@article {446, title = {Integrating transcriptomic and metabolomic analysis to understand natural leaf senescence in sunflower.}, journal = {Plant Biotechnol J}, volume = {14}, year = {2016}, month = {2016 Feb}, pages = {719-34}, abstract = {

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.

}, keywords = {Gas Chromatography-Mass Spectrometry, Gene Expression Profiling, Gene Expression Regulation, Plant, Gene ontology, Genes, Plant, Helianthus, Ions, metabolomics, Oligonucleotide Array Sequence Analysis, Plant Leaves, Principal Component Analysis, RNA, Messenger, Transcription Factors}, issn = {1467-7652}, doi = {10.1111/pbi.12422}, author = {Moschen, Sebasti{\'a}n and Bengoa Luoni, Sof{\'\i}a and Di Rienzo, Julio A and Caro, Mar{\'\i}a Del Pilar and Tohge, Takayuki and Watanabe, Mutsumi and Hollmann, Julien and Gonzalez, Sergio and Rivarola, M{\'a}ximo and Garcia-Garcia, Francisco and Dopazo, Joaquin and Hopp, Horacio Esteban and Hoefgen, Rainer and Fernie, Alisdair R and Paniego, Norma and Fernandez, Paula and Heinz, Ruth A} } @article {507, title = {Novel genes detected by transcriptional profiling from whole-blood cells in patients with early onset of acute coronary syndrome.}, journal = {Clin Chim Acta}, volume = {421}, year = {2013}, month = {2013 Jun 05}, pages = {184-90}, abstract = {

BACKGROUND: Genome-wide expression analysis using microarrays has been used as a research strategy to discovery new biomarkers and candidate genes for a number of diseases. We aim to find new biomarkers for the prediction of acute coronary syndrome (ACS) with a differentially expressed mRNA profiling approach using whole genomic expression analysis in a peripheral blood cell model from patients with early ACS.

METHODS AND RESULTS: This study was carried out in two phases. On phase 1 a restricted clinical criteria (ACS-Ph1, n=9 and CG-Ph1, n=6) was used in order to select potential mRNA biomarkers candidates. A subsequent phase 2 study was performed using selected phase 1 markers analyzed by RT-qPCR using a larger and independent casuistic (ACS-Ph2, n=74 and CG-Ph2, n=41). A total of 549 genes were found to be differentially expressed in the first 48 h after the ACS-Ph1. Technical and biological validation further confirmed that ALOX15, AREG, BCL2A1, BCL2L1, CA1, COX7B, ECHDC3, IL18R1, IRS2, KCNE1, MMP9, MYL4 and TREML4, are differentially expressed in both phases of this study.

CONCLUSIONS: Transcriptomic analysis by microarray technology demonstrated differential expression during a 48 h time course suggesting a potential use of some of these genes as biomarkers for very early stages of ACS, as well as for monitoring early cardiac ischemic recovery.

}, keywords = {Acute Coronary Syndrome, Acute-Phase Proteins, Adult, biomarkers, Blood Cells, Early Diagnosis, gene expression, Gene Expression Profiling, Humans, Male, Middle Aged, Oligonucleotide Array Sequence Analysis, RNA, Messenger, Transcriptome}, issn = {1873-3492}, doi = {10.1016/j.cca.2013.03.011}, author = {Silbiger, Vivian N and Luchessi, Andr{\'e} D and Hirata, Ros{\'a}rio D C and Lima-Neto, L{\'\i}dio G and Cavichioli, D{\'e}bora and Carracedo, {\'A}ngel and Bri{\'o}n, Maria and Dopazo, Joaquin and Garcia-Garcia, Francisco and Dos Santos, Elizabete S and Ramos, Rui F and Sampaio, Marcelo F and Armaganijan, Dikran and Sousa, Amanda G M R and Hirata, Mario H} } @article {516, title = {IL1β induces mesenchymal stem cells migration and leucocyte chemotaxis through NF-κB.}, journal = {Stem Cell Rev Rep}, volume = {8}, year = {2012}, month = {2012 Sep}, pages = {905-16}, abstract = {

Mesenchymal stem cells are often transplanted into inflammatory environments where they are able to survive and modulate host immune responses through a poorly understood mechanism. In this paper we analyzed the responses of MSC to IL-1β: a representative inflammatory mediator. Microarray analysis of MSC treated with IL-1β revealed that this cytokine activateds a set of genes related to biological processes such as cell survival, cell migration, cell adhesion, chemokine production, induction of angiogenesis and modulation of the immune response. Further more detailed analysis by real-time PCR and functional assays revealed that IL-1β mainly increaseds the production of chemokines such as CCL5, CCL20, CXCL1, CXCL3, CXCL5, CXCL6, CXCL10, CXCL11 and CX(3)CL1, interleukins IL-6, IL-8, IL23A, IL32, Toll-like receptors TLR2, TLR4, CLDN1, metalloproteins MMP1 and MMP3, growth factors CSF2 and TNF-α, together with adhesion molecules ICAM1 and ICAM4. Functional analysis of MSC proliferation, migration and adhesion to extracellular matrix components revealed that IL-1β did not affect proliferation but also served to induce the secretion of trophic factors and adhesion to ECM components such as collagen and laminin. IL-1β treatment enhanced the ability of MSC to recruit monocytes and granulocytes in vitro. Blockade of NF-κβ transcription factor activation with IκB kinase beta (IKKβ) shRNA impaired MSC migration, adhesion and leucocyte recruitment, induced by IL-1β demonstrating that NF-κB pathway is an important downstream regulator of these responses. These findings are relevant to understanding the biological responses of MSC to inflammatory environments.

}, keywords = {Cell Adhesion, Cell Movement, Cell Proliferation, Chemokines, Chemotaxis, Leukocyte, Collagen, Fibronectins, Gene Expression Profiling, Gene Knockdown Techniques, HEK293 Cells, Humans, I-kappa B Kinase, Inflammation Mediators, Intercellular Signaling Peptides and Proteins, Interleukin-1beta, Laminin, Leukocytes, Mesenchymal Stem Cells, NF-kappa B, Oligonucleotide Array Sequence Analysis, RNA Interference, Signal Transduction}, issn = {2629-3277}, doi = {10.1007/s12015-012-9364-9}, author = {Carrero, Rub{\'e}n and Cerrada, Inmaculada and Lled{\'o}, Elisa and Dopazo, Joaquin and Garcia-Garcia, Francisco and Rubio, Mari-Paz and Trigueros, C{\'e}sar and Dorronsoro, Akaitz and Ruiz-Sauri, Amparo and Montero, Jos{\'e} Anastasio and Sep{\'u}lveda, Pilar} } @article {532, title = {Early transcriptional defense responses in Arabidopsis cell suspension culture under high-light conditions.}, journal = {Plant Physiol}, volume = {156}, year = {2011}, month = {2011 Jul}, pages = {1439-56}, abstract = {

The early transcriptional defense responses and reactive oxygen species (ROS) production in Arabidopsis (Arabidopsis thaliana) cell suspension culture (ACSC), containing functional chloroplasts, were examined at high light (HL). The transcriptional analysis revealed that most of the ROS markers identified among the 449 transcripts with significant differential expression were transcripts specifically up-regulated by singlet oxygen ((1)O(2)). On the contrary, minimal correlation was established with transcripts specifically up-regulated by superoxide radical or hydrogen peroxide. The transcriptional analysis was supported by fluorescence microscopy experiments. The incubation of ACSC with the (1)O(2) sensor green reagent and 2{\textquoteright},7{\textquoteright}-dichlorofluorescein diacetate showed that the 30-min-HL-treated cultures emitted fluorescence that corresponded with the production of (1)O(2) but not of hydrogen peroxide. Furthermore, the in vivo photodamage of the D1 protein of photosystem II indicated that the photogeneration of (1)O(2) took place within the photosystem II reaction center. Functional enrichment analyses identified transcripts that are key components of the ROS signaling transduction pathway in plants as well as others encoding transcription factors that regulate both ROS scavenging and water deficit stress. A meta-analysis examining the transcriptional profiles of mutants and hormone treatments in Arabidopsis showed a high correlation between ACSC at HL and the fluorescent mutant family of Arabidopsis, a producer of (1)O(2) in plastids. Intriguingly, a high correlation was also observed with ABA deficient1 and more axillary growth4, two mutants with defects in the biosynthesis pathways of two key (apo)carotenoid-derived plant hormones (i.e. abscisic acid and strigolactones, respectively). ACSC has proven to be a valuable system for studying early transcriptional responses to HL stress.

}, keywords = {Arabidopsis, Blotting, Western, Cell Culture Techniques, Cells, Cultured, Chloroplasts, Cluster Analysis, Gene Expression Profiling, Gene Expression Regulation, Plant, Hydrogen Peroxide, Light, mutation, Oligonucleotide Array Sequence Analysis, Photosystem II Protein Complex, Plant Growth Regulators, Reproducibility of Results, Reverse Transcriptase Polymerase Chain Reaction, RNA, Messenger, Signal Transduction, Stress, Physiological, Transcription, Genetic}, issn = {1532-2548}, doi = {10.1104/pp.111.177766}, author = {Gonz{\'a}lez-P{\'e}rez, Sergio and Guti{\'e}rrez, Jorge and Garcia-Garcia, Francisco and Osuna, Daniel and Dopazo, Joaquin and Lorenzo, Oscar and Revuelta, Jos{\'e} L and Arellano, Juan B} } @article {580, title = {Functional assessment of time course microarray data.}, journal = {BMC Bioinformatics}, volume = {10 Suppl 6}, year = {2009}, month = {2009 Jun 16}, pages = {S9}, abstract = {

MOTIVATION: Time-course microarray experiments study the progress of gene expression along time across one or several experimental conditions. Most developed analysis methods focus on the clustering or the differential expression analysis of genes and do not integrate functional information. The assessment of the functional aspects of time-course transcriptomics data requires the use of approaches that exploit the activation dynamics of the functional categories to where genes are annotated.

METHODS: We present three novel methodologies for the functional assessment of time-course microarray data. i) maSigFun derives from the maSigPro method, a regression-based strategy to model time-dependent expression patterns and identify genes with differences across series. maSigFun fits a regression model for groups of genes labeled by a functional class and selects those categories which have a significant model. ii) PCA-maSigFun fits a PCA model of each functional class-defined expression matrix to extract orthogonal patterns of expression change, which are then assessed for their fit to a time-dependent regression model. iii) ASCA-functional uses the ASCA model to rank genes according to their correlation to principal time expression patterns and assess functional enrichment on a GSA fashion. We used simulated and experimental datasets to study these novel approaches. Results were compared to alternative methodologies.

RESULTS: Synthetic and experimental data showed that the different methods are able to capture different aspects of the relationship between genes, functions and co-expression that are biologically meaningful. The methods should not be considered as competitive but they provide different insights into the molecular and functional dynamic events taking place within the biological system under study.

}, keywords = {Computer Simulation, Gene Expression Profiling, Oligonucleotide Array Sequence Analysis, Time Factors}, issn = {1471-2105}, doi = {10.1186/1471-2105-10-S6-S9}, author = {Nueda, Maria Jos{\'e} and Sebasti{\'a}n, Patricia and Tarazona, Sonia and Garcia-Garcia, Francisco and Dopazo, Joaquin and Ferrer, Alberto and Conesa, Ana} } @article {593, title = {GEPAS, a web-based tool for microarray data analysis and interpretation.}, journal = {Nucleic Acids Res}, volume = {36}, year = {2008}, month = {2008 Jul 01}, pages = {W308-14}, abstract = {

Gene Expression Profile Analysis Suite (GEPAS) is one of the most complete and extensively used web-based packages for microarray data analysis. During its more than 5 years of activity it has continuously been updated to keep pace with the state-of-the-art in the changing microarray data analysis arena. GEPAS offers diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and functional profiling of the experiment. New options for time-course (or dose-response) experiments, microarray-based class prediction, new clustering methods and new tests for differential expression have been included. The new pipeliner module allows automating the execution of sequential analysis steps by means of a simple but powerful graphic interface. An extensive re-engineering of GEPAS has been carried out which includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. GEPAS is nowadays the most quoted web tool in its field and it is extensively used by researchers of many countries and its records indicate an average usage rate of 500 experiments per day. GEPAS, is available at http://www.gepas.org.

}, keywords = {Computer Graphics, Dose-Response Relationship, Drug, Gene Expression Profiling, Internet, Kinetics, Oligonucleotide Array Sequence Analysis, Software}, issn = {1362-4962}, doi = {10.1093/nar/gkn303}, author = {T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Carbonell, Jos{\'e} and Huerta-Cepas, Jaime and Minguez, Pablo and Alloza, Eva and Al-Shahrour, F{\'a}tima and Vegas-Azc{\'a}rate, Susana and Goetz, Stefan and Escobar, Pablo and Garcia-Garcia, Francisco and Conesa, Ana and Montaner, David and Dopazo, Joaquin} }