57 research outputs found

    MEME-ChIP: motif analysis of large DNA datasets

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    Motivation: Advances in high-throughput sequencing have resulted in rapid growth in large, high-quality datasets including those arising from transcription factor (TF) ChIP-seq experiments. While there are many existing tools for discovering TF binding site motifs in such datasets, most web-based tools cannot directly process such large datasets

    The cerebellar transcriptome during postnatal development of the Ts1Cje mouse, a segmental trisomy model for Down syndrome

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    The central nervous system of persons with Down syndrome presents cytoarchitectural abnormalities that likely result from gene-dosage effects affecting the expression of key developmental genes. To test this hypothesis, we have investigated the transcriptome of the cerebellum of the Ts1Cje mouse model of Down syndrome during postnatal development using microarrays and quantitative PCR (qPCR). Genes present in three copies were consistently overexpressed, with a mean ratio relative to euploid of 1.52 as determined by qPCR. Out of 63 three-copy genes tested, only five, nine and seven genes had ratios >2 or <1.2 at postnatal days 0 (P0), P15 and P30, respectively. This gene-dosage effect was associated with a dysregulation of the expression of some two-copy genes. Out of 8258 genes examined, the Ts1Cje/euploid ratios differed significantly from 1.0 for 406 (80 and 154 with ratios above 1.5 and below 0.7, respectively), 333 (11 above 1.5 and 55 below 0.7) and 246 genes (59 above 1.5 and 69 below 0.7) at P0, P15 and P30, respectively. Among the two-copy genes differentially expressed in the trisomic cerebellum, six homeobox genes, two belonging to the Notch pathway, were severely repressed. Overall, at P0, transcripts involved in cell differentiation and development were over-represented among the dysregulated genes, suggesting that cell differentiation and migration might be more altered than cell proliferation. Finally, global gene profiling revealed that transcription in Ts1Cje mice is more affected by the developmental changes than by the trisomic state, and that there is no apparent detectable delay in the postnatal development of the cerebellum of Ts1Cje mic

    A parallel, distributed-memory framework for comparative motif discovery

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    The increasing number of sequenced organisms has opened new possibilities for the computational discovery of cis-regulatory elements ('motifs') based on phylogenetic footprinting. Word-based, exhaustive approaches are among the best performing algorithms, however, they pose significant computational challenges as the number of candidate motifs to evaluate is very high. In this contribution, we describe a parallel, distributed-memory framework for de novo comparative motif discovery. Within this framework, two approaches for phylogenetic footprinting are implemented: an alignment-based and an alignment-free method. The framework is able to statistically evaluate the conservation of motifs in a search space containing over 160 million candidate motifs using a distributed-memory cluster with 200 CPU cores in a few hours. Software available from http://bioinformatics.intec.ugent.be/blsspeller

    Characterization of the neural stem cell gene regulatory network identifies OLIG2 as a multifunctional regulator of self-renewal

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    The gene regulatory network (GRN) that supports neural stem cell (NS cell) self-renewal has so far been poorly characterized. Knowledge of the central transcription factors (TFs), the noncoding gene regulatory regions that they bind to, and the genes whose expression they modulate will be crucial in unlocking the full therapeutic potential of these cells. Here, we use DNase-seq in combination with analysis of histone modifications to identify multiple classes of epigenetically and functionally distinct cis-regulatory elements (CREs). Through motif analysis and ChIP-seq, we identify several of the crucial TF regulators of NS cells. At the core of the network are TFs of the basic helix-loop-helix (bHLH), nuclear factor I (NFI), SOX, and FOX families, with CREs often densely bound by several of these different TFs. We use machine learning to highlight several crucial regulatory features of the network that underpin NS cell self-renewal and multipotency. We validate our predictions by functional analysis of the bHLH TF OLIG2. This TF makes an important contribution to NS cell self-renewal by concurrently activating pro-proliferation genes and preventing the untimely activation of genes promoting neuronal differentiation and stem cell quiescence.Welcome Trust grants: (WT095908, WT098051), FEBS Long-Term Fellowship, Medical Research Council Grant-in-Aid (U117570528)

    DLocalMotif: a discriminative approach for discovering local motifs in protein sequences

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    Motivation: Local motifs are patterns of DNA or protein sequences that occur within a sequence interval relative to a biologically defined anchor or landmark. Current protein motif discovery methods do not adequately consider such constraints to identify biologically significant motifs that are only weakly over-represented but spatially confined. Using negatives, i.e. sequences known to not contain a local motif, can further increase the specificity of their discovery

    Combining Computational Prediction of Cis-Regulatory Elements with a New Enhancer Assay to Efficiently Label Neuronal Structures in the Medaka Fish

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    The developing vertebrate nervous system contains a remarkable array of neural cells organized into complex, evolutionarily conserved structures. The labeling of living cells in these structures is key for the understanding of brain development and function, yet the generation of stable lines expressing reporter genes in specific spatio-temporal patterns remains a limiting step. In this study we present a fast and reliable pipeline to efficiently generate a set of stable lines expressing a reporter gene in multiple neuronal structures in the developing nervous system in medaka. The pipeline combines both the accurate computational genome-wide prediction of neuronal specific cis-regulatory modules (CRMs) and a newly developed experimental setup to rapidly obtain transgenic lines in a cost-effective and highly reproducible manner. 95% of the CRMs tested in our experimental setup show enhancer activity in various and numerous neuronal structures belonging to all major brain subdivisions. This pipeline represents a significant step towards the dissection of embryonic neuronal development in vertebrates

    The Light Responsive Transcriptome of the Zebrafish: Function and Regulation

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    Most organisms possess circadian clocks that are able to anticipate the day/night cycle and are reset or “entrained” by the ambient light. In the zebrafish, many organs and even cultured cell lines are directly light responsive, allowing for direct entrainment of the clock by light. Here, we have characterized light induced gene transcription in the zebrafish at several organizational levels. Larvae, heart organ cultures and cell cultures were exposed to 1- or 3-hour light pulses, and changes in gene expression were compared with controls kept in the dark. We identified 117 light regulated genes, with the majority being induced and some repressed by light. Cluster analysis groups the genes into five major classes that show regulation at all levels of organization or in different subset combinations. The regulated genes cover a variety of functions, and the analysis of gene ontology categories reveals an enrichment of genes involved in circadian rhythms, stress response and DNA repair, consistent with the exposure to visible wavelengths of light priming cells for UV-induced damage repair. Promoter analysis of the induced genes shows an enrichment of various short sequence motifs, including E- and D-box enhancers that have previously been implicated in light regulation of the zebrafish period2 gene. Heterologous reporter constructs with sequences matching these motifs reveal light regulation of D-box elements in both cells and larvae. Morpholino-mediated knock-down studies of two homologues of the D-box binding factor Tef indicate that these are differentially involved in the cell autonomous light induction in a gene-specific manner. These findings suggest that the mechanisms involved in period2 regulation might represent a more general pathway leading to light induced gene expression

    Ranking insertion, deletion and nonsense mutations based on their effect on genetic information

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    <p>Abstract</p> <p>Background</p> <p>Genetic variations contribute to normal phenotypic differences as well as diseases, and new sequencing technologies are greatly increasing the capacity to identify these variations. Given the large number of variations now being discovered, computational methods to prioritize the functional importance of genetic variations are of growing interest. Thus far, the focus of computational tools has been mainly on the prediction of the effects of amino acid changing single nucleotide polymorphisms (SNPs) and little attention has been paid to indels or nonsense SNPs that result in premature stop codons.</p> <p>Results</p> <p>We propose computational methods to rank insertion-deletion mutations in the coding as well as non-coding regions and nonsense mutations. We rank these variations by measuring the extent of their effect on biological function, based on the assumption that evolutionary conservation reflects function. Using sequence data from budding yeast and human, we show that variations which that we predict to have larger effects segregate at significantly lower allele frequencies, and occur less frequently than expected by chance, indicating stronger purifying selection. Furthermore, we find that insertions, deletions and premature stop codons associated with disease in the human have significantly larger predicted effects than those not associated with disease. Interestingly, the large-effect mutations associated with disease show a similar distribution of predicted effects to that expected for completely random mutations.</p> <p>Conclusions</p> <p>This demonstrates that the evolutionary conservation context of the sequences that harbour insertions, deletions and nonsense mutations can be used to predict and rank the effects of the mutations.</p

    AMD, an Automated Motif Discovery Tool Using Stepwise Refinement of Gapped Consensuses

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    Motif discovery is essential for deciphering regulatory codes from high throughput genomic data, such as those from ChIP-chip/seq experiments. However, there remains a lack of effective and efficient methods for the identification of long and gapped motifs in many relevant tools reported to date. We describe here an automated tool that allows for de novo discovery of transcription factor binding sites, regardless of whether the motifs are long or short, gapped or contiguous
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