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3D genome structure

Cortés-Ciriano I, Lee JJK, Xi R, Jain D, Jung YL, Yang L, Gordenin D, Klimczak LJ, Zhang CZ, Pellman DS, Group PCAWGSVW, Park PJ, Consortium PCAWG. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing. Nature Genetics 2020;52(3):331-341.Abstract
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Chromothripsis is a mutational phenomenon characterized by massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in selected cancer types have suggested that chromothripsis may be more common than initially inferred from low-resolution copy-number data. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we analyze patterns of chromothripsis across 2,658 tumors from 38 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of more than 50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy-number states, a considerable fraction of events involve multiple chromosomes and additional structural alterations. In addition to non-homologous end joining, we detect signatures of replication-associated processes and templated insertions. Chromothripsis contributes to oncogene amplification and to inactivation of genes such as mismatch-repair-related genes. These findings show that chromothripsis is a major process that drives genome evolution in human cancer.
Lee S, Bakker C, Vitzthum C, Alver BH, Park PJ*. Pairs and Pairix: a file format and a tool for efficient storage and retrieval for Hi-C read pairs. Bioinformatics 2022;Abstract
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SUMMARY: As the amount of three-dimensional chromosomal interaction data continues to increase, storing and accessing such data efficiently becomes paramount. We introduce Pairs, a block-compressed text file format for storing paired genomic coordinates from Hi-C data, and Pairix, an open-source C application to index and query Pairs files. Pairix (also available in Python and R) extends the functionalities of Tabix to paired coordinates data. We have also developed PairsQC, a collapsible HTML quality control report generator for Pairs files. AVAILABILITY: The format specification and source code are available at https://github.com/4dn-dcic/pairix, https://github.com/4dn-dcic/Rpairix and https://github.com/4dn-dcic/pairsqc.
Reiff SB, Schroeder AJ, Kırlı K, Cosolo A, Bakker C, Mercado L, Lee S, Veit AD, Balashov AK, Vitzthum C, Ronchetti W, Pitman KM, Johnson J, Ehmsen SR, Kerpedjiev P, Abdennur N, Imakaev M, Öztürk SU, Çamoğlu U, Mirny LA, Gehlenborg N*, Alver BH*, Park PJ*. The 4D Nucleome Data Portal as a resource for searching and visualizing curated nucleomics data. Nature Communications 2022;13(1):2365.Abstract
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The 4D Nucleome (4DN) Network aims to elucidate the complex structure and organization of chromosomes in the nucleus and the impact of their disruption in disease biology. We present the 4DN Data Portal ( https://data.4dnucleome.org/ ), a repository for datasets generated in the 4DN network and relevant external datasets. Datasets were generated with a wide range of experiments, including chromosome conformation capture assays such as Hi-C and other innovative sequencing and microscopy-based assays probing chromosome architecture. All together, the 4DN data portal hosts more than 1800 experiment sets and 36000 files. Results of sequencing-based assays from different laboratories are uniformly processed and quality-controlled. The portal interface allows easy browsing, filtering, and bulk downloads, and the integrated HiGlass genome browser allows interactive visualization and comparison of multiple datasets. The 4DN data portal represents a primary resource for chromosome contact and other nuclear architecture data for the scientific community.
Jung YL, Kirli K, Alver BH, Park PJ. Resources and challenges for integrative analysis of nuclear architecture data. Curr Opin Genet Dev 2021;67:103-110.Abstract
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A large amount of genomic data for profiling three-dimensional genome architecture have accumulated from large-scale consortium projects as well as from individual laboratories. In this review, we summarize recent landmark datasets and collections in the field. We describe the challenges in collection, annotation, and analysis of these data, particularly for integration of sequencing and microscopy data. We introduce efforts from consortia and independent groups to harmonize diverse datasets. As the resolution and throughput of sequencing and imaging technologies continue to increase, more efficient utilization and integration of collected data will be critical for a better understanding of nuclear architecture.
Jain D, Chu C, Alver BH, Lee S, Lee EA, Park PJ*. HiTea: a computational pipeline to identify non-reference transposable element insertions in Hi-C data. Bioinformatics 2021;37(8):1045-1051.Abstract
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Hi-C is a common technique for assessing 3D chromatin conformation. Recent studies have shown that long-range interaction information in Hi-C data can be used to generate chromosome-length genome assemblies and identify large-scale structural variations. Here, we demonstrate the use of Hi-C data in detecting mobile transposable element (TE) insertions genome-wide. Our pipeline Hi-C-based TE analyzer (HiTea) capitalizes on clipped Hi-C reads and is aided by a high proportion of discordant read pairs in Hi-C data to detect insertions of three major families of active human TEs. Despite the uneven genome coverage in Hi-C data, HiTea is competitive with the existing callers based on whole-genome sequencing (WGS) data and can supplement the WGS-based characterization of the TE-insertion landscape. We employ the pipeline to identify TE-insertions from human cell-line Hi-C samples. AVAILABILITY AND IMPLEMENTATION: HiTea is available at https://github.com/parklab/HiTea and as a Docker image. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Wang S, Lee S, Chu C, Jain D, Kerpedjiev P, Nelson GM, Walsh JM, Alver BH, Park PJ. HiNT: a computational method for detecting copy number variations and translocations from Hi-C data. Genome Biology 2020;21(1):73.Abstract
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The three-dimensional conformation of a genome can be profiled using Hi-C, a technique that combines chromatin conformation capture with high-throughput sequencing. However, structural variations often yield features that can be mistaken for chromosomal interactions. Here, we describe a computational method HiNT (Hi-C for copy Number variation and Translocation detection), which detects copy number variations and interchromosomal translocations within Hi-C data with breakpoints at single base-pair resolution. We demonstrate that HiNT outperforms existing methods on both simulated and real data. We also show that Hi-C can supplement whole-genome sequencing in structure variant detection by locating breakpoints in repetitive regions.
Horton CA, Alver B, Park PJ. GiniQC: a measure for quantifying noise in single-cell Hi-C data. Bioinformatics 2020;Abstract
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Single-cell Hi-C (scHi-C) allows the study of cell-to-cell variability in chromatin structure and dynamics. However, the high level of noise inherent in current scHi-C protocols necessitates careful assessment of data quality before biological conclusions can be drawn. Here we present GiniQC, which quantifies unevenness in the distribution of inter-chromosomal reads in the scHi-C contact matrix to measure the level of noise. Our examples show the utility of GiniQC in assessing the quality of scHi-C data as a complement to existing quality control measures. We also demonstrate how GiniQC can help inform the impact of various data processing steps on data quality.
Kerpedjiev P, Abdennur N, Lekschas F, McCallum C, Dinkla K, Strobelt H, Luber JM, Ouellette SB, Azhir A, Kumar N, Hwang J, Lee S, Alver BH, Pfister H, Mirny LA, Park PJ, Gehlenborg N. HiGlass: web-based visual exploration and analysis of genome interaction maps. Genome Biol 2018;19(1):125.Abstract
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We present HiGlass, an open source visualization tool built on web technologies that provides a rich interface for rapid, multiplex, and multiscale navigation of 2D genomic maps alongside 1D genomic tracks, allowing users to combine various data types, synchronize multiple visualization modalities, and share fully customizable views with others. We demonstrate its utility in exploring different experimental conditions, comparing the results of analyses, and creating interactive snapshots to share with collaborators and the broader public. HiGlass is accessible online at http://higlass.io and is also available as a containerized application that can be run on any platform.
Dekker J, Belmont AS, Guttman M, Leshyk VO, Lis JT, Lomvardas S, Mirny LA, O'Shea CC, Park PJ, Ren B, Politz JRC, Shendure J, Zhong S, Network N4D. The 4D nucleome project. Nature 2017;549(7671):219-226.Abstract
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The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the goal of gaining deeper mechanistic insights into how the nucleus is organized and functions. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Validated experimental technologies will be combined with biophysical approaches to generate quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells.
Apostolou E*, Ferrari F*, Walsh RM, Bar-Nur O, Stadtfeld M, Cheloufi S, Stuart HT, Polo JM, Ohsumi TK, Borowsky ML, Kharchenko PV, Park PJ**, Hochedlinger K**. Genome-wide chromatin interactions of the Nanog locus in pluripotency, differentiation, and reprogramming. Cell Stem Cell 2013;12(6):699-712.Abstract
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The chromatin state of pluripotency genes has been studied extensively in embryonic stem cells (ESCs) and differentiated cells, but their potential interactions with other parts of the genome remain largely unexplored. Here, we identified a genome-wide, pluripotency-specific interaction network around the Nanog promoter by adapting circular chromosome conformation capture sequencing. This network was rearranged during differentiation and restored in induced pluripotent stem cells. A large fraction of Nanog-interacting loci were bound by Mediator or cohesin in pluripotent cells. Depletion of these proteins from ESCs resulted in a disruption of contacts and the acquisition of a differentiation-specific interaction pattern prior to obvious transcriptional and phenotypic changes. Similarly, the establishment of Nanog interactions during reprogramming often preceded transcriptional upregulation of associated genes, suggesting a causative link. Our results document a complex, pluripotency-specific chromatin "interactome" for Nanog and suggest a functional role for long-range genomic interactions in the maintenance and induction of pluripotency.