Javier Santoyo

Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling

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.

GEPAS: a web-based resource for microarray gene expression data analysis

We present a web-based pipeline for microarray gene expression profile analysis, GEPAS, which stands for Gene Expression Profile Analysis Suite (http://gepas.bioinfo.cnio.es). GEPAS is composed of different interconnected modules which include tools for data pre-processing, two-conditions comparison, unsupervised and supervised clustering (which include some of the most popular methods as well as home made algorithms) and several tests for differential gene expression among different classes, continuous variables or survival analysis. A multiple purpose tool for data mining, based on Gene Ontology, is also linked to the tools, which constitutes a very convenient way of analysing clustering results. On-line tutorials are available from our main web server (http://bioinfo.cnio.es).

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.

Mutation spectrum of EYS in Spanish patients with autosomal recessive retinitis pigmentosa

Retinitis pigmentosa (RP) is a heterogeneous group of inherited retinal dystrophies characterised ultimately by the loss of photoreceptor cells. We have recently identified a new gene (EYS) encoding an ortholog of Drosophila spacemaker (spam) as a commonly mutated gene in autosomal recessive RP. In the present study, we report the identification of 73 sequence variations in EYS, of which 28 are novel. Of these, 42.9% (12/28) are very likely pathogenic, 17.9% (5/28) are possibly pathogenic, whereas 39.3% (11/28) are SNPs. In addition, we have detected 3 pathogenic changes previously reported in other populations. We are also presenting the characterisation of EYS homologues in different species, and a detailed analysis of the EYS domains, with the identification of an interesting novel feature: a putative coiled‐coil domain. Majority of the mutations in the arRP patients have been found within the domain structures of EYS. The minimum observed prevalence of distinct EYS mutations in our group of patients is of 15.9% (15/94), confirming a major involvement of EYS in the pathogenesis of arRP in the Spanish population. Along with the detection of three recurrent mutations in Caucasian population, our hypothesis of EYS being the first prevalent gene in arRP has been reinforced in the present study.

Integrated analysis of whole-exome sequencing and transcriptome profiling in males with autism spectrum disorders

BackgroundAutism spectrum disorders (ASD) are a group of neurodevelopmental disorders with high heritability. Recent findings support a highly heterogeneous and complex genetic etiology including rare de novo and inherited mutations or chromosomal rearrangements as well as double or multiple hits.MethodsWe performed whole-exome sequencing (WES) and blood cell transcriptome by RNAseq in a subset of male patients with idiopathic ASD (n = 36) in order to identify causative genes, transcriptomic alterations, and susceptibility variants.ResultsWe detected likely monogenic causes in seven cases: five de novo (SCN2A, MED13L, KCNV1, CUL3, and PTEN) and two inherited X-linked variants (MAOA and CDKL5). Transcriptomic analyses allowed the identification of intronic causative mutations missed by the usual filtering of WES and revealed functional consequences of some rare mutations. These included aberrant transcripts (PTEN, POLR3C), deregulated expression in 1.7% of mutated genes (that is, SEMA6B, MECP2, ANK3, CREBBP), allele-specific expression (FUS, MTOR, TAF1C), and non-sense-mediated decay (RIT1, ALG9). The analysis of rare inherited variants showed enrichment in relevant pathways such as the PI3K-Akt signaling and the axon guidance.ConclusionsIntegrative analysis of WES and blood RNAseq data has proven to be an efficient strategy to identify likely monogenic forms of ASD (19% in our cohort), as well as additional rare inherited mutations that can contribute to ASD risk in a multifactorial manner. Blood transcriptomic data, besides validating 88% of expressed variants, allowed the identification of missed intronic mutations and revealed functional correlations of genetic variants, including changes in splicing, expression levels, and allelic expression.

Mutation Screening of Multiple Genes in Spanish Patients with Autosomal Recessive Retinitis Pigmentosa by Targeted Resequencing

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.

A map of human microRNA variation uncovers unexpectedly high levels of variability.

BackgroundMicroRNAs (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 a healthy population seems an obvious requirement for future research on miRNA-related pathologies.MethodsData on 14 populations from the 1000 Genomes Project were analyzed, along with new data extracted from 60 exomes of healthy individuals from a population from southern Spain, sequenced in the context of the Medical Genome Project, to derive an accurate map of miRNA variability.ResultsDespite 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.ConclusionsDespite an expectation that miRNAs would be highly conserved genomic elements, our study reports a level of variability comparable to that observed for coding genes.

Using gene ontology on genome-scale studies to find significant associations of biologically relevant terms to groups of genes

The analysis of genome-scale data from different high throughput techniques usually involves the grouping of genes based on experimental criteria. These groups are a consequence of the biological roles the genes are playing within the cell. Establishing which of these groups are functionally important is essential. Gene ontology terms provide a specialised vocabulary to describe the relevant biological properties of genes. We used a simple procedure to extract terms that are significantly over or under-represented in sets of genes within the context of a genome-scale experiment. Said procedure, which takes the multiple-testing nature of the statistical contrast into account, has been implemented as a Web application, FatiGO, allowing for easy and interactive querying. Several examples demonstrate its application and the type of information that can be extracted. Although a number of genes still lack gene ontology annotations, the results were informative enough to characterise the biological processes in the systems analysed.

Assessing Differential Expression Measurements by Highly Parallel Pyrosequencing and DNA Microarrays: A Comparative Study

To explore the feasibility of pyrosequencing for quantitative differential gene expression analysis we have performed a comparative study of the results of the sequencing experiments to those obtained by a conventional DNA microarray platform. A conclusion from our analysis is that, over a threshold of 35 normalized reads per gene, the measurements of gene expression display a good correlation with the references. The observed concordance between pyrosequencing and DNA microarray platforms beyond the threshold was of 0.8, measured as a Pearsons correlation coefficient. In differential gene expression the initial aim is the quantification the differences among transcripts when comparing experimental conditions. Thus, even in a scenario of low coverage the concordance in the measurements is quite acceptable. On the other hand, the comparatively longer read size obtained by pyrosequencing allows detecting unconventional splicing forms.