Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A prostate cancer chromatin interaction map

ABSTRACT: A high-resolution 3D epigenomic map reveals insights into the creation of the prostate cancer transcriptome Prostate cancer (PCa) is the leading cancer among men in the United States. To understand gene regulation in 3D, chromatin interactions in prostate cancer cell is measured using in situ Hi-C. To better understand the impact of chromatin structure on regulation of the prostate cancer transcriptome, we developed high-resolution chromatin interaction maps in normal and prostate cancer cells using in situ Hi-C. By combining the in situ Hi-C data with active and repressive histone marks, CTCF binding sites, nucleosome-depleted regions, and transcriptome profiling, we identified topologically associating domains that changed in size and epigenetic states between normal and prostate cancer cells. Moreover, we identified normal and prostate cancer-specific enhancer-promoter loops and involved transcription factors. This creation of 3D epigenomic maps will enable a better understanding of prostate cancer biology and mechanisms of gene regulation.

ORGANISM(S): Homo sapiens

PROVIDER: GSE118629 | GEO | 2019/09/13

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

5C-ID: Increased resolution Chromosome-Conformation-CaptureCarbon-Copy with in situ 3C and double alternating primer design

Project description:Mammalian genomes are folded in a hierarchy of compartments, topologically associating domains (TADs), subTADs and looping interactions. Currently, there is a great need to evaluate the link between chromatin topology and genome function across many biological conditions and genetic perturbations. Hi-C generates high quality, high resolution maps of looping interactions genome-wide, but is intractable for high-throughput screening of loops across conditions due to the requirement of an enormous number of reads (>6 Billion) per library. Here, we describe 5C-ID, an updated version of Chromosome-Conformation-Capture-Carbon-Copy (5C) with restriction digest and ligation performed in the nucleus (in situ ChromosomeConformation-Capture (3C)) and ligation-mediated amplification performed with a new double alternating design. 5C-ID reduces spatial noise and enables higher resolution 3D genome folding maps than canonical 5C, allowing for a marked improvement in sensitivity and specificity of loop detection. 5C-ID enables the creation of high-resolution, high-coverage maps of chromatin loops in up to a 30 Megabase subset of the genome at a fraction of the cost of Hi-C.

2018-05-07 | GSE114121 | GEO

Chromatin extrusion explains key features of loop and domain formation in wild-type and engineered genomes

Project description:We recently used in situ Hi-C to create kilobase-resolution 3D maps of mammalian genomes. Here, we combine these with new Hi-C, microscopy, and genome-editing experiments to study the physical structure of chromatin fibers, domains, and loops. We find that the observed contact domains are inconsistent with the equilibrium state for an ordinary condensed polymer. Combining Hi-C data and novel mathematical theorems, we show that contact domains are also not consistent with a fractal globule. Instead, we use physical simulations to study two models of genome folding. In one, intermonomer attraction during polymer condensation leads to formation of an anisotropic "tension globule." In the other, CTCF and cohesin act together to extrude loops during interphase. Both models are consistent with the observed contact domains and with the observation that contact domains tend to form inside loops. However, the extrusion model explains a far wider array of observations, such as why loops tend not to overlap and why the CTCF-binding motifs at pairs of loop anchors lie in the convergent orientation. Finally, we perform 13 genome-editing experiments examining the effect of altering CTCF-binding sites on chromatin folding. The convergent rule correctly predicts the affected loop in every case. Moreover, the extrusion model accurately predicts in silico the 3D maps resulting from each experiment using only the location of CTCF-binding sites in the WT. Thus, we show that it is possible to disrupt, restore, and move loops and domains using targeted mutations as small as a single base pair. in situ Hi-C and HYbrid Capture Hi-C (Hi-C2) were used to probe the three-dimensional structure of the genome in two different human cell types before and after genome editing.

2015-10-23 | E-GEOD-74072 | biostudies-arrayexpress

The 3D chromatin landscape of rhabdomyosarcoma [ChIP-Seq]

Project description:Rhabdomyosarcoma (RMS) is a pediatric soft tissue cancer with no precision therapy available for affected patients. We hypothesized that with a general paucity of known mutations in RMS, chromatin structural driving mechanisms are essential for tumor proliferation. Thus, we carried out high-depth in situ Hi-C in representative cell lines and patient-derived xenografts to understand chromatin architecture in each major RMS subtype. We report a comprehensive 3D chromatin structural analysis and characterization of fusion-positive (FP-RMS) and fusion-negative rhabdomyosarcoma (FN-RMS). We have generated spike-in in situ Hi-C chromatin interaction maps for the commonest FP-RMS and FN-RMS cell lines, and compared our data with patient derived xenograft (PDX) models. In our studies we uncover common and distinct structural elements in large Mb-scale chromatin compartments, tumor-essential genes within variable topologically associating domains, and unique patterns of structural variation. This study enables a comprehensive resource for contextualizing gene regulation events in RMS, and high-depth chromatin interactivity maps for identification of functionally critical chromatin domains in this tumor.

2023-06-13 | GSE215202 | GEO

The 3D chromatin landscape of rhabdomyosarcoma [HiC]

2023-06-13 | GSE215172 | GEO

3D chromatin structure in colon cancer

Project description:We report the application of in situ Hi-C technology to 40 colorectal cancer patients and 10 paired-normal tissue to identify CRC specific changes in 3D chromatin structure. The chromatin contact matrices were generated by the sequencing data and image processing/deep learning-based algorithm was proposed to identify long-range abnormal chromatin interaction patterns in the contact matrices. The tumor specific 3D chromatin structure changes and the enhancer-promoter rewiring mediated by the identified chromatin structure changes were analyzed. The complex chromosome-wide rearrangements such as chromothripsis and its effect to 3D chromatin structure were also observed.

2023-07-27 | GSE137188 | GEO

Comparative Characterization of 3D Chromatin Organization in Triple-Negative Breast Cancers [ATAC-seq]

Project description:Triple-negative breast cancer (TNBC) is malignant cancer with a high risk of recurrence. To date, the underlying 3D chromatin organizations of TNBC have remained unclear. Here, using in situ Hi-C, we characterized the 3D chromatin organizations in cells representing five distinct subtypes of breast cancer (including TNBC) and TNBC tissues, compared to normal cells/tissues. We found that the global and local 3D architectures are severely disrupted in TNBC cells. Importantly, we detected CTCF-dependent TNBC-susceptible loss/gain of 3D chromatin organizations and found that these changes were strongly associated with perturbed chromatin accessibility and transcriptional dysregulations. Although some discrepancies exist between TNBC cell lines and tissues, we observed that perturbed local 3D architectures found in TNBC cells are partially conserved in TNBC tissues. Furthermore, we discovered distinct tissue-specific chromatin loops by comparing normal and TNBC tissues. Collectively, our findings provide important features of 3D chromatin organization in TNBC.

2022-05-06 | GSE167153 | GEO

Comparative Characterization of 3D Chromatin Organization in Triple-Negative Breast Cancers [RNA-seq]

2022-05-06 | GSE167152 | GEO

Comparative Characterization of 3D Chromatin Organization in Triple-Negative Breast Cancers [ChIP-seq]

2022-05-06 | GSE167151 | GEO

Comparative Characterization of 3D Chromatin Organization in Triple-Negative Breast Cancers [Hi-C]

2022-05-06 | GSE167150 | GEO

Integrative Hi-C maps of pancreatic cancer

Project description:Pancreatic cancer's poor prognosis is caused by distal metastasis, which is associated with epigenomic changes. However, the roles of 3D epigenome in pancreatic cancer biology, especially its metastasis, remain unclear. Here we compare the 3D epigenomic and transcriptomic features among cells derived from pancreatic epithelial, primary and metastatic pancreatic cancer by integrated analysis of in situ Hi-C, ChIP-seq, ATAC-seq, and RNA-seq data. We found A/B compartments, topologically associated domains (TADs), chromatin loops changed significantly in metastatic pancreatic cancer cells, which is associated with epigenetic state alterations. Moreover, we identified upregulated genes, which are located in switched compartments, common TADs with epigenetic state changing, specific TAD boundaries, and metastasis-specific enhancer-promoter loops, are related to cancer metastasis. We also find that the transcription factors mediated specific enhancer-promoter loops formation are also associated with metastasis. Taken together, these results provide a 3D epigenomic map of pancreatic cancer metastasis, which expands our knowledge of the epigenetic mechanism of pancreatic cancer metastasis and enables a better understanding of pancreatic cancer pathobiology.

2021-08-11 | GSE149103 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data