Application of Hi-C sequencing to detect structural variants in B-cell acute lymphoblastic leukemia
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PROVIDER: EGAS00001005605 | EGA |
REPOSITORIES: EGA
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Project description:We describe Hi-C, a method that probes the three-dimensional architecture of whole genomes by coupling proximity-based ligation with massively parallel sequencing. We constructed spatial proximity maps of the human genome with Hi-C at a resolution of 1Mb. These maps confirm the presence of chromosome territories and the spatial proximity of small, gene-rich chromosomes. We identified an additional level of genome organization that is characterized by the spatial segregation of open and closed chromatin to form two genome-wide compartments. At the megabase scale, the chromatin conformation is consistent with a fractal globule, a knot-free conformation that enables maximally dense packing while preserving the ability to easily fold and unfold any genomic locus. The fractal globule is distinct from the more commonly used globular equilibrium model. Our results demonstrate the power of Hi-C to map the dynamic conformations of whole genomes. These expression data are used in the paper to show that there are marked differences in mRNA expression between loci in the open and closed chromatin compartments. Experiment Overall Design: Affy Expression array for GM06690 cells
2009-10-10 | E-GEOD-18350 | biostudies-arrayexpress
Project description:We describe Hi-C, a method that probes the three-dimensional architecture of whole genomes by coupling proximity-based ligation with massively parallel sequencing. We constructed spatial proximity maps of the human genome with Hi-C at a resolution of 1Mb. These maps confirm the presence of chromosome territories and the spatial proximity of small, gene-rich chromosomes. We identified an additional level of genome organization that is characterized by the spatial segregation of open and closed chromatin to form two genome-wide compartments. At the megabase scale, the chromatin conformation is consistent with a fractal globule, a knot-free conformation that enables maximally dense packing while preserving the ability to easily fold and unfold any genomic locus. The fractal globule is distinct from the more commonly used globular equilibrium model. Our results demonstrate the power of Hi-C to map the dynamic conformations of whole genomes. These expression data are used in the paper to show that there are marked differences in mRNA expression between loci in the open and closed chromatin compartments.
2009-10-01 | GSE18350 | GEO
Project description:Two biological replicates Hi-C and HPV16-specific Region Capture Hi-C libraries were prepared for each of the W12 cell lines. Capture Hi-C was performed using HPV16-specific RNA baits. Hi-C libraries alone were prepared from normal cervix tissue (Ncx).
2021-06-18 | E-MTAB-10152 | biostudies-arrayexpress
Project description:We propose a novel in situ Hi-C method named Bridge-Linker-Hi-C (BL-Hi-C) for structural and regulatory chromatin interactions capture by restriction enzyme targeting and two-step proximity ligation. It improves the sensitivity and specificity for active chromatin loop detection and can reveal a better enhancer-promoter regulatory architecture than conventional method at a lower sequencing depth and with a simpler protocol.
2018-01-23 | GSE93921 | GEO
Project description:We have analyzed publicly available K562 Hi-C data, which enables genome-wide unbiased capturing of chromatin interactions, using a Mixture Poisson Regression Model to define a highly specific set of interacting genomic regions. We integrated multiple ENCODE Consortium resources with the Hi-C data, using DNase-seq data and ChIP-seq data for 46 transcription factors and 8 histone modifications. We classified 12 different sets (clusters) of interacting loci that can be distinguished by their chromatin modifications and which can be categorized into three types of chromatin hubs. The different clusters of loci display very different relationships with transcription factor binding sites. As expected, many of the transcription factors show binding patterns specific to clusters composed of interacting loci that encompass promoters or enhancers. However, cluster 6, which is distinguished by marks of open chromatin but not by marks of active enhancers or promoters, was not bound by most transcription factors but was highly enriched for 3 transcription factors (GATA1, GATA2, and c-Jun) and 3 chromatin modifiers (BRG1, INI1, and SIRT6). To validate the identification of the clusters and to dissect the impact of chromatin organization on gene regulation, we performed RNA-seq analyses before and after knockdown of GATA1 or GATA2. We found that knockdown of the GATA factors greatly alters the expression of genes within cluster 6. Our work, in combination with previous studies linking regulation by GATA factors with c-Jun and BRG1, provide genome-wide evidence that Hi-C data identifies sets of biologically relevant interacting loci. RNA-seq of control, siGATA1 and siGATA2 K562 cells
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2017-10-31 | GSE89324 | GEO
Project description:CD4(+)Foxp3(+) regulatory T (Treg) cells originate primarily from thymic differentiation, but conversion of mature T lymphocytes to Foxp3 positivity can be elicited by several means, including in vitro activation in the presence of TGF-beta. Retinoic acid (RA) increases TGF-beta-induced expression of Foxp3, through unknown molecular mechanisms. We showed here that, rather than enhancing TGF-beta signaling directly in naive CD4(+) T cells, RA negatively regulated an accompanying population of CD4(+) T cells with a CD44(hi) memory and effector phenotype. These memory cells actively inhibited the TGF-beta-induced conversion of naive CD4(+) T cells through the synthesis of a set of cytokines (IL-4, IL-21, IFN-gamma) whose expression was coordinately curtailed by RA. This indirect effect was evident in vivo and required the expression of the RA receptor alpha. Thus, cytokine-producing CD44(hi) cells actively restrain TGF-beta-mediated Foxp3 expression in naive T cells, and this balance can be shifted or fine-tuned by RA. All gene expression profiles were obtained from highly purified T cell populations sorted by flow cytometry. To reduce variability, cells from multiple mice were pooled for sorting, and replicates were generated for essentially all groups. RNA from 0.5-3 x 105 cells was amplified, labeled, and hybridized to Affymetrix M430v2 microarrays. Raw data were preprocessed with the RMA algorithm in GenePattern, and averaged expression values were used for analysis.
2008-11-16 | E-GEOD-13306 | biostudies-arrayexpress