ABSTRACT: Promoter Capture Hi-C on chicken liver and skeletal muscle. Promoter Capture Hi-C data was generated to support annotation of regulatory elements of coding and non-coding genes and to evaluate the tissue-specificity of such regulatory elements. This study is part of GENE-SWitCH and the FAANG project, promoting rapid prepublication of data to support the research community. These data are released under Fort Lauderdale principles, as confirmed in the Toronto Statement (Toronto International Data Release Workshop. Birney et al. 2009. Pre-publication data sharing. Nature 461:168-170). Any use of this dataset must abide by the FAANG data sharing principles. Data producers reserve the right to make the first publication of a global analysis of this data. If you are unsure if you are allowed to publish on this dataset, please contact the FAANG Data Coordination Centre and FAANG Consortium (email faang-dcc@ebi.ac.uk and copy faang@iastate.edu) to enquire. The full guidelines can be found at http://www.faang.org/data-share-principle.
Project description:The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the spatio-temporal expression of their target genes through physical contact, often bridging considerable (in some cases hundreds of kilobases) genomic distances and bypassing nearby genes. The human genome harbors an estimated one million enhancers, the vast majority of which have unknown gene targets. Assigning distal regulatory regions to their target genes is thus crucial to understand gene expression control. We developed Promoter Capture Hi-C (PCHi-C) to enable the genome-wide detection of distal promoter-interacting regions (PIRs), for all promoters in a single experiment. In PCHi-C, highly complex Hi-C libraries are specifically enriched for promoter sequences through in-solution hybrid selection with thousands of biotinylated RNA baits complementary to the ends of all promoter-containing restriction fragments. The aim is to then pull-down promoter sequences and their frequent interaction partners such as enhancers and other potential regulatory elements. After high-throughput paired-end sequencing, a statistical test is applied to each promoter-ligated restriction fragment to identify significant PIRs at the restriction fragment level. We have used PCHi-C to generate an atlas of long-range promoter interactions in dozens of human and mouse cell types. These promoter interactome maps have contributed to a greater understanding of mammalian gene expression control by assigning putative regulatory regions to their target genes and revealing preferential spatial promoter-promoter interaction networks. This information also has high relevance to understanding human genetic disease and the identification of potential disease genes, by linking non-coding disease-associated sequence variants in or near control sequences to their target genes.
Project description:Genome organisation determines chromosome interactions between regulatory elements, such as promoters and enhancers, influencing gene expression. Despite the fact that it is possible to assess whether a gene is actively transcribed, it has been challenging to point out the genomic regions that are involved in the regulation of a particular gene. We are interested in better understanding the interactions between promoters and their regulatory elements in colorectal cancer in order to unveil novel non-coding regions which might have a role in tumour development. To do so, we utilise the HiC method complemented with promoter capture in combination with NGS to map promoter interactions in two CRC cell lines, representing two distinct CRC subtypes.
Project description:Efforts are being directed to systematically analyze the non-coding regions of the genome for cancer-driving mutations1-6. cis-regulatory elements (CREs) represent a highly enriched subset of the non-coding regions of the genome in which to search for such mutations. Here we use high-throughput chromosome conformation capture techniques (Hi-C) for 19,023 promoter fragments to catalog the regulatory landscape of colorectal cancer in cell lines, mapping CREs and integrating these with whole-genome sequence and expression data from The Cancer Genome Atlas7,8. We identify a recurrently mutated CRE interacting with the ETV1 promoter affecting gene expression. ETV1 expression influences cell viability and is associated with patient survival. We further refine our understanding of the regulatory effects of copy-number variations, showing that RASL11A is targeted by a previously identified enhancer amplification1. This study reveals new insights into the complex genetic alterations driving tumor development, providing a paradigm for employing chromosome conformation capture to decipher non-coding CREs relevant to cancer biology.
Project description:Long-range interactions between regulatory elements and promoters are key in gene transcriptional control; however, their study requires large amounts of starting material, which is not compatible with clinical scenarios nor the study of rare cell populations. Here we introduce low input capture Hi-C (liCHi-C) as a cost-effective, flexible method to map and robustly compare promoter interactomes at high resolution. As proof of its broad applicability, we implement liCHi-C to study normal and malignant human hematopoietic hierarchy in clinical samples. We demonstrate that the dynamic promoter architecture identifies developmental trajectories and orchestrates transcriptional transitions during cell-state commitment. Moreover, liCHi-C enables the identification of disease-relevant cell types, genes and pathways potentially deregulated by non-coding alterations at distal regulatory elements. Finally, we show that liCHi-C can be harnessed to uncover genome-wide structural variants, resolve their breakpoints and infer their pathogenic effects. Collectively, our optimized liCHi-C method expands the study of 3D chromatin organization to unique, low-abundance cell populations, and offers an opportunity to uncover factors and regulatory networks involved in disease pathogenesis.
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.
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.
Project description:Hi-C, capture Hi-C (CHC) and Capture-C have contributed greatly to our present understanding of the three-dimensional organization of genomes in the context of transcriptional regulation by characterizing the roles of topological associated domains, enhancer promoter loops and other three-dimensional genomic interactions. The analysis is based on counts of chimeric read pairs that map to interacting regions of the genome. However, the processing and quality control presents a number of unique challenges. We review here the experimental and computational foundations and explain how the characteristics of restriction digests, sonication fragments and read pairs can be exploited to distinguish technical artefacts from valid read pairs originating from true chromatin interactions.