Luis Quintales

Abstract Summary: 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 Contact: rodri@usal.es

BACKGROUND: Microarray 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. RESULTS: We 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/bicoverlapper CONCLUSION: The 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.

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.

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.