Biology subjects

Manke, T.

Publications and source records attributed to Manke, T..

8 recordsLinked to original sources

bioRxiv2018

snakePipes enable flexible, scalable and integrative epigenomic analysis

The scale and diversity of epigenomics data has been rapidly increasing and ever more studies now present analyses of data from multiple epigenomic techniques. Performing such integrative analysis is time-consuming, especially for exploratory research, since there are currently no pipelines available that allow fast processing of datasets from multiple epigenomic assays while also allow for flexibility in running or upgrading the workflows. Here we present a solution to this problem: snakePipes, which can process and perform downstream analysis of data from all common epigenomic techniques (ChIP-seq, RNA-seq, Bisulfite-seq, ATAC-seq, Hi-C and single-cell RNA-seq) in a single package. We demonstrate how snakePipes can simplify integrative analysis by reproducing and extending the results from a recently published large-scale epigenomics study with a few simple commands. snakePipes are available under an open-source license at https://github.com/maxplanck-ie/snakepipes.

genomics↗

bioRxiv2018

Parkour LIMS: facilitating high-quality sample preparation in next generation sequencing

SummaryThis paper presents Parkour, a software package for sample processing and quality management of next generation sequencing data and samples. Starting with user requests, Parkour allows tracking and assessing samples based on predefined quality criteria through different stages of the sample preparation workflow. Ideally suited for academic core laboratories, the software aims to maximize efficiency and reduce turnaround time by intelligent sample grouping and a clear assignment of staff to work units. Tools for automated invoicing, interactive statistics on facility usage and simple report generation minimize administrative tasks. Provided as a web application, Parkour is a convenient tool for both deep sequencing service users and laboratory personal. A set of web APIs allow coordinated information sharing with local and remote bioinformaticians. The flexible structure allows workflow customization and simple addition of new features as well as the expansion to other domains.\n\nAvailability and implementationThe code and documentation are available at https://github.com/maxplanck-ie/parkour\n\nContactboenisch@ie-freiburg.mpg.de

genomics↗

bioRxiv2018

Integrative analysis of single cell expression data reveals distinct regulatory states in bidirectional promoters

BackgroundBidirectional promoters (BPs) are prevalent in eukaryotic genomes. However, it is poorly understood how the cell integrates different epigenomic information, such as transcription factor (TF) binding and chromatin marks, to drive gene expression at BPs. Single cell sequencing technologies are revolutionizing the field of genome biology. Therefore, this study focuses on the integration of single cell RNA-seq data with bulk ChIP-seq and other epigenetics data, for which single cell technologies are not yet established, in the context of BPs.\n\nResultsWe performed integrative analyses of novel human single cell RNA-seq (scRNA-seq) data with bulk ChIP-seq and other epigenetics data. scRNA-seq data revealed distinct transcription states of BPs that were previously not recognized. We find associations between these transcription states to distinct patterns in structural gene features, DNA accessibility, histone modification, DNA methylation and TF binding profiles.\n\nConclusionsOur results suggest that a complex interplay of all of these elements is required to achieve BP-specific transcriptional output in this specialized promoter configuration. Further, our study implies that novel statistical methods can be developed to deconvolute masked subpopulations of cells measured with different bulk epigenomic assays using scRNA-seq data.

genomics↗

bioRxiv2018

Ultra-parallel ChIP-seq by barcoding of intact nuclei

Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) is an invaluable tool for mapping chromatin-associated proteins. However, sample preparation is still a largely individual and labor-intensive process that hinders assay throughput and comparability. Here, we present a novel method for ultra-parallelized high-throughput ChIP-seq that addresses the aforementioned problems. The method, called RELACS (Restriction Enzyme-based Labeling of Chromatin in Situ), employs barcoding of chromatin within intact nuclei extracted from different sources (e.g. tissues, treatments, time points). Barcoded nuclei are pooled and processed within the same ChIP, for maximal comparability and significant workload reduction. The choice of user-friendly, straightforward, enzymatic steps for chromatin fragmentation and barcoding makes RELACS particularly suitable for implementation large-scale clinical studies and scarce samples. RELACS can generate ChIP-seq libraries from hundreds of samples within three days and with less than 1000 cells per sample.

genomics↗

bioRxiv2018

Partially methylated domains are hallmarks of a cell specific epigenome topology

BackgroundPartially methylated domains, PMDs, are extended regions in the genome exhibiting a reduced average DNA-methylation level. PMDs cover gene-poor and transcriptionally inactive regions and tend to be heterochromatic. Here, we present a first comprehensive comparative analysis of PMDs across more than 190 WGBS methylomes of human and mouse cells providing a deep insight into structural and functional features associated with PMDs.\n\nResultsPMDs are ubiquitous signatures covering up to 75% of the genome in human and mouse cells irrespective of their tissue or cell origin. Additionally, each cell type comes with a distinct set of specific PMDs, and genes expressed in such PMDs show a strong cell type effect. Demethylation strength varies in PMDs with a tendency towards a more pronounced effect in differentiating and replicating cells. The strongest demethylation is observed in highly proliferating and immortal cancer cell lines. A decrease of DNA-methylation within PMDs tends to be linked to an increase in heterochromatic histone marks and a decrease of gene expressions. Characteristic combinations of heterochromatic signatures in PMDs are linked to domains of early, middle and late DNA-replication.\n\nConclusionPMDs are prominent signatures of long-range epigenomic organization. Integrative analysis identifies PMDs as important general, lineage- and cell-type specific topological features. PMD changes are hallmarks of cell differentiation. Demethylation of PMDs combined with increased heterochromatic marks is a feature linked to enhanced cell proliferation. In combination with broad histone marks PMDs demarcate distinct domains of late DNA-replication.

bioinformatics↗

bioRxiv2017

Community-driven data analysis training for biology

The primary problem with the explosion of biomedical datasets is not the data itself, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key feature of our system is that it is not a static but a continuously improved collection of tutorials. By coupling tutorials with a web-based analysis framework, biomedical researchers can learn by performing computation themselves through a web-browser without the need to install software or search for example datasets. Our ultimate goal is to expand the breadth of training materials to include fundamental statistical and data science topics and to precipitate a complete re-engineering of undergraduate and graduate curricula in life sciences.

bioinformatics↗

bioRxiv2017

High-resolution TADs reveal DNA sequences underlying genome organization in flies

Eukaryotic chromatin is partitioned into domains called TADs that are broadly conserved between species and virtually identical among cell types within the same species. Previous studies in mammals have shown that the DNA binding protein CTCF and cohesin contribute to a fraction of TAD boundaries. Apart from this, the molecular mechanisms governing this partitioning remain poorly understood. Using our new software, HiCExplorer, we annotated high-resolution (570 bp) TAD boundaries in flies and identified eight DNA motifs enriched at boundaries. Known insulator proteins bind five of these motifs while the remaining three motifs are novel. We find that boundaries are either at core promoters of active genes or at non-promoter regions of inactive chromatin and that these two groups are characterized by different sets of DNA motifs. Most boundaries are present at divergent promoters of constitutively expressed genes and the gene expression tends to be coordinated within TADs. In contrast to mammals, the CTCF motif is only present on 2% of boundaries in flies. We demonstrate that boundaries can be accurately predicted using only the motif sequences, along with open chromatin, suggesting that DNA sequence encodes the 3D genome architecture in flies. Finally, we present an interactive online database to access and explore the spatial organization of fly, mouse and human genomes, available at http://chorogeome.ie-freiburg.mpg.de.

genomics↗

bioRxiv2016

normR: Regime enrichment calling for ChIP-seq data

ChIP-seq probes genome-wide localization of DNA-associated proteins. To mitigate technical biases ChIP-seq read densities are normalized to read densities obtained by a control. Our statistical framework \"normR\" achieves a sensitive normalization by accounting for the effect of putative protein-bound regions on the overall read statistics. Here, we demonstrate normRs suitability in three studies: (i) calling enrichment for high (H3K4me3) and low (H3K36me3) signal-to-ratio data; (ii) identifying two previously undescribed H3K27me3 and H3K9me3 heterochromatic regimes of broad and peak enrichment; and (iii) calling differential H3K4me3 or H3K27me3-enrichment between HepG2 hepatocarcinoma cells and primary human Hepatocytes. normR is readily available on http://bioconductor.org/packages/normr

bioinformatics↗