Thomas Manke

deepTools: a flexible platform for exploring deep-sequencing data

We present a Galaxy based web server for processing and visualizing deeply sequenced data. The web servers core functionality consists of a suite of newly developed tools, called deepTools, that enable users with little bioinformatic background to explore the results of their sequencing experiments in a standardized setting. Users can upload pre-processed files with continuous data in standard formats and generate heatmaps and summary plots in a straight-forward, yet highly customizable manner. In addition, we offer several tools for the analysis of files containing aligned reads and enable efficient and reproducible generation of normalized coverage files. As a modular and open-source platform, deepTools can easily be expanded and customized to future demands and developments. The deepTools webserver is freely available at http://deeptools.ie-freiburg.mpg.de and is accompanied by extensive documentation and tutorials aimed at conveying the principles of deep-sequencing data analysis. The web server can be used without registration. deepTools can be installed locally either stand-alone or as part of Galaxy.

deepTools2: a next generation web server for deep-sequencing data analysis

We present an update to our Galaxy-based web server for processing and visualizing deeply sequenced data. Its core tool set, deepTools, allows users to perform complete bioinformatic workflows ranging from quality controls and normalizations of aligned reads to integrative analyses, including clustering and visualization approaches. Since we first described our deepTools Galaxy server in 2014, we have implemented new solutions for many requests from the community and our users. Here, we introduce significant enhancements and new tools to further improve data visualization and interpretation. deepTools continue to be open to all users and freely available as a web service at deeptools.ie-freiburg.mpg.de. The new deepTools2 suite can be easily deployed within any Galaxy framework via the toolshed repository, and we also provide source code for command line usage under Linux and Mac OS X. A public and documented API for access to deepTools functionality is also available.

Predicting transcription factor affinities to DNA from a biophysical model

MOTIVATION Theoretical efforts to understand the regulation of gene expression are traditionally centered around the identification of transcription factor binding sites at specific DNA positions. More recently these efforts have been supplemented by experimental data for relative binding affinities of proteins to longer intergenic sequences. The question arises to what extent these two approaches converge. In this paper, we adopt a physical binding model to predict the relative binding affinity of a transcription factor for a given sequence. RESULTS We find that a significant fraction of genome-wide binding data in yeast can be accounted for by simple count matrices and a physical model with only two parameters. We demonstrate that our approach is both conceptually and practically more powerful than traditional methods, which require selection of a cutoff. Our analysis yields biologically meaningful parameters, suitable for predicting relative binding affinities in the absence of experimental binding data. AVAILABILITY The C source code for our TRAP program is freely available for non-commercial use at http://www.molgen.mpg.de/~manke/papers/TFaffinities/

A transcription factor–based mechanism for mouse heterochromatin formation

Heterochromatin is important for genome integrity and stabilization of gene-expression programs. We have identified the transcription factors Pax3 and Pax9 as redundant regulators of mouse heterochromatin, as they repress RNA output from major satellite repeats by associating with DNA within pericentric heterochromatin. Simultaneous depletion of Pax3 and Pax9 resulted in dramatic derepression of major satellite transcripts, persistent impairment of heterochromatic marks and defects in chromosome segregation. Genome-wide analyses of methylated histone H3 at Lys9 showed enrichment at intergenic major satellite repeats only when these sequences retained intact binding sites for Pax and other transcription factors. Additionally, bioinformatic interrogation of all histone methyltransferase Suv39h–dependent heterochromatic repeat regions in the mouse genome revealed a high concordance with the presence of transcription factor binding sites. These data define a general model in which reiterated arrangement of transcription factor binding sites within repeat sequences is an intrinsic mechanism of the formation of heterochromatin.

Suv39h-Dependent H3K9me3 Marks Intact Retrotransposons and Silences LINE Elements in Mouse Embryonic Stem Cells

Heterochromatin is required to restrict aberrant expression of retrotransposons, but it remains poorly defined due to the underlying repeat-rich sequences. We dissected Suv39h-dependent histone H3 lysine 9 trimethylation (H3K9me3) by genome-wide ChIP sequencing in mouse embryonic stem cells (ESCs). Refined bioinformatic analyses of repeat subfamilies indicated selective accumulation of Suv39h-dependent H3K9me3 at interspersed repetitive elements that cover ∼5% of the ESC epigenome. The majority of the ∼8,150 intact long interspersed nuclear elements (LINEs) and endogenous retroviruses (ERVs), but only a minor fraction of the >1.8 million degenerate and truncated LINEs/ERVs, are enriched for Suv39h-dependent H3K9me3. Transcriptional repression of intact LINEs and ERVs is differentially regulated by Suv39h and other chromatin modifiers in ESCs but governed by DNA methylation in committed cells. These data provide a function for Suv39h-dependent H3K9me3 chromatin to specifically repress intact LINE elements in the ESC epigenome.

PASTAA: identifying transcription factors associated with sets of co-regulated genes

Motivation: A major challenge in regulatory genomics is the identification of associations between functional categories of genes (e.g. tissues, metabolic pathways) and their regulating transcription factors (TFs). While, for a limited number of categories, the regulating TFs are already known, still for many functional categories the responsible factors remain to be elucidated. Results: We put forward a novel method (PASTAA) for detecting transcriptions factors associated with functional categories, which utilizes the prediction of binding affinities of a TF to promoters. This binding strength information is compared to the likelihood of membership of the corresponding genes in the functional category under study. Coherence between the two ranked datasets is seen as an indicator of association between a TF and the category. PASTAA is applied primarily to the determination of TFs driving tissue-specific expression. We show that PASTAA is capable of recovering many TFs acting tissue specifically and, in addition, provides novel associations so far not detected by alternative methods. The application of PASTAA to detect TFs involved in the regulation of tissue-specific gene expression revealed a remarkable number of experimentally supported associations. The validated success for various datasets implies that PASTAA can directly be applied for the detection of TFs associated with newly derived gene sets. Availability: The PASTAA source code as well as a corresponding web interface is freely available at http://trap.molgen.mpg.de Contact: roider@molgen.mpg.de Supplementary information: Supplementary data are available at Bioinformatics online.

Transcription factor binding predictions using TRAP for the analysis of ChIP-seq data and regulatory SNPs

The transcription factor affinity prediction (TRAP) method calculates the affinity of transcription factors for DNA sequences on the basis of a biophysical model. This method has proven to be useful for several applications, including for determining the putative target genes of a given factor. This protocol covers two other applications: (i) determining which transcription factors have the highest affinity in a set of sequences (illustrated with chromatin immunoprecipitation–sequencing (ChIP-seq) peaks), and (ii) finding which factor is the most affected by a regulatory single-nucleotide polymorphism. The protocol describes how to use the TRAP web tools to address these questions, and it also presents a way to run TRAP on random control sequences to better estimate the significance of the results. All of the tools are fully available online and do not need any additional installation. The complete protocol takes about 45 min, but each individual tool runs in a few minutes.

MicroRNAs Differentially Expressed in Postnatal Aortic Development Downregulate Elastin via 3′ UTR and Coding-Sequence Binding Sites

Elastin production is characteristically turned off during the maturation of elastin-rich organs such as the aorta. MicroRNAs (miRNAs) are small regulatory RNAs that down-regulate target mRNAs by binding to miRNA regulatory elements (MREs) typically located in the 3′ UTR. Here we show a striking up-regulation of miR-29 and miR-15 family miRNAs during murine aortic development with commensurate down-regulation of targets including elastin and other extracellular matrix (ECM) genes. There were a total of 14 MREs for miR-29 in the coding sequences (CDS) and 3′ UTR of elastin, which was highly significant, and up to 22 miR-29 MREs were found in the CDS of multiple ECM genes including several collagens. This overrepresentation was conserved throughout mammalian evolution. Luciferase reporter assays showed synergistic effects of miR-29 and miR-15 family miRNAs on 3′ UTR and coding-sequence elastin constructs. Our results demonstrate that multiple miR-29 and miR-15 family MREs are characteristic for some ECM genes and suggest that miR-29 and miR-15 family miRNAs are involved in the down-regulation of elastin in the adult aorta.

Heterochromatin boundaries are hotspots for de novo kinetochore formation

The centromere-specific histone H3 variant CENH3 (also known as CENP-A) is considered to be an epigenetic mark for establishment and propagation of centromere identity. Pulse induction of CENH3 (Drosophila CID) in Schneider S2 cells leads to its incorporation into non-centromeric regions and generates CID islands that resist clearing from chromosome arms for multiple cell generations. We demonstrate that CID islands represent functional ectopic kinetochores, which are non-randomly distributed on the chromosome and show a preferential localization near telomeres and pericentric heterochromatin in transcriptionally silent, intergenic chromatin domains. Although overexpression of heterochromatin protein 1 (HP1) or increasing histone acetylation interferes with CID island formation on a global scale, induction of a locally defined region of synthetic heterochromatin by targeting HP1–LacI fusions to stably integrated Lac operator arrays produces a proximal hotspot for CID deposition. These data indicate that the characteristics of regions bordering heterochromatin promote de novo kinetochore assembly and thereby contribute to centromere identity.

Paracrine control of oligodendrocyte differentiation by SRF-directed neuronal gene expression

In neurons, serum response factor (SRF)-directed transcription regulates migration, axon pathfinding and synapse function. We found that forebrain-specific, neuron-restricted SRF ablation in mice elevated oligodendrocyte precursors while inhibiting terminal oligodendrocyte differentiation. Myelin gene and protein expression were downregulated and we observed a lack of oligodendrocytes in mixed neuron/glia and oligodendrocyte-enriched cultures derived from Srf−/− mutants. Ultrastructural inspection revealed myelination defects and axonal degeneration in Srf−/− mutants. Consistent with our finding that neuronal SRF depletion impaired oligodendrocyte fate in a non–cell autonomous manner, neuron-restricted expression of constitutively active SRF-VP16 affected neighboring oligodendrocyte maturation. Genome-wide transcriptomics identified candidate genes for paracrine regulation of oligodendrocyte development, including connective tissue growth factor (CTGF), whose expression is repressed by SRF. Adenovirus-mediated CTGF expression in vivo revealed that CTGF blocks excessive oligodendrocyte differentiation. In vitro, CTGF-mediated inhibition of oligodendrocyte maturation involved sequestration and thereby counteraction of insulin growth factor 1–stimulated oligodendrocyte differentiation.