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Hi-C following CTCF RNAi in LNCaP cells to determine changes to topological domains

ABSTRACT: This study aimed to ascertain the effect of CTCF RNAi on gene expression, chromatin conformation and the chromatin environment in prostate cancer cell line, LNCaP

ORGANISM(S): Homo sapiens

PROVIDER: GSE125640 | GEO | 2020/01/01

REPOSITORIES: GEO

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Expression data from CTCF RNAi experiments in LNCaP cell line

Project description:This study aimed to ascertain the effect of CTCF RNAi on gene expression, chromatin conformation and the chromatin environment in prostate cancer cell line, LNCaP

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ChIP-seq for CTCF, H3K4me3 and H3K27ac following CTCF RNAi in LNCaP cells and IMR90 cells

Project description:This study aimed to ascertain the effect of CTCF RNAi on gene expression, chromatin conformation and the chromatin environment in prostate cancer cell line, LNCaP This study aimed to confirm loss of CTCF sites following CTCF RNAi in IMR90 cells

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Hi-C following CTCF RNAi in LNCaP cells to determine changes to topological domains

Project description:Hi-C following CTCF RNAi in LNCaP cells to determine changes to topological domains

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NETWORK MODELLING OF TOPOLOGICAL DOMAINS USING HI-C DATA.

Project description:Chromosome conformation capture experiments such as Hi-C are used to map the three-dimensional spatial organization of genomes. One specific feature of the 3D organization is known as topologically associating domains (TADs), which are densely interacting, contiguous chromatin regions playing important roles in regulating gene expression. A few algorithms have been proposed to detect TADs. In particular, the structure of Hi-C data naturally inspires application of community detection methods. However, one of the drawbacks of community detection is that most methods take exchangeability of the nodes in the network for granted; whereas the nodes in this case, that is, the positions on the chromosomes, are not exchangeable. We propose a network model for detecting TADs using Hi-C data that takes into account this nonexchangeability. in addition, our model explicitly makes use of cell-type specific CTCF binding sites as biological covariates and can be used to identify conserved TADs across multiple cell types. The model leads to a likelihood objective that can be efficiently optimized via relaxation. We also prove that when suitably initialized, this model finds the underlying TAD structure with high probability. using simulated data, we show the advantages of our method and the caveats of popular community detection methods, such as spectral clustering, in this application. Applying our method to real Hi-C data, we demonstrate the domains identified have desirable epigenetic features and compare them across different cell types.

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Expression data from CTCF RNAi experiments in LNCaP cell line

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LNCaP cells in response to DHT stimulation and inhibition/knockdown of TOPO2B

Project description:Microarray experiments were carried out to ascertain whether TOP2β is required for DHT induced androgen receptor target gene expression. We investigated the effect of pharmacological inhibition or RNA interference-mediated depletion of TOP2β on gene expression in androgen-dependent LNCaP prostate cancer cells.

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Hi-C from LNCaP clone FGC (ENCSR346DCU)

Project description:HiC experiment done on LNCaP clone FGC For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODE_Data_Use_Policy_for_External_Users_03-07-14.pdf

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LNCaP cells in response to DHT stimulation and inhibition/knockdown of TOPO2B

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Epigenetic maintenance of topological domains in the rearranged gibbon genome [Hi-C]

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