@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 {514, title = {Extensive translatome remodeling during ER stress response in mammalian cells.}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e35915}, abstract = {

In this work we have described the translatome of two mammalian cell lines, NIH3T3 and Jurkat, by scoring the relative polysome association of \~{}10,000 mRNA under normal and ER stress conditions. We have found that translation efficiencies of mRNA correlated poorly with transcript abundance, although a general tendency was observed so that the highest translation efficiencies were found in abundant mRNA. Despite the differences found between mouse (NIH3T3) and human (Jurkat) cells, both cell types share a common translatome composed by \~{}800-900 mRNA that encode proteins involved in basic cellular functions. Upon stress, an extensive remodeling in translatomes was observed so that translation of \~{}50\% of mRNA was inhibited in both cell types, this effect being more dramatic for those mRNA that accounted for most of the cell translation. Interestingly, we found two subsets comprising 1000-1500 mRNA whose translation resisted or was induced by stress. Translation arrest resistant class includes many mRNA encoding aminoacyl tRNA synthetases, ATPases and enzymes involved in DNA replication and stress response such as BiP. This class of mRNA is characterized by high translation rates in both control and stress conditions. Translation inducible class includes mRNA whose translation was relieved after stress, showing a high enrichment in early response transcription factors of bZIP and zinc finger C2H2 classes. Unlike yeast, a general coordination between changes in translation and transcription upon stress (potentiation) was not observed in mammalian cells. Among the different features of mRNA analyzed, we found a relevant association of translation efficiency with the presence of upstream ATG in the 5{\textquoteright}UTR and with the length of coding sequence of mRNA, and a looser association with other parameters such as the length and the G+C content of 5{\textquoteright}UTR. A model for translatome remodeling during the acute phase of stress response in mammalian cells is proposed.

}, keywords = {Animals, Endoplasmic Reticulum Stress, Humans, Jurkat Cells, Mice, NIH 3T3 Cells, Oligonucleotide Array Sequence Analysis, Protein Biosynthesis, RNA, Messenger, Transcription, Genetic}, issn = {1932-6203}, doi = {10.1371/journal.pone.0035915}, author = {Ventoso, Iv{\'a}n and Kochetov, Alex and Montaner, David and Dopazo, Joaquin and Santoyo, Javier} } @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 {529, title = {Differential expression in RNA-seq: a matter of depth.}, journal = {Genome Res}, volume = {21}, year = {2011}, month = {2011 Dec}, pages = {2213-23}, abstract = {

Next-generation sequencing (NGS) technologies are revolutionizing genome research, and in particular, their application to transcriptomics (RNA-seq) is increasingly being used for gene expression profiling as a replacement for microarrays. However, the properties of RNA-seq data have not been yet fully established, and additional research is needed for understanding how these data respond to differential expression analysis. In this work, we set out to gain insights into the characteristics of RNA-seq data analysis by studying an important parameter of this technology: the sequencing depth. We have analyzed how sequencing depth affects the detection of transcripts and their identification as differentially expressed, looking at aspects such as transcript biotype, length, expression level, and fold-change. We have evaluated different algorithms available for the analysis of RNA-seq and proposed a novel approach--NOISeq--that differs from existing methods in that it is data-adaptive and nonparametric. Our results reveal that most existing methodologies suffer from a strong dependency on sequencing depth for their differential expression calls and that this results in a considerable number of false positives that increases as the number of reads grows. In contrast, our proposed method models the noise distribution from the actual data, can therefore better adapt to the size of the data set, and is more effective in controlling the rate of false discoveries. This work discusses the true potential of RNA-seq for studying regulation at low expression ranges, the noise within RNA-seq data, and the issue of replication.

}, keywords = {Algorithms, Expressed Sequence Tags, Gene Expression Profiling, Gene Expression Regulation, Humans, Models, Genetic, Oligonucleotide Array Sequence Analysis}, issn = {1549-5469}, doi = {10.1101/gr.124321.111}, author = {Tarazona, Sonia and Garc{\'\i}a-Alcalde, Fernando and Dopazo, Joaquin and Ferrer, Alberto and Conesa, Ana} } @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 {536, title = {Mutation screening of multiple genes in Spanish patients with autosomal recessive retinitis pigmentosa by targeted resequencing.}, journal = {PLoS One}, volume = {6}, year = {2011}, month = {2011}, pages = {e27894}, abstract = {

Retinitis Pigmentosa (RP) is a heterogeneous group of inherited retinal dystrophies characterised ultimately by the loss of photoreceptor cells. RP is the leading cause of visual loss in individuals younger than 60 years, with a prevalence of about 1 in 4000. The molecular genetic diagnosis of autosomal recessive RP (arRP) is challenging due to the large genetic and clinical heterogeneity. Traditional methods for sequencing arRP genes are often laborious and not easily available and a screening technique that enables the rapid detection of the genetic cause would be very helpful in the clinical practice. The goal of this study was to develop and apply microarray-based resequencing technology capable of detecting both known and novel mutations on a single high-throughput platform. Hence, the coding regions and exon/intron boundaries of 16 arRP genes were resequenced using microarrays in 102 Spanish patients with clinical diagnosis of arRP. All the detected variations were confirmed by direct sequencing and potential pathogenicity was assessed by functional predictions and frequency in controls. For validation purposes 4 positive controls for variants consisting of previously identified changes were hybridized on the array. As a result of the screening, we detected 44 variants, of which 15 are very likely pathogenic detected in 14 arRP families (14\%). Finally, the design of this array can easily be transformed in an equivalent diagnostic system based on targeted enrichment followed by next generation sequencing.

}, keywords = {Alleles, DNA Mutational Analysis, Exons, Genetic Variation, Genome, Hispanic or Latino, Humans, Introns, Language, mutation, Mutation, Missense, Oligonucleotide Array Sequence Analysis, Polymerase Chain Reaction, Reproducibility of Results, Retinitis pigmentosa, United States}, issn = {1932-6203}, doi = {10.1371/journal.pone.0027894}, author = {Gonz{\'a}lez-del Pozo, Mar{\'\i}a and Borrego, Salud and Barrag{\'a}n, Isabel and Pieras, Juan I and Santoyo, Javier and Matamala, Nerea and Naranjo, Bel{\'e}n and Dopazo, Joaquin and Anti{\v n}olo, Guillermo} } @article {547, title = {DNA methylation epigenotypes in breast cancer molecular subtypes.}, journal = {Breast Cancer Res}, volume = {12}, year = {2010}, month = {2010}, pages = {R77}, abstract = {

INTRODUCTION: Identification of gene expression based breast cancer subtypes is considered as a critical means of prognostication. Genetic mutations along with epigenetic alterations contribute to gene expression changes occurring in breast cancer. So far, these epigenetic contributions to sporadic breast cancer subtypes have not been well characterized, and there is only a limited understanding of the epigenetic mechanisms affected in those particular breast cancer subtypes. The present study was undertaken to dissect the breast cancer methylome and deliver specific epigenotypes associated with particular breast cancer subtypes.

METHODS: Using a microarray approach we analyzed DNA methylation in regulatory regions of 806 cancer related genes in 28 breast cancer paired samples. We subsequently performed substantial technical and biological validation by Pyrosequencing, investigating the top qualifying 19 CpG regions in independent cohorts encompassing 47 basal-like, 44 ERBB2+ overexpressing, 48 luminal A and 48 luminal B paired breast cancer/adjacent tissues. Using all-subset selection method, we identified the most subtype predictive methylation profiles in multivariable logistic regression analysis.

RESULTS: The approach efficiently recognized 15 individual CpG loci differentially methylated in breast cancer tumor subtypes. We further identify novel subtype specific epigenotypes which clearly demonstrate the differences in the methylation profiles of basal-like and human epidermal growth factor 2 (HER2)-overexpressing tumors.

CONCLUSIONS: Our results provide evidence that well defined DNA methylation profiles enables breast cancer subtype prediction and support the utilization of this biomarker for prognostication and therapeutic stratification of patients with breast cancer.

}, keywords = {Aged, Breast Neoplasms, CpG Islands, DNA Methylation, Epigenesis, Genetic, Female, Gene Expression Profiling, Genes, p53, Genotype, Humans, Ki-67 Antigen, Middle Aged, mutation, Neoplasm Grading, Oligonucleotide Array Sequence Analysis, Receptor, ErbB-2, Tumor Suppressor Protein p53}, issn = {1465-542X}, doi = {10.1186/bcr2721}, author = {Bediaga, Naiara G and Acha-Sagredo, Amelia and Guerra, Isabel and Viguri, Amparo and Albaina, Carmen and Ruiz Diaz, Irune and Rezola, Ricardo and Alberdi, Maria Jesus and Dopazo, Joaquin and Montaner, David and Renobales, Mertxe and Fernandez, Agustin F and Field, John K and Fraga, Mario F and Liloglou, Triantafillos and de Pancorbo, Marian M} } @article {553, title = {Functional genomics of 5- to 8-cell stage human embryos by blastomere single-cell cDNA analysis.}, journal = {PLoS One}, volume = {5}, year = {2010}, month = {2010 Oct 26}, pages = {e13615}, abstract = {

Blastomere fate and embryonic genome activation (EGA) during human embryonic development are unsolved areas of high scientific and clinical interest. Forty-nine blastomeres from 5- to 8-cell human embryos have been investigated following an efficient single-cell cDNA amplification protocol to provide a template for high-density microarray analysis. The previously described markers, characteristic of Inner Cell Mass (ICM) (n = 120), stemness (n = 190) and Trophectoderm (TE) (n = 45), were analyzed, and a housekeeping pattern of 46 genes was established. All the human blastomeres from the 5- to 8-cell stage embryo displayed a common gene expression pattern corresponding to ICM markers (e.g., DDX3, FOXD3, LEFTY1, MYC, NANOG, POU5F1), stemness (e.g., POU5F1, DNMT3B, GABRB3, SOX2, ZFP42, TERT), and TE markers (e.g., GATA6, EOMES, CDX2, LHCGR). The EGA profile was also investigated between the 5-6- and 8-cell stage embryos, and compared to the blastocyst stage. Known genes (n = 92) such as depleted maternal transcripts (e.g., CCNA1, CCNB1, DPPA2) and embryo-specific activation (e.g., POU5F1, CDH1, DPPA4), as well as novel genes, were confirmed. In summary, the global single-cell cDNA amplification microarray analysis of the 5- to 8-cell stage human embryos reveals that blastomere fate is not committed to ICM or TE. Finally, new EGA features in human embryogenesis are presented.

}, keywords = {Blastomeres, DNA, Complementary, Gene Expression Profiling, Genomics, Humans, Oligonucleotide Array Sequence Analysis}, issn = {1932-6203}, doi = {10.1371/journal.pone.0013615}, author = {Galan, Amparo and Montaner, David and P{\'o}o, M Eugenia and Valbuena, Diana and Ruiz, Veronica and Aguilar, Crist{\'o}bal and Dopazo, Joaquin and Simon, Carlos} } @article {576, title = {Serial Expression Analysis: a web tool for the analysis of serial gene expression data.}, journal = {Nucleic Acids Res}, volume = {38}, year = {2010}, month = {2010 Jul}, pages = {W239-45}, abstract = {

Serial transcriptomics experiments investigate the dynamics of gene expression changes associated with a quantitative variable such as time or dosage. The statistical analysis of these data implies the study of global and gene-specific expression trends, the identification of significant serial changes, the comparison of expression profiles and the assessment of transcriptional changes in terms of cellular processes. We have created the SEA (Serial Expression Analysis) suite to provide a complete web-based resource for the analysis of serial transcriptomics data. SEA offers five different algorithms based on univariate, multivariate and functional profiling strategies framed within a user-friendly interface and a project-oriented architecture to facilitate the analysis of serial gene expression data sets from different perspectives. SEA is available at sea.bioinfo.cipf.es.

}, keywords = {Algorithms, Gene Expression Profiling, Internet, Kinetics, Linear Models, Oligonucleotide Array Sequence Analysis, Software}, issn = {1362-4962}, doi = {10.1093/nar/gkq488}, author = {Nueda, Maria Jos{\'e} and Carbonell, Jos{\'e} and Medina, Ignacio and Dopazo, Joaquin and Conesa, Ana} } @article {578, title = {Exploring the antimicrobial action of a carbon monoxide-releasing compound through whole-genome transcription profiling of Escherichia coli.}, journal = {Microbiology (Reading)}, volume = {155}, year = {2009}, month = {2009 Mar}, pages = {813-824}, abstract = {

We recently reported that carbon monoxide (CO) has bactericidal activity. To understand its mode of action we analysed the gene expression changes occurring when Escherichia coli, grown aerobically and anaerobically, is treated with the CO-releasing molecule CORM-2 (tricarbonyldichlororuthenium(II) dimer). Microarray analysis shows that the E. coli CORM-2 response is multifaceted, with a high number of differentially regulated genes spread through several functional categories, namely genes involved in inorganic ion transport and metabolism, regulators, and genes implicated in post-translational modification, such as chaperones. CORM-2 has a higher impact in E. coli cells grown anaerobically, as judged by the repression of genes belonging to eight functional classes which are not seen in the response of aerobically CORM-2-treated cells. The biological relevance of the variations caused by CORM-2 was substantiated by studying the CORM-2 sensitivity of selected E. coli mutants. The results show that the deletion of redox-sensing regulators SoxS and OxyR increased the sensitivity to CORM-2 and suggest that while SoxS plays an important role in protection against CORM-2 under both growth conditions, OxyR seems to participate only in the aerobic CORM-2 response. Under anaerobic conditions, we found that the heat-shock proteins IbpA and IbpB contribute to CORM-2 defence since the deletion of these genes increases the sensitivity of the strain. The induction of several met genes and the hypersensitivity to CORM-2 of the DeltametR, DeltametI and DeltametN mutant strains suggest that CO has effects on the methionine metabolism of E. coli. CORM-2 also affects the transcription of several E. coli biofilm-related genes and increases biofilm formation in E. coli. In particular, the absence of tqsA or bhsA increases the resistance of E. coli to CORM-2, and deletion of tsqA leads to a strain that has lost its capacity to form biofilm upon treatment with CORM-2. In spite of the relatively stable nature of the CO molecule, our results show that CO is able to trigger a significant alteration in the transcriptome of E. coli which necessarily has effects in several key metabolic pathways.

}, keywords = {Biofilms, Carbon Monoxide, Escherichia coli, Escherichia coli Proteins, Gene Expression Profiling, Gene Expression Regulation, Bacterial, Genes, Bacterial, Genes, Regulator, Genetic Complementation Test, Methionine, Microbial Viability, mutation, Oligonucleotide Array Sequence Analysis, Organometallic Compounds, Phenotype, RNA, Bacterial}, issn = {1350-0872}, doi = {10.1099/mic.0.023911-0}, author = {Nobre, L{\'\i}gia S and Al-Shahrour, F{\'a}tima and Dopazo, Joaquin and Saraiva, L{\'\i}gia M} } @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 {581, title = {Functional signatures identified in B-cell non-Hodgkin lymphoma profiles.}, journal = {Leuk Lymphoma}, volume = {50}, year = {2009}, month = {2009 Oct}, pages = {1699-708}, abstract = {

Gene-expression profiling in B-cell lymphomas has provided crucial data on specific lymphoma types, which can contribute to the identification of essential lymphoma survival genes and pathways. In this study, the gene-expression profiling data of all major B-cell lymphoma types were analyzed by unsupervised clustering. The transcriptome classification so obtained, was explored using gene set enrichment analysis generating a heatmap for B-cell lymphoma that identifies common lymphoma survival mechanisms and potential therapeutic targets, recognizing sets of coregulated genes and functional pathways expressed in different lymphoma types. Some of the most relevant signatures (stroma, cell cycle, B-cell receptor (BCR)) are shared by multiple lymphoma types or subclasses. A specific attention was paid to the analysis of BCR and coregulated pathways, defining molecular heterogeneity within multiple B-cell lymphoma types.

}, keywords = {Adult, Cluster Analysis, Gene Expression Profiling, Gene Expression Regulation, Leukemic, Genetic Heterogeneity, Humans, Lymphoma, B-Cell, Neoplasm Proteins, Oligonucleotide Array Sequence Analysis, RNA, Messenger, RNA, Neoplasm, Transcription, Genetic}, issn = {1029-2403}, doi = {10.1080/10428190903189035}, author = {Aggarwal, Mohit and S{\'a}nchez-Beato, Margarita and G{\'o}mez-L{\'o}pez, Gonzalo and Al-Shahrour, F{\'a}tima and Mart{\'\i}nez, Nerea and Rodr{\'\i}guez, Antonia and Ruiz-Ballesteros, Elena and Camacho, Francisca I and P{\'e}rez-Rosado, Alberto and de la Cueva, Paloma and Artiga, Mar{\'\i}a J and Pisano, David G and Kimby, Eva and Dopazo, Joaquin and Villuendas, Raquel and Piris, Miguel A} } @article {582, title = {Gene set internal coherence in the context of functional profiling.}, journal = {BMC Genomics}, volume = {10}, year = {2009}, month = {2009 Apr 27}, pages = {197}, abstract = {

BACKGROUND: Functional profiling methods have been extensively used in the context of high-throughput experiments and, in particular, in microarray data analysis. Such methods use available biological information to define different types of functional gene modules (e.g. gene ontology -GO-, KEGG pathways, etc.) whose representation in a pre-defined list of genes is further studied. In the most popular type of microarray experimental designs (e.g. up- or down-regulated genes, clusters of co-expressing genes, etc.) or in other genomic experiments (e.g. Chip-on-chip, epigenomics, etc.) these lists are composed by genes with a high degree of co-expression. Therefore, an implicit assumption in the application of functional profiling methods within this context is that the genes corresponding to the modules tested are effectively defining sets of co-expressing genes. Nevertheless not all the functional modules are biologically coherent entities in terms of co-expression, which will eventually hinder its detection with conventional methods of functional enrichment.

RESULTS: Using a large collection of microarray data we have carried out a detailed survey of internal correlation in GO terms and KEGG pathways, providing a coherence index to be used for measuring functional module co-regulation. An unexpected low level of internal correlation was found among the modules studied. Only around 30\% of the modules defined by GO terms and 57\% of the modules defined by KEGG pathways display an internal correlation higher than the expected by chance.This information on the internal correlation of the genes within the functional modules can be used in the context of a logistic regression model in a simple way to improve their detection in gene expression experiments.

CONCLUSION: For the first time, an exhaustive study on the internal co-expression of the most popular functional categories has been carried out. Interestingly, the real level of coexpression within many of them is lower than expected (or even inexistent), which will preclude its detection by means of most conventional functional profiling methods. If the gene-to-function correlation information is used in functional profiling methods, the results obtained improve the ones obtained by conventional enrichment methods.

}, keywords = {Algorithms, Breast Neoplasms, Carcinoma, Intraductal, Noninfiltrating, Computational Biology, Databases, Nucleic Acid, Female, Gene Expression Profiling, Genomics, Humans, Oligonucleotide Array Sequence Analysis, Papillomavirus Infections, Reproducibility of Results}, issn = {1471-2164}, doi = {10.1186/1471-2164-10-197}, author = {Montaner, David and Minguez, Pablo and Al-Shahrour, F{\'a}tima and Dopazo, Joaquin} } @article {591, title = {Expression and microarrays.}, journal = {Methods Mol Biol}, volume = {453}, year = {2008}, month = {2008}, pages = {245-55}, abstract = {

High throughput methodologies have increased by several orders of magnitude the amount of experimental microarray data available. Nevertheless, translating these data into useful biological knowledge remains a challenge. There is a risk of perceiving these methodologies as mere factories that produce never-ending quantities of data if a proper biological interpretation is not provided. Methods of interpreting these data are continuously evolving. Typically, a simple two-step approach has been used, in which genes of interest are first selected based on thresholds for the experimental values, and then enrichment in biologically relevant terms in the annotations of these genes is analyzed in a second step. For various reasons, such methods are quite poor in terms of performance and new procedures inspired by systems biology that directly address sets of functionally related genes are currently under development.

}, keywords = {Animals, Computational Biology, gene expression, Gene Expression Profiling, Humans, Oligonucleotide Array Sequence Analysis}, issn = {1064-3745}, doi = {10.1007/978-1-60327-429-6_12}, author = {Dopazo, Joaquin and Al-Shahrour, F{\'a}tima} } @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} } @article {605, title = {FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments.}, journal = {Nucleic Acids Res}, volume = {35}, year = {2007}, month = {2007 Jul}, pages = {W91-6}, abstract = {

The ultimate goal of any genome-scale experiment is to provide a functional interpretation of the data, relating the available information with the hypotheses that originated the experiment. Thus, functional profiling methods have become essential in diverse scenarios such as microarray experiments, proteomics, etc. We present the FatiGO+, a web-based tool for the functional profiling of genome-scale experiments, specially oriented to the interpretation of microarray experiments. In addition to different functional annotations (gene ontology, KEGG pathways, Interpro motifs, Swissprot keywords and text-mining based bioentities related to diseases and chemical compounds) FatiGO+ includes, as a novelty, regulatory and structural information. The regulatory information used includes predictions of targets for distinct regulatory elements (obtained from the Transfac and CisRed databases). Additionally FatiGO+ uses predictions of target motifs of miRNA to infer which of these can be activated or deactivated in the sample of genes studied. Finally, properties of gene products related to their relative location and connections in the interactome have also been used. Also, enrichment of any of these functional terms can be directly analysed on chromosomal coordinates. FatiGO+ can be found at: http://www.fatigoplus.org and within the Babelomics environment http://www.babelomics.org.

}, keywords = {Amino Acid Motifs, Animals, Binding Sites, Computational Biology, Gene Expression Profiling, Genes, Genomics, Humans, Internet, Oligonucleotide Array Sequence Analysis, Programming Languages, Software, Systems Integration, Transcription Factors}, issn = {1362-4962}, doi = {10.1093/nar/gkm260}, author = {Al-Shahrour, F{\'a}tima and Minguez, Pablo and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Alloza, Eva and Montaner, David and Dopazo, Joaquin} } @article {608, title = {ISACGH: a web-based environment for the analysis of Array CGH and gene expression which includes functional profiling.}, journal = {Nucleic Acids Res}, volume = {35}, year = {2007}, month = {2007 Jul}, pages = {W81-5}, abstract = {

We present the ISACGH, a web-based system that allows for the combination of genomic data with gene expression values and provides different options for functional profiling of the regions found. Several visualization options offer a convenient representation of the results. Different efficient methods for accurate estimation of genomic copy number from array-CGH hybridization data have been included in the program. Moreover, the connection to the gene expression analysis package GEPAS allows the use of different facilities for data pre-processing and analysis. A DAS server allows exporting the results to the Ensembl viewer where contextual genomic information can be obtained. The program is freely available at: http://isacgh.bioinfo.cipf.es or within http://www.gepas.org.

}, keywords = {Animals, Cluster Analysis, Computational Biology, Computer Graphics, Gene Expression Profiling, Humans, Internet, Models, Genetic, Nucleic Acid Hybridization, Oligonucleotide Array Sequence Analysis, Programming Languages, Software, Systems Integration, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gkm257}, author = {Conde, Lucia and Montaner, David and Burguet-Castell, Jordi and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Al-Shahrour, F{\'a}tima and Dopazo, Joaquin} }