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Ferreiro M.J.,Developmental Neurobiology | Rodriguez-Ezpeleta N.,Genome Analysis Platform | Rodriguez-Ezpeleta N.,Tecnalia | Perez C.,CIC Biomagune | And 5 more authors.
BMC Genomics

Background: Neurodegenerative diseases are progressive and irreversible and they can be initiated by mutations in specific genes. Spalt-like genes (Sall) encode transcription factors expressed in the central nervous system. In humans, SALL mutations are associated with hereditary syndromes characterized by mental retardation, sensorineural deafness and motoneuron problems, among others. Drosophila sall mutants exhibit severe neurodegeneration of the central nervous system at embryonic stage 16, which surprisingly reverts later in development at embryonic stage 17, suggesting a potential to recover from neurodegeneration. We hypothesize that this recovery is mediated by a reorganization of the transcriptome counteracting SALL lost. To identify genes associated to neurodegeneration and neuroprotection, we used mRNA-Seq to compare the transcriptome of Drosophila sall mutant and wild type embryos from neurodegeneration and reversal stages.Results: Neurodegeneration stage is associated with transcriptional changes in 220 genes, of which only 5% were already described as relevant for neurodegeneration. Genes related to the groups of Redox, Lifespan/Aging and Mitochondrial diseases are significantly represented at this stage. By contrast, neurodegeneration reversal stage is associated with significant changes in 480 genes, including 424 not previously associated with neuroprotection. Immune response and Salt stress are the most represented groups at this stage. Conclusions: We identify new genes associated to neurodegeneration and neuroprotection by using an mRNA-Seq approach. The strong homology between Drosophila and human genes raises the possibility to unveil novel genes involved in neurodegeneration and neuroprotection also in humans. © 2012 Ferreiro et al.; licensee BioMed Central Ltd. Source

Mosen-Ansorena D.,Genome Analysis Platform | Aransay A.M.,Genome Analysis Platform | Rodriguez-Ezpeleta N.,Tecnalia
BMC Bioinformatics

Background: The detection of genomic copy number alterations (CNA) in cancer based on SNP arrays requires methods that take into account tumour specific factors such as normal cell contamination and tumour heterogeneity. A number of tools have been recently developed but their performance needs yet to be thoroughly assessed. To this aim, a comprehensive model that integrates the factors of normal cell contamination and intra-tumour heterogeneity and that can be translated to synthetic data on which to perform benchmarks is indispensable.Results: We propose such model and implement it in an R package called CnaGen to synthetically generate a wide range of alterations under different normal cell contamination levels. Six recently published methods for CNA and loss of heterozygosity (LOH) detection on tumour samples were assessed on this synthetic data and on a dilution series of a breast cancer cell-line: ASCAT, GAP, GenoCNA, GPHMM, MixHMM and OncoSNP. We report the recall rates in terms of normal cell contamination levels and alteration characteristics: length, copy number and LOH state, as well as the false discovery rate distribution for each copy number under different normal cell contamination levels.Assessed methods are in general better at detecting alterations with low copy number and under a little normal cell contamination levels. All methods except GPHMM, which failed to recognize the alteration pattern in the cell-line samples, provided similar results for the synthetic and cell-line sample sets. MixHMM and GenoCNA are the poorliest performing methods, while GAP generally performed better. This supports the viability of approaches other than the common hidden Markov model (HMM)-based.Conclusions: We devised and implemented a comprehensive model to generate data that simulate tumoural samples genotyped using SNP arrays. The validity of the model is supported by the similarity of the results obtained with synthetic and real data. Based on these results and on the software implementation of the methods, we recommend GAP for advanced users and GPHMM for a fully driven analysis. © 2012 Mosén-Ansorena et al.; licensee BioMed Central Ltd. Source

Cortazar A.R.,Genome Analysis Platform | Oguiza J.A.,University of Pamplona | Aransay A.M.,Genome Analysis Platform | Lavin J.L.,Genome Analysis Platform
Amino Acids

Full sets of proteins that are transported to the extracellular space, called secretomes, have been studied for a variety of organisms to understand their potential role in crucial metabolic pathways and complex health conditions. However, there is a lack of tools for integrative classical analysis of secretomes that consider all the data sources available nowadays. Thus, PECAS (Prokaryotic and Eukaryotic Classical Analysis of Secretome) has been developed to provide a well-established prediction pipeline on secreted proteins for prokaryote and eukaryote species. © 2015 Springer-Verlag Wien Source

Mosen-Ansorena D.,Genome Analysis Platform | Aransay A.M.,Genome Analysis Platform
BMC Bioinformatics

Background: SNP arrays output two signals that reflect the total genomic copy number (LRR) and the allelic ratio (BAF), which in combination allow the characterisation of allele-specific copy numbers (ASCNs). While methods based on hidden Markov models (HMMs) have been extended from array comparative genomic hybridisation (aCGH) to jointly handle the two signals, only one method based on change-point detection, ASCAT, performs bivariate segmentation.Results: In the present work, we introduce a generic framework for bivariate segmentation of SNP array data for ASCN analysis. For the matter, we discuss the characteristics of the typically applied BAF transformation and how they affect segmentation, introduce concepts of multivariate time series analysis that are of concern in this field and discuss the appropriate formulation of the problem. The framework is implemented in a method named CnaStruct, the bivariate form of the structural change model (SCM), which has been successfully applied to transcriptome mapping and aCGH.Conclusions: On a comprehensive synthetic dataset, we show that CnaStruct outperforms the segmentation of existing ASCN analysis methods. Furthermore, CnaStruct can be integrated into the workflows of several ASCN analysis tools in order to improve their performance, specially on tumour samples highly contaminated by normal cells. © 2013 Mosén-Ansorena and Aransay; licensee BioMed Central Ltd. Source

Rumbo-Feal S.,University of La Coruna | Gomez M.J.,CSIC - National Institute of Aerospace Technology | Gayoso C.,University of La Coruna | Alvarez-Fraga L.,University of La Coruna | And 9 more authors.

Acinetobacter baumannii has emerged as a dangerous opportunistic pathogen, with many strains able to form biofilms and thus cause persistent infections. The aim of the present study was to use high-throughput sequencing techniques to establish complete transcriptome profiles of planktonic (free-living) and sessile (biofilm) forms of A. ATCC 17978 and thereby identify differences in their gene expression patterns. Collections of mRNA from planktonic (both exponential and stationary phase cultures) and sessile (biofilm) cells were sequenced. Six mRNA libraries were prepared following the mRNA-Seq protocols from Illumina. Reads were obtained in a HiScanSQ platform and mapped against the complete genome to describe the complete mRNA transcriptomes of planktonic and sessile cells. The results showed that the gene expression pattern of A. baumannii biofilm cells was distinct from that of planktonic cells, including 1621 genes over-expressed in biofilms relative to stationary phase cells and 55 genes expressed only in biofilms. These differences suggested important changes in amino acid and fatty acid metabolism, motility, active transport, DNA-methylation, iron acquisition, transcriptional regulation, and quorum sensing, among other processes. Disruption or deletion of five of these genes caused a significant decrease in biofilm formation ability in the corresponding mutant strains. Among the genes over-expressed in biofilm cells were those in an operon involved in quorum sensing. One of them, encoding an acyl carrier protein, was shown to be involved in biofilm formation as demonstrated by the significant decrease in biofilm formation by the corresponding knockout strain. The present work serves as a basis for future studies examining the complex network systems that regulate bacterial biofilm formation and maintenance. © 2013 Rumbo-Feal et al. Source

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