01104nas a2200241 4500008004100000022001400041245015500055210006900210260000800279300000700287490000700294520032500301100001800626700002200644700002100666700002000687700002700707700002700734700001700761700002000778700001800798856004600816 2015 eng d a1471-216400aInvolvement of a citrus meiotic recombination TTC-repeat motif in the formation of gross deletions generated by ionizing radiation and MULE activation0 aInvolvement of a citrus meiotic recombination TTCrepeat motif in cFeb a690 v163 aTransposable-element mediated chromosomal rearrangements require the involvement of two transposons and two double-strand breaks (DSB) located in close proximity. In radiobiology, DSB proximity is also a major factor contributing to rearrangements. However, the whole issue of DSB proximity remains virtually unexplored.1 aTerol, Javier1 aIbañez, Victoria1 aCarbonell, José1 aAlonso, Roberto1 aEstornell, Leandro, H.1 aLicciardello, Concetta1 aGut, Ivo, G.1 aDopazo, Joaquin1 aTalon, Manuel uhttps://doi.org/10.1186/s12864-015-1280-302538nas a2200241 4500008004100000022001400041245015600055210006900211260001600280300000700296490000700303520174800310100001802058700002202076700002102098700002002119700002602139700002702165700001602192700002102208700001802229856004902247 2015 eng d a1471-216400aInvolvement of a citrus meiotic recombination TTC-repeat motif in the formation of gross deletions generated by ionizing radiation and MULE activation.0 aInvolvement of a citrus meiotic recombination TTCrepeat motif in c2015 Feb 13 a690 v163 aBACKGROUND: Transposable-element mediated chromosomal rearrangements require the involvement of two transposons and two double-strand breaks (DSB) located in close proximity. In radiobiology, DSB proximity is also a major factor contributing to rearrangements. However, the whole issue of DSB proximity remains virtually unexplored. RESULTS: Based on DNA sequencing analysis we show that the genomes of 2 derived mutations, Arrufatina (sport) and Nero (irradiation), share a similar 2 Mb deletion of chromosome 3. A 7 kb Mutator-like element found in Clemenules was present in Arrufatina in inverted orientation flanking the 5’ end of the deletion. The Arrufatina Mule displayed "dissimilar" 9-bp target site duplications separated by 2 Mb. Fine-scale single nucleotide variant analyses of the deleted fragments identified a TTC-repeat sequence motif located in the center of the deletion responsible of a meiotic crossover detected in the citrus reference genome. CONCLUSIONS: Taken together, this information is compatible with the proposal that in both mutants, the TTC-repeat motif formed a triplex DNA structure generating a loop that brought in close proximity the originally distinct reactive ends. In Arrufatina, the loop brought the Mule ends nearby the 2 distinct insertion target sites and the inverted insertion of the transposable element between these target sites provoked the release of the in-between fragment. This proposal requires the involvement of a unique transposon and sheds light on the unresolved question of how two distinct sites become located in close proximity. These observations confer a crucial role to the TTC-repeats in fundamental plant processes as meiotic recombination and chromosomal rearrangements.1 aTerol, Javier1 aIbañez, Victoria1 aCarbonell, José1 aAlonso, Roberto1 aEstornell, Leandro, H1 aLicciardello, Concetta1 aGut, Ivo, G1 aDopazo, Joaquín1 aTalon, Manuel uhttp://www.biomedcentral.com/1471-2164/16/6902231nas a2200313 4500008004100000022001400041245008600055210006900141260001300210300001100223490000700234520127400241653001201515653001101527653001301538653000901551653002401560653002801584653002401612653001301636653001801649100003001667700002101697700002401718700002101742700002001763700002001783856011401803 2013 eng d a1362-496200aInferring the functional effect of gene expression changes in signaling pathways.0 aInferring the functional effect of gene expression changes in si c2013 Jul aW213-70 v413 a
Signaling pathways constitute a valuable source of information that allows interpreting the way in which alterations in gene activities affect to particular cell functionalities. There are web tools available that allow viewing and editing pathways, as well as representing experimental data on them. However, few methods aimed to identify the signaling circuits, within a pathway, associated to the biological problem studied exist and none of them provide a convenient graphical web interface. We present PATHiWAYS, a web-based signaling pathway visualization system that infers changes in signaling that affect cell functionality from the measurements of gene expression values in typical expression microarray case-control experiments. A simple probabilistic model of the pathway is used to estimate the probabilities for signal transmission from any receptor to any final effector molecule (taking into account the pathway topology) using for this the individual probabilities of gene product presence/absence inferred from gene expression values. Significant changes in these probabilities allow linking different cell functionalities triggered by the pathway to the biological problem studied. PATHiWAYS is available at: http://pathiways.babelomics.org/.
10aAnimals10aHumans10aInternet10aMice10aModels, Statistical10aReceptors, Cell Surface10aSignal Transduction10aSoftware10aTranscriptome1 aSebastián-Leon, Patricia1 aCarbonell, José1 aSalavert, Francisco1 aSánchez, Rubén1 aMedina, Ignacio1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/inferring-functional-effect-gene-expression-changes-signaling-pathways02674nas a2200313 4500008004100000022001400041245008800055210006900143260001600212300000700228490000600235520174000241653000801981100002101989700001602010700001602026700001902042700002002061700002602081700002002107700002902127700002802156700003302184700001702217700002702234700002502261700002002286856005402306 2012 eng d a1756-994X00aA map of human microRNA variation uncovers unexpectedly high levels of variability.0 amap of human microRNA variation uncovers unexpectedly high level c2012 Aug 20 a620 v43 aABSTRACT: BACKGROUND: MicroRNAs (miRNAs) are key components of the gene regulatory network in many species. During the past few years, these regulatory elements have been shown to be involved in an increasing number and range of diseases. Consequently, the compilation of a comprehensive map of natural variability in healthy population seems an obvious requirement for future research on miRNA-related pathologies. METHODS: Data on 14 populations from the 1000 Genomes Project were analysed, along with new data extracted from 60 exomes of healthy individuals from a southern Spain population, sequenced in the context of the Medical Genome Project, to derive an accurate map of miRNA variability. RESULTS: Despite the common belief that miRNAs are highly conserved elements, analysis of the sequences of the 1,152 individuals indicated that the observed level of variability is double what was expected. A total of 527 variants were found. Among these, 45 variants affected the recognition region of the corresponding miRNA and were found in 43 different miRNAs, 26 of which are known to be involved in 57 diseases. Different parts of the mature structure of the miRNA were affected to different degrees by variants, which suggests the existence of a selective pressure related to the relative functional impact of the change. Moreover, 41 variants showed a significant deviation from the Hardy-Weinberg equilibrium, which supports the existence of a selective process against some alleles. The average number of variants per individual in miRNAs was 28. CONCLUSIONS: Despite an expectation that miRNAs would be highly conserved genomic elements, our study reports a level of variability comparable to that observed for coding genes.10aNGS1 aCarbonell, José1 aAlloza, Eva1 aArce, Pablo1 aBorrego, Salud1 aSantoyo, Javier1 aRuiz-Ferrer, Macarena1 aMedina, Ignacio1 aJiménez-Almazán, Jorge1 aMéndez-Vidal, Cristina1 adel Pozo, María, González-1 aVela, Alicia1 aBhattacharya, Shomi, S1 aAntiňolo, Guillermo1 aDopazo, Joaquin uhttp://genomemedicine.com/content/4/8/62/abstract01929nas a2200253 4500008004100000022001400041245006800055210006500123260001600188300001100204490000700215520118200222653000801404100003001412700002901442700002101471700001801492700001801510700002001528700002101548700002101569700001601590856006901606 2012 eng d a1367-481100aQualimap: evaluating next-generation sequencing alignment data.0 aQualimap evaluating nextgeneration sequencing alignment data c2012 Oct 15 a2678-90 v283 aMOTIVATION: The sequence alignment/map (SAM) and the binary alignment/map (BAM) formats have become the standard method of representation of nucleotide sequence alignments for next-generation sequencing data. SAM/BAM files usually contain information from tens to hundreds of millions of reads. Often, the sequencing technology, protocol and/or the selected mapping algorithm introduce some unwanted biases in these data. The systematic detection of such biases is a non-trivial task that is crucial to drive appropriate downstream analyses. RESULTS: We have developed Qualimap, a Java application that supports user-friendly quality control of mapping data, by considering sequence features and their genomic properties. Qualimap takes sequence alignment data and provides graphical and statistical analyses for the evaluation of data. Such quality-control data are vital for highlighting problems in the sequencing and/or mapping processes, which must be addressed prior to further analyses. AVAILABILITY: Qualimap is freely available from http://www.qualimap.org. CONTACT: aconesa@cipf.es SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.10aNGS1 aGarcía-Alcalde, Fernando1 aOkonechnikov, Konstantin1 aCarbonell, José1 aCruz, Luis, M1 aGötz, Stefan1 aTarazona, Sonia1 aDopazo, Joaquín1 aMeyer, Thomas, F1 aConesa, Ana uhttp://bioinformatics.oxfordjournals.org/content/28/20/2678.long02025nas a2200349 4500008004100000022001400041245011700055210006900172260001300241300001100254490000700265520090400272653002501176653001301201653001301214653001401227653002301241653001301264100002101277700002101298700002301319700002001342700002101362700001701383700002401400700003301424700002401457700002001481700002001501700002001521856013401541 2011 eng d a1362-496200aPhylemon 2.0: a suite of web-tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing.0 aPhylemon 20 a suite of webtools for molecular evolution phylogen c2011 Jul aW470-40 v393 aPhylemon 2.0 is a new release of the suite of web tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing. It has been designed as a response to the increasing demand of molecular sequence analyses for experts and non-expert users. Phylemon 2.0 has several unique features that differentiates it from other similar web resources: (i) it offers an integrated environment that enables evolutionary analyses, format conversion, file storage and edition of results; (ii) it suggests further analyses, thereby guiding the users through the web server; and (iii) it allows users to design and save phylogenetic pipelines to be used over multiple genes (phylogenomics). Altogether, Phylemon 2.0 integrates a suite of 30 tools covering sequence alignment reconstruction and trimming; tree reconstruction, visualization and manipulation; and evolutionary hypotheses testing.
10aEvolution, Molecular10aGenomics10aInternet10aPhylogeny10aSequence Alignment10aSoftware1 aSánchez, Rubén1 aSerra, François1 aTárraga, Joaquín1 aMedina, Ignacio1 aCarbonell, José1 aPulido, Luis1 aDe Maria, Alejandro1 aCapella-Gutíerrez, Salvador1 aHuerta-Cepas, Jaime1 aGabaldón, Toni1 aDopazo, Joaquin1 aDopazo, Hernán uhttps://www.clinbioinfosspa.es/content/phylemon-20-suite-web-tools-molecular-evolution-phylogenetics-phylogenomics-and-hypotheses02554nas a2200361 4500008004100000245014100041210006900182260001600251300003100267490000700298520145100305653001501756653002001771653001501791653001001806653000801816653000901824100002001833700002101853700001701874700002101891700001801912700001601930700002301946700002901969700002701998700002002025700002302045700002002068700002002088700002102108856006302129 2010 eng d00aBabelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling.0 aBabelomics an integrative platform for the analysis of transcrip c2010 May 16 aW210-W213. Featured in NAR0 v383 aBabelomics is a response to the growing necessity of integrating and analyzing different types of genomic data in an environment that allows an easy functional interpretation of the results. Babelomics includes a complete suite of methods for the analysis of gene expression data that include normalization (covering most commercial platforms), pre-processing, differential gene expression (case-controls, multiclass, survival or continuous values), predictors, clustering; large-scale genotyping assays (case controls and TDTs, and allows population stratification analysis and correction). All these genomic data analysis facilities are integrated and connected to multiple options for the functional interpretation of the experiments. Different methods of functional enrichment or gene set enrichment can be used to understand the functional basis of the experiment analyzed. Many sources of biological information, which include functional (GO, KEGG, Biocarta, Reactome, etc.), regulatory (Transfac, Jaspar, ORegAnno, miRNAs, etc.), text-mining or protein-protein interaction modules can be used for this purpose. Finally a tool for the de novo functional annotation of sequences has been included in the system. This provides support for the functional analysis of non-model species. Mirrors of Babelomics or command line execution of their individual components are now possible. Babelomics is available at http://www.babelomics.org.
10ababelomics10agene expression10agenotyping10agepas10aGSA10aGWAS1 aMedina, Ignacio1 aCarbonell, José1 aPulido, Luis1 aMadeira, Sara, C1 aGoetz, Stefan1 aConesa, Ana1 aTárraga, Joaquín1 aPascual-Montano, Alberto1 aNogales-Cadenas, Ruben1 aSantoyo, Javier1 aGarcía, Francisco1 aMarbà, Martina1 aMontaner, David1 aDopazo, Joaquín uhttp://nar.oxfordjournals.org/content/38/suppl_2/W210.full01786nas a2200277 4500008004100000022001400041245009200055210006900147260001300216300001200229490000700241520089700248653001501145653003001160653001301190653001301203653001801216653004401234653001301278100002401291700002101315700002001336700002001356700001601376856011601392 2010 eng d a1362-496200aSerial Expression Analysis: a web tool for the analysis of serial gene expression data.0 aSerial Expression Analysis a web tool for the analysis of serial c2010 Jul aW239-450 v383 aSerial 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.
10aAlgorithms10aGene Expression Profiling10aInternet10aKinetics10aLinear Models10aOligonucleotide Array Sequence Analysis10aSoftware1 aNueda, Maria, José1 aCarbonell, José1 aMedina, Ignacio1 aDopazo, Joaquin1 aConesa, Ana uhttps://www.clinbioinfosspa.es/content/serial-expression-analysis-web-tool-analysis-serial-gene-expression-data02028nas a2200349 4500008004100000022001400041245014400055210006900199260001300268300001100281490000700292520085700299653002501156653002101181653001101202653001001213653002201223653003401245653001101279653003601290653001301326653002801339100002001367700002001387700002101407700002601428700002101454700002301475700002501498700002001523856013501543 2009 eng d a1362-496200aGene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies.0 aGene setbased analysis of polymorphisms finding pathways or biol c2009 Jul aW340-40 v373 aGenome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap/.
10aBiological Phenomena10aBreast Neoplasms10aFemale10aGenes10aGenetic Variation10aGenome-Wide Association Study10aHumans10aPolymorphism, Single Nucleotide10aSoftware10aUser-Computer Interface1 aMedina, Ignacio1 aMontaner, David1 aBonifaci, Núria1 aPujana, Miguel, Angel1 aCarbonell, José1 aTárraga, Joaquín1 aAl-Shahrour, Fátima1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/gene-set-based-analysis-polymorphisms-finding-pathways-or-biological-processes-associated-001715nas a2200265 4500008004100000245014300041210006900184300001300253490000700266520085600273653001501129653001301144653001101157653002701168653000801195100002001203700002001223700002101243700002601264700002101290700002301311700002401334700002001358856007101378 2009 eng d00aGene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies0 aGene setbased analysis of polymorphisms finding pathways or biol aW340-3440 v373 aGenome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap/
10ababelomics10agene set10aGESBAP10apathway-based analysis10aSNP1 aMedina, Ignacio1 aMontaner, David1 aBonifaci, Núria1 aPujana, Miguel, Angel1 aCarbonell, José1 aTárraga, Joaquín1 aAl-Shahrour, Fatima1 aDopazo, Joaquin uhttp://nar.oxfordjournals.org/cgi/content/abstract/37/suppl_2/W34002503nas a2200385 4500008004100000022001400041245007700055210006900132260001600201300001200217490000700229520130100236653002201537653003701559653003001596653001301626653001301639653004401652653001301696100002301709700002001732700002101752700002401773700001901797700001601816700002501832700002801857700001801885700001901903700002901922700001601951700002001967700002001987856011002007 2008 eng d a1362-496200aGEPAS, a web-based tool for microarray data analysis and interpretation.0 aGEPAS a webbased tool for microarray data analysis and interpret c2008 Jul 01 aW308-140 v363 aGene 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.
10aComputer Graphics10aDose-Response Relationship, Drug10aGene Expression Profiling10aInternet10aKinetics10aOligonucleotide Array Sequence Analysis10aSoftware1 aTárraga, Joaquín1 aMedina, Ignacio1 aCarbonell, José1 aHuerta-Cepas, Jaime1 aMinguez, Pablo1 aAlloza, Eva1 aAl-Shahrour, Fátima1 aVegas-Azcárate, Susana1 aGoetz, Stefan1 aEscobar, Pablo1 aGarcia-Garcia, Francisco1 aConesa, Ana1 aMontaner, David1 aDopazo, Joaquin uhttps://www.clinbioinfosspa.es/content/gepas-web-based-tool-microarray-data-analysis-and-interpretation-0