Project description:4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait") that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes. 4C-Seq experiments from Igh and Cd83 bait in activated B cells and Tcrb (Eb) bait in double negative T cells and immature B cells. RNA-Seq and ATAC-Seq experiments in DN and Immature B cells.
Project description:The relationship between chromatin organization and transcriptional regulation is an area of intense investigation. We have characterized the spatial relationships between alleles of the Oct4, Sox2, and Nanog genes in single cells during the earliest stages of mouse embryonic stem cell (ESC) differentiation and during embryonic development. We describe homologous pairing of the Oct4 alleles during ESC differentiation and embryogenesis, and present evidence that pairing is correlated with the kinetics of ESC differentiation. Importantly, we identify critical DNA elements within the Oct4 promoter/enhancer region that mediate pairing of Oct4 alleles. Finally, we show that mutation of OCT4/SOX2 binding sites within this region abolishes inter-chromosomal interactions and affects accumulation of the repressive H3K9me2 modification at the Oct4 enhancer. Our findings demonstrate that chromatin organization and transcriptional programs are intimately connected in ESCs, and that the dynamic positioning of the Oct4 alleles is associated with the transition from pluripotency to lineage specification. Examination of chromatin contacts between Oct4 alleles using PE-4Cseq
Project description:In order to identify other molecular aberrations that may cooperate with IDH1R132MUT in gliomagenesis, we performed CpG-island methylation profiling analysis using MSRE (Tran et al. Front. Neurosci. 3:57. Doi: 10.3389/neuro.15.005.2009) on a subset of IDH1R132MUT and IDH1R132WT GBMs and found a distinct pattern of CpG island hypermethylation that was detected in all GBMs and lower grade gliomas with IDH1R132MUT. While absent from nearly all IDH1R132WT glioma, the methylation pattern in IDH1R132MUT GBMs shows similarity to the recently reported CpG island methylator phenotype (CIMP) found to be tightly associated with IDH1R132MUT gliomas(Noushmehr et al. Cancer Cell, Volume 17, Issue 5, 18 May 2010, Pages 510-522, ISSN 1535-6108, DOI: 10.1016/j.ccr.2010.03.017). Methylation profiling performed on 40 distinct brain tumor samples: 7 Anaplastic Astrocytomas, including 3 IDH1MUT and 4 IDH1WT; 5 Lowgrade Astrocytomas, including 4 IDH1MUT and 1 IDH1WT; 28 Glioblastoma, including 8 IDH1MUT and 20 IDH1WT.
Project description:To investigate the interaction landscape at the GILZ locus we performed 4C-seq in A549 (ATCC CCL-185) and U2OS cells stably expressing rat GR (Rogatsky et al. , Mol Cell Biol, 1997. 17(6): p. 3181-93.) upon hormone treatment (1.5 h, 1 M dexamethasone). Experiments were performed in two biological replicates using hg19 chrX:106,960,488-106,960,865 as a viewpoint.
Project description:We established a protocol of the SuperSAGE technology combined with next-generation sequencing, coined “High-Throughput (HT-) SuperSAGE”. SuperSAGE is a method of digital gene expression profiling that allows isolation of 26-bp tag fragments from expressed transcripts. In the present protocol, index (barcode) sequences are employed to discriminate tags from different samples. Such barcodes permit to enable researchers to analyze digital tags from many transcriptomes of many samples in a single sequencing run by simply pooling the libraries. Here, we demonstrated that HT-SuperSAGE provided highly sensitive, reproducible and accurate digital gene expression data. By increasing throughput for analysis in HT-SuperSAGE, various applications were expected and several examples of its applications were introduced in the present study, including analyses of laser-microdissected cells, biological replicates or tag extraction using different anchoring enzymes. 27 different tissue samples from three different life organisms were analyzed. About 2 samples, three different anchoring enzymes were employed.
Project description:In this experiment, we've examined chromatin conformation differences of E14 mESC against cohesin and Ring1b degrons. We performed a modified in situ Hi-C protocol from (Rao et al., 2014) that can be found in detail at (Díaz et al., 2018). Samples were digested with MboI restriction enzyme. The aim of the experiment was to characterize the role of cohesin and polycomb on the 3D structure of mouse chromatin.
Project description:FOXO transcription factors are key players in diverse cellular responses affecting tumorigenesis, stem cell maintenance and lifespan. To gain insight into mechanisms of FOXO regulated gene expression, we studied genome-wide effects of FOXO3 activation. Profiling RNA polymerase II (RNAPII) changes shows FOXO3 regulates gene expression through transcription initiation. Correlative analysis of FOXO3 and RNAPII ChIP-seq profiles demonstrates FOXO3 to act as a transcriptional activator. Furthermore, this analysis reveals a significant part of FOXO3 gene regulation proceeds through enhancer regions. FOXO3 binds to and activates enhancers as shown by the presence of and changes in enhancer-specific histone modifications and RNAPII occupancy. In addition, FOXO3-mediated enhancer regulation correlates with regulation of adjacent genes and existence of chromatin loops between FOXO3 bound enhancers and regulated genes. Combined, our data elucidate how FOXOs regulate gene transcription and provide insight into mechanisms by which FOXOs can induce different gene expression programs depending on chromatin architecture. seven 4C view point were analyzed on DLD1 colon carcinoma cells containing 4OH-Tamoxifen inducible FOXO3A3-ER (DL23 cells, Kops et al., 2002, Mol Cell Biol), to investigate 3D topology around FOXO3 bound regions and FOXO3 regulated genes before and 4 hours after addition of tamoxifen. 4C procedure, as published before (Splinter et al., 2001, Genes Dev). Cells are cross linked using 1% formaldehyde for 10min at room temperature, nuclei are isolated, after which chromatin is digested with DpnII and subsequently ligated under diluted conditions. After reversal of the cross links the DNA is purified and treated with the second restriction enzyme treatment (Csp). After a second re-ligation step the sample is purified and ligated fragments are analyzed by inverse PCR.
Project description:In this experiment, we've examined chromatin conformation of OG2 (B6; CBA-Tg(Pou5f1-EGFP)2Mnn/J; stock number 004654) mouse stem cells cultured as described in (Shi et al., 2008), using different amounts of starting cells. We performed a modified in situ Hi-C protocol for 6 samples digested with MboI restriction enzyme having as starting material 1 million (M), 100 thousand (k), 50k, 25k, 10k or 1k cells. As well as, to 2 samples digested with HindIII restriction enzyme that had as starting material 5M or 100k cells. Traditional in situ Hi-C protocols recommend 5-10 million starting cells. The aim of the experiment was to assess the impact of decreasing the cell number on reproducibility, library complexity, chromatin structure visualization in order to adapt the method to the study of rare cell populations. Furthermore, we have characterised the 3D structure of peripheral blood mononuclear cells (PBMCs) obtained from a blood extraction from a healthy donor and from a lymph node biopsy from a DLBCL patient as a proof of concept for the suitability of Low-C for rare cell population analysis.
Project description:We performed Hi-C analysis of Escherichia coli MG1655 cells in exponential and stationary growth phase. We could detect long-range interactions predominantly in the Ori domain of the chromosome. Interestingly, the use of a new type of control revealed that these interactions are mostly crosslinking independent. 6 samples from exponential phase growth in M9 medium; 6 samples from stationary phase growth in M9 medium; for each growth condition, 3 samples were with crosslinking and 3 samples were without.
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.