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Joaquín Dopazo

Publications and source records attributed to Joaquín Dopazo.

At least 19 recordsLinked to original sources

Prophet, a web-based tool for class prediction using microarray data.

UNLABELLED: Sample classification and class prediction is the aim of many gene expression studies. We present a web-based application, Prophet, which builds prediction rules and allows using them for further sample classification. Prophet automatically chooses the best classifier, along with the optimal selection of genes, using a strategy that renders unbiased cross-validated errors. Prophet is linked to different microarray data analysis modules, and includes a unique feature: the possibility of performing the functional interpretation of the molecular signature found. AVAILABILITY: Prophet can be found at the URL http://prophet.bioinfo.cipf.es/ or within the GEPAS package at http://www.gepas.org/ SUPPLEMENTARY INFORMATION: http://gepas.bioinfo.cipf.es/tutorial/prophet.html.

Algorithms↗

ERCC4 associated with breast cancer risk: a two-stage case-control study using high-throughput genotyping.

The failure of linkage studies to identify further high-penetrance susceptibility genes for breast cancer points to a polygenic model, with more common variants having modest effects on risk, as the most likely candidate. We have carried out a two-stage case-control study in two European populations to identify low-penetrance genes for breast cancer using high-throughput genotyping. Single-nucleotide polymorphisms (SNPs) were selected across preselected cancer-related genes, choosing tagSNPs and functional variants where possible. In stage 1, genotype frequencies for 640 SNPs in 111 genes were compared between 864 breast cancer cases and 845 controls from the Spanish population. In stage 2, candidate SNPs identified in stage 1 (nominal P < 0.01) were tested in a Finnish series of 884 cases and 1,104 controls. Of the 10 candidate SNPs in seven genes identified in stage 1, one (rs744154) on intron 1 of ERCC4, a gene belonging to the nucleotide excision repair pathway, was associated with recessive protection from breast cancer after adjustment for multiple testing in stage 2 (odds ratio, 0.57; Bonferroni-adjusted P = 0.04). After considering potential functional SNPs in the region of high linkage disequilibrium that extends across the entire gene and upstream into the promoter region, we concluded that rs744154 itself could be causal. Although intronic, it is located on the first intron, in a region that is highly conserved across species, and could therefore be functionally important. This study suggests that common intronic variation in ERCC4 is associated with protection from breast cancer.

Adult↗

PupaSuite: finding functional single nucleotide polymorphisms for large-scale genotyping purposes.

We have developed a web tool, PupaSuite, for the selection of single nucleotide polymorphisms (SNPs) with potential phenotypic effect, specifically oriented to help in the design of large-scale genotyping projects. PupaSuite uses a collection of data on SNPs from heterogeneous sources and a large number of pre-calculated predictions to offer a flexible and intuitive interface for selecting an optimal set of SNPs. It improves the functionality of PupaSNP and PupasView programs and implements new facilities such as the analysis of user's data to derive haplotypes with functional information. A new estimator of putative effect of polymorphisms has been included that uses evolutionary information. Also SNPeffect database predictions have been included. The PupaSuite web interface is accessible through http://pupasuite.bioinfo.cipf.es and through http://www.pupasnp.org.

Algorithms↗

BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments.

We present a new version of Babelomics, a complete suite of web tools for functional analysis of genome-scale experiments, with new and improved tools. New functionally relevant terms have been included such as CisRed motifs or bioentities obtained by text-mining procedures. An improved indexing has considerably speeded up several of the modules. An improved version of the FatiScan method for studying the coordinate behaviour of groups of functionally related genes is presented, along with a similar tool, the Gene Set Enrichment Analysis. Babelomics is now more oriented to test systems biology inspired hypotheses. Babelomics can be found at http://www.babelomics.org.

Animals↗

Next station in microarray data analysis: GEPAS.

The Gene Expression Profile Analysis Suite (GEPAS) has been running for more than four years. During this time it has evolved to keep pace with the new interests and trends in the still changing world of microarray data analysis. GEPAS has been designed to provide an intuitive although powerful web-based interface that offers diverse analysis options from the early step of preprocessing (normalization of Affymetrix and two-colour microarray experiments and other preprocessing options), to the final step of the functional annotation of the experiment (using Gene Ontology, pathways, PubMed abstracts etc.), and include different possibilities for clustering, gene selection, class prediction and array-comparative genomic hybridization management. GEPAS is extensively used by researchers of many countries and its records indicate an average usage rate of 400 experiments per day. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://www.gepas.org.

Cluster Analysis↗

Positive selection, relaxation, and acceleration in the evolution of the human and chimp genome.

For years evolutionary biologists have been interested in searching for the genetic bases underlying humanness. Recent efforts at a large or a complete genomic scale have been conducted to search for positively selected genes in human and in chimp. However, recently developed methods allowing for a more sensitive and controlled approach in the detection of positive selection can be employed. Here, using 13,198 genes, we have deduced the sets of genes involved in rate acceleration, positive selection, and relaxation of selective constraints in human, in chimp, and in their ancestral lineage since the divergence from murids. Significant deviations from the strict molecular clock were observed in 469 human and in 651 chimp genes. The more stringent branch-site test of positive selection detected 108 human and 577 chimp positively selected genes. An important proportion of the positively selected genes did not show a significant acceleration in rates, and similarly, many of the accelerated genes did not show significant signals of positive selection. Functional differentiation of genes under rate acceleration, positive selection, and relaxation was not statistically significant between human and chimp with the exception of terms related to G-protein coupled receptors and sensory perception. Both of these were over-represented under relaxation in human in relation to chimp. Comparing differences between derived and ancestral lineages, a more conspicuous change in trends seems to have favored positive selection in the human lineage. Since most of the positively selected genes are different under the same functional categories between these species, we suggest that the individual roles of the alternative positively selected genes may be an important factor underlying biological differences between these species.

Adaptation, Biological↗

Selective pressures at a codon-level predict deleterious mutations in human disease genes.

Deleterious mutations affecting biological function of proteins are constantly being rejected by purifying selection from the gene pool. The non-synonymous/synonymous substitution rate ratio (omega) is a measure of selective pressure on amino acid replacement mutations for protein-coding genes. Different methods have been developed in order to predict non-synonymous changes affecting gene function. However, none has considered the estimation of selective constraints acting on protein residues. Here, we have used codon-based maximum likelihood models in order to estimate the selective pressures on the individual amino acid residues of a well-known model protein: p53. We demonstrate that the number of residues under strong purifying selection in p53 is much higher than those that are strictly conserved during the evolution of the species. In agreement with theoretical expectations, residues that have been noted to be of structural relevance, or in direct association with DNA, were among those showing the highest signals of purifying selection. Conversely, those changing according to a neutral, or nearly neutral mode of evolution, were observed to be irrelevant for protein function. Finally, using more than 40 human disease genes, we demonstrate that residues evolving under strong selective pressures (omega<0.1) are significantly associated (p<0.01) with human disease. We hypothesize that non-synonymous change on amino acids showing omega<0.1 will most likely affect protein function. The application of this evolutionary prediction at a genomic scale will provide an a priori hypothesis of the phenotypic effect of non-synonymous coding single nucleotide polymorphisms (SNPs) in the human genome.

Amino Acid Sequence↗

Bioinformatics and cancer: an essential alliance.

Modern research in cancer has been revolutionized by the introduction of new high-throughput methodologies such as DNA microarrays. Keeping the pace with these technologies, the bioinformatics offer new solutions for data analysis and, what is more important, it permits to formulate a new class of hypothesis inspired in systems biology, more oriented to blocks of functionally-related genes. Although software implementations for this new methodologies is new there are some options already available. Bioinformatic solutions for other high-throughput techniques such as array-CGH of large-scale genotyping is also revised.

Chromosome Aberrations↗

Functional interpretation of microarray experiments.

Over the past few years, due to the popularisation of high-throughput methodologies such as DNA microarrays, the possibility of obtaining experimental data has increased significantly. Nevertheless, the interpretation of the results, which involves translating these data into useful biological knowledge, still remains a challenge. The methods and strategies used for this interpretation are in continuous evolution and new proposals are constantly arising. Initially, a two-step approach was used in which genes of interest were initially selected, based on thresholds that consider only experimental values, and then in a second, independent step the enrichment of these genes in biologically relevant terms, was analysed. For different reasons, these methods are relatively poor in terms of performance and a new generation of procedures, which draw inspiration from systems biology criteria, are currently under development. Such procedures, aim to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes.

Diabetes Mellitus↗

BABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments.

We present Babelomics, a complete suite of web tools for the functional analysis of groups of genes in high-throughput experiments, which includes the use of information on Gene Ontology terms, interpro motifs, KEGG pathways, Swiss-Prot keywords, analysis of predicted transcription factor binding sites, chromosomal positions and presence in tissues with determined histological characteristics, through five integrated modules: FatiGO (fast assignment and transference of information), FatiWise, transcription factor association test, GenomeGO and tissues mining tool, respectively. Additionally, another module, FatiScan, provides a new procedure that integrates biological information in combination with experimental results in order to find groups of genes with modest but coordinate significant differential behaviour. FatiScan is highly sensitive and is capable of finding significant asymmetries in the distribution of genes of common function across a list of ordered genes even if these asymmetries were not extreme. The strong multiple-testing nature of the contrasts made by the tools is taken into account. All the tools are integrated in the gene expression analysis package GEPAS. Babelomics is the natural evolution of our tool FatiGO (which analysed almost 22,000 experiments during the last year) to include more sources on information and new modes of using it. Babelomics can be found at http://www.babelomics.org.

Binding Sites↗

PupasView: a visual tool for selecting suitable SNPs, with putative pathological effect in genes, for genotyping purposes.

We have developed a web tool, PupasView, for the selection of single nucleotide polymorphisms (SNPs) with potential phenotypic effect. PupasView constitutes an interactive environment in which functional information and population frequency data can be used as sequential filters over linkage disequilibrium parameters to obtain a final list of SNPs optimal for genotyping purposes. PupasView is the first resource that integrates phenotypic effects caused by SNPs at both the translational and the transcriptional level. PupasView retrieves SNPs that could affect conserved regions that the cellular machinery uses for the correct processing of genes (intron/exon boundaries or exonic splicing enhancers), predicted transcription factor binding sites and changes in amino acids in the proteins for which a putative pathological effect is calculated. The program uses the mapping of SNPs in the genome provided by Ensembl. PupasView will be of much help in studies of multifactorial disorders, where the use of functional SNPs will increase the sensitivity of the identification of the genes responsible for the disease. The PupasView web interface is accessible through http://pupasview.ochoa.fib.es and through http://www.pupasnp.org.

Computer Graphics↗

GEPAS, an experiment-oriented pipeline for the analysis of microarray gene expression data.

The Gene Expression Profile Analysis Suite, GEPAS, has been running for more than three years. With >76,000 experiments analysed during the last year and a daily average of almost 300 analyses, GEPAS can be considered a well-established and widely used platform for gene expression microarray data analysis. GEPAS is oriented to the analysis of whole series of experiments. Its design and development have been driven by the demands of the biomedical community, probably the most active collective in the field of microarray users. Although clustering methods have obviously been implemented in GEPAS, our interest has focused more on methods for finding genes differentially expressed among distinct classes of experiments or correlated to diverse clinical outcomes, as well as on building predictors. There is also a great interest in CGH-arrays which fostered the development of the corresponding tool in GEPAS: InSilicoCGH. Much effort has been invested in GEPAS for developing and implementing efficient methods for functional annotation of experiments in the proper statistical framework. Thus, the popular FatiGO has expanded to a suite of programs for functional annotation of experiments, including information on transcription factor binding sites, chromosomal location and tissues. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://www.gepas.org.

Algorithms↗

Genome-scale evidence of the nematode-arthropod clade.

BACKGROUND: The issue of whether coelomates form a single clade, the Coelomata, or whether all animals that moult an exoskeleton (such as the coelomate arthropods and the pseudocoelomate nematodes) form a distinct clade, the Ecdysozoa, is the most puzzling issue in animal systematics and a major open-ended subject in evolutionary biology. Previous single-gene and genome-scale analyses designed to resolve the issue have produced contradictory results. Here we present the first genome-scale phylogenetic evidence that strongly supports the Ecdysozoa hypothesis. RESULTS: Through the most extensive phylogenetic analysis carried out to date, the complete genomes of 11 eukaryotic species have been analyzed in order to find homologous sequences derived from 18 human chromosomes. Phylogenetic analysis of datasets showing an increased adjustment to equal evolutionary rates between nematode and arthropod sequences produced a gradual change from support for Coelomata to support for Ecdysozoa. Transition between topologies occurred when fast-evolving sequences of Caenorhabditis elegans were removed. When chordate, nematode and arthropod sequences were constrained to fit equal evolutionary rates, the Ecdysozoa topology was statistically accepted whereas Coelomata was rejected. CONCLUSIONS: The reliability of a monophyletic group clustering arthropods and nematodes was unequivocally accepted in datasets where traces of the long-branch attraction effect were removed. This is the first phylogenomic evidence to strongly support the 'moulting clade' hypothesis.

Animals↗

Discovering molecular functions significantly related to phenotypes by combining gene expression data and biological information.

MOTIVATION: The analysis of genome-scale data from different high throughput techniques can be used to obtain lists of genes ordered according to their different behaviours under distinct experimental conditions corresponding to different phenotypes (e.g. differential gene expression between diseased samples and controls, different response to a drug, etc.). The order in which the genes appear in the list is a consequence of the biological roles that the genes play within the cell, which account, at molecular scale, for the macroscopic differences observed between the phenotypes studied. Typically, two steps are followed for understanding the biological processes that differentiate phenotypes at molecular level: first, genes with significant differential expression are selected on the basis of their experimental values and subsequently, the functional properties of these genes are analysed. Instead, we present a simple procedure which combines experimental measurements with available biological information in a way that genes are simultaneously tested in groups related by common functional properties. The method proposed constitutes a very sensitive tool for selecting genes with significant differential behaviour in the experimental conditions tested. RESULTS: We propose the use of a method to scan ordered lists of genes. The method allows the understanding of the biological processes operating at molecular level behind the macroscopic experiment from which the list was generated. This procedure can be useful in situations where it is not possible to obtain statistically significant differences based on the experimental measurements (e.g. low prevalence diseases, etc.). Two examples demonstrate its application in two microarray experiments and the type of information that can be extracted.

Biomarkers, Tumor↗

A novel candidate region linked to development of both pheochromocytoma and head/neck paraganglioma.

Although the histologic distinction between pheochromocytomas and head and neck paragangliomas is clear, little is known about the genetic differences between them. To date, various sets of genes have been found to be involved in inherited susceptibility to developing both tumor types, but the genes involved in sporadic pathogenesis are still unknown. To define new candidate regions, we performed CGH analysis on 29 pheochromocytomas and on 24 paragangliomas mainly of head and neck origin (20 of 24), which allowed us to differentiate between the two tumor types. Loss of 3q was significantly more frequent in pheochromocytomas, and loss of 1q appeared only in paragangliomas. We also found gain of 11q13 to be a significantly frequent alteration in malignant cases of both types. In addition, recurrent loss of 8p22-23 was found in 62% of pheochromocytomas (including all malignant cases) versus in 33% of paragangliomas, suggesting that this region contains candidate genes involved in the pathogenesis of this abnormality. Using FISH analysis on tissue microarrays, we confirmed genomic deletion of this region in 55% of pheochromocytomas compared to 12% of paragangliomas. Loss of 8p22-23 appears to be an important event in the sporadic development of these tumors, and additional molecular studies are necessary to identify candidate genes in this chromosomal region.

Adolescent↗

Phenotypic characterization of BRCA1 and BRCA2 tumors based in a tissue microarray study with 37 immunohistochemical markers.

Familial breast cancers that are associated with BRCA1 or BRCA2 germline mutations differ in both their morphological and immunohistochemical characteristics. To further characterize the molecular difference between genotypes, the authors evaluated the expression of 37 immunohistochemical markers in a tissue microarray (TMA) containing cores from 20 BRCA1, 14 BRCA2, and 59 sporadic age-matched breast carcinomas. Markers analyzed included, amog others, common markers in breast cancer, such as hormone receptors, p53 and HER2, along with 15 molecules involved in cell cycle regulation, such as cyclins, cyclin dependent kinases (CDK) and CDK inhibitors (CDKI), apoptosis markers, such as BCL2 and active caspase 3, and two basal/myoepithelial markers (CK 5/6 and P-cadherin). In addition, we analyzed the amplification of CCND1, CCNE, HER2 and MYC by FISH. Unsupervised cluster data analysis of both hereditary and sporadic cases using the complete set of immunohistochemical markers demonstrated that most BRCA1-associated carcinomas grouped in a branch of ER-, HER2-negative tumors that expressed basal cell markers and/or p53 and had higher expression of activated caspase 3. The cell cycle proteins associated with these tumors were E2F6, cyclins A, B1 and E, SKP2 and Topo IIalpha. In contrast, most BRCA2-associated carcinomas grouped in a branch composed by ER/PR/BCL2-positive tumors with a higher expression of the cell cycle proteins cyclin D1, cyclin D3, p27, p16, p21, CDK4, CDK2 and CDK1. In conclusion, our study in hereditary breast cancer tumors analyzing 37 immunohistochemical markers, define the molecular differences between BRCA1 and BRCA2 tumors with respect to hormonal receptors, cell cycle, apoptosis and basal cell markers.

Adult↗

Highly specific and accurate selection of siRNAs for high-throughput functional assays.

MOTIVATION: Small interfering RNA (siRNA) is widely used in functional genomics to silence genes by decreasing their expression to study the resulting phenotypes. The possibility of performing large-scale functional assays by gene silencing accentuates the necessity of a software capable of the high-throughput design of highly specific siRNA. The main objective sought was the design of a large number of siRNAs with appropriate thermodynamic properties and, especially, high specificity. Since all the available procedures require, to some extent, manual processing of the results to guarantee specific results, specificity constitutes to date, the major obstacle to the complete automation of all the steps necessary for the selection of optimal candidate siRNAs. RESULT: Here, we present a program that for the first time completely automates the search for siRNAs. In SiDE, the most complete set of rules for the selection of siRNA candidates (including G+C content, nucleotides at determined positions, thermodynamic properties, propensity to form internal hairpins, etc.) is implemented and moreover, specificity is achieved by a conceptually new method. After selecting possible siRNA candidates with the optimal functional properties, putative unspecific matches, which can cause cross-hybridization, are checked in databases containing a unique entry for each gene. These truly non-redundant databases are constructed from the genome annotations (Ensembl). Also intron/exon boundaries, presence of polymorphisms (single nucleotide polymorphisms) specificity for either gene or transcript, and other features can be selected to be considered in the design of siRNAs. AVAILABILITY: The program is available as a web server at http://side.bioinfo.cnio.es. The program was written under the GPL license. CONTACT: jdopazo@cnio.es.

Algorithms↗