Spatial chromatin architecture alteration by structural variations in human genomes at the population scale

Multi-omics analysis in primary T cells elucidates mechanisms behind disease-associated genetic loci

BACKGROUND

Genome-wide association studies (GWAS) have uncovered the genetic basis behind many diseases and conditions. However, most of these genetic loci affect regulatory regions, making the interpretation challenging. Chromatin conformation has a fundamental role in gene regulation and is frequently used to associate potential target genes to regulatory regions. However, previous studies mostly used small sample sizes and immortalized cell lines instead of primary cells.

RESULTS

Here we present the most extensive dataset of chromatin conformation with matching gene expression and chromatin accessibility from primary CD4+ and CD8+ T cells to date, isolated from psoriatic arthritis patients and healthy controls. We generated 108 Hi-C libraries (49 billion reads), 128 RNA-seq libraries and 126 ATAC-seq libraries. These data enhance our understanding of the mechanisms by which GWAS variants impact gene regulation, revealing how genetic variation alters chromatin accessibility and structure in primary cells at an unprecedented scale. We refine the mapping of GWAS loci to implicated regulatory elements, such as CTCF binding sites and other enhancer elements, aiding gene assignment. We uncover BCL2L11 as the probable causal gene within the rheumatoid arthritis (RA) locus rs13396472, despite the GWAS variants' intronic positioning relative to ACOXL, and we identify mechanisms involving SESN3 dysregulation in the RA locus rs4409785.

CONCLUSIONS

Given these genes' significant role in T cell development and maturation, our work deepens our comprehension of autoimmune disease pathogenesis, suggesting potential treatment targets. In addition, our dataset provides a valuable resource for the investigation of immune-mediated diseases and gene regulatory mechanisms.

L-type calcium channels and neuropsychiatric diseases: Insights into genetic risk variant-associated genomic regulation and impact on brain development

Recent human genetic studies have linked a variety of genetic variants in the CACNA1C and CACNA1D genes to neuropsychiatric and neurodevelopmental disorders. This is not surprising given the work from multiple laboratories using cell and animal models that have established that Cav1.2 and Cav1.3 L-type calcium channels (LTCCs), encoded by CACNA1C and CACNA1D, respectively, play a key role in various neuronal processes that are essential for normal brain development, connectivity, and experience-dependent plasticity. Of the multiple genetic aberrations reported, genome-wide association studies (GWASs) have identified multiple single nucleotide polymorphisms (SNPs) in CACNA1C and CACNA1D that are present within introns, in accordance with the growing body of literature establishing that large numbers of SNPs associated with complex diseases, including neuropsychiatric disorders, are present within non-coding regions. How these intronic SNPs affect gene expression has remained a question. Here, we review recent studies that are beginning to shed light on how neuropsychiatric-linked non-coding genetic variants can impact gene expression via regulation at the genomic and chromatin levels. We additionally review recent studies that are uncovering how altered calcium signaling through LTCCs impact some of the neuronal developmental processes, such as neurogenesis, neuron migration, and neuron differentiation. Together, the described changes in genomic regulation and disruptions in neurodevelopment provide possible mechanisms by which genetic variants of LTCC genes contribute to neuropsychiatric and neurodevelopmental disorders.

cudaMMC: GPU-enhanced multiscale Monte Carlo chromatin 3D modelling

MOTIVATION

Investigating the 3D structure of chromatin provides new insights into transcriptional regulation. With the evolution of 3C next-generation sequencing methods like ChiA-PET and Hi-C, the surge in data volume has highlighted the need for more efficient chromatin spatial modelling algorithms. This study introduces the cudaMMC method, based on the Simulated Annealing Monte Carlo approach and enhanced by GPU-accelerated computing, to efficiently generate ensembles of chromatin 3D structures.

RESULTS

The cudaMMC calculations demonstrate significantly faster performance with better stability compared to our previous method on the same workstation. cudaMMC also substantially reduces the computation time required for generating ensembles of large chromatin models, making it an invaluable tool for studying chromatin spatial conformation.

AVAILABILITY AND IMPLEMENTATION

Open-source software and manual and sample data are freely available on https://github.com/SFGLab/cudaMMC.

Inferring CTCF-binding patterns and anchored loops across human tissues and cell types

CCCTC-binding factor (CTCF) is a transcription regulator with a complex role in gene regulation. The recognition and effects of CTCF on DNA sequences, chromosome barriers, and enhancer blocking are not well understood. Existing computational tools struggle to assess the regulatory potential of CTCF-binding sites and their impact on chromatin loop formation. Here we have developed a deep-learning model, DeepAnchor, to accurately characterize CTCF binding using high-resolution genomic/epigenomic features. This has revealed distinct chromatin and sequence patterns for CTCF-mediated insulation and looping. An optimized implementation of a previous loop model based on DeepAnchor score excels in predicting CTCF-anchored loops. We have established a compendium of CTCF-anchored loops across 52 human tissue/cell types, and this suggests that genomic disruption of these loops could be a general mechanism of disease pathogenesis. These computational models and resources can help investigate how CTCF-mediated cis-regulatory elements shape context-specific gene regulation in cell development and disease progression.

Applications of advanced technologies for detecting genomic structural variation

Chromosomal structural variation (SV) encompasses a heterogenous class of genetic variants that exerts strong influences on human health and disease. Despite their importance, many structural variants (SVs) have remained poorly characterized at even a basic level, a discrepancy predicated upon the technical limitations of prior genomic assays. However, recent advances in genomic technology can identify and localize SVs accurately, opening new questions regarding SV risk factors and their impacts in humans. Here, we first define and classify human SVs and their generative mechanisms, highlighting characteristics leveraged by various SV assays. We next examine the first-ever gapless assembly of the human genome and the technical process of assembling it, which required third-generation sequencing technologies to resolve structurally complex loci. The new portions of that "telomere-to-telomere" and subsequent pangenome assemblies highlight aspects of SV biology likely to develop in the near-term. We consider the strengths and limitations of the most promising new SV technologies and when they or longstanding approaches are best suited to meeting salient goals in the study of human SV in population-scale genomics research, clinical, and public health contexts. It is a watershed time in our understanding of human SV when new approaches are expected to fundamentally change genomic applications.

Evolution of 3D chromatin organization at different scales

Most animal genomes fold in 3D chromatin domains called topologically associated domains (TADs) that facilitate interactions between cis-regulatory elements (CREs) and promoters. Owing to their critical role in the control of developmental gene expression, we explore how TADs have shaped animal evolution. In the light of recent studies that profile TADs in disparate animal lineages, we discuss their phylogenetic distribution and the mechanisms that underlie their formation. We present evidence indicating that TADs are plastic entities composed of genomic strata of different ages: ancient cores are combined with newer regions and brought into extant TADs through genomic rearrangements. We highlight that newly incorporated TAD strata enable the establishment of new CRE-promoter interactions and in turn new expression patterns that can drive phenotypical innovation. We further highlight how subtle changes in chromatin folding may fine-tune the expression levels of developmental genes and hold a potential for evolutionary significance.

Unravelling the tumour genome: The evolutionary and clinical impacts of structural variants in tumourigenesis

Structural variants (SVs) represent a major source of aberration in tumour genomes. Given the diversity in the size and type of SVs present in tumours, the accurate detection and interpretation of SVs in tumours is challenging. New classes of complex structural events in tumours are discovered frequently, and the definitions of the genomic consequences of complex events are constantly being refined. Detailed analyses of short-read whole-genome sequencing (WGS) data from large tumour cohorts facilitate the interrogation of SVs at orders of magnitude greater scale and depth. However, the inherent technical limitations of short-read WGS prevent us from accurately detecting and investigating the impact of all the SVs present in tumours. The expanded use of long-read WGS will be critical for improving the accuracy of SV detection, and in fully resolving complex SV events, both of which are crucial for determining the impact of SVs on tumour progression and clinical outcome. Despite the present limitations, we demonstrate that SVs play an important role in tumourigenesis. In particular, SVs contribute significantly to late-stage tumour development and to intratumoural heterogeneity. The evolutionary trajectories of SVs represent a window into the clonal dynamics in tumours, a comprehensive understanding of which will be vital for influencing patient outcomes in the future. Recent findings have highlighted many clinical applications of SVs in cancer, from early detection to biomarkers for treatment response and prognosis. As the methods to detect and interpret SVs improve, elucidating the full breadth of the complex SV landscape and determining how these events modulate tumour evolution will improve our understanding of cancer biology and our ability to capitalise on the utility of SVs in the clinical management of cancer patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Chromosomal Translocations Detection in Cancer Cells Using Chromosomal Conformation Capture Data

Complex chromosomal rearrangements such as translocations play a critical role in oncogenesis. Translocation detection is vital to decipher their biological role in activating cancer-associated mechanisms. High-throughput chromosomal conformations capture (Hi-C) data have shown promising progress in unveiling the genome variations in a disease condition. Until now, multiple structural data (Hi-C)-based methods are available that can detect translocations in cancer genomes. However, the consistency and specificity of Hi-C-based translocation results still need to be validated with conventional methods. This study used Hi-C data of cancerous cell lines, namely lung cancer (A549), Chronic Myelogenous Leukemia (K562), and Acute Monocytic Leukemia (THP-1), to detect the translocations. The results were cross-validated through whole-genome sequencing (WGS) and paired-read analysis. Moreover, PCR amplification validated the presence of translocated reads in different chromosomes. By integrating different data types, we showed that the results of Hi-C data are as reliable as WGS and can be utilized as an assistive method for detecting translocations in the diseased genome. Our findings support the utility of Hi-C technology to detect the translocations and study their effects on the three-dimensional architecture of the genome in cancer condition.

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.

Identification of Genetic Loci for Sugarcane Leaf Angle at Different Developmental Stages by Genome-Wide Association Study

Sugarcane (Saccharum spp.) is an efficient crop mainly used for sugar and bioethanol production. High yield and high sucrose of sugarcane are always the fundamental demands in sugarcane growth worldwide. Leaf angle and size of sugarcane can be attributed to planting density, which was associated with yield. In this study, we performed genome-wide association studies (GWAS) with a panel of 216 sugarcane core parents and their derived lines (natural population) to determine the genetic basis of leaf angle and key candidate genes with +2, +3, and +4 leaf at the seedling, elongation, and mature stages. A total of 288 significantly associated loci of sugarcane leaf angle at different developmental stages (eight phenotypes) were identified by GWAS with 4,027,298 high-quality SNP markers. Among them, one key locus and 11 loci were identified in all three stages and two stages, respectively. An InDel marker (SNP Ss6A_102766953) linked to narrow leaf angle was obtained. Overall, 4,089 genes were located in the confidence interval of significant loci, among which 3,892 genes were functionally annotated. Finally, 13 core parents and their derivatives tagged with SNPs were selected for marker-assisted selection (MAS). These candidate genes are mainly related to MYB transcription factors, auxin response factors, serine/threonine protein kinases, etc. They are directly or indirectly associated with leaf angle in sugarcane. This research provided a large number of novel genetic resources for the improvement of leaf angles and simultaneously to high yield and high bioethanol production.

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.

3DSNP 2.0: update and expansion of the noncoding genomic variant annotation database

The rapid development of single-molecule long-read sequencing (LRS) and single-cell assay for transposase accessible chromatin sequencing (scATAC-seq) technologies presents both challenges and opportunities for the annotation of noncoding variants. Here, we updated 3DSNP, a comprehensive database for human noncoding variant annotation, to expand its applications to structural variation (SV) and to implement variant annotation down to single-cell resolution. The updates of 3DSNP include (i) annotation of 108 317 SVs from a full spectrum of functions, especially their potential effects on three-dimensional chromatin structures, (ii) evaluation of the accessible chromatin peaks flanking the variants across 126 cell types/subtypes in 15 human fetal tissues and 54 cell types/subtypes in 25 human adult tissues by integrating scATAC-seq data and (iii) expansion of Hi-C data to 49 human cell types. In summary, this version is a significant and comprehensive improvement over the previous version. The 3DSNP v2.0 database is freely available at https://omic.tech/3dsnpv2/.

Expanding the conservation genomics toolbox: Incorporating structural variants to enhance genomic studies for species of conservation concern

Structural variants (SVs) are large rearrangements (>50 bp) within the genome that impact gene function and the content and structure of chromosomes. As a result, SVs are a significant source of functional genomic variation, that is, variation at genomic regions underpinning phenotype differences, that can have large effects on individual and population fitness. While there are increasing opportunities to investigate functional genomic variation in threatened species via single nucleotide polymorphism (SNP) data sets, SVs remain understudied despite their potential influence on fitness traits of conservation interest. In this future-focused Opinion, we contend that characterizing SVs offers the conservation genomics community an exciting opportunity to complement SNP-based approaches to enhance species recovery. We also leverage the existing literature-predominantly in human health, agriculture and ecoevolutionary biology-to identify approaches for readily characterizing SVs and consider how integrating these into the conservation genomics toolbox may transform the way we manage some of the world's most threatened species.

From DNA human sequence to the chromatin higher order organisation and its biological meaning: Using biomolecular interaction networks to understand the influence of structural variation on spatial genome organisation and its functional effect

The three-dimensional structure of the human genome has been proven to have a significant functional impact on gene expression. The high-order spatial chromatin is organised first by looping mediated by multiple protein factors, and then it is further formed into larger structures of topologically associated domains (TADs) or chromatin contact domains (CCDs), followed by A/B compartments and finally the chromosomal territories (CTs). The genetic variation observed in human population influences the multi-scale structures, posing a question regarding the functional impact of structural variants reflected by the variability of the genes expression patterns. The current methods of evaluating the functional effect include eQTLs analysis which uses statistical testing of influence of variants on spatially close genes. Rarely, non-coding DNA sequence changes are evaluated by their impact on the biomolecular interaction network (BIN) reflecting the cellular interactome that can be analysed by the classical graph-theoretic algorithms. Therefore, in the second part of the review, we introduce the concept of BIN, i.e. a meta-network model of the complete molecular interactome developed by integrating various biological networks. The BIN meta-network model includes DNA-protein binding by the plethora of protein factors as well as chromatin interactions, therefore allowing connection of genomics with the downstream biomolecular processes present in a cell. As an illustration, we scrutinise the chromatin interactions mediated by the CTCF protein detected in a ChIA-PET experiment in the human lymphoblastoid cell line GM12878. In the corresponding BIN meta-network the DNA spatial proximity is represented as a graph model, combined with the Proteins-Interaction Network (PIN) of human proteome using the Gene Association Network (GAN). Furthermore, we enriched the BIN with the signalling and metabolic pathways and Gene Ontology (GO) terms to assert its functional context. Finally, we mapped the Single Nucleotide Polymorphisms (SNPs) from the GWAS studies and identified the chromatin mutational hot-spots associated with a significant enrichment of SNPs related to autoimmune diseases. Afterwards, we mapped Structural Variants (SVs) from healthy individuals of 1000 Genomes Project and identified an interesting example of the missing protein complex associated with protein Q6GYQ0 due to a deletion on chromosome 14. Such an analysis using the meta-network BIN model is therefore helpful in evaluating the influence of genetic variation on spatial organisation of the genome and its functional effect in a cell.

SATB1-mediated chromatin landscape in T cells

The regulatory circuits that define developmental decisions of thymocytes are still incompletely resolved. SATB1 protein is predominantly expressed at the CD4⁺CD8⁺cell stage exerting its broad transcription regulation potential with both activatory and repressive roles. A series of post-translational modifications and the presence of potential SATB1 protein isoforms indicate the complexity of its regulatory potential. The most apparent mechanism of its involvement in gene expression regulation is via the orchestration of long-range chromatin loops between genes and their regulatory elements. Multiple SATB1 perturbations in mice uncovered a link to autoimmune diseases while clinical investigations on cancer research uncovered that SATB1 has a promoting role in several types of cancer and can be used as a prognostic biomarker. SATB1 is a multivalent tissue-specific factor with a broad and yet undetermined regulatory potential. Future investigations on this protein could further uncover T cell-specific regulatory pathways and link them to (patho)physiology.

Characterization of structural variation in Tibetans reveals new evidence of high-altitude adaptation and introgression

BACKGROUND

Structural variation (SV) acts as an essential mutational force shaping the evolution and function of the human genome. However, few studies have examined the role of SVs in high-altitude adaptation and little is known of adaptive introgressed SVs in Tibetans so far.

RESULTS

Here, we generate a comprehensive catalog of SVs in a Chinese Tibetan (n = 15) and Han (n = 10) population using nanopore sequencing technology. Among a total of 38,216 unique SVs in the catalog, 27% are sequence-resolved for the first time. We systematically assess the distribution of these SVs across repeat sequences and functional genomic regions. Through genotyping in additional 276 genomes, we identify 69 Tibetan-Han stratified SVs and 80 candidate adaptive genes. We also discover a few adaptive introgressed SV candidates and provide evidence for a deletion of 335 base pairs at 1p36.32.

CONCLUSIONS

Overall, our results highlight the important role of SVs in the evolutionary processes of Tibetans' adaptation to the Qinghai-Tibet Plateau and provide a valuable resource for future high-altitude adaptation studies.

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.

Predicting Genome Architecture: Challenges and Solutions

Genome architecture plays a pivotal role in gene regulation. The use of high-throughput methods for chromatin profiling and 3-D interaction mapping provide rich experimental data sets describing genome organization and dynamics. These data challenge development of new models and algorithms connecting genome architecture with epigenetic marks. In this review, we describe how chromatin architecture could be reconstructed from epigenetic data using biophysical or statistical approaches. We discuss the applicability and limitations of these methods for understanding the mechanisms of chromatin organization. We also highlight the emergence of new predictive approaches for scoring effects of structural variations in human cells.

3D-GNOME 2.0: a three-dimensional genome modeling engine for predicting structural variation-driven alterations of chromatin spatial structure in the human genome

Structural variants (SVs) that alter DNA sequence emerge as a driving force involved in the reorganisation of DNA spatial folding, thus affecting gene transcription. In this work, we describe an improved version of our integrated web service for structural modeling of three-dimensional genome (3D-GNOME), which now incorporates all types of SVs to model changes to the reference 3D conformation of chromatin. In 3D-GNOME 2.0, the default reference 3D genome structure is generated using ChIA-PET data from the GM12878 cell line and SVs data are sourced from the population-scale catalogue of SVs identified by the 1000 Genomes Consortium. However, users may also submit their own structural data to set a customized reference genome structure, and/or a custom input list of SVs. 3D-GNOME 2.0 provides novel tools to inspect, visualize and compare 3D models for regions that differ in terms of their linear genomic sequence. Contact diagrams are displayed to compare the reference 3D structure with the one altered by SVs. In our opinion, 3D-GNOME 2.0 is a unique online tool for modeling and analyzing conformational changes to the human genome induced by SVs across populations. It can be freely accessed at https://3dgnome.cent.uw.edu.pl/.

Epigenetic Vulnerability of Insulator CTCF Motifs at Parkinson's Disease-Associated Genes in Response to Neurotoxicant Rotenone

CCCTC-binding factor (CTCF) is a regulatory protein that binds DNA to control spatial organization and transcription. The sequence-specific binding of CTCF is variable and is impacted by nearby epigenetic patterns. It has been demonstrated that non-coding genetic variants cluster with CTCF sites in topological associating domains and thus can affect CTCF activity on gene expression. Therefore, environmental factors that alter epigenetic patterns at CTCF binding sites may dictate the interaction of non-coding genetic variants with regulatory proteins. To test this mechanism, we treated human cell line HEK293 with rotenone for 24 h and characterized its effect on global epigenetic patterns specifically at regulatory regions of Parkinson's disease (PD) risk loci. We used RNA sequencing to examine changes in global transcription and identified over 2000 differentially expressed genes (DEGs, >1.5-fold change, FDR < 0.05). Among these DEGs, 13 were identified as PD-associated genes according to Genome-wide association studies meta-data. We focused on eight genes that have non-coding risk variants and a prominent CTCF binding site. We analyzed methylation of a total of 165 CGs surrounding CTCF binding sites and detected differential methylation (|>1%|, q < 0.05) in 45 CGs at 7 PD-associated genes. Of these 45 CGs, 47% were hypomethylated and 53% were hypermethylated. Interestingly, 5 out of the 7 genes had correlated gene upregulation with CG hypermethylation at CTCF and gene downregulation with CG hypomethylation at CTCF. We also investigated active H3K27ac surrounding the same CTCF binding sites within these seven genes. We observed a significant increase in H3K27ac in four genes (FDR < 0.05). Three genes (PARK2, GPRIN3, FER) showed increased CTCF binding in response to rotenone. Our data indicate that rotenone alters regulatory regions of PD-associated genes through changes in epigenetic patterns, and these changes impact high-order chromatin organization to increase the influence of non-coding variants on genome integrity and cellular survival.

Free energy-based model of CTCF-mediated chromatin looping in the human genome

In recent years, high-throughput techniques have revealed considerable structural organization of the human genome with diverse regions of the chromatin interacting with each other in the form of loops. Some of these loops are quite complex and may encompass regions comprised of many interacting chain segments around a central locus. Popular techniques for extracting this information are chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) and high-throughput chromosome conformation capture (Hi-C). Here, we introduce a physics-based method to predict the three-dimensional structure of chromatin from population-averaged ChIA-PET data. The approach uses experimentally-validated data from human B-lymphoblastoid cells to generate 2D meta-structures of chromatin using a dynamic programming algorithm that explores the chromatin free energy landscape. By generating both optimal and suboptimal meta-structures we can calculate both the free energy and additionally the relative thermodynamic probability. A 3D structure prediction program with applied restraints then can be used to generate the tertiary structures. The main advantage of this approach for population-averaged experimental data is that it provides a way to distinguish between the principal and the spurious contacts. This study also finds that euchromatin appear to have rather precisely regulated 2D meta-structures compared to heterochromatin. The program source-code is available at https://github.com/plewczynski/looper.

intansv: an R package for integrative analysis of structural variations

Identification of structural variations between individuals is very important for the understanding of phenotype variations and diseases. Despite the existence of dozens of programs for prediction of structural variations, none of them is the golden standard in this field and the results of multiple programs were usually integrated to get more reliable predictions. Annotation and visualization of structural variations are important for the understanding of their functions. However, no program provides these functions currently as far as we are concerned. We report an R package, intansv, which can integrate the predictions of multiple programs as well as annotate and visualize structural variations. The source code and the help manual of intansv is freely available at https://github.com/venyao/intansv and http://www.bioconductor.org/packages/devel/bioc/html/intansv.html.

Exploring 3D chromatin contacts in gene regulation: The evolution of approaches for the identification of functional enhancer-promoter interaction

Mechanisms underlying gene regulation are key to understand how multicellular organisms with various cell types develop from the same genetic blueprint. Dynamic interactions between enhancers and genes are revealed to play central roles in controlling gene transcription, but the determinants to link functional enhancer-promoter pairs remain elusive. A major challenge is the lack of reliable approach to detect and verify functional enhancer-promoter interactions (EPIs). In this review, we summarized the current methods for detecting EPIs and described how developing techniques facilitate the identification of EPI through assessing the merits and drawbacks of these methods. We also reviewed recent state-of-art EPI prediction methods in terms of their rationale, data usage and characterization. Furthermore, we briefly discussed the evolved strategies for validating functional EPIs.

The 3D Genome as a Target for Anticancer Therapy

The role of 3D genome organization in the precise regulation of gene expression is well established. Accordingly, the mechanistic connections between 3D genome alterations and disease development are becoming increasingly apparent. This opinion article provides a snapshot of our current understanding of the 3D genome alterations associated with cancers. We discuss potential connections of the 3D genome and cancer transcriptional addiction phenomenon as well as molecular mechanisms of action of 3D genome-disrupting drugs. Finally, we highlight issues and perspectives raised by the discovery of the first pharmaceutical strongly affecting 3D genome organization.

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.