Role of DNA methylation in modulating transcription factor occupancy
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE50610 | GEO | 2014/02/28
SECONDARY ACCESSION(S): PRJNA218088
REPOSITORIES: GEO
Similar Datasets
Project description:This data includes regulatory factor profiling using DNase and ChIP-seq and methylation profiling using bisulfite-seq. We investigated CTCF occupancy in the context of reduced methylation by performing genome-wide profiling with chromatin immunoprecipitation (ChIP-seq) in HCT116 cells and DNMT1 and DNMT3B double knockout (DKO) HCT116 cells. We also profiled HCT116 and DKO using DNaseI-seq and ChIP-seq for trimethylation of histone 3 lysine 4 (H3K4me3) and acetylation of histone 3 lysine 27 (H3K27ac), Finally, we performed ChIP-seq on 3 replicates of mock-treated and 2 replicates of 5-aza-CdR-treated K562 cells.
2014-02-28 | E-GEOD-50610 | biostudies-arrayexpress
Project description:The main goal of the project is to develop a new generation of bioinformatics resources for the integrative analysis of multiple types of 'omics data. These resources include both novel statistical methodologies as well as user-friendly software implementations. STATegra methods address many aspects of the 'omics data integration problem such as the design of multi-omics experiments, integrative transcriptional and regulatory networks, integrative variable selection, data fusion, integration of public domain data, and integrative pathway analysis. To support method development STATegra uses a model biological system, namely the differentiation process of mouse pre-B-cells. The STATegra consortium generated data focused on a critical step in the differentiation of B lymphocytes, which are key components of the adaptive immune system. Transcription factors of the Ikaros family are central to the normal differentiation of B cell progenitors and their expression increases in response to developmental stage-specific signals to terminate the proliferation of B cell progenitors and to initiate their differentiation. In particular, a novel biological system that models the transition from the pre-BI stage to the pre-BII subsequent stage, where B cell progenitors undergo growth arrest and differentiation, was used. The approach involves a pre-B cell line, B3, and an inducible version of the Ikaros transcription factor, Ikaros-ERt2. Ikaros factors act to down-regulate genes that drive proliferation and to simultaneously up-regulate the expression of genes that promote the differentiation of B cell progenitors. Hence, in the B3 system, before induction of Ikaros, cells proliferate and their gene expression pattern is similar to proliferating B cell progenitors in vivo. Following Ikaros induction, B3 cells undergo gene expression changes that resemble those that occur in vivo during the transition from cycling to resting pre-B cells, followed by a marked reduction in cellular proliferation and by G1 arrest. On this system the consortium has created a high-quality data collection consisting of a replicated time course using seven different 'omics platforms: RNA-seq, miRNA-seq, ChIP-seq, DNase-seq, Methyl-seq, proteomics and metabolomics, which is used to assess and to validate STATegra methods. The STATegra experimental design consists of a 6 point time course that captures the differentiation of B3 cells containing Ikaros-ERt2 upon Ikaros induction within a 24 hr period. The process was sampled at 0, 2, 6, 12, 18, and 24 hrs respectively after Ikaros induction by Tamoxifen. As control, B3 cells transfected with an empty vector were treated and sampled in the same way as the inducible line. Eight different 'omic technologies were measured on this system: RNA-seq, miRNA-seq, DNase-seq, RRBS-seq, ChIP-seq, scRNA-seq, Proteomics and Metabolomics. Generally, three biological replicates were obtained per platform and were processed as independent batches. Metabolomics analysis was performed using 4 biological batches (7, 8, 9 and 10) and at times 0, 2, 6, 12, 18 and 24 hrs respectively. Each sample was analyzed using gas chromatography mass spectrometry (GC-MS) and liquid chromatography mass spectrometry (LC-MS).
2016-12-15 | MTBLS283 | MetaboLights
Project description:DNase I footprinting is an established assay for identifying transcription factor (TF)-DNA interactions with single base pair resolution. High throughput DNase-seq assays have recently been used to detect in vivo DNase footprints across the genome. A number of computational approaches have been developed to accurately identify DNase-seq footprints and these methods have been used as a predictor of TF-DNA interactions by itself or in combination with other epigenetic features. However, recent studies have pointed to a substantial cleavage bias of DNase and its impact on footprinting, casting doubts on its predictive performance. To assess the potential for using DNaseI to identify individual binding sites, we performed DNase-seq experiments on deproteinized naked genomic DNA isolated from two different cell types and determined sequence cleavage bias associated with the DNase-seq protocol. This allowed us to build cleavage bias corrected footprint models specific to individual transcription factors. The predictive performance of these DNase-seq-based binding site models demonstrated that predicted footprints corresponded to high confidence TF-DNA interactions.
2014-09-04 | GSE61105 | GEO
Project description:DNase I footprinting is an established assay for identifying transcription factor (TF)-DNA interactions with single base pair resolution. High throughput DNase-seq assays have recently been used to detect in vivo DNase footprints across the genome. A number of computational approaches have been developed to accurately identify DNase-seq footprints and these methods have been used as a predictor of TF-DNA interactions by itself or in combination with other epigenetic features. However, recent studies have pointed to a substantial cleavage bias of DNase and its impact on footprinting, casting doubts on its predictive performance. To assess the potential for using DNaseI to identify individual binding sites, we performed DNase-seq experiments on deproteinized naked genomic DNA isolated from two different cell types and determined sequence cleavage bias associated with the DNase-seq protocol. This allowed us to build cleavage bias corrected footprint models specific to individual transcription factors. The predictive performance of these DNase-seq-based binding site models demonstrated that predicted footprints corresponded to high confidence TF-DNA interactions. To quantify the DNase I sequence-dependent cleavage bias, we performed DNase-seq experiments using deproteinized DNA from K562 and MCF7 cell lines.
2014-09-04 | E-GEOD-61105 | biostudies-arrayexpress
Project description:<p>We generated primary cultures from mechanically isolated kidney glomeruli (filtration unit of the nephron) which are composed of podocytes and mesangial cells. In parallel, we generated primary kidney cortex tubule cell cultures, which are composed primarily of proximal tubule cells. Early passage cultures of these two cell types were subjected to chromatin accessibility profiling (DNase-Seq) and gene expression profiling (RNA-Seq). We found thousands of dynamically regulated enhancers in both cell types that potentially regulate nearby and distal target genes that are differentially expressed. These data will be useful for understanding the epigenomic regulation of gene transcription in key kidney cell types.</p>
| phs001720 | dbGaP
Project description:We report scM&T-seq, a method for parallel single-cell genome-wide methylome and transcriptome sequencing, allowing discovery of associations between transcriptional and epigenetic variation. Profiling of 61 mouse embryonic stem cells confirmed known links between DNA methylation and transcription. Notably, the method reveals novel associations between heterogeneous methylation of distal regulatory elements and transcriptional heterogeneity of key pluripotency genes. E14 ES cells were grown in either serum/LIF or 2i culture conditions and separated into single cells. RNA-Seq or Bisulfite-Seq libraries were prepared. This Series includes only the Bisulfite-Seq data. The list of 61 samples that passed QC in both BS-seq and RNA-seq is included in "Supplementary Table 1" of the associated manuscript.
2015-12-24 | E-GEOD-68642 | biostudies-arrayexpress
Project description:Genome-wide chromatin accessibility profiling in adult human heart using DNase-seq
| PRJNA414336 | ENA
Project description:Sequencing files provided here are mouse liver DNase-seq for male mouse livers collected at either a peak or trough of GH/STAT5 activity. This is part of a larger study that includes DNase-seq in mouse liver from hypophysectomized males, females, and hypox-male mice given a single dose of GH. DNase hypersensitivity site (DHS) analysis of these livers established that the naturally occurring, endogenous male rhythm of plasma GH pulse-stimulated liver STAT5 activation induces dynamic, repeated cycles of chromatin opening and closing at several thousand liver DHS and comprises a novel mechanism conferring male bias to liver chromatin accessibility.
2023-08-21 | GSE131848 | GEO
Project description:This data includes regulatory factor profiling using ChIP-seq.
2014-10-07 | GSE50611 | GEO