Luis Quintales

BicOverlapper: A tool for bicluster visualization

UNLABELLED BicOverlapper is a tool to visualize biclusters from gene-expression matrices in a way that helps to compare biclustering methods, to unravel trends and to highlight relevant genes and conditions. A visual approach can complement biological and statistical analysis and reduce the time spent by specialists interpreting the results of biclustering algorithms. The technique is based on a force-directed graph where biclusters are represented as flexible overlapped groups of genes and conditions. AVAILABILITY The BicOverlapper software and supplementary material are available at http://vis.usal.es/bicoverlapper

A visual analytics approach for understanding biclustering results from microarray data.

BackgroundMicroarray analysis is an important area of bioinformatics. In the last few years, biclustering has become one of the most popular methods for classifying data from microarrays. Although biclustering can be used in any kind of classification problem, nowadays it is mostly used for microarray data classification. A large number of biclustering algorithms have been developed over the years, however little effort has been devoted to the representation of the results.ResultsWe present an interactive framework that helps to infer differences or similarities between biclustering results, to unravel trends and to highlight robust groupings of genes and conditions. These linked representations of biclusters can complement biological analysis and reduce the time spent by specialists on interpreting the results. Within the framework, besides other standard representations, a visualization technique is presented which is based on a force-directed graph where biclusters are represented as flexible overlapped groups of genes and conditions. This microarray analysis framework (BicOverlapper), is available at http://vis.usal.es/bicoverlapperConclusionThe main visualization technique, tested with different biclustering results on a real dataset, allows researchers to extract interesting features of the biclustering results, especially the highlighting of overlapping zones that usually represent robust groups of genes and/or conditions. The visual analytics methodology will permit biology experts to study biclustering results without inspecting an overwhelming number of biclusters individually.

Nucleosomal organization of replication origins and meiotic recombination hotspots in fission yeast

In Schizosaccharomyces pombe, DNA replication origins (ORIs) and meiotic recombination hotspots lack consensus sequences and show a bias towards mapping to large intergenic regions (IGRs). To explore whether this preference depended on underlying chromatin features, we have generated genome‐wide nucleosome profiles during mitosis and meiosis. We have found that meiotic double‐strand break sites (DSBs) colocalize with nucleosome‐depleted regions (NDRs) and that large IGRs include clusters of NDRs that overlap with almost half of all DSBs. By contrast, ORIs do not colocalize with NDRs and they are regulated independently of DSBs. Physical relocation of NDRs at ectopic loci or modification of their genomic distribution during meiosis was paralleled by the generation of new DSB sites. Over 80% of all meiotic DSBs colocalize with NDRs that are also present during mitosis, indicating that the recombination pattern is largely dependent on constitutive properties of the genome and, to a lesser extent, on the transcriptional profile during meiosis. The organization of ORIs and of DSBs regions in S. pombe reveals similarities and differences relative to Saccharomyces cerevisiae.

Gcn5 facilitates Pol II progression, rather than recruitment to nucleosome-depleted stress promoters, in Schizosaccharomyces pombe.

In the fission yeast, the MAP kinase Sty1 and the transcription factor Atf1 regulate up to 400 genes in response to environmental signals, and both proteins have been shown to bind to their promoters in a stress-dependent manner. In a genetic search, we have isolated the histone H3 acetyltransferase Gcn5, a component of the SAGA complex, as being essential for oxidative stress survival and activation of those genes. Upon stress, Gcn5 is recruited to promoters and coding sequences of stress genes in a Sty1- and Atf1-dependent manner, causing both an enhanced acetylation of histone H3 and nucleosome eviction. Unexpectedly, recruitment of RNA polymerase II (Pol II) is not impaired in Δgcn5 cells. We show here that stress genes display a 400-bp long nucleosome depleted region upstream of the transcription start site even prior to activation. Stress treatment does not alter promoter nucleosome architecture, but induces eviction of the downstream nucleosomes at stress genes, which is not observed in Δgcn5 cells. We conclude that, while Pol II is recruited to nucleosome-free stress promoters in a transcription factor dependent manner, Gcn5 mediates eviction of nucleosomes positioned downstream of promoters, allowing efficient Pol II progression along the genes.

Building knowledge discovery-driven models for decision support in project management

Accurate estimations of software size in the early stages of a software project are critical in software project management because they lead to a good planning and reduce project costs. In this work, the relation between early software size measures as the function points and measures of the final product as the lines of code has been studied. A process to refine association rules, based on the generation of unexpected patterns, is proposed. The goal is to generate strong association rules between attributes that can be obtained early in the project and the final software size.

Clustered regulatory elements at nucleosome-depleted regions punctuate a constant nucleosomal landscape in Schizosaccharomyces pombe

BackgroundNucleosomes facilitate the packaging of the eukaryotic genome and modulate the access of regulators to DNA. A detailed description of the nucleosomal organization under different transcriptional programmes is essential to understand their contribution to genomic regulation.ResultsTo visualize the dynamics of individual nucleosomes under different transcriptional programmes we have generated high-resolution nucleosomal maps in Schizosaccharomyces pombe. We show that 98.5% of the genome remains almost invariable during mitosis and meiosis while remodelling is limited to approximately 1100 nucleosomes in the promoters of a subset of meiotic genes. These inducible nucleosome-depleted regions (NDR) and also those constitutively present in the genome overlap precisely with clusters of binding sites for transcription factors (TF) specific for meiosis and for different functional classes of genes, respectively. Deletion of two TFs affects only a small fraction of all the NDRs to which they bind in vivo, indicating that TFs collectively contribute to NDR maintenance.ConclusionsOur results show that the nucleosomal profile in S. pombe is largely maintained under different physiological conditions and patterns of gene expression. This relatively constant landscape favours the concentration of regulators in constitutive and inducible NDRs. The combinatorial analysis of binding motifs in this discrete fraction of the genome will facilitate the definition of the transcriptional regulatory networks.

Methods to bicluster validation and comparison in microarray data

There are lots of validation indexes and techniques to study clustering results. Biclustering algorithms have been applied in Systems Biology, principally in DNA Microarray analysis, for the last years, with great success. Nowadays, there is a big set of biclustering algorithms each one based in different concepts, but there are few intercomparisons that measure their performance. We review and present here some numerical measures, new and evolved from traditional clustering validation techniques, to allow comparisons and validation of biclustering algorithms.

Comparative analysis of methods for genome-wide nucleosome cartography

Nucleosomes contribute to compacting the genome into the nucleus and regulate the physical access of regulatory proteins to DNA either directly or through the epigenetic modifications of the histone tails. Precise mapping of nucleosome positioning across the genome is, therefore, essential to understanding the genome regulation. In recent years, several experimental protocols have been developed for this purpose that include the enzymatic digestion, chemical cleavage or immunoprecipitation of chromatin followed by next-generation sequencing of the resulting DNA fragments. Here, we compare the performance and resolution of these methods from the initial biochemical steps through the alignment of the millions of short-sequence reads to a reference genome to the final computational analysis to generate genome-wide maps of nucleosome occupancy. Because of the lack of a unified protocol to process data sets obtained through the different approaches, we have developed a new computational tool (NUCwave), which facilitates their analysis, comparison and assessment and will enable researchers to choose the most suitable method for any particular purpose. NUCwave is freely available at http://nucleosome.usal.es/nucwave along with a step-by-step protocol for its use.

BicOverlapper 2.0: Visual Analysis for Gene Expression

Motivation: Systems biology demands the use of several point of views to get a more comprehensive understanding of biological problems. This usually leads to take into account different data regarding the problem at hand, but it also has to do with using different perspectives of the same data. This multifaceted aspect of systems biology often requires the use of several tools, and it is often hard to get a seamless integration of all of them, which would help the analyst to have an interactive discourse with the data. Results: Focusing on expression profiling, BicOverlapper 2.0 visualizes the most relevant aspects of the analysis, including expression data, profiling analysis results and functional annotation. It also integrates several state-of-the-art numerical methods, such as differential expression analysis, gene set enrichment or biclustering. Availability and implementation: BicOverlapper 2.0 is available at: http://vis.usal.es/bicoverlapper2 Contact: rodri@usal.es

New Insights into the RNA-Based Mechanism of Action of the Anticancer Drug 5′-Fluorouracil in Eukaryotic Cells

5-Fluorouracil (5FU) is a chemotherapeutic drug widely used in treating a range of advanced, solid tumours and, in particular, colorectal cancer. Here, we used high-density tiling DNA microarray technology to obtain the specific transcriptome-wide response induced by 5FU in the eukaryotic model Schizosaccharomyces pombe. This approach combined with real-time quantitative PCR analysis allowed us to detect splicing defects of a significant number of intron-containing mRNA, in addition to identify some rRNA and tRNA processing defects after 5FU treatment. Interestingly, our studies also revealed that 5FU specifically induced the expression of certain genes implicated in the processing of mRNA, tRNA and rRNA precursors, and in the post-transcriptional modification of uracil residues in RNA. The transcription of several tRNA genes was also significantly induced after drug exposure. These transcriptional changes might represent a cellular response mechanism to counteract 5FU damage since deletion strains for some of these up-regulated genes were hypersensitive to 5FU. Moreover, most of these RNA processing genes have human orthologs that participate in conserved pathways, suggesting that they could be novel targets to improve the efficacy of 5FU-based treatments.