TAD fusion score: discovery and ranking the contribution of deletions to genome structure

TAD border deletion at the Kit locus causes tissue-specific ectopic activation of a neighboring gene

Topologically associated domains (TADs) restrict promoter-enhancer interactions, thereby maintaining the spatiotemporal pattern of gene activity. However, rearrangements of the TADs boundaries do not always lead to significant changes in the activity pattern. Here, we investigated the consequences of the TAD boundaries deletion on the expression of developmentally important genes encoding tyrosine kinase receptors: Kit, Kdr, Pdgfra. We used genome editing in mice to delete the TADs boundaries at the Kit locus and characterized chromatin folding and gene expression in pure cultures of fibroblasts, mast cells, and melanocytes. We found that although Kit is highly active in both mast cells and melanocytes, deletion of the TAD boundary between the Kit and Kdr genes results in ectopic activation only in melanocytes. Thus, the epigenetic landscape, namely the mutual arrangement of enhancers and actively transcribing genes, is important for predicting the consequences of the TAD boundaries removal. We also found that mice without a TAD border between the Kit and Kdr genes have a phenotypic manifestation of the mutation - a lighter coloration. Thus, the data obtained shed light on the principles of interaction between the 3D chromatin organization and epigenetic marks in the regulation of gene activity.

Evolutionary analysis of gene ages across TADs associates chromatin topology with whole-genome duplications

Topologically associated domains (TADs) are interaction subnetworks of chromosomal regions in 3D genomes. TAD boundaries frequently coincide with genome breaks while boundary deletion is under negative selection, suggesting that TADs may facilitate genome rearrangements and evolution. We show that genes co-localize by evolutionary age in humans and mice, resulting in TADs having different proportions of younger and older genes. We observe a major transition in the age co-localization patterns between the genes born during vertebrate whole-genome duplications (WGDs) or before and those born afterward. We also find that genes recently duplicated in primates and rodents are more frequently essential when they are located in old-enriched TADs and interact with genes that last duplicated during the WGD. Therefore, the evolutionary relevance of recent genes may increase when located in TADs with established regulatory networks. Our data suggest that TADs could play a role in organizing ancestral functions and evolutionary novelty.

Haplotype-resolved 3D chromatin architecture of the hybrid pig

In diploid mammals, allele-specific three-dimensional (3D) genome architecture may lead to imbalanced gene expression. Through ultradeep in situ Hi-C sequencing of three representative somatic tissues (liver, skeletal muscle, and brain) from hybrid pigs generated by reciprocal crosses of phenotypically and physiologically divergent Berkshire and Tibetan pigs, we uncover extensive chromatin reorganization between homologous chromosomes across multiple scales. Haplotype-based interrogation of multi-omic data revealed the tissue dependence of 3D chromatin conformation, suggesting that parent-of-origin-specific conformation may drive gene imprinting. We quantify the effects of genetic variations and histone modifications on allelic differences of long-range promoter-enhancer contacts, which likely contribute to the phenotypic differences between the parental pig breeds. We also observe the fine structure of somatically paired homologous chromosomes in the pig genome, which has a functional implication genome-wide. This work illustrates how allele-specific chromatin architecture facilitates concomitant shifts in allele-biased gene expression, as well as the possible consequential phenotypic changes in mammals.

Three-dimensional genome structure and function

Linear DNA undergoes a series of compression and folding events, forming various three-dimensional (3D) structural units in mammalian cells, including chromosomal territory, compartment, topologically associating domain, and chromatin loop. These structures play crucial roles in regulating gene expression, cell differentiation, and disease progression. Deciphering the principles underlying 3D genome folding and the molecular mechanisms governing cell fate determination remains a challenge. With advancements in high-throughput sequencing and imaging techniques, the hierarchical organization and functional roles of higher-order chromatin structures have been gradually illuminated. This review systematically discussed the structural hierarchy of the 3D genome, the effects and mechanisms of cis-regulatory elements interaction in the 3D genome for regulating spatiotemporally specific gene expression, the roles and mechanisms of dynamic changes in 3D chromatin conformation during embryonic development, and the pathological mechanisms of diseases such as congenital developmental abnormalities and cancer, which are attributed to alterations in 3D genome organization and aberrations in key structural proteins. Finally, prospects were made for the research about 3D genome structure, function, and genetic intervention, and the roles in disease development, prevention, and treatment, which may offer some clues for precise diagnosis and treatment of related diseases.

Assessing chromatin relocalization in 3D using the patient rule induction method

Three-dimensional (3D) genome architecture is critical for numerous cellular processes, including transcription, while certain conformation-driven structural alterations are frequently oncogenic. Inferring 3D chromatin configurations has been advanced by the emergence of chromatin conformation capture assays, notably Hi-C, and attendant 3D reconstruction algorithms. These have enhanced understanding of chromatin spatial organization and afforded numerous downstream biological insights. Until recently, comparisons of 3D reconstructions between conditions and/or cell types were limited to prescribed structural features. However, multiMDS, a pioneering approach developed by Rieber and Mahony (2019). that performs joint reconstruction and alignment, enables quantification of all locus-specific differences between paired Hi-C data sets. By subsequently mapping these differences to the linear (1D) genome the identification of relocalization regions is facilitated through the use of peak calling in conjunction with continuous wavelet transformation. Here, we seek to refine this approach by performing the search for significant relocalization regions in terms of the 3D structures themselves, thereby retaining the benefits of 3D reconstruction and avoiding limitations associated with the 1D perspective. The search for (extreme) relocalization regions is conducted using the patient rule induction method (PRIM). Considerations surrounding orienting structures with respect to compartmental and principal component axes are discussed, as are approaches to inference and reconstruction accuracy assessment. The illustration makes recourse to comparisons between four different cell types.

Function and Evolution of the Loop Extrusion Machinery in Animals

Structural maintenance of chromosomes (SMC) complexes are essential proteins found in genomes of all cellular organisms. Essential functions of these proteins, such as mitotic chromosome formation and sister chromatid cohesion, were discovered a long time ago. Recent advances in chromatin biology showed that SMC proteins are involved in many other genomic processes, acting as active motors extruding DNA, which leads to the formation of chromatin loops. Some loops formed by SMC proteins are highly cell type and developmental stage specific, such as SMC-mediated DNA loops required for VDJ recombination in B-cell progenitors, or dosage compensation in Caenorhabditis elegans and X-chromosome inactivation in mice. In this review, we focus on the extrusion-based mechanisms that are common for multiple cell types and species. We will first describe an anatomy of SMC complexes and their accessory proteins. Next, we provide biochemical details of the extrusion process. We follow this by the sections describing the role of SMC complexes in gene regulation, DNA repair, and chromatin topology.

Transcriptional and functional consequences of alterations to MEF2C and its topological organization in neuronal models

Point mutations and structural variants that directly disrupt the coding sequence of MEF2C have been associated with a spectrum of neurodevelopmental disorders (NDDs). However, the impact of MEF2C haploinsufficiency on neurodevelopmental pathways and synaptic processes is not well understood, nor are the complex mechanisms that govern its regulation. To explore the functional changes associated with structural variants that alter MEF2C expression and/or regulation, we generated an allelic series of 204 isogenic human induced pluripotent stem cell (hiPSC)-derived neural stem cells and glutamatergic induced neurons. These neuronal models harbored CRISPR-engineered mutations that involved direct deletion of MEF2C or deletion of the boundary points for topologically associating domains (TADs) and chromatin loops encompassing MEF2C. Systematic profiling of mutation-specific alterations, contrasted to unedited controls that were exposed to the same guide RNAs for each edit, revealed that deletion of MEF2C caused differential expression of genes associated with neurodevelopmental pathways and synaptic function. We also discovered significant reduction in synaptic activity measured by multielectrode arrays (MEAs) in neuronal cells. By contrast, we observed robust buffering against MEF2C regulatory disruption following deletion of a distal 5q14.3 TAD and loop boundary, whereas homozygous loss of a proximal loop boundary resulted in down-regulation of MEF2C expression and reduced electrophysiological activity on MEA that was comparable to direct gene disruption. Collectively, these studies highlight the considerable functional impact of MEF2C deletion in neuronal cells and systematically characterize the complex interactions that challenge a priori predictions of regulatory consequences from structural variants that disrupt three-dimensional genome organization.

The 3D architecture of the pepper genome and its relationship to function and evolution

The organization of chromatin into self-interacting domains is universal among eukaryotic genomes, though how and why they form varies considerably. Here we report a chromosome-scale reference genome assembly of pepper (Capsicum annuum) and explore its 3D organization through integrating high-resolution Hi-C maps with epigenomic, transcriptomic, and genetic variation data. Chromatin folding domains in pepper are as prominent as TADs in mammals but exhibit unique characteristics. They tend to coincide with heterochromatic regions enriched with retrotransposons and are frequently embedded in loops, which may correlate with transcription factories. Their boundaries are hotspots for chromosome rearrangements but are otherwise depleted for genetic variation. While chromatin conformation broadly affects transcription variance, it does not predict differential gene expression between tissues. Our results suggest that pepper genome organization is explained by a model of heterochromatin-driven folding promoted by transcription factories and that such spatial architecture is under structural and functional constraints.

The organization of chromatin into self-interacting domains is universal among eukaryotic genomes. Here, the authors report a reference-grade pepper genome assembly and use this reference to help describe the relationship among 3D chromatin conformation, chromatin function, and gene expression.

Dynamic Interplay between Structural Variations and 3D Genome Organization in Pancreatic Cancer

Structural variations (SVs) are the greatest source of variations in the genome and can lead to oncogenesis. However, the identification and interpretation of SVs in human cancer remain technologically challenging. Here, long-read sequencing is first employed to depict the signatures of structural variations in carcinogenesis of human pancreatic ductal epithelium. Then widespread reprogramming of the 3D chromatin architecture is revealed by an in situ Hi-C technique. Integrative analyses indicate that the distribution pattern of SVs among the 3D genome is highly cell-type specific and the bulk remodeling effects of SVs in the chromatin organization partly depend on intercellular genomic heterogeneity. Meanwhile, contact domains tend to minimize these disrupting effects of SVs within local adjacent genomic regions to maintain overall stability. Notably, complex genomic rearrangements involving two key driver genes CDKN2A and SMAD4 are identified, and their influence on the expression of oncogenes MIR31HG, MYO5B, etc., are further elucidated from both a linear view and 3D perspective. Overall, this work provides a genome-wide resource and highlights the impact, complexity, and dynamicity of the interplay between structural variations and high-order chromatin organization, which expands the current understanding of the pathogenesis of SVs in human cancer.

Computational and experimental methods for classifying variants of unknown clinical significance

The increase in sequencing capacity, reduction in costs, and national and international coordinated efforts have led to the widespread introduction of next-generation sequencing (NGS) technologies in patient care. More generally, human genetics and genomic medicine are gaining importance for more and more patients. Some communities are already discussing the prospect of sequencing each individual's genome at time of birth. Together with digital health records, this shall enable individualized treatments and preventive measures, so-called precision medicine. A central step in this process is the identification of disease causal mutations or variant combinations that make us more susceptible for diseases. Although various technological advances have improved the identification of genetic alterations, the interpretation and ranking of the identified variants remains a major challenge. Based on our knowledge of molecular processes or previously identified disease variants, we can identify potentially functional genetic variants and, using different lines of evidence, we are sometimes able to demonstrate their pathogenicity directly. However, the vast majority of variants are classified as variants of uncertain clinical significance (VUSs) with not enough experimental evidence to determine their pathogenicity. In these cases, computational methods may be used to improve the prioritization and an increasing toolbox of experimental methods is emerging that can be used to assay the molecular effects of VUSs. Here, we discuss how computational and experimental methods can be used to create catalogs of variant effects for a variety of molecular and cellular phenotypes. We discuss the prospects of integrating large-scale functional data with machine learning and clinical knowledge for the development of accurate pathogenicity predictions for clinical applications.

TADreg: a versatile regression framework for TAD identification, differential analysis and rearranged 3D genome prediction

Background/Aim

In higher eukaryotes, the three-dimensional (3D) organization of the genome is intimately related to numerous key biological functions including gene expression, DNA repair and DNA replication regulations. Alteration of 3D organization, in particular topologically associating domains (TADs), is detrimental to the organism and can give rise to a broad range of diseases such as cancers.

Methods

Here, we propose a versatile regression framework which not only identifies TADs in a fast and accurate manner, but also detects differential TAD borders across conditions for which few methods exist, and predicts 3D genome reorganization after chromosomal rearrangement. Moreover, the framework is biologically meaningful, has an intuitive interpretation and is easy to visualize.

Result and conclusion

The novel regression ranks among top TAD callers. Moreover, it identifies new features of the genome we called TAD facilitators, and that are enriched with specific transcription factors. It also unveils the importance of cell-type specific transcription factors in establishing novel TAD borders during neuronal differentiation. Lastly, it compares favorably with the state-of-the-art method for predicting rearranged 3D genome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04614-0.

A framework to score the effects of structural variants in health and disease

While technological advances improved the identification of structural variants (SVs) in the human genome, their interpretation remains challenging. Several methods utilize individual mechanistic principles like the deletion of coding sequence or 3D genome architecture disruptions. However, a comprehensive tool using the broad spectrum of available annotations is missing. Here, we describe CADD-SV, a method to retrieve and integrate a wide set of annotations to predict the effects of SVs. Previously, supervised learning approaches were limited due to a small number and biased set of annotated pathogenic or benign SVs. We overcome this problem by using a surrogate training-objective, the Combined Annotation Dependent Depletion (CADD) of functional variants. We use human and chimpanzee derived SVs as proxy-neutral and contrast them with matched simulated variants as proxy-deleterious, an approach that has proven powerful for short sequence variants. Our tool computes summary statistics over diverse variant annotations and uses random forest models to prioritize deleterious structural variants. The resulting CADD-SV scores correlate with known pathogenic and rare population variants. We further show that we can prioritize somatic cancer variants as well as noncoding variants known to affect gene expression. We provide a website and offline-scoring tool for easy application of CADD-SV.

High-throughput chromosome conformation capture-based analysis of higher-order chromatin structure in nasopharyngeal carcinoma

Background

Firstly, we aimed to compare the differences of higher-order chromatin structure between nasopharyngeal carcinoma (NPC) and normal nasopharyngeal tissues. The second objective was to analyze the specific chromatin interaction site of NPC and the NPC-related genes regulated by this interaction site.

Methods

We included 6 NPC patients and 6 healthy controls to obtain the sequencing results of highest-throughput chromosome conformation capture (Hi-C) technique, followed by further analysis of the specific chromatin interaction sites in NPC.

Results

We found an abnormal ultra-long distance interaction site on the chromosome 7p in the CNE210 sample, which was caused by a fusion gene SEPT7P2-PSPH. Additionally, a significant interaction site between chromosome 8q and 3p was revealed in the samples CNE25, CNE29, and CNE211, which was the interaction between 1.5 kb downstream of ASAP1 and 0.8 kb upstream of CTNNB1 gene. Further quantitative polymerase chain reaction (qPCR) revealed that ASAP1 and CTNNB1 genes were more highly expressed in CNE25, CNE29, and CNE211 than in the Np group, preliminarily indicating that this interaction site was likely related to the high expression of ASAP1 and CTNNB1 in NPC.

Conclusions

Through Hi-C analysis, we analyzed the specific chromatin interaction sites associated with NPC, and found the chromosomal translocation and chromatin interaction sites associated with NPC based on statistical analysis. This study has certain guiding significance for in-depth study of the mechanism of NPC occurrence and development.

Predicting pathogenic non-coding SVs disrupting the 3D genome in 1646 whole cancer genomes using multiple instance learning

Over the past years, large consortia have been established to fuel the sequencing of whole genomes of many cancer patients. Despite the increased abundance in tools to study the impact of SNVs, non-coding SVs have been largely ignored in these data. Here, we introduce svMIL2, an improved version of our Multiple Instance Learning-based method to study the effect of somatic non-coding SVs disrupting boundaries of TADs and CTCF loops in 1646 cancer genomes. We demonstrate that svMIL2 predicts pathogenic non-coding SVs with an average AUC of 0.86 across 12 cancer types, and identifies non-coding SVs affecting well-known driver genes. The disruption of active (super) enhancers in open chromatin regions appears to be a common mechanism by which non-coding SVs exert their pathogenicity. Finally, our results reveal that the contribution of pathogenic non-coding SVs as opposed to driver SNVs may highly vary between cancers, with notably high numbers of genes being disrupted by pathogenic non-coding SVs in ovarian and pancreatic cancer. Taken together, our machine learning method offers a potent way to prioritize putatively pathogenic non-coding SVs and leverage non-coding SVs to identify driver genes. Moreover, our analysis of 1646 cancer genomes demonstrates the importance of including non-coding SVs in cancer diagnostics.

Hi-C as a molecular rangefinder to examine genomic rearrangements

The mammalian genome is highly packed into the nucleus. Over the past decade, the development of Hi-C has contributed significantly to our understanding of the three-dimensional (3D) chromatin structure, uncovering the principles and functions of higher-order chromatin organizations. Recent studies have repositioned its property in spatial proximity measurement to address challenging problems in genome analyses including genome assembly, haplotype phasing, and the detection of genomic rearrangements. In particular, the power of Hi-C in detecting large-scale structural variations (SVs) in the cancer genome has been demonstrated, which is challenging to be addressed solely with short-read-based whole-genome sequencing analyses. In this review, we first provide a comprehensive view of Hi-C as an intuitive and effective SV detection tool. Then, we introduce recently developed bioinformatics tools utilizing Hi-C to investigate genomic rearrangements. Finally, we discuss the potential application of single-cell Hi-C to address the heterogeneity of genomic rearrangements and sub-population identification in the cancer genome.

Topologically associating domains and their role in the evolution of genome structure and function in Drosophila

Topologically associating domains (TADs) were recently identified as fundamental units of three-dimensional eukaryotic genomic organization, although our knowledge of the influence of TADs on genome evolution remains preliminary. To study the molecular evolution of TADs in Drosophila species, we constructed a new reference-grade genome assembly and accompanying high-resolution TAD map for D. pseudoobscura Comparison of D. pseudoobscura and D. melanogaster, which are separated by ∼49 million years of divergence, showed that ∼30%-40% of their genomes retain conserved TADs. Comparative genomic analysis of 17 Drosophila species revealed that chromosomal rearrangement breakpoints are enriched at TAD boundaries but depleted within TADs. Additionally, genes within conserved TADs show lower expression divergence than those located in nonconserved TADs. Furthermore, we found that a substantial proportion of long genes (>50 kbp) in D. melanogaster (42%) and D. pseudoobscura (26%) constitute their own TADs, implying transcript structure may be one of the deterministic factors for TAD formation. By using structural variants (SVs) identified from 14 D. melanogaster strains, its three closest sibling species from the D. simulans species complex, and two obscura clade species, we uncovered evidence of selection acting on SVs at TAD boundaries, but with the nature of selection differing between SV types. Deletions are depleted at TAD boundaries in both divergent and polymorphic SVs, suggesting purifying selection, whereas divergent tandem duplications are enriched at TAD boundaries relative to polymorphism, suggesting they are adaptive. Our findings highlight how important TADs are in shaping the acquisition and retention of structural mutations that fundamentally alter genome organization.

svMIL: predicting the pathogenic effect of TAD boundary-disrupting somatic structural variants through multiple instance learning

Motivation

Despite the fact that structural variants (SVs) play an important role in cancer, methods to predict their effect, especially for SVs in non-coding regions, are lacking, leaving them often overlooked in the clinic. Non-coding SVs may disrupt the boundaries of Topologically Associated Domains (TADs), thereby affecting interactions between genes and regulatory elements such as enhancers. However, it is not known when such alterations are pathogenic. Although machine learning techniques are a promising solution to answer this question, representing the large number of interactions that an SV can disrupt in a single feature matrix is not trivial.

Results

We introduce svMIL: a method to predict pathogenic TAD boundary-disrupting SV effects based on multiple instance learning, which circumvents the need for a traditional feature matrix by grouping SVs into bags that can contain any number of disruptions. We demonstrate that svMIL can predict SV pathogenicity, measured through same-sample gene expression aberration, for various cancer types. In addition, our approach reveals that somatic pathogenic SVs alter different regulatory interactions than somatic non-pathogenic SVs and germline SVs.

Availability and implementation

All code for svMIL is publicly available on GitHub: https://github.com/UMCUGenetics/svMIL.

Supplementary information

Supplementary data are available at Bioinformatics online.

CHESS enables quantitative comparison of chromatin contact data and automatic feature extraction

Dynamic changes in the three-dimensional (3D) organization of chromatin are associated with central biological processes, such as transcription, replication and development. Therefore, the comprehensive identification and quantification of these changes is fundamental to understanding of evolutionary and regulatory mechanisms. Here, we present Comparison of Hi-C Experiments using Structural Similarity (CHESS), an algorithm for the comparison of chromatin contact maps and automatic differential feature extraction. We demonstrate the robustness of CHESS to experimental variability and showcase its biological applications on (1) interspecies comparisons of syntenic regions in human and mouse models; (2) intraspecies identification of conformational changes in Zelda-depleted Drosophila embryos; (3) patient-specific aberrant chromatin conformation in a diffuse large B-cell lymphoma sample; and (4) the systematic identification of chromatin contact differences in high-resolution Capture-C data. In summary, CHESS is a computationally efficient method for the comparison and classification of changes in chromatin contact data.

Single-cell strand sequencing of a macaque genome reveals multiple nested inversions and breakpoint reuse during primate evolution

Rhesus macaque is an Old World monkey that shared a common ancestor with human ∼25 Myr ago and is an important animal model for human disease studies. A deep understanding of its genetics is therefore required for both biomedical and evolutionary studies. Among structural variants, inversions represent a driving force in speciation and play an important role in disease predisposition. Here we generated a genome-wide map of inversions between human and macaque, combining single-cell strand sequencing with cytogenetics. We identified 375 total inversions between 859 bp and 92 Mbp, increasing by eightfold the number of previously reported inversions. Among these, 19 inversions flanked by segmental duplications overlap with recurrent copy number variants associated with neurocognitive disorders. Evolutionary analyses show that in 17 out of 19 cases, the Hominidae orientation of these disease-associated regions is always derived. This suggests that duplicated sequences likely played a fundamental role in generating inversions in humans and great apes, creating architectures that nowadays predispose these regions to disease-associated genetic instability. Finally, we identified 861 genes mapping at 156 inversions breakpoints, with some showing evidence of differential expression in human and macaque cell lines, thus highlighting candidates that might have contributed to the evolution of species-specific features. This study depicts the most accurate fine-scale map of inversions between human and macaque using a two-pronged integrative approach, such as single-cell strand sequencing and cytogenetics, and represents a valuable resource toward understanding of the biology and evolution of primate species.

Identification of Structural Variation in Chimpanzees Using Optical Mapping and Nanopore Sequencing

Recent efforts to comprehensively characterize great ape genetic diversity using short-read sequencing and single-nucleotide variants have led to important discoveries related to selection within species, demographic history, and lineage-specific traits. Structural variants (SVs), including deletions and inversions, comprise a larger proportion of genetic differences between and within species, making them an important yet understudied source of trait divergence. Here, we used a combination of long-read and -range sequencing approaches to characterize the structural variant landscape of two additional Pan troglodytes verus individuals, one of whom carries 13% admixture from Pan troglodytes troglodytes. We performed optical mapping of both individuals followed by nanopore sequencing of one individual. Filtering for larger variants (>10 kbp) and combined with genotyping of SVs using short-read data from the Great Ape Genome Project, we identified 425 deletions and 59 inversions, of which 88 and 36, respectively, were novel. Compared with gene expression in humans, we found a significant enrichment of chimpanzee genes with differential expression in lymphoblastoid cell lines and induced pluripotent stem cells, both within deletions and near inversion breakpoints. We examined chromatin-conformation maps from human and chimpanzee using these same cell types and observed alterations in genomic interactions at SV breakpoints. Finally, we focused on 56 genes impacted by SVs in >90% of chimpanzees and absent in humans and gorillas, which may contribute to chimpanzee-specific features. Sequencing a greater set of individuals from diverse subspecies will be critical to establish the complete landscape of genetic variation in chimpanzees.

The effects of common structural variants on 3D chromatin structure

Background

Three-dimensional spatial organization of chromosomes is defined by highly self-interacting regions 0.1–1 Mb in size termed Topological Associating Domains (TADs). Genetic factors that explain dynamic variation in TAD structure are not understood. We hypothesize that common structural variation (SV) in the human population can disrupt regulatory sequences and thereby influence TAD formation. To determine the effects of SVs on 3D chromatin organization, we performed chromosome conformation capture sequencing (Hi-C) of lymphoblastoid cell lines from 19 subjects for which SVs had been previously characterized in the 1000 genomes project. We tested the effects of common deletion polymorphisms on TAD structure by linear regression analysis of nearby quantitative chromatin interactions (contacts) within 240 kb of the deletion, and we specifically tested the hypothesis that deletions at TAD boundaries (TBs) could result in large-scale alterations in chromatin conformation.

Results

Large (> 10 kb) deletions had significant effects on long-range chromatin interactions. Deletions were associated with increased contacts that span the deleted region and this effect was driven by large deletions that were not located within a TAD boundary (nonTB). Some deletions at TBs, including a 80 kb deletion of the genes CFHR1 and CFHR3, had detectable effects on chromatin contacts. However for TB deletions overall, we did not detect a pattern of effects that was consistent in magnitude or direction. Large inversions in the population had a distinguishable signature characterized by a rearrangement of contacts that span its breakpoints.

Conclusions

Our study demonstrates that common SVs in the population impact long-range chromatin structure, and deletions and inversions have distinct signatures. However, the effects that we observe are subtle and variable between loci. Genome-wide analysis of chromatin conformation in large cohorts will be needed to quantify the influence of common SVs on chromatin structure.

TAD fusion score: discovery and ranking the contribution of deletions to genome structure

Deletions that fuse two adjacent topologically associating domains (TADs) can cause severe developmental disorders. We provide a formal method to quantify deletions based on their potential disruption of the three-dimensional genome structure, denoted as the TAD fusion score. Furthermore, we show that deletions that cause TAD fusion are rare and under negative selection in the general population. Finally, we show that our method correctly gives higher scores to deletions reported to cause various disorders, including developmental disorders and cancer, in comparison to the deletions reported in the 1000 Genomes Project. The TAD fusion score tool is publicly available at https://github.com/HormozdiariLab/TAD-fusion-score .