Chromatin Contact Maps Research Articles

Machine Learning Reveals the Diversity of Human 3D Chromatin Contact Patterns.

Understanding variation in chromatin contact patterns across diverse humans is critical for interpreting noncoding variants and their effects on gene expression and phenotypes. However, experimental determination of chromatin contact patterns across large samples is prohibitively expensive. To overcome this challenge, we develop and validate a machine learning method to quantify the variation in 3D chromatin contacts at 2 kilobase resolution from genome sequence alone. We apply this approach to thousands of human genomes from the 1000 Genomes Project and the inferred hominin ancestral genome. While patterns of 3D contact divergence genome wide are qualitatively similar to patterns of sequence divergence, we find substantial differences in 3D divergence and sequence divergence in local 1 megabase genomic windows. In particular, we identify 392 windows with significantly greater 3D divergence than expected from sequence. Moreover, for 31% of genomic windows, a single individual has a rare divergent 3D contact map pattern. Using in silico mutagenesis, we find that most single nucleotide sequence changes do not result in changes to 3D chromatin contacts. However, in windows with substantial 3D divergence just one or a few variants can lead to divergent 3D chromatin contacts without the individuals carrying those variants having high sequence divergence. In summary, inferring 3D chromatin contact maps across human populations reveals variable contact patterns. We anticipate that these genetically diverse maps of 3D chromatin contact will provide a reference for future work on the function and evolution of 3D chromatin contact variation across human populations.

An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases.

Transcribed enhancer maps can reveal nuclear interactions underpinning each cell type and connect specific cell types to diseases. Using a 5' single-cell RNA sequencing approach, we defined transcription start sites of enhancer RNAs and other classes of coding and noncoding RNAs in human CD4+ T cells, revealing cellular heterogeneity and differentiation trajectories. Integration of these datasets with single-cell chromatin profiles showed that active enhancers with bidirectional RNA transcription are highly cell type-specific and that disease heritability is strongly enriched in these enhancers. The resulting cell type-resolved multimodal atlas of bidirectionally transcribed enhancers, which we linked with promoters using fine-scale chromatin contact maps, enabled us to systematically interpret genetic variants associated with a range of immune-mediated diseases.

Dynamic chromatin architecture of the porcine adipose tissues with weight gain and loss

Using an adult female miniature pig model with diet-induced weight gain/weight loss, we investigated the regulatory mechanisms of three-dimensional (3D) genome architecture in adipose tissues (ATs) associated with obesity. We generated 249 high-resolution in situ Hi-C chromatin contact maps of subcutaneous AT and three visceral ATs, analyzing transcriptomic and chromatin architectural changes under different nutritional treatments. We find that chromatin architecture remodeling underpins transcriptomic divergence in ATs, potentially linked to metabolic risks in obesity development. Analysis of chromatin architecture among subcutaneous ATs of different mammals suggests the presence of transcriptional regulatory divergence that could explain phenotypic, physiological, and functional differences in ATs. Regulatory element conservation analysis in pigs and humans reveals similarities in the regulatory circuitry of genes responsible for the obesity phenotype and identified non-conserved elements in species-specific gene sets that underpin AT specialization. This work provides a data-rich tool for discovering obesity-related regulatory elements in humans and pigs.

A global high-density chromatin interaction network reveals functional long-range and trans-chromosomal relationships

BackgroundChromatin contacts are essential for gene-expression regulation; however, obtaining a high-resolution genome-wide chromatin contact map is still prohibitively expensive owing to large genome sizes and the quadratic scale of pairwise data. Chromosome conformation capture (3C)-based methods such as Hi-C have been extensively used to obtain chromatin contacts. However, since the sparsity of these maps increases with an increase in genomic distance between contacts, long-range or trans-chromatin contacts are especially challenging to sample.ResultsHere, we create a high-density reference genome-wide chromatin contact map using a meta-analytic approach. We integrate 3600 human, 6700 mouse, and 500 fly Hi-C experiments to create species-specific meta-Hi-C chromatin contact maps with 304 billion, 193 billion, and 19 billion contacts in respective species. We validate that meta-Hi-C contact maps are uniquely powered to capture functional chromatin contacts in both cis and trans. We find that while individual dataset Hi-C networks are largely unable to predict any long-range coexpression (median 0.54 AUC), meta-Hi-C networks perform comparably in both cis and trans (0.65 AUC vs 0.64 AUC). Similarly, for long-range expression quantitative trait loci (eQTL), meta-Hi-C contacts outperform all individual Hi-C experiments, providing an improvement over the conventionally used linear genomic distance-based association. Assessing between species, we find patterns of chromatin contact conservation in both cis and trans and strong associations with coexpression even in species for which Hi-C data is lacking.ConclusionsWe have generated an integrated chromatin interaction network which complements a large number of methodological and analytic approaches focused on improved specificity or interpretation. This high-depth “super-experiment” is surprisingly powerful in capturing long-range functional relationships of chromatin interactions, which are now able to predict coexpression, eQTLs, and cross-species relationships. The meta-Hi-C networks are available at https://labshare.cshl.edu/shares/gillislab/resource/HiC/.

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.

The Visayan Warty Pig (Sus cebifrons) Genome Provides Insight Into Chromosome Evolution and Sensory Adaptation in Pigs.

It is largely unknown how mammalian genomes evolve under rapid speciation and environmental adaptation. An excellent model for understanding fast evolution is provided by the genus Sus, which diverged relatively recently and lacks postzygotic isolation. Here, we present a high-quality reference genome of the Visayan warty pig, which is specialized to a tropical island environment. Comparing the genome sequences and chromatin contact maps of the Visayan warty pig (Sus cebifrons) and domestic pig (Sus scrofa), we characterized the dynamics of chromosomal structure evolution during Sus speciation, revealing the similar chromosome conformation as the potential biological mechanism of frequent postdivergence hybridization among Suidae. We further investigated the different signatures of adaptive selection and domestication in Visayan warty pig and domestic pig with specific emphasize on the evolution of olfactory and gustatory genes, elucidating higher olfactory diversity in Visayan warty pig and positive and relaxed evolution of bitter and fat taste receptors, respectively, in domestic pig. Our comprehensive evolutionary and comparative genome analyses provide insight into the dynamics of genomes and how these change over relative short evolutionary times, as well as how these genomic differences encode for differences in the phenotypes.

NicE-C efficiently reveals open chromatin-associated chromosome interactions at high resolution.

Enhancer–promoter communication is known to regulate spatiotemporal dynamics of gene expression. Several methods are available to capture enhancer–promoter interactions, but they either require large amounts of starting materials and are costly, or provide a relative low resolution in chromatin contact maps. Here, we present nicking enzyme-assisted open chromatin interaction capture (NicE-C), a method that leverages nicking enzyme–mediated open chromatin profiling and chromosome conformation capture to enable robust and cost-effective detection of open chromatin interactions at high resolution, especially enhancer–promoter interactions. Using TNF stimulation and mouse kidney aging as models, we applied NicE-C to reveal characteristics of dynamic enhancer–promoter interactions.

Understanding 3D genome organization by multidisciplinary methods.

Understanding how chromatin is folded in the nucleus is fundamental to understanding its function. Although 3D genome organization has been historically difficult to study owing to a lack of relevant methodologies, major technological breakthroughs in genome-wide mapping of chromatin contacts and advances in imaging technologies in the twenty-first century considerably improved our understanding of chromosome conformation and nuclear architecture. In this Review, we discuss methods of 3D genome organization analysis, including sequencing-based techniques, such as Hi-C and its derivatives, Micro-C, DamID and others; microscopy-based techniques, such as super-resolution imaging coupled with fluorescence in situ hybridization (FISH), multiplex FISH, in situ genome sequencing and live microscopy methods; and computational and modelling approaches. We describe the most commonly used techniques and their contribution to our current knowledge of nuclear architecture and, finally, we provide a perspective on up-and-coming methods that open possibilities for future major discoveries.

Identification and utilization of copy number information for correcting Hi-C contact map of cancer cell lines

BackgroundHi-C and its variant techniques have been developed to capture the spatial organization of chromatin. Normalization of Hi-C contact map is essential for accurate modeling and interpretation of high-throughput chromatin conformation capture (3C) experiments. Hi-C correction tools were originally developed to normalize systematic biases of karyotypically normal cell lines. However, a vast majority of available Hi-C datasets are derived from cancer cell lines that carry multi-level DNA copy number variations (CNVs). CNV regions display over- or under-representation of interaction frequencies compared to CN-neutral regions. Therefore, it is necessary to remove CNV-driven bias from chromatin interaction data of cancer cell lines to generate a euploid-equivalent contact map.ResultsWe developed the HiCNAtra framework to compute high-resolution CNV profiles from Hi-C or 3C-seq data of cancer cell lines and to correct chromatin contact maps from systematic biases including CNV-associated bias. First, we introduce a novel ‘entire-fragment’ counting method for better estimation of the read depth (RD) signal from Hi-C reads that recapitulates the whole-genome sequencing (WGS)-derived coverage signal. Second, HiCNAtra employs a multimodal-based hierarchical CNV calling approach, which outperformed OneD and HiNT tools, to accurately identify CNVs of cancer cell lines. Third, incorporating CNV information with other systematic biases, HiCNAtra simultaneously estimates the contribution of each bias and explicitly corrects the interaction matrix using Poisson regression. HiCNAtra normalization abolishes CNV-induced artifacts from the contact map generating a heatmap with homogeneous signal. When benchmarked against OneD, CAIC, and ICE methods using MCF7 cancer cell line, HiCNAtra-corrected heatmap achieves the least 1D signal variation without deforming the inherent chromatin interaction signal. Additionally, HiCNAtra-corrected contact frequencies have minimum correlations with each of the systematic bias sources compared to OneD’s explicit method. Visual inspection of CNV profiles and contact maps of cancer cell lines reveals that HiCNAtra is the most robust Hi-C correction tool for ameliorating CNV-induced bias.ConclusionsHiCNAtra is a Hi-C-based computational tool that provides an analytical and visualization framework for DNA copy number profiling and chromatin contact map correction of karyotypically abnormal cell lines. HiCNAtra is an open-source software implemented in MATLAB and is available at https://github.com/AISKhalil/HiCNAtra.

Network-based method for regions with statistically frequent interchromosomal interactions at single-cell resolution

BackgroundChromosome conformation capture-based methods, especially Hi-C, enable scientists to detect genome-wide chromatin interactions and study the spatial organization of chromatin, which plays important roles in gene expression regulation, DNA replication and repair etc. Thus, developing computational methods to unravel patterns behind the data becomes critical. Existing computational methods focus on intrachromosomal interactions and ignore interchromosomal interactions partly because there is no prior knowledge for interchromosomal interactions and the frequency of interchromosomal interactions is much lower while the search space is much larger. With the development of single-cell technologies, the advent of single-cell Hi-C makes interrogating the spatial structure of chromatin at single-cell resolution possible. It also brings a new type of frequency information, the number of single cells with chromatin interactions between two disjoint chromosome regions.ResultsConsidering the lack of computational methods on interchromosomal interactions and the unsurprisingly frequent intrachromosomal interactions along the diagonal of a chromatin contact map, we propose a computational method dedicated to analyzing interchromosomal interactions of single-cell Hi-C with this new frequency information. To the best of our knowledge, our proposed tool is the first to identify regions with statistically frequent interchromosomal interactions at single-cell resolution. We demonstrate that the tool utilizing networks and binomial statistical tests can identify interesting structural regions through visualization, comparison and enrichment analysis and it also supports different configurations to provide users with flexibility.ConclusionsIt will be a useful tool for analyzing single-cell Hi-C interchromosomal interactions.

Benchmark of software tools for prokaryotic chromosomal interaction domain identification.

MotivationThe application of genome-wide chromosome conformation capture (3C) methods to prokaryotes provided insights into the spatial organization of their genomes and identified patterns conserved across the tree of life, such as chromatin compartments and contact domains. Prokaryotic genomes vary in GC content and the density of restriction sites along the chromosome, suggesting that these properties should be considered when planning experiments and choosing appropriate software for data processing. Diverse algorithms are available for the analysis of eukaryotic chromatin contact maps, but their potential application to prokaryotic data has not yet been evaluated.ResultsHere, we present a comparative analysis of domain calling algorithms using available single-microbe experimental data. We evaluated the algorithms’ intra-dataset reproducibility, concordance with other tools and sensitivity to coverage and resolution of contact maps. Using RNA-seq as an example, we showed how orthogonal biological data can be utilized to validate the reliability and significance of annotated domains. We also suggest that in silico simulations of contact maps can be used to choose optimal restriction enzymes and estimate theoretical map resolutions before the experiment. Our results provide guidelines for researchers investigating microbes and microbial communities using high-throughput 3C assays such as Hi-C and 3C-seq.Availability and implementationThe code of the analysis is available at https://github.com/magnitov/prokaryotic_cids.Supplementary information Supplementary data are available at Bioinformatics online.

Assessing stationary distributions derived from chromatin contact maps

BackgroundThe spatial configuration of chromosomes is essential to various cellular processes, notably gene regulation, while architecture related alterations, such as translocations and gene fusions, are often cancer drivers. Thus, eliciting chromatin conformation is important, yet challenging due to compaction, dynamics and scale. However, a variety of recent assays, in particular Hi-C, have generated new details of chromatin structure, spawning a number of novel biological findings. Many findings have resulted from analyses on the level of native contact data as generated by the assays. Alternatively, reconstruction based approaches often proceed by first converting contact frequencies into distances, then generating a three dimensional (3D) chromatin configuration that best recapitulates these distances. Subsequent analyses can enrich contact level analyses via superposition of genomic attributes on the reconstruction. But, such advantages depend on the accuracy of the reconstruction which, absent gold standards, is inherently difficult to assess. Attempts at accuracy evaluation have relied on simulation and/or FISH imaging that typically features a handful of low resolution probes. While newly advanced multiplexed FISH imaging offers possibilities for refined 3D reconstruction accuracy evaluation, availability of such data is limited due to assay complexity and the resolution thereof is appreciably lower than the reconstructions being assessed. Accordingly, there is demand for new methods of reconstruction accuracy appraisal.ResultsHere we explore the potential of recently proposed stationary distributions, hereafter StatDns, derived from Hi-C contact matrices, to serve as a basis for reconstruction accuracy assessment. Current usage of such StatDns has focussed on the identification of highly interactive regions (HIRs): computationally defined regions of the genome purportedly involved in numerous long-range intra-chromosomal contacts. Consistent identification of HIRs would be informative with respect to inferred 3D architecture since the corresponding regions of the reconstruction would have an elevated number of k nearest neighbors (kNNs). More generally, we anticipate a monotone decreasing relationship between StatDn values and kNN distances. After initially evaluating the reproducibility of StatDns across replicate Hi-C data sets, we use this implied StatDn - kNN relationship to gauge the utility of StatDns for reconstruction validation, making recourse to both real and simulated examples.ConclusionsOur analyses demonstrate that, as constructed, StatDns do not provide a suitable measure for assessing the accuracy of 3D genome reconstructions. Whether this is attributable to specific choices surrounding normalization in defining StatDns or to the logic underlying their very formulation remains to be determined.

Chromosomal-level assembly of Takifugu obscurus (Abe, 1949) genome using third-generation DNA sequencing and Hi-C analysis.

The Tetraodontidae family are known to have relatively small and compact genomes compared to other vertebrates. The obscure puffer fish Takifugu obscurus is an anadromous species that migrates to freshwater from the sea for spawning. Thus the euryhaline characteristics of T. obscurus have been investigated to gain understanding of their survival ability, osmoregulation, and other homeostatic mechanisms in both freshwater and seawater. In this study, a high quality chromosome-level reference genome for T. obscurus was constructed using long-read Pacific Biosciences (PacBio) Sequel sequencing and a Hi-C-based chromatin contact map platform. The final genome assembly of T. obscurus is 381Mb, with a contig N50 length of 3,296kb and longest length of 10.7Mb, from a total of 62Gb of raw reads generated using single-molecule real-time sequencing technology from a PacBio Sequel platform. The PacBio data were further clustered into chromosome-scale scaffolds using a Hi-C approach, resulting in a 373Mb genome assembly with a contig N50 length of 15.2Mb and and longest length of 28Mb. When we directly compared the 22 longest scaffolds of T. obscurus to the 22 chromosomes of the tiger puffer Takifugu rubripes, a clear one-to-one orthologous relationship was observed between the two species, supporting the chromosome-level assembly of T. obscurus. This genome assembly can serve as a valuable genetic resource for exploring fugu-specific compact genome characteristics, and will provide essential genomic information for understanding molecular adaptations to salinity fluctuations and the evolution of osmoregulatory mechanisms.

ChiTaRS 5.0: the comprehensive database of chimeric transcripts matched with druggable fusions and 3D chromatin maps.

Chimeric RNA transcripts are formed when exons from two genes fuse together, often due to chromosomal translocations, transcriptional errors or trans-splicing effect. While these chimeric RNAs produce functional proteins only in certain cases, they play a significant role in disease phenotyping and progression. ChiTaRS 5.0 (http://chitars.md.biu.ac.il/) is the latest and most comprehensive chimeric transcript repository, with 111 582 annotated entries from eight species, including 23 167 known human cancer breakpoints. The database includes unique information correlating chimeric breakpoints with 3D chromatin contact maps, generated from public datasets of chromosome conformation capture techniques (Hi–C). In this update, we have added curated information on druggable fusion targets matched with chimeric breakpoints, which are applicable to precision medicine in cancers. The introduction of a new section that lists chimeric RNAs in various cell-lines is another salient feature. Finally, using text-mining techniques, novel chimeras in Alzheimer's disease, schizophrenia, dyslexia and other diseases were collected in ChiTaRS. Thus, this improved version is an extensive catalogue of chimeras from multiple species. It extends our understanding of the evolution of chimeric transcripts in eukaryotes and contributes to the analysis of 3D genome conformational changes and the functional role of chimeras in the etiopathogenesis of cancers and other complex diseases.

A Chromosome-Scale Reference Assembly of a Tibetan Loach, Triplophysa siluroides.

Cobitoidea is one of the two superfamilies in Cypriniformes; however, few genomes have been sequenced for Cobitoidea fishes. Here, we obtained a total of 252.90 Gb of short Illumina reads and 31.60 Gb of long PacBio Sequel reads, representing approximate genome coverage of 256× and 50×, respectively. The final assembled genome is about 583.47 Mb with contig N50 sizes of 2.87 Mb, which accounts for 91.44% of the estimated genome size of 638.07 Mb. Using Hi-C–based chromatin contact maps, 99.31% of the genome assembly was placed into 25 chromosomes, and the N50 is 22.3 Mb. The gene annotation completeness was evaluated by BUSCO, and 2,470 of the 2,586 conserved genes (95.5%) could be found in our assembly. Repetitive elements were calculated to reach 33.08% of the whole genome. Moreover, we identified 25,406 protein-coding genes, of which 92.59% have been functionally annotated. This genome assembly will be a valuable genomic resource to understand the biology of the Tibetan loaches and will also set a stage for comparative analysis of the classification, diversification, and adaptation of fishes in Cobitoidea.

Multivariate genome-wide association study of rapid automatised naming and rapid alternating stimulus in Hispanic American and African–American youth

BackgroundRapid automatised naming (RAN) and rapid alternating stimulus (RAS) are reliable predictors of reading disability. The underlying biology of reading disability is poorly understood. However, the high correlation among RAN,...

Finding Nemo's Genes: A chromosome-scale reference assembly of the genome of the orange clownfish Amphiprion percula.

The iconic orange clownfish, Amphiprion percula, is a model organism for studying the ecology and evolution of reef fishes, including patterns of population connectivity, sex change, social organization, habitat selection and adaptation to climate change. Notably, the orange clownfish is the only reef fish for which a complete larval dispersal kernel has been established and was the first fish species for which it was demonstrated that antipredator responses of reef fishes could be impaired by ocean acidification. Despite its importance, molecular resources for this species remain scarce and until now it lacked a reference genome assembly. Here, we present a de novo chromosome‐scale assembly of the genome of the orange clownfish Amphiprion percula. We utilized single‐molecule real‐time sequencing technology from Pacific Biosciences to produce an initial polished assembly comprised of 1,414 contigs, with a contig N50 length of 1.86 Mb. Using Hi‐C‐based chromatin contact maps, 98% of the genome assembly were placed into 24 chromosomes, resulting in a final assembly of 908.8 Mb in length with contig and scaffold N50s of 3.12 and 38.4 Mb, respectively. This makes it one of the most contiguous and complete fish genome assemblies currently available. The genome was annotated with 26,597 protein‐coding genes and contains 96% of the core set of conserved actinopterygian orthologs. The availability of this reference genome assembly as a community resource will further strengthen the role of the orange clownfish as a model species for research on the ecology and evolution of reef fishes.

GenomeDISCO: a concordance score for chromosome conformation capture experiments using random walks on contact map graphs.

The three-dimensional organization of chromatin plays a critical role in gene regulation and disease. High-throughput chromosome conformation capture experiments such as Hi-C are used to obtain genome-wide maps of three-dimensional chromatin contacts. However, robust estimation of data quality and systematic comparison of these contact maps is challenging due to the multi-scale, hierarchical structure of chromatin contacts and the resulting properties of experimental noise in the data. Measuring concordance of contact maps is important for assessing reproducibility of replicate experiments and for modeling variation between different cellular contexts. We introduce a concordance measure called DIfferences between Smoothed COntact maps (GenomeDISCO) for assessing the similarity of a pair of contact maps obtained from chromosome conformation capture experiments. The key idea is to smooth contact maps using random walks on the contact map graph, before estimating concordance. We use simulated datasets to benchmark GenomeDISCO's sensitivity to different types of noise that affect chromatin contact maps. When applied to a large collection of Hi-C datasets, GenomeDISCO accurately distinguishes biological replicates from samples obtained from different cell types. GenomeDISCO also generalizes to other chromosome conformation capture assays, such as HiChIP. Software implementing GenomeDISCO is available at https://github.com/kundajelab/genomedisco. Supplementary data are available at Bioinformatics online.

High-Resolution Locus-Specific Mapping of Chromatin Contacts using Two-Photon Photoactivated DNA Cross-Linking

Spatial organization of the genome remains an interesting and not fully understood area of nuclear architecture and gene regulation. Recently, there have been many technological and methodological developments towards this end from both imaging and genomic perspectives. Here we present a novel method to examine genomic contacts in vivo near a specific locus or nuclear region of interest. Using 3D localized two-photon excitation and a photoactivatable DNA crosslinker, the chromatin within a femtoliter volume around the region of interest can be labeled with an affinity tag. By carrying out this process on many cells using an automated microscope, we can then isolate the genomic DNA and pulldown the crosslinked DNA. While several DNA cross-linkers may be suitable for this method, we have initially focused on psoralen based compounds which are easily UV or two-photon photoactivated to form inter-strand DNA crosslinks preferentially at 5'-TpA dinucleotides in the genome. For photophysical optimization of the method, we use fluorescently labeled genomic loci where 200 copies of a transgene have been integrated at a single locus in U2OS cells. The DNA is extracted and purified using an affinity tag pull-down and the efficiency of crosslinking is quantified via qPCR. After the optimal photoactivation parameters are determined, the genomic locus will be irradiated and the crosslinked DNA extracted and sequenced as a proof-of-principle experiment. The long-term goal is to create a new method to bioinformatically map chromatin fragments at a nuclear region of interest, which can be performed before and after gene activation for any gene of interest.

Convergence of topological domain boundaries, insulators, and polytene interbands revealed by high-resolution mapping of chromatin contacts in the early Drosophila melanogaster embryo.

High-throughput assays of three-dimensional interactions of chromosomes have shed considerable light on the structure of animal chromatin. Despite this progress, the precise physical nature of observed structures and the forces that govern their establishment remain poorly understood. Here we present high resolution Hi-C data from early Drosophila embryos. We demonstrate that boundaries between topological domains of various sizes map to DNA elements that resemble classical insulator elements: short genomic regions sensitive to DNase digestion that are strongly bound by known insulator proteins and are frequently located between divergent promoters. Further, we show a striking correspondence between these elements and the locations of mapped polytene interband regions. We believe it is likely this relationship between insulators, topological boundaries, and polytene interbands extends across the genome, and we therefore propose a model in which decompaction of boundary-insulator-interband regions drives the organization of interphase chromosomes by creating stable physical separation between adjacent domains.