@article {1115, title = {Involvement of a citrus meiotic recombination TTC-repeat motif in the formation of gross deletions generated by ionizing radiation and MULE activation.}, journal = {BMC genomics}, volume = {16}, year = {2015}, month = {2015 Feb 13}, pages = {69}, abstract = {BACKGROUND: 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{\textquoteright} 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.}, issn = {1471-2164}, doi = {10.1186/s12864-015-1280-3}, url = {http://www.biomedcentral.com/1471-2164/16/69}, author = {Terol, Javier and Iba{\~n}ez, Victoria and Carbonell, Jos{\'e} and Alonso, Roberto and Estornell, Leandro H and Licciardello, Concetta and Gut, Ivo G and Joaqu{\'\i}n Dopazo and Talon, Manuel} } @article {563, title = {Involvement of a citrus meiotic recombination TTC-repeat motif in the formation of gross deletions generated by ionizing radiation and MULE activation}, journal = {BMC Genomics}, volume = {16}, year = {2015}, month = {Feb}, pages = {69}, abstract = {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.}, issn = {1471-2164}, doi = {10.1186/s12864-015-1280-3}, url = {https://doi.org/10.1186/s12864-015-1280-3}, author = {Terol, Javier and Iba{\~n}ez, Victoria and Carbonell, Jos{\'e} and Alonso, Roberto and Estornell, Leandro H. and Licciardello, Concetta and Gut, Ivo G. and Dopazo, Joaquin and Talon, Manuel} } @article {500, title = {Inferring the functional effect of gene expression changes in signaling pathways.}, journal = {Nucleic Acids Res}, volume = {41}, year = {2013}, month = {2013 Jul}, pages = {W213-7}, abstract = {

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/.

}, keywords = {Animals, Humans, Internet, Mice, Models, Statistical, Receptors, Cell Surface, Signal Transduction, Software, Transcriptome}, issn = {1362-4962}, doi = {10.1093/nar/gkt451}, author = {Sebasti{\'a}n-Leon, Patricia and Carbonell, Jos{\'e} and Salavert, Francisco and S{\'a}nchez, Rub{\'e}n and Medina, Ignacio and Dopazo, Joaquin} } @article {920, title = {A map of human microRNA variation uncovers unexpectedly high levels of variability.}, journal = {Genome medicine}, volume = {4}, year = {2012}, month = {2012 Aug 20}, pages = {62}, abstract = {ABSTRACT: 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.}, keywords = {NGS}, issn = {1756-994X}, doi = {10.1186/gm363}, url = {http://genomemedicine.com/content/4/8/62/abstract}, author = {Carbonell, Jos{\'e} and Alloza, Eva and Arce, Pablo and Borrego, Salud and Santoyo, Javier and Ruiz-Ferrer, Macarena and Medina, Ignacio and Jim{\'e}nez-Almaz{\'a}n, Jorge and M{\'e}ndez-Vidal, Cristina and Gonz{\'a}lez-del Pozo, Mar{\'\i}a and Vela, Alicia and Bhattacharya, Shomi S and Anti{\v n}olo, Guillermo and Dopazo, Joaquin} } @article {938, title = {Qualimap: evaluating next-generation sequencing alignment data.}, journal = {Bioinformatics (Oxford, England)}, volume = {28}, year = {2012}, month = {2012 Oct 15}, pages = {2678-9}, abstract = {MOTIVATION: 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.}, keywords = {NGS}, issn = {1367-4811}, doi = {10.1093/bioinformatics/bts503}, url = {http://bioinformatics.oxfordjournals.org/content/28/20/2678.long}, author = {Garc{\'\i}a-Alcalde, Fernando and Okonechnikov, Konstantin and Carbonell, Jos{\'e} and Cruz, Luis M and G{\"o}tz, Stefan and Sonia Tarazona and Joaqu{\'\i}n Dopazo and Meyer, Thomas F and Ana Conesa} } @article {539, title = {Phylemon 2.0: a suite of web-tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing.}, journal = {Nucleic Acids Res}, volume = {39}, year = {2011}, month = {2011 Jul}, pages = {W470-4}, abstract = {

Phylemon 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.

}, keywords = {Evolution, Molecular, Genomics, Internet, Phylogeny, Sequence Alignment, Software}, issn = {1362-4962}, doi = {10.1093/nar/gkr408}, author = {S{\'a}nchez, Rub{\'e}n and Serra, Fran{\c c}ois and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Carbonell, Jos{\'e} and Pulido, Luis and De Maria, Alejandro and Capella-Gut{\'\i}errez, Salvador and Huerta-Cepas, Jaime and Gabald{\'o}n, Toni and Dopazo, Joaquin and Dopazo, Hern{\'a}n} } @article {20478823, title = {Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling.}, journal = {Nucleic Acids Research}, volume = {38}, year = {2010}, month = {2010 May 16}, pages = {W210-W213. Featured in NAR}, chapter = {Featured in NAR}, abstract = {

Babelomics 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.

}, keywords = {babelomics, gene expression, genotyping, gepas, GSA, GWAS}, url = {http://nar.oxfordjournals.org/content/38/suppl_2/W210.full}, author = {Medina, Ignacio and Carbonell, Jos{\'e} and Pulido, Luis and Madeira, Sara C and Goetz, Stefan and Ana Conesa and T{\'a}rraga, Joaqu{\'\i}n and Pascual-Montano, Alberto and Nogales-Cadenas, Ruben and Santoyo, Javier and Garc{\'\i}a, Francisco and Marb{\`a}, Martina and Montaner, David and Joaqu{\'\i}n Dopazo} } @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 {IgnacioMedina07012009, title = {Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies}, journal = {Nucl. Acids Res.}, volume = {37}, number = {suppl_2}, year = {2009}, pages = {W340-344}, abstract = {

Genome-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/

}, keywords = {babelomics, gene set, GESBAP, pathway-based analysis, SNP}, doi = {10.1093/nar/gkp481}, url = {http://nar.oxfordjournals.org/cgi/content/abstract/37/suppl_2/W340}, author = {Medina, Ignacio and Montaner, David and Bonifaci, N{\'u}ria and Pujana, Miguel Angel and Carbonell, Jos{\'e} and T{\'a}rraga, Joaqu{\'\i}n and Fatima Al-Shahrour and Dopazo, Joaquin} } @article {583, title = {Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies.}, journal = {Nucleic Acids Res}, volume = {37}, year = {2009}, month = {2009 Jul}, pages = {W340-4}, abstract = {

Genome-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/.

}, keywords = {Biological Phenomena, Breast Neoplasms, Female, Genes, Genetic Variation, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Software, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gkp481}, author = {Medina, Ignacio and Montaner, David and Bonifaci, N{\'u}ria and Pujana, Miguel Angel and Carbonell, Jos{\'e} and T{\'a}rraga, Joaqu{\'\i}n and Al-Shahrour, F{\'a}tima and Dopazo, Joaquin} } @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} }