Quality estimation of multiple sequence alignments by Bayesian hypothesis testing

Summary: In this work we present a web-based tool for estimating multiple alignment quality using Bayesian hypothesis testing. The proposed method is very simple, easily implemented and not time consuming with a linear complexity. We evaluated method against a series of different alignments (a set of random and biologically derived alignments) and compared the results with tools based on classical statistical methods (such as sFFT and csFFT). Taking correlation coefficient as an objective criterion of the true quality, we found that Bayesian hypothesis testing performed better on average than the classical methods we tested. This approach may be used independently or as a component of any tool in computational biology which is based on the statistical estimation of alignment quality. Availability: http://www.fmi.ch/groups/functional.genomics/tool.htm Contact: [email protected] Supplementary information: Supplementary data are available from http://www.fmi.ch/groups/functional.genomics/tool-Supp.ht

Position dependencies in transcription factor binding sites

Motivation: Most of the available tools for transcription factor binding site prediction are based on methods which assume no sequence dependence between the binding site base positions. Our primary objective was to investigate the statistical basis for either a claim of dependence or independence, to determine whether such a claim is generally true, and to use the resulting data to develop improved scoring functions for binding-site prediction. Results: Using three statistical tests, we analyzed the number of binding sites showing dependent positions. We analyzed transcription factor-DNA crystal structures for evidence of position dependence. Our final conclusions were that some factors show evidence of dependencies whereas others do not. We observed that the conformational energy (Z-score) of the transcription factor-DNA complexes was lower (better) for sequences that showed dependency than for those that did not (P < 0.02). We suggest that where evidence exists for dependencies, these should be modeled to improve binding-site predictions. However, when no significant dependency is found, this correction should be omitted. This may be done by converting any existing scoring function which assumes independence into a form which includes a dependency correction. We present an example of such an algorithm and its implementation as a web tool. Availability: http://promoterplot.fmi.ch/cgi-bin/dep.html Contact: [email protected] Supplementary information: Supplementary data (1, 2, 3, 4, 5, 6, 7 and 8) are available at Bioinformatics onlin

Overestimation of alternative splicing caused by variable probe characteristics in exon arrays

In higher eukaryotes, alternative splicing is a common mechanism for increasing transcriptome diversity. Affymetrix exon arrays were designed as a tool for monitoring the relative expression levels of hundreds of thousands of known and predicted exons with a view to detecting alternative splicing events. In this article, we have analyzed exon array data from many different human and mouse tissues and have uncovered a systematic relationship between transcript-fold change and alternative splicing as reported by the splicing index. Evidence from dilution experiments and deep sequencing suggest that this effect is of technical rather than biological origin and that it is driven by sequence features of the probes. This effect is substantial and results in a 12-fold overestimation of alternative splicing events in genes that are differentially expressed. By cross-species exon array comparison, we could further show that the systematic bias persists even across species boundaries. Failure to consider this effect in data analysis would result in the reproducible false detection of apparently conserved alternative splicing events. Finally, we have developed a software in R called COSIE (Corrected Splicing Indices for Exon arrays) that for any given set of new exon array experiments corrects for the observed bias and improves the detection of alternative splicing (available at www.fmi.ch/groups/gbioinfo

Multiple domains are involved in the targeting of the mouse DNA methyltransferase to the DNA replication foci

It has been shown that, during the S-phase of the cell cycle, the mouse DNA methyltransferase (DNA MTase) is targeted to sites of DNA replication by an amino acid sequence (aa 207-455) lying in the N-terminal domain of the enzyme [Leonhardt, H., Page, A. W., Weier, H. U. and Bestor, T. H. (1992) Cell, 71, 865-873]. In this paper it is shown, by using enhanced green fluorescent protein (EGFP) fusions, that other peptide sequences of DNA MTase are also involved in this targeting. The work focuses on a sequence, downstream of the reported targeting sequence (TS), which is homologous to the Polybromo-1 protein. This motif (designated as PBHD) is separated from the reported targeting sequence by a zinc-binding motif [Bestor, T. H. (1992) EMBO J, 11, 2611-2617]. Primed in situ extension using centromeric-specific primers was used to show that both the host DNA MTase and EGFP fusion proteins containing the targeting sequences were localized to centromeric, but not telomeric, regions during late S-phase and mitosis. Also found was that, in ∼10% of the S-phase cells, the EGFP fusions did not co-localize with the centromeric regions. Mutants containing either, or both, of these targeting sequences could act as dominant negative mutants against the host DNA MTase. EGFP fusion proteins, containing the reported TS (aa 207-455), were targeted to centromeric regions throughout the mitotic stage which lead to the discovery of a similar behavior of the endogenous DNA MTase although the host MTase showed much less intense staining than in S-phase cells. The biological role of the centromeric localization of DNA MTase during mitosis is currently unknow

PromoterPlot: a graphical display of promoter similarities by pattern recognition

PromoterPlot (http://promoterplot.fmi.ch) is a web-based tool for simplifying the display and processing of transcription factor searches using either the commercial or free TransFac distributions. The input sequence is a TransFac search (public version) or FASTA/Affymetrix IDs (local install). It uses an intuitive pattern recognition algorithm for finding similarities between groups of promoters by dividing transcription factor predictions into conserved triplet models. To minimize the number of false-positive models, it can optionally exclude factors that are known to be unexpressed or inactive in the cells being studied based on microarray or proteomic expression data. The program will also estimate the likelihood of finding a pattern by chance based on the frequency observed in a control set of mammalian promoters we obtained from Genomatix. The results are stored as an interactive SVG web page on our serve

PromoterPlot: a graphical display of promoter similarities by pattern recognition

PromoterPlot () is a web-based tool for simplifying the display and processing of transcription factor searches using either the commercial or free TransFac distributions. The input sequence is a TransFac search (public version) or FASTA/Affymetrix IDs (local install). It uses an intuitive pattern recognition algorithm for finding similarities between groups of promoters by dividing transcription factor predictions into conserved triplet models. To minimize the number of false-positive models, it can optionally exclude factors that are known to be unexpressed or inactive in the cells being studied based on microarray or proteomic expression data. The program will also estimate the likelihood of finding a pattern by chance based on the frequency observed in a control set of mammalian promoters we obtained from Genomatix. The results are stored as an interactive SVG web page on our server

Human Cytomegalovirus Escapes a Naturally Occurring Neutralizing Antibody by Incorporating It into Assembling Virions

SummaryHuman cytomegalovirus (CMV) is a common but difficult to treat infection of immunocompromised patients. MSL-109 is a human monoclonal IgG isolated from a CMV seropositive individual that recognizes the viral glycoprotein H (gH) surface antigen complexes that mediate entry. Although MSL-109 blocks CMV infection in vitro, it lacked sufficient efficacy in human trials, and CMV isolated from treated patients suggested the evolution of MSL-109 resistance. To understand how CMV escapes MSL-109, we characterized a MSL-109-resistant CMV strain. Our results elucidate a nongenetic escape mechanism in which the antibody is selectively taken up by infected cells and incorporated into assembling virions in a dose-dependent manner. The resistant virus then utilizes the Fc domain of the incorporated antibody to infect naive nonimmune cells. This resistance mechanism may explain the clinical failure of MSL-109, illustrate a general mechanism of viral antibody escape, and inform antiviral vaccine and therapeutic development

Overestimation of alternative splicing caused by variable probe characteristics in exon arrays

In higher eukaryotes, alternative splicing is a common mechanism for increasing transcriptome diversity. Affymetrix exon arrays were designed as a tool for monitoring the relative expression levels of hundreds of thousands of known and predicted exons with a view to detecting alternative splicing events. In this article, we have analyzed exon array data from many different human and mouse tissues and have uncovered a systematic relationship between transcript-fold change and alternative splicing as reported by the splicing index. Evidence from dilution experiments and deep sequencing suggest that this effect is of technical rather than biological origin and that it is driven by sequence features of the probes. This effect is substantial and results in a 12-fold overestimation of alternative splicing events in genes that are differentially expressed. By cross-species exon array comparison, we could further show that the systematic bias persists even across species boundaries. Failure to consider this effect in data analysis would result in the reproducible false detection of apparently conserved alternative splicing events. Finally, we have developed a software in R called COSIE (Corrected Splicing Indices for Exon arrays) that for any given set of new exon array experiments corrects for the observed bias and improves the detection of alternative splicing (available at www.fmi.ch/groups/gbioinfo)

Non-genotoxic carcinogen exposure induces defined changes in the 5-hydroxymethylome.

BACKGROUND: Induction and promotion of liver cancer by exposure to non-genotoxic carcinogens coincides with epigenetic perturbations, including specific changes in DNA methylation. Here we investigate the genome-wide dynamics of 5-hydroxymethylcytosine (5hmC) as a likely intermediate of 5-methylcytosine (5mC) demethylation in a DNA methylation reprogramming pathway. We use a rodent model of non-genotoxic carcinogen exposure using the drug phenobarbital. RESULTS: Exposure to phenobarbital results in dynamic and reciprocal changes to the 5mC/5hmC patterns over the promoter regions of a cohort of genes that are transcriptionally upregulated. This reprogramming of 5mC/5hmC coincides with characteristic changes in the histone marks H3K4me2, H3K27me3 and H3K36me3. Quantitative analysis of phenobarbital-induced genes that are involved in xenobiotic metabolism reveals that both DNA modifications are lost at the transcription start site, while there is a reciprocal relationship between increasing levels of 5hmC and loss of 5mC at regions immediately adjacent to core promoters. CONCLUSIONS: Collectively, these experiments support the hypothesis that 5hmC is a potential intermediate in a demethylation pathway and reveal precise perturbations of the mouse liver DNA methylome and hydroxymethylome upon exposure to a rodent hepatocarcinogen.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Decatransin, a novel natural product inhibiting protein translocation at the Sec61/SecY translocon

A new cyclic decadepsipeptide was isolated from Chaetosphaeria tulasneorum with potent bioactivity on mammalian and yeast cells. Chemogenomic profiling in S. cerevisiae indicated that the Sec61 translocon, the machinery for protein translocation and membrane insertion at the endoplasmic reticulum, is the target. The profiles were similar to those of cyclic heptadepsipeptides of a distinct chemotype (HUN-7293/cotransin) that had previously been shown to inhibit cotranslational translocation at the mammalian Sec61 translocon. Unbiased, genome-wide mutagenesis followed by full-genome sequencing in both fungal and mammalian cells identified dominant mutations in Sec61p/Sec61α1 to confer resistance. Most, but not all, of these mutations affected inhibition by both chemotypes, despite an absence of structural similarity. Biochemical analysis confirmed inhibition of protein translocation into the endoplasmic reticulum of both co- and posttranslationally translocated substrates by both chemotypes, demonstrating a mechanism independent of a translating ribosome. Most interestingly, both chemotypes were found to also inhibit SecYEG, the bacterial Sec61 homolog. We suggest "decatransin" as the name for this novel decadepsipeptide translocation inhibitor