Dataset Information

Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements.

ABSTRACT: Sparse profiling of CpG methylation in blood by microarrays has identified epigenetic links to common diseases. Here we apply methylC-capture sequencing (MCC-Seq) in a clinical population of ~200 adipose tissue and matched blood samples (N_total~400), providing high-resolution methylation profiling (>1.3?M CpGs) at regulatory elements. We link methylation to cardiometabolic risk through associations to circulating plasma lipid levels and identify lipid-associated CpGs with unique localization patterns in regulatory elements. We show distinct features of tissue-specific versus tissue-independent lipid-linked regulatory regions by contrasting with parallel assessments in ~800 independent adipose tissue and blood samples from the general population. We follow-up on adipose-specific regulatory regions under (1) genetic and (2) epigenetic (environmental) regulation via integrational studies. Overall, the comprehensive sequencing of regulatory element methylomes reveals a rich landscape of functional variants linked genetically as well as epigenetically to plasma lipid traits.

SUBMITTER: Allum F

PROVIDER: S-EPMC6418220 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements.

Allum Fiona F Hedman Åsa K ÅK Shao Xiaojian X Cheung Warren A WA Vijay Jinchu J Guénard Frédéric F Kwan Tony T Simon Marie-Michelle MM Ge Bing B Moura Cristiano C Boulier Elodie E Rönnblom Lars L Bernatsky Sasha S Lathrop Mark M McCarthy Mark I MI Deloukas Panos P Tchernof André A Pastinen Tomi T Vohl Marie-Claude MC Grundberg Elin E

Nature communications 20190314 1

Sparse profiling of CpG methylation in blood by microarrays has identified epigenetic links to common diseases. Here we apply methylC-capture sequencing (MCC-Seq) in a clinical population of ~200 adipose tissue and matched blood samples (N<sub>total</sub>~400), providing high-resolution methylation profiling (>1.3 M CpGs) at regulatory elements. We link methylation to cardiometabolic risk through associations to circulating plasma lipid levels and identify lipid-associated CpGs with unique local ...[more]

PMID: 30872577

Similar Datasets

Project description:Human pluripotent stem cell derived models that accurately recapitulate neural development in vitro and allow for the generation of specific neuronal subtypes are of major interest to the stem cell and biomedical community. Notch signaling, particularly through the Notch effector HES5, is a major pathway critical for the onset and maintenance of neural progenitor cells (NPCs) in the embryonic and adult nervous system1-3. Use of a HES5 reporter enables the isolation distinct populations of human embryonic stem (ES) cell derived NPCs that represent building blocks of cortical development in vitro4. Here, we report the transcriptional and epigenomic analysis of six consecutive stages of human ES cell differentiation along the neural lineage aimed at modeling key cell fate decisions including specification, expansion and patterning during the ontogeny of neural stem and progenitor cells. In order to dissect the regulatory mechanisms that orchestrate the stage-specific differentiation process we developed a computational framework to infer key regulators of each cell state transition based on the progressive remodeling of the epigenetic landscape and then validated these through a pooled shRNA screen. We were also able to refine our previous observations on epigenetic priming at transcription factor binding sites and show here that they are mediated by combinations of core and stage-specific factors. Taken together, we demonstrate the utility of our reference maps and outline a general framework, not limited to the context of the neural lineage, to dissect regulatory circuits of differentiation. hESC were differentiated in vitro into 5 different NPC populations (NE, ERG, MRG, LRG and LNP) over a time period of 220 days. The hESCs and the first 3 NPC populations (NE, ERG, MRG) were subjected to ChIP-Seq for H3K4m3, H3K4me1, H3K27ac and H3K27me3 as well as RNA-Seq with two biological replicates each as well as whole genome bisulfite sequencing in singlicate. The last two populations (LRG, LNP) were both profiled by RRBS and the LRG populations also by RNA-Seq. In addition, each of the first three NPC populations were differentiated into more mature neuronal populations (NEdN, ERGdN, MRGdN). The LRG population was differentiated along the astrocyte fate (LRGdA). Each of these more mature populations was subjected to RNA-Seq in replicate. Finally, the NE and MRG populations were profiled for the transcription facctor OTX2 by ChIP-Seq.

Project description:Fission yeast Schizosaccharomyces pombe and budding yeast Saccharomyces cerevisiae are among the original model organisms in the study of the cell-division cycle. Unlike budding yeast, no large-scale regulatory network has been constructed for fission yeast. It has only been partially characterized. As a result, important regulatory cascades in budding yeast have no known or complete counterpart in fission yeast.By integrating genome-wide data from multiple time course cell cycle microarray experiments we reconstructed a gene regulatory network. Based on the network, we discovered in addition to previously known regulatory hubs in M phase, a new putative regulatory hub in the form of the HMG box transcription factor SPBC19G7.04. Further, we inferred periodic activities of several less known transcription factors over the course of the cell cycle, identified over 500 putative regulatory targets and detected many new phase-specific and conserved cis-regulatory motifs. In particular, we show that SPBC19G7.04 has highly significant periodic activity that peaks in early M phase, which is coordinated with the late G2 activity of the forkhead transcription factor fkh2. Finally, using an enhanced Bayesian algorithm to co-cluster the expression data, we obtained 31 clusters of co-regulated genes 1) which constitute regulatory modules from different phases of the cell cycle, 2) whose phase order is coherent across the 10 time course experiments, and 3) which lead to identification of phase-specific control elements at both the transcriptional and post-transcriptional levels in S. pombe. In particular, the ribosome biogenesis clusters expressed in G2 phase reveal new, highly conserved RNA motifs.Using a systems-level analysis of the phase-specific nature of the S. pombe cell cycle gene regulation, we have provided new testable evidence for post-transcriptional regulation in the G2 phase of the fission yeast cell cycle. Based on this comprehensive gene regulatory network, we demonstrated how one can generate and investigate plausible hypotheses on fission yeast cell cycle regulation which can potentially be explored experimentally.

Dataset Information

Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements.

Publications

Dissecting features of epigenetic variants underlying cardiometabolic risk using full-resolution epigenome profiling in regulatory elements.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure