Inferring time-course chromatin states for promoter-enhancer pairs based on Hi-C data
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ABSTRACT:
PROVIDER: PRJNA637218 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11922700_1.fastq.gz | Fastqsanger.gz | |||
| SRR11922700_2.fastq.gz | Fastqsanger.gz | |||
| SRR11922701_1.fastq.gz | Fastqsanger.gz | |||
| SRR11922701_2.fastq.gz | Fastqsanger.gz | |||
| SRR11922702_1.fastq.gz | Fastqsanger.gz |
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Project description:Co-localized combinations of histone modifications ("chromatin states") have been shown to correlate with promoter and enhancer activity. Changes in chromatin states over multiple time points ("chromatin state trajectories") have previously been analyzed at promoter and enhancers separately. With the advent of time-course Hi-C data it is now possible to connect promoters and enhancers and to analyze chromatin state trajectories at promoter-enhancer pairs. We present TimelessFlex, a framework for investigating chromatin state trajectories at promoter-enhancer pairs based on Hi-C information.
2021-02-02 | GSE151769 | GEO
Project description:BackgroundCo-localized combinations of histone modifications ("chromatin states") have been shown to correlate with promoter and enhancer activity. Changes in chromatin states over multiple time points ("chromatin state trajectories") have previously been analyzed at promoter and enhancers separately. With the advent of time series Hi-C data it is now possible to connect promoters and enhancers and to analyze chromatin state trajectories at promoter-enhancer pairs.ResultsWe present TimelessFlex, a framework for investigating chromatin state trajectories at promoters and enhancers and at promoter-enhancer pairs based on Hi-C information. TimelessFlex extends our previous approach Timeless, a Bayesian network for clustering multiple histone modification data sets at promoter and enhancer feature regions. We utilize time series ATAC-seq data measuring open chromatin to define promoters and enhancer candidates. We developed an expectation-maximization algorithm to assign promoters and enhancers to each other based on Hi-C interactions and jointly cluster their feature regions into paired chromatin state trajectories. We find jointly clustered promoter-enhancer pairs showing the same activation patterns on both sides but with a stronger trend at the enhancer side. While the promoter side remains accessible across the time series, the enhancer side becomes dynamically more open towards the gene activation time point. Promoter cluster patterns show strong correlations with gene expression signals, whereas Hi-C signals get only slightly stronger towards activation. The code of the framework is available at https://github.com/henriettemiko/TimelessFlex .ConclusionsTimelessFlex clusters time series histone modifications at promoter-enhancer pairs based on Hi-C and it can identify distinct chromatin states at promoter and enhancer feature regions and their changes over time.
| S-EPMC7841892 | biostudies-literature
Project description:Chromatin organisation of trophoblast stem cells (TSC) were compared with that of embryonic stem cells (ESC). The method enriches Hi-C libraries, to detect promoter interactions at restriction fragment level. We prepared Hi-C libraries from TSC and ESC (serum grown) samples and enriched them with a promoter capture bait system that captures ~22.000 promoters. Promoter interactions were then analysed using the GOTHiC pipeline.
2018-09-05 | E-MTAB-6585 | biostudies-arrayexpress
Project description:Serum-to-2i interconversion of mouse Embryonic Stem Cells (mESCs) is a valuable in vitro model for early embryonic development. To assess whether 3D chromatin organization changes during this transition, we established Capture Hi-C with target-sequence enrichment of DNase I hypersensitive sites. We detected extremely long-range intra- and inter-chromosomal interactions between a small subset of H3K27me3 marked bivalent promoters involving the Hox clusters in serum grown cells. Notably, these promoter-mediated interactions are not present in 2i ground-state pluripotent mESCs but appear upon further development into primed-like serum mESCs. Reverting serum mESCs to ground-state 2i mESCs removes these promoter-promoter interactions in a spatiotemporal manner. H3K27me3, which is largely absent at bivalent promoters in ground-state 2i mESCs, is necessary but not sufficient to establish these interactions, as confirmed by Capture Hi-C on Eed-/- serum mESCs. Our results implicate H3K27me3 and PRC2 as critical players in chromatin alteration during priming of ESCs for differentiation. To study dynamics in chromatin architecture and to characterize long-range interaction, we performed Hi-C using DpnII as the restriction enzyme, potentially reaching a genome-wide coverage at a less than 1Kb resolution. We subsequently performed enrichment of interaction by a target capture similar to the exome sequencing approach. We enriched for DNaseI hyper-sensitive sites (DHSâs) in chromatin from mESCs. Probes were designed against the union of all DHSâs of Serum and 2i mESCs. Capture Hi-C reveals Extremely Long-Range Interactions (ELRI) in Serum but not in 2i ESCs. We observed H3K27me3 as a prominent characteristic, but not exclusive feature of ELRI loci in Serum mESCs. To further elucidate the involvement of constituents of PRC1 and PRC2 in ELRI, we performed ChIP-seq experiment on Suz12 and Ring1B during serum-to-2i transition. In addition, RNA-seq was performed to compare the expression levels of genes.
2015-12-07 | E-GEOD-72164 | biostudies-arrayexpress
Project description:CD34+ heamatopoietic stem cells were isolated from the bone marrow of two healthy donors undergoing total hip replacement. Promoter capture Hi-C (PCHi-C) was performed on these cells using the protocol according to Mifsud et al. 2015, with the exception that ligation was performed in situ, and a slightly modified bait capture set was used. Bait positions in hg19 are included as an additional file.
2021-10-15 | E-MTAB-10701 | biostudies-arrayexpress
Project description:Development of new reagents for protein cross-linking is continually ongoing. The chemical formulas of the linker adducts formed by these reagents are usually deduced from expert knowledge, and then validated by mass spectrometry. Clearly, it would have been more rigorous if the adduct masses are inferred directly from the data without any prior assumption on the chemistries. Unfortunately, the analysis tools that are currently available to detect chemical modifications on linear peptides are not applicable to the case of two cross-linked peptides. Here we show that an adaptation of the open search strategy that works on linear peptides can be used to study cross-link modifications between pairs of peptides. We benchmark our approach by correctly inferring the linker masses of two well-known reagents - DSS and formaldehyde - to accuracies of a few parts per million. We then investigate the cross-linking chemistries of two poorly characterized reagents - EMCS and glutaraldehyde. In the case of EMCS, we find that the expected cross-linking chemistry is accompanied by a competing chemistry that targets other amino acid types. In the case of glutaraldehyde, we find that the chemical formula of the dominant linker is C5H4, which indicates a ringed aromatic structure. These results demonstrate that, at very little effort, our approach can yield non-trivial insights to facilitate the studies of new cross-linkers.
2021-09-09 | PXD020704 | Pride
Project description:Capture Hi-C (CHi-C) is a state-of-the art method for profiling chromosomal interactions involving targeted regions of interest (such as gene promoters) globally and at high resolution. Signal detection in CHi-C data involves a number of statistical challenges that are not observed when using other Hi-C-like techniques. We present a background model, and algorithms for normalisation and multiple testing that are specifically adapted to CHi-C experiments, in which many spatially dispersed regions are captured, such as in Promoter CHi-C. We implement these procedures in CHiCAGO (http://regulatorygenomicsgroup.org/chicago), an open-source package for robust interaction detection in CHi-C. We validate CHiCAGO by showing that promoter-interacting regions detected with this method are enriched for regulatory features and disease-associated SNPs. Three human CHi-C biological replicates were generated (comprising 1, 2and 3 technical replicates). Two mouse CHi-C biological replicates were generated (both comprising three technical replicates) and a mouse Hi-C dataset. The publicly available HiCUP pipeline (doi: 10.12688/f1000research.7334.1) was used to process the raw sequencing reads. This pipeline was used to map the read pairs against the mouse (mm9) and human (hg19) genomes, to filter experimental artefacts (such as circularized reads and re-ligations), and to remove duplicate reads. For the CHi-C data, the resulting BAM files were processed into CHiCAGO input files, retaining only those read pairs that mapped, at least on one end, to a captured bait. CHiCAGO then identified Hi-C restriction fragments interacting, with statistical significant, to captured baits.
2016-05-18 | E-GEOD-81503 | biostudies-arrayexpress
Project description:To identify distal chromatin contacts between promoters and their putative regulatory elements in SGBS preadipocytes and hypothalamic arcuate-like neurons derived from iPSC, we performed Hi-C with a capture step to enrich the library for contacts involving promoters. Hi-C with a capture step was performed according to PMID: 29988018
2021-03-20 | E-MTAB-10200 | biostudies-arrayexpress
Project description:BackgroundThe nonrandom radial organization of eukaryotic chromosome territories (CTs) inside the nucleus plays an important role in nuclear functional compartmentalization. Increasingly, chromosome conformation capture (Hi-C) based approaches are being used to characterize the genome structure of many cell types and conditions. Computational methods to extract 3D arrangements of CTs from this type of pairwise contact data will thus increase our ability to analyze CT organization in a wider variety of biological situations.ResultsA number of full-scale polymer models have successfully reconstructed the 3D structure of chromosome territories from Hi-C. To supplement such methods, we explore alternative, direct, and less computationally intensive approaches to capture radial CT organization from Hi-C data. We show that we can infer relative chromosome ordering using PCA on a thresholded inter-chromosomal contact matrix. We simulate an ensemble of possible CT arrangements using a force-directed network layout algorithm and propose an approach to integrate additional chromosome properties into our predictions. Our CT radial organization predictions have a high correlation with microscopy imaging data for various cell nucleus geometries (lymphoblastoid, skin fibroblast, and breast epithelial cells), and we can capture previously documented changes in senescent and progeria cells.ConclusionsOur analysis approaches provide rapid and modular approaches to screen for alterations in CT organization across widely available Hi-C data. We demonstrate which stages of the approach can extract meaningful information, and also describe limitations of pairwise contacts alone to predict absolute 3D positions.
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