Biomedical subjects

Martin Vingron

Publications and source records attributed to Martin Vingron.

At least 37 records · Page 2Linked to original sources

PubMed2005

Gene expression in kidney cancer is associated with cytogenetic abnormalities, metastasis formation, and patient survival.

Current diagnosis of renal cancer consists of histopathologic examination of tissue sections and classification into tumor stages and grades of malignancy. Until recently, molecular differences between tumor types were largely unknown. To examine such differences, we did gene expression measurements of 112 renal cell carcinoma and normal kidney samples on renal cell carcinoma-specific cDNA microarrays containing 4,207 genes and expressed sequence tags. The gene expression patterns showed deregulation of complete biological pathways in the tumors. Many of the molecular changes corresponded well to the histopathologic tumor types, and a set of 80 genes was sufficient to classify tumors with a very low error rate. Distinct gene expression signatures were associated with chromosomal abnormalities of tumor cells, metastasis formation, and patient survival. The data highlight the benefit of microarrays to detect novel tumor classes and to identify genes that are associated with patient variables and tumor properties.

Adult↗

PubMed2005

The SYSTERS Protein Family Database in 2005.

The SYSTERS project aims to provide a meaningful partitioning of the whole protein sequence space by a fully automatic procedure. A refined two-step algorithm assigns each protein to a family and a superfamily. The sequence data underlying SYSTERS release 4 now comprise several protein sequence databases derived from completely sequenced genomes (ENSEMBL, TAIR, SGD and GeneDB), in addition to the comprehensive Swiss-Prot/TrEMBL databases. The SYSTERS web server (http://systers.molgen.mpg.de) provides access to 158 153 SYSTERS protein families. To augment the automatically derived results, information from external databases like Pfam and Gene Ontology are added to the web server. Furthermore, users can retrieve pre-processed analyses of families like multiple alignments and phylogenetic trees. New query options comprise a batch retrieval tool for functional inference about families based on automatic keyword extraction from sequence annotations. A new access point, PhyloMatrix, allows the retrieval of phylogenetic profiles of SYSTERS families across organisms with completely sequenced genomes.

Algorithms↗

PubMed2005

Comparative analysis of cell cycle regulated genes in eukaryotes.

We compared microarray experiments on cell cycle of three model eukaryotes: budding and fission yeast and human cells. Only 112 orthologous groups were cyclic in the three model organisms. The common set of cyclic orthologs includes many taking part in the cell cycle progression, like cyclin B homologs, CDC5, SCH9, DSK2, ZPR1. Proteins involved in DNA replication included histones, some checkpoint kinases and some proteins regulating DNA damage and repair. Conserved cyclic proteins involved in cytokinesis included myosins and kinesins. Many groups of genes related to translation and other metabolic processes were also cyclic in all three organisms. This reflects rebuilding of cellular components after the replication and changes of metabolism during the cell cycle. Many genes important in cell cycle control are not cyclic or not conserved. This includes transcription factors implicated in the regulation of budding yeast cell cycle. The partially overlapping roles of regulatory proteins might allow the evolutionary substitution of components of cell cycle.

Computational Biology↗

PubMed2005

Lethality and entropy of protein interaction networks.

We characterize protein interaction networks in terms of network entropy. This approach suggests a ranking principle, which strongly correlates with elements of functional importance, such as lethal proteins. Our combined analysis of protein interaction networks and functional profiles in single cellular yeast and multi-cellular worm shows that proteins with large contribution to network entropy are preferentially lethal. While entropy is inherently a dynamical concept, the present analysis incorporates only structural information. Our result therefore highlights the importance of topological features, which appear as correlates of an underlying dynamical property, and which in turn determine functional traits. We argue that network entropy is a natural extension of previously studied observables, such as pathway multiplicity and centrality. It is also applicable to networks in which the processes can be quantified and therefore serves as a link to study questions of structural and dynamical robustness in a unified way.

Animals↗

PubMed2004

The SRF target gene Fhl2 antagonizes RhoA/MAL-dependent activation of SRF.

RhoA signaling regulates the activity of the transcription factor SRF (serum response factor) during muscle differentiation. How RhoA signaling is integrated at SRF target promoters to achieve muscle-lineage-specific expression is largely unknown. Using large-scale expression profiling combined with bioinformatic and biochemical approaches, we identified several SRF target genes, including Fhl2, encoding a transcriptional cofactor that is highly expressed in the heart. SRF binds the Fhl2 promoter in vivo and regulates Fhl2 expression in response to RhoA activation. FHL2 protein and SRF interact physically, and FHL2 binds the promoters of SRF-responsive smooth muscle (SM) genes, but not the promoters of immediate-early genes (IEGs), in response to RhoA. FHL2 antagonizes induction of SM genes, but not IEGs or cardiac genes, by competing with the coactivator MAL/MRTF-A for SRF binding. Our findings identify an autoregulatory mechanism to selectively regulate subsets of RhoA-activated SRF target genes.

Animals↗

PubMed2004

SITEBLAST--rapid and sensitive local alignment of genomic sequences employing motif anchors.

MOTIVATION: Comparative sequence analysis is the essence of many approaches to genome annotation. Heuristic alignment algorithms utilize similar seed pairs to anchor an alignment. Some applications of local alignment algorithms (e.g. phylogenetic footprinting) would benefit from including prior knowledge (e.g. binding site motifs) in the alignment building process. RESULTS: We introduce predefined sequence patterns as anchor points into a heuristic local alignment strategy. We extended the BLASTZ program for this purpose. A set of seed patterns is either given as consensus sequences in IUPAC code or position-weight-matrices. Phylogenetic footprinting of promoter regions is one of many potential applications for the SITEBLAST software. AVAILABILITY: The source code is freely available to the academic community from http://corg.molgen.mpg.de/software

Algorithms↗

PubMed2004

Strengths and weaknesses of EST-based prediction of tissue-specific alternative splicing.

BACKGROUND: Alternative splicing contributes significantly to the complexity of the human transcriptome and proteome. Computational prediction of alternative splice isoforms are usually based on EST sequences that also allow to approximate the expression pattern of the related transcripts. However, the limited number of tissues represented in the EST data as well as the different cDNA construction protocols may influence the predictive capacity of ESTs to unravel tissue-specifically expressed transcripts. METHODS: We predict tissue and tumor specific splice isoforms based on the genomic mapping (SpliceNest) of the EST consensus sequences and library annotation provided in the GeneNest database. We further ascertain the potentially rare tissue specific transcripts as the ones represented only by ESTs derived from normalized libraries. A subset of the predicted tissue and tumor specific isoforms are then validated via RT-PCR experiments over a spectrum of 40 tissue types. RESULTS: Our strategy revealed 427 genes with at least one tissue specific transcript as well as 1120 genes showing tumor specific isoforms. While our experimental evaluation of computationally predicted tissue-specific isoforms revealed a high success rate in confirming the expression of these isoforms in the respective tissue, the strategy frequently failed to detect the expected restricted expression pattern. The analysis of putative lowly expressed transcripts using normalized cDNA libraries suggests that our ability to detect tissue-specific isoforms strongly depends on the expression level of the respective transcript as well as on the sensitivity of the experimental methods. Especially splice isoforms predicted to be disease-specific tend to represent transcripts that are expressed in a set of healthy tissues rather than novel isoforms. CONCLUSIONS: We propose to combine the computational prediction of alternative splice isoforms with experimental validation for efficient delineation of an accurate set of tissue-specific transcripts.

Alternative Splicing↗

PubMed2004

Functional inference from non-random distributions of conserved predicted transcription factor binding sites.

MOTIVATION: Our understanding of how genes are regulated in a concerted fashion is still limited. Especially, complex phenomena like cell cycle regulation in multicellular organisms are poorly understood. Therefore, we investigated conserved predicted transcription factor binding sites (TFBSs) in man-mouse upstream regions of genes that can be associated to a particular cell cycle phase in HeLa cells. TFBSs were predicted from selected binding site motifs (represented by position weight matrices, PWMs) based on a statistical approach. A regulatory role for a transcription factor is more probable if its predicted TFBSs are enriched in upstream regions of genes, that are associated with a subset of cell cycle phases. We tested for this association by computing exact P-values for the observed phase distributions under the null distribution defined by the relative amount of conserved upstream sequence of genes per cell cycle phase. We considered non-exonic and 5'-untranslated region (5'-UTR) binding sites separately and corrected for multiple testing by taking the false discovery rate into account. RESULTS: We identified 22 non-exonic and 11 5'-UTR significant PWM phase distributions although expecting one false discovery. Many of the corresponding transcription factors (e.g. members of the thyroid hormone/retinoid receptor subfamily) have already been associated with cell cycle regulation, proliferation and development. It appears that our method is a suitable tool for detecting putative cell cycle regulators in the realm of known human transcription factors. AVAILABILITY: Further details and supplementary data can be obtained from http://corg.molgen.mpg.de/cellcycle

Animals↗

PubMed2004

Optimal robust non-unique probe selection using Integer Linear Programming.

MOTIVATION: Besides their prevalent use for analyzing gene expression, microarrays are an efficient tool for biological, medical and industrial applications due to their ability to assess the presence or absence of biological agents, the targets, in a sample. Given a collection of genetic sequences of targets one faces the challenge of finding short oligonucleotides, the probes, which allow detection of targets in a sample. Each hybridization experiment determines whether the probe binds to its corresponding sequence in the target. Depending on the problem, the experiments are conducted using either unique or non-unique probes and usually assume that only one target is present in the sample. The problem at hand is to compute a design, i.e. a minimal set of probes that allows to infer the targets in the sample from the result of the hybridization experiment. If we allow to test for more than one target in the sample, the design of the probe set becomes difficult in the case of non-unique probes. RESULTS: Building upon previous work on group testing for microarrays, we describe the first approach to select a minimal probe set for the case of non-unique probes in the presence of a small number of multiple targets in the sample. The approach is based on an ILP formulation and a branch-and-cut algorithm. Our preliminary implementation greatly reduces the number of probes needed while preserving the decoding capabilities. AVAILABILITY: http://www.inf.fu-berlin.de/inst/ag-bio

Algorithms↗

PubMed2004

A DNA microarray for fission yeast: minimal changes in global gene expression after temperature shift.

Completion of the fission yeast genome sequence has opened up possibilities for post-genomic approaches. We have constructed a DNA microarray for genome-wide gene expression analysis in fission yeast. The microarray contains DNA fragments, PCR-amplified from a genomic DNA template, that represent > 99% of the 5000 or so annotated fission yeast genes, as well as a number of control sequences. The GenomePRIDE software used attempts to design similarly sized DNA fragments corresponding to gene regions within single exons, near the 3'-end of genes that lack homology to other fission yeast genes. To validate the design and utility of the array, we studied expression changes after a 2 h temperature shift from 25 degrees C to 36 degrees C, conditions widely used when studying temperature-sensitive mutants. Obligingly, the vast majority of genes do not change more than two-fold, supporting the widely held view that temperature-shift experiments specifically reveal phenotypes associated with temperature-sensitive mutants. However, we did identify a small group of genes that showed a reproducible change in expression. Importantly, most of these corresponded to previously characterized heat-shock genes, whose expression has been reported to change after more extreme temperature shifts than those used here. We conclude that the DNA microarray represents a useful resource for fission yeast researchers as well as the broader yeast community, since it will facilitate comparison with the distantly related budding yeast, Saccharomyces cerevisiae. To maximize the utility of this resource, the array and its component parts are fully described in On-line Supplementary Information and are also available commercially.

DNA, Fungal↗

PubMed2004

IntAct: an open source molecular interaction database.

IntAct provides an open source database and toolkit for the storage, presentation and analysis of protein interactions. The web interface provides both textual and graphical representations of protein interactions, and allows exploring interaction networks in the context of the GO annotations of the interacting proteins. A web service allows direct computational access to retrieve interaction networks in XML format. IntAct currently contains approximately 2200 binary and complex interactions imported from the literature and curated in collaboration with the Swiss-Prot team, making intensive use of controlled vocabularies to ensure data consistency. All IntAct software, data and controlled vocabularies are available at http://www.ebi.ac.uk/intact.

Animals↗

PubMed2004

Annotating significant pairs of transcription factor binding sites in regulatory DNA.

In the presented work we search for transcription factor binding sites (BS) by including additional information about typical BS patterns. The new proposed score combines the ordinary profile score based on TRANSFAC-matrices together with a score based on pairs of BS. The latter score positively weights pairs of BS that tend to occur together in many regulatory DNA-sequences, in contrast to a random background model. The empirical BS pair frequencies result from our evaluation of a large dataset of orthologous genes.

Animals↗

PubMed2003

Analysis of CREM-dependent gene expression during mouse spermatogenesis.

The transcription factors CREM, CREB, and ATF-1 constitute a subfamily of beta-Zip transcription factors. Several different kinase cascades regulate the activity of these proteins. The activator splice-isoform CREMtau is specifically and highly expressed in post-meiotic germ cells during mouse spermatogenesis. Male mice lacking CREMtau expression are sterile because of stage-specific arrest of sperm maturation as the spermatids undergo apoptosis. In order to characterize the genes that are controlled by CREM during post-meiotic differentiation of round spermatids, we compared the expression levels of mRNA prepared from testes of wild-type and CREM-deficient mice by suppression subtractive hybridization (SSH) and affymetrix oligonucleotide arrays. A set of 956 unique sequences found in the CREM SSH library was further characterized by generating stage-specific expression profiles during spermatogenesis by hybridization with cDNA from pre-pubertal mice at defined stages of spermatogenesis using nylon DNA arrays. The resulting expression profiles were arranged in a linear order according to similarity in their profile shapes to find co-regulation of functionally related genes. Our data shows that a large number of genes are transcriptionally activated in round spermatids when CREM activity is maximal, including functional groups like transcription factors, proteins involved in signal transduction, and metabolic enzymes, therefore providing novel information of post-meiotic expression of many known as well as novel genes that are either directly or indirectly influenced by CREM expression.

Animals↗

PubMed2003

On the power of profiles for transcription factor binding site detection.

Transcription factor binding site (TFBS) detection plays an important role in computational biology, with applications in gene finding and gene regulation. The sites are often modeled by gapless profiles, also known as position-weight matrices. Past research has focused on the significance of profile scores (the ability to avoid false positives), but this alone is not enough: The profile must also possess the power to detect the true positive signals. Several completed genomes are now available, and the search for TFBSs is moving to a large scale; so discriminating signal from noise becomes even more challenging. Since TFBS profiles are usually estimated from only a few experimentally confirmed instances, careful regularization is an important issue. We present a novel method that is well suited for this situation. We further develop measures that help in judging profile quality, based on both sensitivity and selectivity of a profile. It is shown that these quality measures can be efficiently computed, and we propose statistically well-founded methods to choose score thresholds. Our findings are applied to the TRANSFAC database of transcription factor binding sites. The results are disturbing: If we insist on a significance level of 5% in sequences of length 500, only 19% of the profiles detect a true signal instance with 95% success probability under varying background sequence compositions.

Journal Article↗

PubMed2003

Correlating protein-DNA and protein-protein interaction networks.

Here, we search protein-DNA binding data for prevalent pairs and higher-order tuples of co-occurring transcription factors (TF) in Saccharomyces cerevisiae. While the identification of such modules is dependent on uncertainties of genome-wide data sets, we find several biologically meaningful examples, which allow putative annotation of yet unclassified genes. For the frequently occurring transcriptional module Mcm1-Fkh2-Ndd1, we identified several new target genes involved in cell-cycle control and filament formation. Using large-scale protein interaction data, we demonstrate a significant correlation between co-occurrence of TF binding sites and the vicinity in the protein interaction network. In particular we find that directly interacting transcription factors and those which are members of a protein complex are more likely to occur together as putative DNA-binding modules.

DNA↗

PubMed2003

Genome-scale design of PCR primers and long oligomers for DNA microarrays.

During the last years, the demand for custom-made cDNA chips/arrays as well as whole genome chips is increasing rapidly. The efficient selection of gene-specific primers/oligomers is of the utmost importance for the successful production of such chips. We developed GenomePRIDE, a highly flexible and scalable software for designing primers/oligomers for large-scale projects. The program is able to generate either long oligomers (40-70 bases), or PCR primers for the amplification of gene-specific DNA fragments of user-defined length. Additionally, primers can be designed in-frame in order to facilitate large-scale cloning into expression vectors. Furthermore, GenomePRIDE can be adapted to specific applications such as the generation of genomic amplicon arrays or the design of fragments specific for alternative splice isoforms. We tested the performance of GenomePRIDE on the entire genomes of Listeria monocytogenes (1584 gene-specific PCRs, 48 long oligomers) as well as of eukaryotes such as Schizosaccharomyces pombe (5006 gene-specific PCRs), and Drosophila melanogaster (21 306 gene-specific PCRs). With its computing speed of 1000 primer pairs per hour and a PCR amplification success of 99%, GenomePRIDE represents an extremely cost- and time-effective program.

Animals↗

PubMed2003

Genome-wide array analysis of normal and malformed human hearts.

BACKGROUND: We present the first genome-wide cDNA array analysis of human congenitally malformed hearts and attempted to partially elucidate these complex phenotypes. Most congenital heart defects, which account for the largest number of birth defects in humans, represent complex genetic disorders. As a consequence of the malformation, abnormal hemodynamic features occur and cause an adaptation process of the heart. METHODS AND RESULTS: The statistical analysis of our data suggests distinct gene expression profiles associated with tetralogy of Fallot, ventricular septal defect, and right ventricular hypertrophy. Applying correspondence analysis, we could associate specific gene functions to specific phenotypes. Furthermore, our study design allows the suggestion that alterations associated with primary genetic abnormalities can be distinguished from those associated with the adaptive response of the heart to the malformation (right ventricular pressure overload hypertrophy). We provide evidence for the molecular transition of the hypertrophic right ventricle to normal left ventricular characteristics. Furthermore, we present data on chamber-specific gene expression. CONCLUSIONS: Our findings propose that array analysis of malformed human hearts opens a new window to understand the complex genetic network of cardiac development and adaptation. For detailed access, see the online-only Data Supplement.

Adaptation, Physiological↗

PubMed2003

Parameter estimation for the calibration and variance stabilization of microarray data.

We derive and validate an estimator for the parameters of a transformation for the joint calibration (normalization) and variance stabilization of microarray intensity data. With this, the variances of the transformed intensities become approximately independent of their expected values. The transformation is similar to the logarithm in the high intensity range, but has a smaller slope for intensities close to zero. Applications have shown better sensitivity and specificity for the detection of differentially expressed genes. In this paper, we describe the theoretical aspects of the method. We incorporate calibration and variance-mean dependence into a statistical model and use a robust variant of the maximum-likelihood method to estimate the transformation parameters. Using simulations, we investigate the size of the estimation error and its dependence on sample size and the presence of outliers. We find that the error decreases with the square root of the number of probes per array and that the estimation is robust against the presence of differentially expressed genes. Software is publicly available as an R package through the Bioconductor project (http://www.bioconductor.org).

Journal Article↗