts of the important vegetable crop Brassica oleracea var. italica (broccoli), and eco-physiological responses such as accumulation of non-volatile secondary metabolites were related to transcriptional responses with Agilent One-Color Gene Expression Microarray analysis using the 2×204 k format Brassica microarray. UV-B radiation effects have usually been linked to increases in phenolic compounds. As expected, the flavonoids kaempferol and quercetin accumulated in broccoli sprouts (the aerial part of the seedlings) 24 h after UV-B treatment. A new finding is the specific UV-B-mediated induction of glucosinolates (GS), especially of 4-methylsulfinylbutyl GS and 4-methoxy-indol-3-ylmethyl GS, while carotenoids and Chl levels remained unaffected. Accumulation of defensive GS metabolites was accompanied by increased expression of genes associated with salicylate and jasmonic acid signaling defense pathways and up-regulation of genes responsive to fungal and bacterial pathogens. Concomitantly, plant pre-exposure to moderate UV-B doses had negative effects on the performance of the caterpillar Pieris brassicae (L.) and on the population growth of the aphid Myzus persicae (Sulzer). Moreover, insect-specific induction of GS in broccoli sprouts was affected by UV-B pre-treatment.

Antisense inhibition of the 2-oxoglutarate dehydrogenase complex in tomato demonstrates its importance for plant respiration and during leaf senescence and fruit maturation.

Transgenic tomato (Solanum lycopersicum) plants expressing a fragment of the gene encoding the E1 subunit of the 2-oxoglutarate dehydrogenase complex in the antisense orientation and exhibiting substantial reductions in the activity of this enzyme exhibit a considerably reduced rate of respiration. They were, however, characterized by largely unaltered photosynthetic rates and fruit yields but restricted leaf, stem, and root growth. These lines displayed markedly altered metabolic profiles, including changes in tricarboxylic acid cycle intermediates and in the majority of the amino acids but unaltered pyridine nucleotide content both in leaves and during the progression of fruit ripening. Moreover, they displayed a generally accelerated development exhibiting early flowering, accelerated fruit ripening, and a markedly earlier onset of leaf senescence. In addition, transcript and selective hormone profiling of gibberellins and abscisic acid revealed changes only in the former coupled to changes in transcripts encoding enzymes of gibberellin biosynthesis. The data obtained are discussed in the context of the importance of this enzyme in both photosynthetic and respiratory metabolism as well as in programs of plant development connected to carbon-nitrogen interactions.

RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics.

Recent rapid advances in next generation RNA sequencing (RNA-Seq)-based provide researchers with unprecedentedly large data sets and open new perspectives in transcriptomics. Furthermore, RNA-Seq-based transcript profiling can be applied to non-model and newly discovered organisms because it does not require a predefined measuring platform (like e.g. microarrays). However, these novel technologies pose new challenges: the raw data need to be rigorously quality checked and filtered prior to analysis, and proper statistical methods have to be applied to extract biologically relevant information. Given the sheer volume of data, this is no trivial task and requires a combination of considerable technical resources along with bioinformatics expertise. To aid the individual researcher, we have developed RobiNA as an integrated solution that consolidates all steps of RNA-Seq-based differential gene-expression analysis in one user-friendly cross-platform application featuring a rich graphical user interface. RobiNA accepts raw FastQ files, SAM/BAM alignment files and counts tables as input. It supports quality checking, flexible filtering and statistical analysis of differential gene expression based on state-of-the art biostatistical methods developed in the R/Bioconductor projects. In-line help and a step-by-step manual guide users through the analysis. Installer packages for Mac OS X, Windows and Linux are available under the LGPL licence from http://mapman.gabipd.org/web/guest/robin.

Arbuscule-containing and non-colonized cortical cells of mycorrhizal roots undergo extensive and specific reprogramming during arbuscular mycorrhizal development.

Most vascular plants form a mutualistic association with arbuscular mycorrhizal (AM) fungi, known as AM symbiosis. The development of AM symbiosis is an asynchronous process, and mycorrhizal roots therefore typically contain several symbiotic structures and various cell types. Hence, the use of whole-plant organs for downstream analyses can mask cell-specific variations in gene expression. To obtain insight into cell-specific reprogramming during AM symbiosis, comparative analyses of various cell types were performed using laser capture microdissection combined with microarray hybridization. Remarkably, the most prominent transcriptome changes were observed in non-arbuscule-containing cells of mycorrhizal roots, indicating a drastic reprogramming of these cells during root colonization that may be related to subsequent fungal colonization. A high proportion of transcripts regulated in arbuscule-containing cells and non-arbuscule-containing cells encode proteins involved in transport processes, transcriptional regulation and lipid metabolism, indicating that reprogramming of these processes is of particular importance for AM symbiosis.

Systems biology of tomato fruit development: combined transcript, protein, and metabolite analysis of tomato transcription factor (nor, rin) and ethylene receptor (Nr) mutants reveals novel regulatory interactions.

Tomato (Solanum lycopersicum) is an established model to study fleshy fruit development and ripening. Tomato ripening is regulated independently and cooperatively by ethylene and transcription factors, including nonripening (NOR) and ripening-inhibitor (RIN). Mutations of NOR, RIN, and the ethylene receptor Never-ripe (Nr), which block ethylene perception and inhibit ripening, have proven to be great tools for advancing our understanding of the developmental programs regulating ripening. In this study, we present systems analysis of nor, rin, and Nr at the transcriptomic, proteomic, and metabolomic levels during development and ripening. Metabolic profiling marked shifts in the abundance of metabolites of primary metabolism, which lead to decreases in metabolic activity during ripening. When combined with transcriptomic and proteomic data, several aspects of the regulation of metabolism during ripening were revealed. First, correlations between the expression levels of a transcript and the abundance of its corresponding protein were infrequently observed during early ripening, suggesting that posttranscriptional regulatory mechanisms play an important role in these stages; however, this correlation was much greater in later stages. Second, we observed very strong correlation between ripening-associated transcripts and specific metabolite groups, such as organic acids, sugars, and cell wall-related metabolites, underlining the importance of these metabolic pathways during fruit ripening. These results further revealed multiple ethylene-associated events during tomato ripening, providing new insights into the molecular biology of ethylene-mediated ripening regulatory networks.

Large-scale transcriptome analysis in chickpea (Cicer arietinum L.), an orphan legume crop of the semi-arid tropics of Asia and Africa.

Chickpea (Cicer arietinum L.) is an important legume crop in the semi-arid regions of Asia and Africa. Gains in crop productivity have been low however, particularly because of biotic and abiotic stresses. To help enhance crop productivity using molecular breeding techniques, next generation sequencing technologies such as Roche/454 and Illumina/Solexa were used to determine the sequence of most gene transcripts and to identify drought-responsive genes and gene-based molecular markers. A total of 103,215 tentative unique sequences (TUSs) have been produced from 435,018 Roche/454 reads and 21,491 Sanger expressed sequence tags (ESTs). Putative functions were determined for 49,437 (47.8%) of the TUSs, and gene ontology assignments were determined for 20,634 (41.7%) of the TUSs. Comparison of the chickpea TUSs with the Medicago truncatula genome assembly (Mt 3.5.1 build) resulted in 42,141 aligned TUSs with putative gene structures (including 39,281 predicted intron/splice junctions). Alignment of ∼37 million Illumina/Solexa tags generated from drought-challenged root tissues of two chickpea genotypes against the TUSs identified 44,639 differentially expressed TUSs. The TUSs were also used to identify a diverse set of markers, including 728 simple sequence repeats (SSRs), 495 single nucleotide polymorphisms (SNPs), 387 conserved orthologous sequence (COS) markers, and 2088 intron-spanning region (ISR) markers. This resource will be useful for basic and applied research for genome analysis and crop improvement in chickpea.

SLocX: Predicting Subcellular Localization of Arabidopsis Proteins Leveraging Gene Expression Data.

Despite the growing volume of experimentally validated knowledge about the subcellular localization of plant proteins, a well performing in silico prediction tool is still a necessity. Existing tools, which employ information derived from protein sequence alone, offer limited accuracy and/or rely on full sequence availability. We explored whether gene expression profiling data can be harnessed to enhance prediction performance. To achieve this, we trained several support vector machines to predict the subcellular localization of Arabidopsis thaliana proteins using sequence derived information, expression behavior, or a combination of these data and compared their predictive performance through a cross-validation test. We show that gene expression carries information about the subcellular localization not available in sequence information, yielding dramatic benefits for plastid localization prediction, and some notable improvements for other compartments such as the mitochondrion, the Golgi, and the plasma membrane. Based on these results, we constructed a novel subcellular localization prediction engine, SLocX, combining gene expression profiling data with protein sequence-based information. We then validated the results of this engine using an independent test set of annotated proteins and a transient expression of GFP fusion proteins. Here, we present the prediction framework and a website of predicted localizations for Arabidopsis. The relatively good accuracy of our prediction engine, even in cases where only partial protein sequence is available (e.g., in sequences lacking the N-terminal region), offers a promising opportunity for similar application to non-sequenced or poorly annotated plant species. Although the prediction scope of our method is currently limited by the availability of expression information on the ATH1 array, we believe that the advances in measuring gene expression technology will make our method applicable for all Arabidopsis proteins.

Algorithm-driven artifacts in median polish summarization of microarray data.

BACKGROUND: High-throughput measurement of transcript intensities using Affymetrix type oligonucleotide microarrays has produced a massive quantity of data during the last decade. Different preprocessing techniques exist to convert the raw signal intensities measured by these chips into gene expression estimates. Although these techniques have been widely benchmarked in the context of differential gene expression analysis, there are only few examples where their performance has been assessed in respect to coexpression-based studies such as sample classification. RESULTS: In the present paper we benchmark the three most used normalization procedures (MAS5, RMA and GCRMA) in the context of inter-array correlation analysis, confirming and extending the finding that RMA and GCRMA consistently overestimate sample similarity upon normalization. We determine that median polish summarization is responsible for generating a large proportion of these over-similarity artifacts. Furthermore, we show that most affected probesets show also internal signal disagreement, and tend to be composed by individual probes hitting different gene transcripts. We finally provide a correction to the RMA/GCRMA summarization procedure that massively reduces inter-array correlation artifacts, without affecting the detection of differentially expressed genes. CONCLUSIONS: We propose tRMA as a modification of RMA to normalize microarray experiments for correlation-based analysis.

Robin: an intuitive wizard application for R-based expression microarray quality assessment and analysis.

The wide application of high-throughput transcriptomics using microarrays has generated a plethora of technical platforms, data repositories, and sophisticated statistical analysis methods, leaving the individual scientist with the problem of choosing the appropriate approach to address a biological question. Several software applications that provide a rich environment for microarray analysis and data storage are available (e.g. GeneSpring, EMMA2), but these are mostly commercial or require an advanced informatics infrastructure. There is a need for a noncommercial, easy-to-use graphical application that aids the lab researcher to find the proper method to analyze microarray data, without this requiring expert understanding of the complex underlying statistics, or programming skills. We have developed Robin, a Java-based graphical wizard application that harnesses the advanced statistical analysis functions of the R/BioConductor project. Robin implements streamlined workflows that guide the user through all steps of two-color, single-color, or Affymetrix microarray analysis. It provides functions for thorough quality assessment of the data and automatically generates warnings to notify the user of potential outliers, low-quality chips, or low statistical power. The results are generated in a standard format that allows ready use with both specialized analysis tools like MapMan and PageMan and generic spreadsheet applications. To further improve user friendliness, Robin includes both integrated help and comprehensive external documentation. To demonstrate the statistical power and ease of use of the workflows in Robin, we present a case study in which we apply Robin to analyze a two-color microarray experiment comparing gene expression in tomato (Solanum lycopersicum) leaves, flowers, and roots.

Gene expression profiling in susceptible interaction of grapevine with its fungal pathogen Eutypa lata: extending MapMan ontology for grapevine.

BACKGROUND: Whole genome transcriptomics analysis is a very powerful approach because it gives an overview of the activity of genes in certain cells or tissue types. However, biological interpretation of such results can be rather tedious. MapMan is a software tool that displays large datasets (e.g. gene expression data) onto diagrams of metabolic pathways or other processes and thus enables easier interpretation of results. The grapevine (Vitis vinifera) genome sequence has recently become available bringing a new dimension into associated research. Two microarray platforms were designed based on the TIGR Gene Index database and used in several physiological studies. RESULTS: To enable easy and effective visualization of those and further experiments, annotation of Vitis vinifera Gene Index (VvGI version 5) to MapMan ontology was set up. Due to specificities of grape physiology, we have created new pictorial representations focusing on three selected pathways: carotenoid pathway, terpenoid pathway and phenylpropanoid pathway, the products of these pathways being important for wine aroma, flavour and colour, as well as plant defence against pathogens. This new tool was validated on Affymetrix microarrays data obtained during berry ripening and it allowed the discovery of new aspects in process regulation. We here also present results on transcriptional profiling of grape plantlets after exposal to the fungal pathogen Eutypa lata using Operon microarrays including visualization of results with MapMan. The data show that the genes induced in infected plants, encode pathogenesis related proteins and enzymes of the flavonoid metabolism, which are well known as being responsive to fungal infection. CONCLUSION: The extension of MapMan ontology to grapevine together with the newly constructed pictorial representations for carotenoid, terpenoid and phenylpropanoid metabolism provide an alternative approach to the analysis of grapevine gene expression experiments performed with Affymetrix or Operon microarrays. MapMan was first validated on an already published dataset and later used to obtain an overview of transcriptional changes in a susceptible grapevine - Eutypa lata interaction at the time of symptoms development, where we showed that the responsive genes belong to families known to be involved in the plant defence towards fungal infection (PR-proteins, enzymes of the phenylpropanoid pathway).