02395nas a2200313   4500008004100000022001400041245011300055210006900168260001600237300000800253490000700261520133500268653001201603653002301615653003001638653004201668653001301710653002701723653001801750653002801768100002101796700002201817700002201839700002101861700002101882700002001903700001901923856013901942       2017                        eng d  a1471-210500aATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data.0 aATGC transcriptomics a webbased application to integrate explore  c2017 Feb 22  a1210 v183 a<p><b>BACKGROUND: </b>In the last years, applications based on massively parallelized RNA sequencing (RNA-seq) have become valuable approaches for studying non-model species, e.g., without a fully sequenced genome. RNA-seq is a useful tool for detecting novel transcripts and genetic variations and for evaluating differential gene expression by digital measurements. The large and complex datasets resulting from functional genomic experiments represent a challenge in data processing, management, and analysis. This problem is especially significant for small research groups working with non-model species.</p><p><b>RESULTS: </b>We developed a web-based application, called ATGC transcriptomics, with a flexible and adaptable interface that allows users to work with new generation sequencing (NGS) transcriptomic analysis results using an ontology-driven database. This new application simplifies data exploration, visualization, and integration for a better comprehension of the results.</p><p><b>CONCLUSIONS: </b>ATGC transcriptomics provides access to non-expert computer users and small research groups to a scalable storage option and simple data integration, including database administration and management. The software is freely available under the terms of GNU public license at http://atgcinta.sourceforge.net .</p>10aAnimals10aDatabases, Genetic10aGene Expression Profiling10aHigh-Throughput Nucleotide Sequencing10aInternet10aSequence Analysis, RNA10aTranscriptome10aUser-Computer Interface1 aGonzalez, Sergio1 aClavijo, Bernardo1 aRivarola, Máximo1 aMoreno, Patricio1 aFernandez, Paula1 aDopazo, Joaquin1 aPaniego, Norma  uhttp://clinbioinfosspa.es/content/atgc-transcriptomics-web-based-application-integrate-explore-and-analyze-de-novo-transcriptomic-data03062nas a2200433   4500008004100000022001400041245016000055210006900215260001300284300001200297490000700309520160000316653001601916653003801932653001501970653001701985653001902002653002702021653001502048653002602063653002602089653001002115100002402125700002402149700001902173700002002192700002202212700002102234700002202255700002902277700002002306700001802326700002002344700002402364700001902388700002102407700001902428856018102447       2017                        eng d  a1573-502800aIntegration of transcriptomic and metabolic data reveals hub transcription factors involved in drought stress response in sunflower (Helianthus annuus L.).0 aIntegration of transcriptomic and metabolic data reveals hub tra  c2017 Jul  a549-5640 v943 a<p>By integration of transcriptional and metabolic profiles we identified pathways and hubs transcription factors regulated during drought conditions in sunflower, useful for applications in molecular and/or biotechnological breeding. Drought is one of the most important environmental stresses that effects crop productivity in many agricultural regions. Sunflower is tolerant to drought conditions but the mechanisms involved in this tolerance remain unclear at the molecular level. The aim of this study was to characterize and integrate transcriptional and metabolic pathways related to drought stress in sunflower plants, by using a system biology approach. Our results showed a delay in plant senescence with an increase in the expression level of photosynthesis related genes as well as higher levels of sugars, osmoprotectant amino acids and ionic nutrients under drought conditions. In addition, we identified transcription factors that were upregulated during drought conditions and that may act as hubs in the transcriptional network. Many of these transcription factors belong to families implicated in the drought response in model species. The integration of transcriptomic and metabolomic data in this study, together with physiological measurements, has improved our understanding of the biological responses during droughts and contributes to elucidate the molecular mechanisms involved under this environmental condition. These findings will provide useful biotechnological tools to improve stress tolerance while maintaining crop yield under restricted water availability.</p>10aChlorophyll10aGene Expression Regulation, Plant10aHelianthus10aPlant Leaves10aPlant Proteins10aProtein Array Analysis10aRNA, Plant10aStress, Physiological10aTranscription Factors10aWater1 aMoschen, Sebastián1 aDi Rienzo, Julio, A1 aHiggins, Janet1 aTohge, Takayuki1 aWatanabe, Mutsumi1 aGonzalez, Sergio1 aRivarola, Máximo1 aGarcia-Garcia, Francisco1 aDopazo, Joaquin1 aHopp, Esteban1 aHoefgen, Rainer1 aFernie, Alisdair, R1 aPaniego, Norma1 aFernandez, Paula1 aHeinz, Ruth, A  uhttp://clinbioinfosspa.es/content/integration-transcriptomic-and-metabolic-data-reveals-hub-transcription-factors-involved-drought-stress-response-sunflower-helianthus-annuus-l03249nas a2200493   4500008004100000022001400041245010800055210006900163260001300232300001100245490000700256520165600263653004101919653003001960653003801990653001802028653001702046653001502063653000902078653001702087653004402104653001702148653003302165653001902198653002602217100002402243700002602267700002402293700002802317700002002345700002202365700002102387700002102408700002202429700002902451700002002480700002702500700002002527700002402547700001902571700002102590700001902611856012502630       2016                        eng d  a1467-765200aIntegrating transcriptomic and metabolomic analysis to understand natural leaf senescence in sunflower.0 aIntegrating transcriptomic and metabolomic analysis to understan  c2016 Feb  a719-340 v143 a<p>Leaf senescence is a complex process, which has dramatic consequences on crop yield. In sunflower, gap between potential and actual yields reveals the economic impact of senescence. Indeed, sunflower plants are incapable of maintaining their green leaf area over sustained periods. This study characterizes the leaf senescence process in sunflower through a systems biology approach integrating transcriptomic and metabolomic analyses: plants being grown under both glasshouse and field conditions. Our results revealed a correspondence between profile changes detected at the molecular, biochemical and physiological level throughout the progression of leaf senescence measured at different plant developmental stages. Early metabolic changes were detected prior to anthesis and before the onset of the first senescence symptoms, with more pronounced changes observed when physiological and molecular variables were assessed under field conditions. During leaf development, photosynthetic activity and cell growth processes decreased, whereas sucrose, fatty acid, nucleotide and amino acid metabolisms increased. Pathways related to nutrient recycling processes were also up-regulated. Members of the NAC, AP2-EREBP, HB, bZIP and MYB transcription factor families showed high expression levels, and their expression level was highly correlated, suggesting their involvement in sunflower senescence. The results of this study thus contribute to the elucidation of the molecular mechanisms involved in the onset and progression of leaf senescence in sunflower leaves as well as to the identification of candidate genes involved in this process. </p>10aGas Chromatography-Mass Spectrometry10aGene Expression Profiling10aGene Expression Regulation, Plant10aGene ontology10aGenes, Plant10aHelianthus10aIons10ametabolomics10aOligonucleotide Array Sequence Analysis10aPlant Leaves10aPrincipal Component Analysis10aRNA, Messenger10aTranscription Factors1 aMoschen, Sebastián1 aLuoni, Sofía, Bengoa1 aDi Rienzo, Julio, A1 aCaro, María, Del Pilar1 aTohge, Takayuki1 aWatanabe, Mutsumi1 aHollmann, Julien1 aGonzalez, Sergio1 aRivarola, Máximo1 aGarcia-Garcia, Francisco1 aDopazo, Joaquin1 aHopp, Horacio, Esteban1 aHoefgen, Rainer1 aFernie, Alisdair, R1 aPaniego, Norma1 aFernandez, Paula1 aHeinz, Ruth, A  uhttp://clinbioinfosspa.es/content/integrating-transcriptomic-and-metabolomic-analysis-understand-natural-leaf-senescence02998nas a2200349   4500008004100000022001400041245015500055210006900210260000900279300001100288490000600299520188000305100002102185700001902206700001702225700002002242700002402262700002202286700002802308700002102336700002002357700002102377700002102398700002302419700002902442700001602471700001802487700002102505700002402526700001902550856007902569       2012                        eng d  a1932-620300aDevelopment, Characterization and Experimental Validation of a Cultivated Sunflower (Helianthus annuus L.) Gene Expression Oligonucleotide Microarray.0 aDevelopment Characterization and Experimental Validation of a Cu  c2012  ae458990 v73 aOligonucleotide-based microarrays with accurate gene coverage represent a key strategy for transcriptional studies in orphan species such as sunflower, H. annuus L., which lacks full genome sequences. The goal of this study was the development and functional annotation of a comprehensive sunflower unigene collection and the design and validation of a custom sunflower oligonucleotide-based microarray. A large scale EST (>130,000 ESTs) curation, assembly and sequence annotation was performed using Blast2GO (www.blast2go.de). The EST assembly comprises 41,013 putative transcripts (12,924 contigs and 28,089 singletons). The resulting Sunflower Unigen Resource (SUR version 1.0) was used to design an oligonucleotide-based Agilent microarray for cultivated sunflower. This microarray includes a total of 42,326 features: 1,417 Agilent controls, 74 control probes for sunflower replicated 10 times (740 controls) and 40,169 different non-control probes. Microarray performance was validated using a model experiment examining the induction of senescence by water deficit. Pre-processing and differential expression analysis of Agilent microarrays was performed using the Bioconductor limma package. The analyses based on p-values calculated by eBayes (p<0.01) allowed the detection of 558 differentially expressed genes between water stress and control conditions; from these, ten genes were further validated by qPCR. Over-represented ontologies were identified using FatiScan in the Babelomics suite. This work generated a curated and trustable sunflower unigene collection, and a custom, validated sunflower oligonucleotide-based microarray using Agilent technology. Both the curated unigene collection and the validated oligonucleotide microarray provide key resources for sunflower genome analysis, transcriptional studies, and molecular breeding for crop improvement.1 aFernandez, Paula1 aSoria, Marcelo1 aBlesa, David1 aDirienzo, Julio1 aMoschen, Sebastián1 aRivarola, Máximo1 aClavijo, Bernardo, Jose1 aGonzalez, Sergio1 aPeluffo, Lucila1 aPríncipi, Dario1 aDosio, Guillermo1 aAguirrezabal, Luis1 aGarcia-Garcia, Francisco1 aConesa, Ana1 aHopp, Esteban1 aDopazo, Joaquín1 aHeinz, Ruth, Amelia1 aPaniego, Norma  uhttp://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0045899