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and Y. R conceptualized the study; X. L. requires extensive folding (Bickmore, 2013). Such folding is presumed to be both specific and functional (Ong and Corces, 2014). However , details regarding general folding principles, distinct topologies and/or relationships to gene activity are still largely unknown. Current technologies in studying 3-dimensional (3D) structures of the human genome include 3D-FISH nuclear imaging and 3D genome mapping. 3D-FISH (fluorescencein situhybridization) can visualize realistic chromosome conformation and individual contacts within nucleus (Cremer et al., 2008). However , it lacks sufficient genomic detail and accuracy. The core strategy in 3D genome mapping is nuclear proximity ligation (Cullen et al., 1993), which allows detection of distant genomic segments residing in close spatial proximity to one another, yet are linearly far away. Using this strategy, a number of high-throughput methods have been developed for genome-wide chromatin interaction mapping, including ChIA-PET and Hi-C (Fullwood et al., 2009; Lieberman-Aiden et al., 2009). ChIA-PET (Chromatin Interaction Analysis by Paired-End Tag sequencing) was designed to detect genome-wide chromatin interactions Scoparone mediated by specific protein factors, whereas Hi-C (High-throughput Chromosome Conformation Capture) was developed to capture all chromatin contacts. Hi-C has been Rabbit Polyclonal to Cytochrome P450 2U1 proven effective for mapping large-scale structures, such as topologically associated domains (TAD) (Dixon et al., 2012); however , it lacks the resolution to detect precise functional interactions mediated by proteins. In contrast, by inclusion of ChIP (chromatin immunoprecipitation), ChIA-PET is unique in detecting protein factor mediated chromatin interactions and is capable of generating high-resolution (~100bp) genome-wide chromatin interaction maps with binding-site specificity among functional elements in human and mouse (Li et al., 2012; Zhang et al., 2013). To comprehensively characterize the 3D topology of chromatin interactions between functional elements and higher-order organization in the human genome, we applied ChIA-PET, targeting on two protein factors, CTCF (CCCTC-binding zinc finger protein) and RNAPII (RNA polymerase II) in a number of human cell lines. CTCF is the master weaver of genome organization Scoparone (Ong and Scoparone Corces, 2014), and Hi-C studies further correlated CTCF binding at TAD boundaries (Dixon et al., 2012; Rao et al., 2014). RNAPII is involved in transcription of all protein-coding and many non-coding genes (Sims et al., 2004). Therefore , comprehensive analyses of chromatin interactions mediated by these two factors have the potential to reveal the overall relationship between organizational structure and transcriptional function. Herein, we demonstrate that ChIA-PET is inclusive for mapping both ChIP-enriched and non-enriched chromatin contacts with haplotype specificity and nucleotide resolution, and we uncovered detailed chromatin topology that provide the framework for regulating transcriptional activity. == Results == == I. ChIA-PET is multifaceted for chromatin interaction mapping == In addition to the original ChIA-PET data deposited in the ENCODE project (ENCODE Project Consortium, 2012), we have generated new CTCF- and RNAPII-mediated chromatin interaction datasets Scoparone using an improved ChIA-PET protocol (Figure S1A) for longer reads (2x150bp). Altogether, we collected 364 million uniquely mapped ChIA-PET reads in 12 ChIA-PET libraries from four human cell lines: GM12878, HeLa, K562 and MCF7 for analysis (Table S1). A ChIA-PET experiment delivers paired-end-tag (PET) sequencing data from self-ligation and inter-ligation products (Figure 1A, S1B). The self-ligation PET data identify ChIP-enriched protein-binding sites. The clustered inter-ligation PET data detect enriched interactions mediated by the ChIP targeted protein factor, whereas the singleton inter-ligation data reflects higher-order topological proximity, similar to Hi-C data (Figure S1B-E). Therefore , in theory, the multifaceted ChIA-PET data is Scoparone ideal for comprehensive 3D genome mapping. == Figure 1 . Characteristics of ChIA-PET data for 3D genome mapping. == A. Graphic of ChIA-PET mapping properties including binding peaks, enriched chromatin interactions, and non-enriched singleton PETs inferring topological neighborhood proximity. B. Comparison between CTCF ChIA-PET andin situHi-C data (GM12878). Left: loop/peak map views of CTCF ChIA-PET data at different zoom-in scopes. For each data track, loop view is at top, peak view at bottom; Y-axis indicates the contact frequency of loops (log10 scale) and intensity of binding peaks (linear scale). The maximum frequency and intensity are given in each data track. PET counts on the left side of each track show the numbers of interaction PETs detected in the given region. Middle & Right: CTCF ChIA-PET contact heatmap and matched zoom-in regions to thein situHi-C contact heatmap (Rao et al., 2014). Total numbers of sequence reads generated for thein situHi-C data,.