HiCORE: Hi-C Analysis for Identification of Core Chromatin Looping Regions with Higher Resolution

Genome-wide chromosome conformation capture (3C)-based high-throughput sequencing (Hi-C) has enabled identification of genome-wide chromatin loops. Because the Hi-C map with restriction fragment resolution is intrinsically associated with sparsity and stochastic noise, Hi-C data are usually binned at particular intervals; however, the binning method has limited reliability, especially at high resolution. Here, we describe a new method called HiCORE, which provides simple pipelines and algorithms to overcome the limitations of single-layered binning and predict core chromatin regions with three-dimensional physical interactions. In this approach, multiple layers of binning with slightly shifted genome coverage are generated, and interacting bins at each layer are integrated to infer narrower regions of chromatin interactions. HiCORE predicts chromatin looping regions with higher resolution, both in human and Arabidopsis genomes, and contributes to the identification of the precise positions of potential genomic elements in an unbiased manner.     

Large-scale reconstruction of 3D structures of human chromosomes from chromosomal contact data

Chromosomes are not positioned randomly within a nucleus, but instead, they adopt preferred spatial conformations to facilitate necessary long-range gene–gene interactions and regulations. Thus, obtaining the 3D shape of chromosomes of a genome is critical for understanding how the genome folds, functions and how its genes interact and are regulated. Here, we describe a method to reconstruct preferred 3D structures of individual chromosomes of the human genome from chromosomal contact data generated by the Hi-C chromosome conformation capturing technique. A novel parameterized objective function was designed for modeling chromosome structures, which was optimized by a gradient descent method to generate chromosomal structural models that could satisfy as many intra-chromosomal contacts as possible. We applied the objective function and the corresponding optimization method to two Hi-C chromosomal data sets of both a healthy and a cancerous human B-cell to construct 3D models of individual chromosomes at resolutions of 1 MB and 200 KB, respectively. The parameters used with the method were calibrated according to an independent fluorescence in situ hybridization experimental data. The structural models generated by our method could satisfy a high percentage of contacts (pairs of loci in interaction) and non-contacts (pairs of loci not in interaction) and were compatible with the known two-compartment organization of human chromatin structures. Furthermore, structural models generated at different resolutions and from randomly permuted data sets were consistent.     

Disclosure of a structural milieu for the proximity ligation reveals the elusive nature of an active chromatin hub

The current progress in the study of the spatial organization of interphase chromosomes became possible owing to the development of the chromosome conformation capture (3C) protocol. The crucial step of this protocol is the proximity ligation—preferential ligation of DNA fragments assumed to be joined within nuclei by protein bridges and solubilized as a common complex after formaldehyde cross-linking and DNA cleavage. Here, we show that a substantial, and in some cases the major, part of DNA is not solubilized from cross-linked nuclei treated with restriction endonuclease(s) and sodium dodecyl sulphate and that this treatment neither causes lysis of the nucleus nor drastically affects its internal organization. Analysis of the ligation frequencies of the mouse β-globin gene domain DNA fragments demonstrated that the previously reported 3C signals were generated predominantly, if not exclusively, in the insoluble portion of the 3C material. The proximity ligation thus occurs within the cross-linked chromatin cage in non-lysed nuclei. The finding does not compromise the 3C protocol but allows the consideration of an active chromatin hub as a folded chromatin domain or a nuclear compartment rather than a rigid complex of regulatory elements.     

Higher-order chromatin domains link eQTLs with the expression of far-away genes

Distal expression quantitative trait loci (distal eQTLs) are genetic mutations that affect the expression of genes genomically far away. However, the mechanisms that cause a distal eQTL to modulate gene expression are not yet clear. Recent high-resolution chromosome conformation capture experiments along with a growing database of eQTLs provide an opportunity to understand the spatial mechanisms influencing distal eQTL associations on a genome-wide scale. We test the hypothesis that spatial proximity contributes to eQTL-gene regulation in the context of the higher-order domain structure of chromatin as determined from recent Hi-C chromosome conformation experiments. This analysis suggests that the large-scale topology of chromatin is coupled with eQTL associations by providing evidence that eQTLs are in general spatially close to their target genes, occur often around topological domain boundaries and preferentially associate with genes across domains. We also find that within-domain eQTLs that overlap with regulatory elements such as promoters and enhancers are spatially more close than the overall set of within-domain eQTLs, suggesting that spatial proximity derived from the domain structure in chromatin plays an important role in the regulation of gene expression.     

染色体构象俘获技术及其研究进展

真核生物中远距离的调控元件往往通过相互作用形成复杂的染色体相互作用网络,对基因的表达进行三维调节,染色体构象俘获是研究染色体相互作用的有力工具。简要综述了染色体构象俘获技术的基本原理及其研究进展,并对相关技术存在的问题进行了分析,对发展趋势进行了展望。     

MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly identifies statistically significant interactions in both Hi-C and capture Hi-C experiments. MaxHiC uses a negative binomial distribution model and a maximum likelihood technique to correct biases in both Hi-C and capture Hi-C libraries. We systematically benchmark MaxHiC against major Hi-C background correction tools including Hi-C significant interaction callers (SIC) and Hi-C loop callers using published Hi-C, capture Hi-C, and Micro-C datasets. Our results demonstrate that 1) Interacting regions identified by MaxHiC have significantly greater levels of overlap with known regulatory features (e.g. active chromatin histone marks, CTCF binding sites, DNase sensitivity) and also disease-associated genome-wide association SNPs than those identified by currently existing models, 2) the pairs of interacting regions are more likely to be linked by eQTL pairs and 3) more likely to link known regulatory features including known functional enhancer-promoter pairs validated by CRISPRi than any of the existing methods. We also demonstrate that interactions between different genomic region types have distinct distance distributions only revealed by MaxHiC. MaxHiC is publicly available as a python package for the analysis of Hi-C, capture Hi-C and Micro-C data.     

Three-Dimensional Genome Architecture Influences Partner Selection for Chromosomal Translocations in Human Disease

Chromosomal translocations are frequent features of cancer genomes that contribute to disease progression. These rearrangements result from formation and illegitimate repair of DNA double-strand breaks (DSBs), a process that requires spatial colocalization of chromosomal breakpoints. The “contact first” hypothesis suggests that translocation partners colocalize in the nuclei of normal cells, prior to rearrangement. It is unclear, however, the extent to which spatial interactions based on three-dimensional genome architecture contribute to chromosomal rearrangements in human disease. Here we intersect Hi-C maps of three-dimensional chromosome conformation with collections of 1,533 chromosomal translocations from cancer and germline genomes. We show that many translocation-prone pairs of regions genome-wide, including the cancer translocation partners BCR-ABL and MYC-IGH, display elevated Hi-C contact frequencies in normal human cells. Considering tissue specificity, we find that translocation breakpoints reported in human hematologic malignancies have higher Hi-C contact frequencies in lymphoid cells than those reported in sarcomas and epithelial tumors. However, translocations from multiple tissue types show significant correlation with Hi-C contact frequencies, suggesting that both tissue-specific and universal features of chromatin structure contribute to chromosomal alterations. Our results demonstrate that three-dimensional genome architecture shapes the landscape of rearrangements directly observed in human disease and establish Hi-C as a key method for dissecting these effects.     

Identifying multi-locus chromatin contacts in human cells using tethered multiple 3C

Background

Several recently developed experimental methods, each an extension of the chromatin conformation capture (3C) assay, have enabled the genome-wide profiling of chromatin contacts between pairs of genomic loci in 3D. Especially in complex eukaryotes, data generated by these methods, coupled with other genome-wide datasets, demonstrated that non-random chromatin folding correlates strongly with cellular processes such as gene expression and DNA replication.

Results

We describe a genome architecture assay, tethered multiple 3C (TM3C), that maps genome-wide chromatin contacts via a simple protocol of restriction enzyme digestion and religation of fragments upon agarose gel beads followed by paired-end sequencing. In addition to identifying contacts between pairs of loci, TM3C enables identification of contacts among more than two loci simultaneously. We use TM3C to assay the genome architectures of two human cell lines: KBM7, a near-haploid chronic leukemia cell line, and NHEK, a normal diploid human epidermal keratinocyte cell line. We confirm that the contact frequency maps produced by TM3C exhibit features characteristic of existing genome architecture datasets, including the expected scaling of contact probabilities with genomic distance, megabase scale chromosomal compartments and sub-megabase scale topological domains. We also confirm that TM3C captures several known cell type-specific contacts, ploidy shifts and translocations, such as Philadelphia chromosome formation (Ph+) in KBM7. We confirm a subset of the triple contacts involving the IGF2-H19 imprinting control region (ICR) using PCR analysis for KBM7 cells. Our genome-wide analysis of pairwise and triple contacts demonstrates their preference for linking open chromatin regions to each other and for linking regions with higher numbers of DNase hypersensitive sites (DHSs) to each other. For near-haploid KBM7 cells, we infer whole genome 3D models that exhibit clustering of small chromosomes with each other and large chromosomes with each other, consistent with previous studies of the genome architectures of other human cell lines.

Conclusion

TM3C is a simple protocol for ascertaining genome architecture and can be used to identify simultaneous contacts among three or four loci. Application of TM3C to a near-haploid human cell line revealed large-scale features of chromosomal organization and multi-way chromatin contacts that preferentially link regions of open chromatin.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1236-7) contains supplementary material, which is available to authorized users.     

Uncovering the statistical physics of 3D chromosomal organization using data-driven modeling

In recent years, much effort has been devoted to understanding the three-dimensional (3D) organization of the genome and how genomic structure mediates nuclear function. The development of experimental techniques that combine DNA proximity ligation with high-throughput sequencing, such as Hi-C, have substantially improved our knowledge about chromatin organization. Numerous experimental advancements, not only utilizing DNA proximity ligation but also high-resolution genome imaging (DNA tracing), have required theoretical modeling to determine the structural ensembles consistent with such data. These 3D polymer models of the genome provide an understanding of the physical mechanisms governing genome architecture. Here, we present an overview of the recent advances in modeling the ensemble of 3D chromosomal structures by employing the maximum entropy approach combined with polymer physics. Particularly, we discuss the minimal chromatin model (MiChroM) along with the “maximum entropy genomic annotations from biomarkers associated with structural ensembles” (MEGABASE) model, which have been remarkably successful in the accurate modeling of chromosomes consistent with both Hi-C and DNA-tracing data.     

Spatial organization of interphase chromosomes and the role of chromatin fibril dynamics in the positioning of genome elements

Many studies are devoted to the analysis of interphase chromosome architecture due to the evidence of the functional-dependent spatial organization of the genome. These studies are based on classical cytological methods, as well as on biochemical approaches (3C, 4C, 5C, Hi-C), which allow one to detect long-range interactions between fragments of chromatin fibril, including the genome-wide interactions. In this review, we discuss the results of these projects, which allow us to explain the functional basis of nucleus multilevel compartmentalization and to identify the principles of high-level chromatin organization. Special attention is paid to the enhancer-promoter interactions, which are important for the regulation of gene expression. In this regard, we provide a new interpretation to the model of an active chromatin hub and to the alternative model of an active chromatin compartment, which was proposed during reconsideration of some steps of the 3C procedure.     

Spatial organization of the mouse genome and its role in recurrent chromosomal translocations

The extent to which the three-dimensional organization of the genome contributes to chromosomal translocations is an important question in cancer genomics. We generated a high-resolution Hi-C spatial organization map of the G1-arrested mouse pro-B cell genome and used high-throughput genome-wide translocation sequencing to map translocations from target DNA double-strand breaks (DSBs) within it. RAG endonuclease-cleaved antigen-receptor loci are dominant translocation partners for target DSBs regardless of genomic position, reflecting high-frequency DSBs at these loci and their colocalization in a fraction of cells. To directly assess spatial proximity contributions, we normalized genomic DSBs via ionizing radiation. Under these conditions, translocations were highly enriched in cis along single chromosomes containing target DSBs and within other chromosomes and subchromosomal domains in a manner directly related to pre-existing spatial proximity. By combining two high-throughput genomic methods in a genetically tractable system, we provide a new lens for viewing cancer genomes.     

qc3C: Reference-free quality control for Hi-C sequencing data

Hi-C is a sample preparation method that enables high-throughput sequencing to capture genome-wide spatial interactions between DNA molecules. The technique has been successfully applied to solve challenging problems such as 3D structural analysis of chromatin, scaffolding of large genome assemblies and more recently the accurate resolution of metagenome-assembled genomes (MAGs). Despite continued refinements, however, preparing a Hi-C library remains a complex laboratory protocol. To avoid costly failures and maximise the odds of successful outcomes, diligent quality management is recommended. Current wet-lab methods provide only a crude assay of Hi-C library quality, while key post-sequencing quality indicators used have—thus far—relied upon reference-based read-mapping. When a reference is accessible, this reliance introduces a concern for quality, where an incomplete or inexact reference skews the resulting quality indicators. We propose a new, reference-free approach that infers the total fraction of read-pairs that are a product of proximity ligation. This quantification of Hi-C library quality requires only a modest amount of sequencing data and is independent of other application-specific criteria. The algorithm builds upon the observation that proximity ligation events are likely to create k-mers that would not naturally occur in the sample. Our software tool (qc3C) is to our knowledge the first to implement a reference-free Hi-C QC tool, and also provides reference-based QC, enabling Hi-C to be more easily applied to non-model organisms and environmental samples. We characterise the accuracy of the new algorithm on simulated and real datasets and compare it to reference-based methods.     

NucleoMap: A computational tool for identifying nucleosomes in ultra-high resolution contact maps

Although poorly positioned nucleosomes are ubiquitous in the eukaryotic genome, they are difficult to identify with existing nucleosome identification methods. Recently available enhanced high-throughput chromatin conformation capture techniques such as Micro-C, DNase Hi-C, and Hi-CO characterize nucleosome-level chromatin proximity, probing the positions of mono-nucleosomes and the spacing between nucleosome pairs at the same time, enabling nucleosome profiling in poorly positioned regions. Here we develop a novel computational approach, NucleoMap, to identify nucleosome positioning from ultra-high resolution chromatin contact maps. By integrating nucleosome read density, contact distances, and binding preferences, NucleoMap precisely locates nucleosomes in both prokaryotic and eukaryotic genomes and outperforms existing nucleosome identification methods in both precision and recall. We rigorously characterize genome-wide association in eukaryotes between the spatial organization of mono-nucleosomes and their corresponding histone modifications, protein binding activities, and higher-order chromatin functions. We also find evidence of two tetra-nucleosome folding structures in human embryonic stem cells and analyze their association with multiple structural and functional regions. Based on the identified nucleosomes, nucleosome contact maps are constructed, reflecting the inter-nucleosome distances and preserving the contact distance profiles in original contact maps.     

ASHIC: hierarchical Bayesian modeling of diploid chromatin contacts and structures

The recently developed Hi-C technique has been widely applied to map genome-wide chromatin interactions. However, current methods for analyzing diploid Hi-C data cannot fully distinguish between homologous chromosomes. Consequently, the existing diploid Hi-C analyses are based on sparse and inaccurate allele-specific contact matrices, which might lead to incorrect modeling of diploid genome architecture. Here we present ASHIC, a hierarchical Bayesian framework to model allele-specific chromatin organizations in diploid genomes. We developed two models under the Bayesian framework: the Poisson-multinomial (ASHIC-PM) model and the zero-inflated Poisson-multinomial (ASHIC-ZIPM) model. The proposed ASHIC methods impute allele-specific contact maps from diploid Hi-C data and simultaneously infer allelic 3D structures. Through simulation studies, we demonstrated that ASHIC methods outperformed existing approaches, especially under low coverage and low SNP density conditions. Additionally, in the analyses of diploid Hi-C datasets in mouse and human, our ASHIC-ZIPM method produced fine-resolution diploid chromatin maps and 3D structures and provided insights into the allelic chromatin organizations and functions. To summarize, our work provides a statistically rigorous framework for investigating fine-scale allele-specific chromatin conformations. The ASHIC software is publicly available at https://github.com/wmalab/ASHIC.     

Comparison of the three-dimensional organization of sperm and fibroblast genomes using the Hi-C approach

BackgroundThe three-dimensional organization of the genome is tightly connected to its biological function. The Hi-C approach was recently introduced as a method that can be used to identify higher-order chromatin interactions genome-wide. The aim of this study was to determine genome-wide chromatin interaction frequencies using the Hi-C approach in mouse sperm cells and embryonic fibroblasts.ResultsThe obtained data demonstrate that the three-dimensional genome organizations of sperm and fibroblast cells show a high degree of similarity both with each other and with the previously described mouse embryonic stem cells. Both A- and B-compartments and topologically associated domains are present in spermatozoa and fibroblasts. Nevertheless, sperm cells and fibroblasts exhibit statistically significant differences between each other in the contact probabilities of defined loci. Tight packaging of the sperm genome results in an enrichment of long-range contacts compared with the fibroblasts. However, only 30% of the differences in the number of contacts are based on differences in the densities of their genome packages; the main source of the differences is the gain or loss of contacts that are specific for defined genome regions. We find that the dependence of the contact probability on genomic distance for sperm is close to the dependence predicted for the fractal globular folding of chromatin.ConclusionsOverall, we can conclude that the three-dimensional structure of the genome is passed through generations without being dramatically changed in sperm cells.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0642-0) contains supplementary material, which is available to authorized users.