ABSTRACT
The regulatory effect of non-coding large-scale structural variations (SVs) on proto-oncogene activation remains unclear. This study investigated SV-mediated gene dysregulation by profiling 3D cancer genome maps from 40 patients with colorectal cancer (CRC). We developed a machine learning-based method for spatial characterization of the altered 3D cancer genome. This revealed a frequent establishment of "de novo chromatin contacts" that can span multiple topologically associating domains (TADs) in addition to the canonical TAD fusion/shuffle model. Using this information, we precisely identified super-enhancer (SE)-hijacking and its clonal characteristics. Clonal SE-hijacking genes, such as TOP2B, are recurrently associated with cell-cycle/DNA-processing functions, which can potentially be used as CRC prognostic markers. Oncogene activation and increased drug resistance due to SE-hijacking were validated by reconstructing the patient's SV using CRISPR-Cas9. Collectively, the spatial and clonality-resolved analysis of the 3D cancer genome reveals regulatory principles of large-scale SVs in oncogene activation and their clinical implications.
Subject(s)
Colorectal Neoplasms , Genome , Humans , Prognosis , Chromatin , DNA , Colorectal Neoplasms/geneticsABSTRACT
Parkinson's disease (PD) is a progressive neurodegenerative disorder. However, cell type-dependent transcriptional regulatory programs responsible for PD pathogenesis remain elusive. Here, we establish transcriptomic and epigenomic landscapes of the substantia nigra by profiling 113,207 nuclei obtained from healthy controls and patients with PD. Our multiomics data integration provides cell type annotation of 128,724 cis-regulatory elements (cREs) and uncovers cell type-specific dysregulations in cREs with a strong transcriptional influence on genes implicated in PD. The establishment of high-resolution three-dimensional chromatin contact maps identifies 656 target genes of dysregulated cREs and genetic risk loci, uncovering both potential and known PD risk genes. Notably, these candidate genes exhibit modular gene expression patterns with unique molecular signatures in distinct cell types, highlighting altered molecular mechanisms in dopaminergic neurons and glial cells including oligodendrocytes and microglia. Together, our single-cell transcriptome and epigenome reveal cell type-specific disruption in transcriptional regulations related to PD.
Subject(s)
Parkinson Disease , Humans , Parkinson Disease/metabolism , Multiomics , Gene Expression Profiling , Dopaminergic Neurons/metabolism , TranscriptomeABSTRACT
A large number of putative cis-regulatory sequences have been annotated in the human genome, but the genes they control remain poorly defined. To bridge this gap, we generate maps of long-range chromatin interactions centered on 18,943 well-annotated promoters for protein-coding genes in 27 human cell/tissue types. We use this information to infer the target genes of 70,329 candidate regulatory elements and suggest potential regulatory function for 27,325 noncoding sequence variants associated with 2,117 physiological traits and diseases. Integrative analysis of these promoter-centered interactome maps reveals widespread enhancer-like promoters involved in gene regulation and common molecular pathways underlying distinct groups of human traits and diseases.
Subject(s)
Chromatin/metabolism , Gene Expression Regulation , Genome, Human , Promoter Regions, Genetic , Regulatory Sequences, Nucleic Acid , Transcription Factors/metabolism , Chromatin/genetics , Genomics , Humans , Transcription Factors/geneticsABSTRACT
Chromosomes located in the nucleus form discrete units of genetic material composed of DNA and protein complexes. The genetic information is encoded in linear DNA sequences, but its interpretation requires an understanding of threedimensional (3D) structure of the chromosome, in which distant DNA sequences can be juxtaposed by highly condensed chromatin packing in the space of nucleus to precisely control gene expression. Recent technological innovations in exploring higher-order chromatin structure have uncovered organizational principles of the 3D genome and its various biological implications. Very recently, it has been reported that large-scale genomic variations may disrupt higher-order chromatin organization and as a consequence, greatly contribute to disease-specific gene regulation for a range of human diseases. Here, we review recent developments in studying the effect of structural variation in gene regulation, and the detection and the interpretation of structural variations in the context of 3D chromatin structure.
Subject(s)
Chromatin/chemistry , Genomic Structural Variation , Imaging, Three-Dimensional , Gene Rearrangement/genetics , GenomeABSTRACT
Three-dimensional (3D) chromatin structure is an emerging paradigm for understanding gene regulation mechanisms. Hi-C (high-throughput chromatin conformation capture), a method to detect long-range chromatin interactions, allows extensive genome-wide investigation of 3D chromatin structure. However, broad application of Hi-C data have been hindered by the level of complexity in processing Hi-C data and the large size of raw sequencing data. In order to overcome these limitations, we constructed a database named 3DIV (a 3D-genome Interaction Viewer and database) that provides a list of long-range chromatin interaction partners for the queried locus with genomic and epigenomic annotations. 3DIV is the first of its kind to collect all publicly available human Hi-C data to provide 66 billion uniformly processed raw Hi-C read pairs obtained from 80 different human cell/tissue types. In contrast to other databases, 3DIV uniquely provides normalized chromatin interaction frequencies against genomic distance dependent background signals and a dynamic browsing visualization tool for the listed interactions, which could greatly advance the interpretation of chromatin interactions. '3DIV' is available at http://kobic.kr/3div.
