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Histone H3 lysine 9 (H3K9) methylation is a central epigenetic modification that defines heterochromatin from unicellular to multicellular organisms. In mammalian cells, H3K9 methylation can be catalyzed by at least six distinct SET domain enzymes: Suv39h1/Suv39h2, Eset1/Eset2 and G9a/Glp. We used mouse embryonic fibroblasts (MEFs) with a conditional mutation for Eset1 and introduced progressive deletions for the other SET domain genes by CRISPR/Cas9 technology. Compound mutant MEFs for all six SET domain lysine methyltransferase (KMT) genes lack all H3K9 methylation states, derepress nearly all families of repeat elements and display genomic instabilities. Strikingly, the 6KO H3K9 KMT MEF cells no longer maintain heterochromatin organization and have lost electron-dense heterochromatin. This is a compelling analysis of H3K9 methylation-deficient mammalian chromatin and reveals a definitive function for H3K9 methylation in protecting heterochromatin organization and genome integrity., Histone H3K9 methylation (H3K9me) states define repressed chromatin in eukaryotic cells. Here the authors reveal complete loss of all H3K9me in mammalian cells through successive deletion of H3K9 methyltransferase genes that results in the dissolution of heterochromatin and the derepression of nearly all repeat families.

Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) is an invaluable tool for mapping chromatin-associated proteins. Current barcoding strategies aim to improve assay throughput and scalability but intense sample handling and lack of standardization over cell types, cell numbers and epitopes hinder wide-spread use in the field. Here, we present a barcoding method to enable high-throughput ChIP-seq using common molecular biology techniques. The method, called RELACS (restriction enzyme-based labeling of chromatin in situ) relies on standardized nuclei extraction from any source and employs chromatin cutting and barcoding within intact nuclei. Barcoded nuclei are pooled and processed within the same ChIP reaction, for maximal comparability and workload reduction. The innovative barcoding concept is particularly user-friendly and suitable for implementation to standardized large-scale clinical studies and scarce samples. Aiming to maximize universality and scalability, RELACS can generate ChIP-seq libraries for transcription factors and histone modifications from hundreds of samples within three days., Laura Arrigoni et al. present RELACS, a method enabling high-throughput ChIP-seq which involves barcoding and processing intact nuclei in the same ChIP reaction. The method is useful for broad cell types and epitopes, robust to experimental conditions, and drastically decreases workload.

Motivation This paper presents Parkour, a software package for sample processing and quality management of next generation sequencing data and samples. Results 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. Availability and implementation The code and documentation are available at https://github.com/maxplanck-ie/parkour. Supplementary information Supplementary data are available at Bioinformatics online.

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.

Summary Due to the rapidly increasing scale and diversity of epigenomic data, modular and scalable analysis workflows are of wide interest. Here we present snakePipes, a workflow package for processing and downstream analysis of data from common epigenomic assays: ChIP-seq, RNA-seq, Bisulfite-seq, ATAC-seq, Hi-C and single-cell RNA-seq. snakePipes enables users to assemble variants of each workflow and to easily install and upgrade the underlying tools, via its simple command-line wrappers and yaml files. Availability and implementation snakePipes can be installed via conda: `conda install -c mpi-ie -c bioconda -c conda-forge snakePipes’. Source code (https://github.com/maxplanck-ie/snakepipes) and documentation (https://snakepipes.readthedocs.io/en/latest/) are available online. Supplementary information Supplementary data are available at Bioinformatics online.

Significance Aging-associated diseases are increasingly common in an aging global population. However, the contributors and origins of differential risk for unhealthy aging remain poorly understood. Using a mouse model, we found that offspring of aged fathers exhibited a reduced life span and more pronounced aging-associated pathologies than animals sired by young fathers. Tissue of offspring and aged fathers revealed shared epigenetic signatures and showed altered activation states of longevity-related cell signaling. Our results suggest that variability in aging trajectories could derive, in part, from the age at conception of the father, a possibility that warrants human epidemiological investigation., Advanced age is not only a major risk factor for a range of disorders within an aging individual but may also enhance susceptibility for disease in the next generation. In humans, advanced paternal age has been associated with increased risk for a number of diseases. Experiments in rodent models have provided initial evidence that paternal age can influence behavioral traits in offspring animals, but the overall scope and extent of paternal age effects on health and disease across the life span remain underexplored. Here, we report that old father offspring mice showed a reduced life span and an exacerbated development of aging traits compared with young father offspring mice. Genome-wide epigenetic analyses of sperm from aging males and old father offspring tissue identified differentially methylated promoters, enriched for genes involved in the regulation of evolutionarily conserved longevity pathways. Gene expression analyses, biochemical experiments, and functional studies revealed evidence for an overactive mTORC1 signaling pathway in old father offspring mice. Pharmacological mTOR inhibition during the course of normal aging ameliorated many of the aging traits that were exacerbated in old father offspring mice. These findings raise the possibility that inherited alterations in longevity pathways contribute to intergenerational effects of aging in old father offspring mice.

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.

We present Bioconda (https://bioconda.github.io), a distribution of bioinformatics software for the lightweight, multiplatform and language-agnostic package manager Conda. Currently, Bioconda offers a collection of over 3000 software packages, which is continuously maintained, updated, and extended by a growing global community of more than 200 contributors. Bioconda improves analysis reproducibility by allowing users to define isolated environments with defined software versions, all of which are easily installed and managed without administrative privileges.

Dietary restriction regimes extend lifespan in various animal models. Here we show that longevity in male C57BL/6J mice subjected to every-other-day feeding is associated with a delayed onset of neoplastic disease that naturally limits lifespan in these animals. We compare more than 200 phenotypes in over 20 tissues in aged animals fed with a lifelong every-other-day feeding or ad libitum access to food diet to determine whether molecular, cellular, physiological and histopathological aging features develop more slowly in every-other-day feeding mice than in controls. We also analyze the effects of every-other-day feeding on young mice on shorter-term every-other-day feeding or ad libitum to account for possible aging-independent restriction effects. Our large-scale analysis reveals overall only limited evidence for a retardation of the aging rate in every-other-day feeding mice. The data indicate that every-other-day feeding-induced longevity is sufficiently explained by delays in life-limiting neoplastic disorders and is not associated with a more general slowing of the aging process in mice., Dietary restriction can extend the life of various model organisms. Here, Xie et al. show that intermittent periods of fasting achieved through every-other-day feeding protect mice against neoplastic disease but do not broadly delay organismal aging in animals.

Maternal folic acid (FA) supplementation prior to and during gestation is recommended for the prevention of neural tube closure defects in the developing embryo. Prior studies, however, suggested that excessive FA supplementation during gestation can be associated with toxic effects on the developing organism. Here, we address whether maternal dietary folic acid supplementation at 40 mg/kg chow (FD), restricted to a period prior to conception, affects neurobehavioural development in the offspring generation. Detailed behavioural analyses showed reversal learning impairments in the Morris water maze in offspring derived from dams exposed to FD prior to conceiving. Furthermore, offspring of FD dams showed minor and transient gene expression differences relative to controls. Our data suggest that temporary exposure of female germ cells to FD is sufficient to cause impaired cognitive flexibility in the subsequent generation.

La version finale de l'article a été déposée sur PMC. The final version of this article has been deposed on PMC; The primary problem with the explosion of biomedical datasets is not the data, 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. This project is accessible at https://training.galaxyproject.org.