Biology subjects

Gruening, B.

Publications and source records attributed to Gruening, B..

3 recordsLinked to original sources

bioRxiv2018

Pou5f3, SoxB1 and Nanog remodel chromatin on High Nucleosome Affinity Regions at Zygotic Genome Activation

The zebrafish embryo is mostly transcriptionally quiescent during the first 10 cell cycles, until the main wave of Zygotic Genome Activation (ZGA) occurs, accompanied by fast chromatin remodeling. At ZGA, homologs of mammalian stem cell transcription factors (TFs) Pou5f3, Nanog and Sox19b bind to thousands of developmental enhancers to initiate transcription. So far, how these TFs influence chromatin dynamics at ZGA has remained unresolved. To address this question, we analyzed nucleosome positions in wild-type and Maternal-Zygotic (MZ) mutants for pou5f3 and nanog by MNase-seq. We show that Nanog, Sox19b and Pou5f3 bind to the High Nucleosome Affinity Regions (HNARs). HNARs are spanning over 600 bp, featuring high in vivo and predicted in vitro nucleosome occupancy and high predicted propeller twist DNA shape value. We suggest a two-step nucleosome destabilization-depletion model, where the same intrinsic DNA properties of HNAR promote both high nucleosome occupancy and differential binding of TFs. In the first step, already prior to ZGA, Pou5f3 and Nanog destabilize nucleosomes on HNAR centers genome-wide. In the second step, post-ZGA, Nanog, Pou5f3 and SoxB1 maintain open chromatin state on the subset of HNARs, acting synergistically. Nanog binds to the HNAR center, while the Pou5f3 stabilizes the flanks. The HNAR model will provide a useful tool for genome regulatory studies in the variety of biological systems.

developmental biology↗

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↗

bioRxiv2017

Strategies for analyzing bisulfite sequencing data

DNA methylation is one of the main epigenetic modifications in the eukaryotic genome; it has been shown to play a role in cell-type specific regulation of gene expression, and therefore cell-type identity. Bisulfite sequencing is the gold-standard for measuring methylation over the genomes of interest. Here, we review several techniques used for the analysis of high-throughput bisulfite sequencing. We introduce specialized short-read alignment techniques as well as pre/post-alignment quality check methods to ensure data quality. Furthermore, we discuss subsequent analysis steps after alignment. We introduce various differential methylation methods and compare their performance using simulated and real bisulfite sequencing datasets. We also discuss the methods used to segment methylomes in order to pinpoint regulatory regions. We introduce annotation methods that can be used for further classification of regions returned by segmentation and differential methylation methods. Finally, we review software packages that implement strategies to efficiently deal with large bisulfite sequencing datasets locally and we discuss online analysis workflows that do not require any prior programming skills. The analysis strategies described in this review will guide researchers at any level to the best practices of bisulfite sequencing analysis.

bioinformatics↗