isolation-processing-murine-white-adipocytes-for-transcriptome

Isolation and Processing of Murine White Adipocytes for Transcriptome and Epigenome Analyses

Obesity is a complex disease influenced by genetics, epigenetics, the environment, and their interactions. Mature adipocytes represent the major cell type ...

Max Planck Institute of Immunobiology and Epigenetics

The global rise in obesity has revitalized a search for genetic and epigenetic factors underlying the disease. We present a Drosophila model of paternal-diet-induced intergenerational metabolic reprogramming (IGMR) and identify genes required for its encoding in offspring. Intriguingly, we find that as little as 2 days of dietary intervention in fathers elicits obesity in offspring. Paternal sugar acts as a physiological suppressor of variegation, desilencing chromatin-state-defined domains in both mature sperm and in offspring embryos. We identify requirements for H3K9/K27me3-dependent reprogramming of metabolic genes in two distinct germline and zygotic windows. Critically, we find evidence that a similar system may regulate obesity susceptibility and phenotype variation in mice and humans. The findings provide insight into the mechanisms underlying intergenerational metabolic reprogramming and carry profound implications for our understanding of phenotypic variation and evolution.

Paternal diet defines offspring chromatin state and intergenerational obesity.

Identifying sequence-structure motifs common to two RNAs can speed up the comparison of structural RNAs substantially. The core algorithm of the existent approach ExpaRNA solves this problem for a priori known input structures. However, such structures are rarely known; moreover, predicting them computationally is no rescue, since single sequence structure prediction is highly unreliable.

ExpaRNA-P: simultaneous exact pattern matching and folding of RNAs.

More than one-half billion people are obese, and despite progress in genetic research, much of the heritability of obesity remains enigmatic. Here, we identify a Trim28-dependent network capable of triggering obesity in a non-Mendelian, "on/off" manner. Trim28(+/D9) mutant mice exhibit a bi-modal body-weight distribution, with isogenic animals randomly emerging as either normal or obese and few intermediates. We find that the obese-"on" state is characterized by reduced expression of an imprinted gene network including Nnat, Peg3, Cdkn1c, and Plagl1 and that independent targeting of these alleles recapitulates the stochastic bi-stable disease phenotype. Adipose tissue transcriptome analyses in children indicate that humans too cluster into distinct sub-populations, stratifying according to Trim28 expression, transcriptome organization, and obesity-associated imprinted gene dysregulation. These data provide evidence of discrete polyphenism in mouse and man and thus carry important implications for complex trait genetics, evolution, and medicine.

Trim28 Haploinsufficiency Triggers Bi-stable Epigenetic Obesity.

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.

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

To date, it remains largely unclear to what extent chromatin machinery contributes to the susceptibility and progression of complex diseases. Here, we combine deep epigenome mapping with single-cell transcriptomics to mine for evidence of chromatin dysregulation in type 2 diabetes. We find two chromatin-state signatures that track β cell dysfunction in mice and humans: ectopic activation of bivalent Polycomb-silenced domains and loss of expression at an epigenomically unique class of lineage-defining genes. β cell-specific Polycomb (Eed/PRC2) loss of function in mice triggers diabetes-mimicking transcriptional signatures and highly penetrant, hyperglycemia-independent dedifferentiation, indicating that PRC2 dysregulation contributes to disease. The work provides novel resources for exploring β cell transcriptional regulation and identifies PRC2 as necessary for long-term maintenance of β cell identity. Importantly, the data suggest a two-hit (chromatin and hyperglycemia) model for loss of β cell identity in diabetes.

The Polycomb-Dependent Epigenome Controls β Cell Dysfunction, Dedifferentiation, and Diabetes.

The Freiburg RNA tools webserver is a well established online resource for RNA-focused research. It provides a unified user interface and comprehensive result visualization for efficient command line tools. The webserver includes RNA-RNA interaction prediction (IntaRNA, CopraRNA, metaMIR), sRNA homology search (GLASSgo), sequence-structure alignments (LocARNA, MARNA, CARNA, ExpaRNA), CRISPR repeat classification (CRISPRmap), sequence design (antaRNA, INFO-RNA, SECISDesign), structure aberration evaluation of point mutations (RaSE), and RNA/protein-family models visualization (CMV), and other methods. Open education resources offer interactive visualizations of RNA structure and RNA-RNA interaction prediction as well as basic and advanced sequence alignment algorithms. The services are freely available at http://rna.informatik.uni-freiburg.de.

Freiburg RNA tools: a central online resource for RNA-focused research and teaching.

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.

snakePipes: facilitating flexible, scalable and integrative epigenomic analysis.

We present the software Condition-specific Regulatory Units Prediction (CRUP) to infer from epigenetic marks a list of regulatory units consisting of dynamically changing enhancers with their target genes. The workflow consists of a novel pre-trained enhancer predictor that can be reliably applied across cell types and species, solely based on histone modification ChIP-seq data. Enhancers are subsequently assigned to different conditions and correlated with gene expression to derive regulatory units. We thoroughly test and then apply CRUP to a rheumatoid arthritis model, identifying enhancer-gene pairs comprising known disease genes as well as new candidate genes.

CRUP: a comprehensive framework to predict condition-specific regulatory units.

RNA plays essential roles in all known forms of life. Clustering RNA sequences with common sequence and structure is an essential step towards studying RNA function. With the advent of high-throughput sequencing techniques, experimental and genomic data are expanding to complement the predictive methods. However, the existing methods do not effectively utilize and cope with the immense amount of data becoming available.

Steffen Heyne

Max Planck Institute of Immunobiology and Epigenetics

Isolation and Processing of Murine White Adipocytes for Transcriptome and Epigenome Analyses