Hi-C as a tool for precise detection and characterisation of chromosomal rearrangements and copy number variation in human tumours

Evaluation of Hi-C sequencing for the detection of gene fusions in hematologic and solid pediatric cancer samples

HiC sequencing is a DNA-based next-generation sequencing method that preserves the 3D conformation of the genome and has shown promise in detecting genomic rearrangements in translational research studies. To evaluate HiC as a potential clinical diagnostic platform, analytical concordance with routine laboratory testing was assessed using primary pediatric leukemia and sarcoma specimens previously positive for clinically significant genomic rearrangements. Archived specimen types tested included viable and nonviable frozen leukemic cells, as well as formalin-fixed paraffin-embedded (FFPE) tumor tissues. Initially, pediatric acute myeloid leukemia (AML) and alveolar rhabdomyosarcoma (A-RMS) specimens with known genomic rearrangements were subjected to HiC analysis to assess analytical concordance. Subsequently, a discovery cohort consisting of AML and acute lymphoblastic leukemia (ALL) cases with no known genomic rearrangements based on prior clinical diagnostic testing were evaluated to determine whether HiC could detect rearrangements. Using a standard sequencing depth of 50 million raw read-pairs per sample, or approximately 5X raw genomic coverage, 100% concordance was observed between HiC and previous clinical cytogenetic and molecular testing. In the discovery cohort, a clinically relevant gene fusion was detected in 45% of leukemia cases (5/11). This study demonstrates the value of HiC sequencing to medical diagnostic testing as it identified several clinically significant rearrangements, including those that might have been missed by current clinical testing workflows.

Key points

HiC sequencing is a DNA-based next-generation sequencing method that preserves the 3D conformation of the genome, facilitating detection of genomic rearrangements.HiC was 100% concordant with clinical diagnostic testing workflows for detecting clinically significant genomic rearrangements in pediatric leukemia and rhabdomyosarcoma specimens.HiC detected clinically significant genomic rearrangements not previously detected by prior clinical cytogenetic and molecular testing.HiC performed well with archived non-viable and viable frozen leukemic cell samples, as well as archived formalin-fixed paraffin-embedded tumor tissue specimens.

Pervasive structural heterogeneity rewires glioblastoma chromosomes to sustain patient-specific transcriptional programs

Glioblastoma multiforme (GBM) encompasses brain malignancies marked by phenotypic and transcriptional heterogeneity thought to render these tumors aggressive, resistant to therapy, and inevitably recurrent. However, little is known about how the spatial organization of GBM genomes underlies this heterogeneity and its effects. Here, we compile a cohort of 28 patient-derived glioblastoma stem cell-like lines (GSCs) known to reflect the properties of their tumor-of-origin; six of these were primary-relapse tumor pairs from the same patient. We generate and analyze 5 kbp-resolution chromosome conformation capture (Hi-C) data from all GSCs to systematically map thousands of standalone and complex structural variants (SVs) and the multitude of neoloops arising as a result. By combining Hi-C, histone modification, and gene expression data with chromatin folding simulations, we explain how the pervasive, uneven, and idiosyncratic occurrence of neoloops sustains tumor-specific transcriptional programs via the formation of new enhancer-promoter contacts. We also show how even moderately recurrent neoloops can relate to patient-specific vulnerabilities. Together, our data provide a resource for dissecting GBM biology and heterogeneity, as well as for informing therapeutic approaches.

Reduced Nephron Endowment in Six2-TGCtg Mice Is Due to Six3 Misexpression by Aberrant Enhancer-Promoter Interactions in the Transgene

Key Points

Background

Lifelong kidney function relies on the complement of nephrons generated during mammalian development from a mesenchymal nephron progenitor cell population. Low nephron endowment confers increased susceptibility to CKD. Reduced nephron numbers in the popular Six2TGC transgenic mouse line may be due to disruption of a regulatory gene at the integration site and/or ectopic expression of a gene(s) contained within the transgene.

Methods

Targeted locus amplification was performed to identify the integration site of the Six2TGC transgene. Genome-wide chromatin conformation capture (Hi-C) datasets were generated from nephron progenitor cells isolated from the Six2TGC +/tg mice, the Cited1 CreERT2/+ control mice, and the Six2TGC +/tg ; Tsc1 +/Flox mice that exhibited restored nephron number compared with Six2TGC +/tg mice. Modified transgenic mice lacking the C-terminal domain of Six3 were used to evaluate the mechanism of nephron number reduction in the Six2TGC +/tg mouse line.

Results

Targeted locus amplification revealed integration of the Six2TGC transgene within an intron of Cntnap5a on chr1, and Hi-C analysis mapped the precise integration of Six2TGC and Cited1 CreERT2 transgenes to chr1 and chr14, respectively. No changes in topology, accessibility, or expression were observed within the 50-megabase region centered on Cntnap5a in Six2TGC +/tg mice compared with control mice. By contrast, we identified an aberrant regulatory interaction between a Six2 distal enhancer and the Six3 promoter contained within the transgene. Increasing the Six2TGC tg to Six2 locus ratio or removing one Six2 allele in Six2TGC +/tg mice caused severe renal hypoplasia. Furthermore, clustered regularly interspaced short palindromic repeats disruption of Six3 within the transgene (Six2TGC ∆Six3CT ) restored nephron endowment to wild-type levels and abolished the stoichiometric effect.

Conclusions

These findings broadly demonstrate the utility of Hi-C data in mapping transgene integration sites and architecture. Data from genetic and biochemical studies together suggest that in Six2TGC kidneys, SIX3 interferes with SIX2 function in nephron progenitor cell renewal through its C-terminal domain.

Droplet Hi-C for Fast and Scalable Profiling of Chromatin Architecture in Single Cells

Comprehensive analysis of chromatin architecture is crucial for understanding the gene regulatory programs during development and in disease pathogenesis, yet current methods often inadequately address the unique challenges presented by analysis of heterogeneous tissue samples. Here, we introduce Droplet Hi-C, which employs a commercial microfluidic device for high-throughput, single-cell chromatin conformation profiling in droplets. Using Droplet Hi-C, we mapped the chromatin architecture at single-cell resolution from the mouse cortex and analyzed gene regulatory programs in major cortical cell types. Additionally, we used this technique to detect copy number variation (CNV), structural variations (SVs) and extrachromosomal DNA (ecDNA) in cancer cells, revealing clonal dynamics and other oncogenic events during treatment. We further refined this technique to allow for joint profiling of chromatin architecture and transcriptome in single cells, facilitating a more comprehensive exploration of the links between chromatin architecture and gene expression in both normal tissues and tumors. Thus, Droplet Hi-C not only addresses critical gaps in chromatin analysis of heterogeneous tissues but also emerges as a versatile tool enhancing our understanding of gene regulation in health and disease.

Cytogenetics in the management of hematological malignancies: An overview of alternative technologies for cytogenetic characterization

Genomic characterization is an essential part of the clinical management of hematological malignancies for diagnostic, prognostic and therapeutic purposes. Although CBA and FISH are still the gold standard in hematology for the detection of CNA and SV, some alternative technologies are intended to complement their deficiencies or even replace them in the more or less near future. In this article, we provide a technological overview of these alternatives. CMA is the historical and well established technique for the high-resolution detection of CNA. For SV detection, there are emerging techniques based on the study of chromatin conformation and more established ones such as RTMLPA for the detection of fusion transcripts and RNA-seq to reveal the molecular consequences of SV. Comprehensive techniques that detect both CNA and SV are the most interesting because they provide all the information in a single examination. Among these, OGM is a promising emerging higher-solution technique that offers a complete solution at a contained cost, at the expense of a relatively low throughput per machine. WGS remains the most adaptable solution, with long-read approaches enabling very high-resolution detection of CAs, but requiring a heavy bioinformatics installation and at a still high cost. However, the development of high-resolution genome-wide detection techniques for CAs allows for a much better description of chromoanagenesis. Therefore, we have included in this review an update on the various existing mechanisms and their consequences and implications, especially prognostic, in hematological malignancies.

Rethinking cancer initiation: The role of large-scale mutational events

Cancer initiation is revisited in light of recent discoveries in cancer pathogenesis. Of note is the detection of mutated cancer genes in benign conditions. More significantly, somatic clones, which harbor mutations in cancer genes, arise in normal tissues from early development through adulthood, but seldom do they transform into cancer. Further, clustered mutational events-kataegis, chromothripsis and chromoplexy-are widespread in cancer, generating point mutations and chromosomal rearrangements in a single cellular catastrophe. These observations are contrary to the prevailing somatic mutation theory, which states that a cancer is caused by the gradual accumulation of mutations over time. A different perspective is proposed within the framework of Waddington's epigenetic landscape wherein tumorigenesis is viewed primarily as a disruption of cell development. Cell types are defined by their specific gene-expression profiles, determined by the gene regulatory network, and can be regarded as attractor states of the network dynamics: they represent specific, self-stabilizing patterns of gene activities across the genome. However, large-scale mutational events reshape the landscape topology, creating abnormal "unphysiological" attractors. This is the crux of the process of initiation. Initiation primes the cell for conversion into a tumor phenotype by oncogenes and tumor suppressor genes, which drive cell proliferation and clonal diversification. This view of tumorigenesis calls for a different approach to therapy.

AML with complex karyotype: extreme genomic complexity revealed by combined long-read sequencing and Hi-C technology

Acute myeloid leukemia with complex karyotype (CK-AML) is associated with poor prognosis, which is only in part explained by underlying TP53 mutations. Especially in the presence of complex chromosomal rearrangements, such as chromothripsis, the outcome of CK-AML is dismal. However, this degree of complexity of genomic rearrangements contributes to the leukemogenic phenotype and treatment resistance of CK-AML remains largely unknown. Applying an integrative workflow for the detection of structural variants (SVs) based on Oxford Nanopore (ONT) genomic DNA long-read sequencing (gDNA-LRS) and high-throughput chromosome confirmation capture (Hi-C) in a well-defined cohort of CK-AML identified regions with an extreme density of SVs. These rearrangements consisted to a large degree of focal amplifications enriched in the proximity of mammalian-wide interspersed repeat elements, which often result in oncogenic fusion transcripts, such as USP7::MVD, or the deregulation of oncogenic driver genes as confirmed by RNA-seq and ONT direct complementary DNA sequencing. We termed this novel phenomenon chromocataclysm. Thus, our integrative SV detection workflow combing gDNA-LRS and Hi-C enables to unravel complex genomic rearrangements at a very high resolution in regions hard to analyze by conventional sequencing technology, thereby providing an important tool to identify novel important drivers underlying cancer with complex karyotypic changes.

Tracing cancer evolution and heterogeneity using Hi-C

Chromosomal rearrangements can initiate and drive cancer progression, yet it has been challenging to evaluate their impact, especially in genetically heterogeneous solid cancers. To address this problem we developed HiDENSEC, a new computational framework for analyzing chromatin conformation capture in heterogeneous samples that can infer somatic copy number alterations, characterize large-scale chromosomal rearrangements, and estimate cancer cell fractions. After validating HiDENSEC with in silico and in vitro controls, we used it to characterize chromosome-scale evolution during melanoma progression in formalin-fixed tumor samples from three patients. The resulting comprehensive annotation of the genomic events includes copy number neutral translocations that disrupt tumor suppressor genes such as NF1, whole chromosome arm exchanges that result in loss of CDKN2A, and whole-arm copy-number neutral loss of homozygosity involving PTEN. These findings show that large-scale chromosomal rearrangements occur throughout cancer evolution and that characterizing these events yields insights into drivers of melanoma progression.

MGA-seq: robust identification of extrachromosomal DNA and genetic variants using multiple genetic abnormality sequencing

Genomic abnormalities are strongly associated with cancer and infertility. In this study, we develop a simple and efficient method - multiple genetic abnormality sequencing (MGA-Seq) - to simultaneously detect structural variation, copy number variation, single-nucleotide polymorphism, homogeneously staining regions, and extrachromosomal DNA (ecDNA) from a single tube. MGA-Seq directly sequences proximity-ligated genomic fragments, yielding a dataset with concurrent genome three-dimensional and whole-genome sequencing information, enabling approximate localization of genomic structural variations and facilitating breakpoint identification. Additionally, by utilizing MGA-Seq, we map focal amplification and oncogene coamplification, thus facilitating the exploration of ecDNA's transcriptional regulatory function.

Reduced nephron endowment in the common Six2-TGC tg mouse line is due to Six3 misexpression by aberrant enhancer-promoter interactions in the transgene

Lifelong kidney function relies on the complement of nephrons generated during mammalian development from a mesenchymal nephron progenitor cell (NPC) population. Low nephron endowment confers increased susceptibility to chronic kidney disease. We asked whether reduced nephron numbers in the popular Six2TGC transgenic mouse line 1 was due to disruption of a regulatory gene at the integration site or to ectopic expression of a gene(s) contained within the transgene. Targeted locus amplification identified integration of the Six2TGC transgene within an intron of Cntnap5a on chr1. We generated Hi-C datasets from NPCs isolated from the Six2TGC tg/+ mice, the Cited1 CreERT2/+ control mice, and the Six2TGC tg/+ ; Tsc1 +/Flox,2 mice that exhibited restored nephron number compared with Six2TGC tg/+ mice, and mapped the precise integration of Six2TGC and Cited1 CreERT2 transgenes to chr1 and chr14, respectively. No changes in topology, accessibility, or expression were observed within the 50-megabase region centered on Cntnap5a in Six2TGC tg/+ mice compared with control mice. By contrast, we identified an aberrant regulatory interaction between a Six2 distal enhancer and the Six3 promoter contained within the transgene. Increasing the Six2TGC tg to Six2 locus ratio or removing one Six2 allele in Six2TGC tg/+ mice, caused severe renal hypoplasia. Furthermore, CRISPR disruption of Six3 within the transgene ( Six2TGC Δ Six3CT ) restored nephron endowment to wildtype levels and abolished the stoichiometric effect. Data from genetic and biochemical studies together suggest that in Six2TGC, SIX3 interferes with SIX2 function in NPC renewal through its C-terminal domain.

Significance

Using high-resolution chromatin conformation and accessibility datasets we mapped the integration site of two popular transgenes used in studies of nephron progenitor cells and kidney development. Aberrant enhancer-promoter interactions drive ectopic expression of Six3 in the Six2TGC tg line which was correlated with disruption of nephrogenesis. Disruption of Six3 within the transgene restored nephron numbers to control levels; further genetic and biochemical studies suggest that Six3 interferes with Six2 -mediated regulation of NPC renewal.

EagleC Explorer: A desktop application for interactively detecting and visualizing SVs and enhancer hijacking on Hi-C contact maps

It has been shown that Hi-C can be used as a powerful tool to detect structural variations (SVs) and enhancer hijacking events. However, there has been no existing programs that can directly visualize and detect such events on a personal computer, which hinders the broad adaption of the technology for intuitive discovery in cancer studies. Here, we introduce the EagleC Explorer, a desktop software that is specifically designed for exploring Hi-C and other chromatin contact data in cancer genomes. EagleC Explorer has a set of unique features, including 1) conveniently visualizing global and local Hi-C data; 2) interactively detecting SVs on a Hi-C map for any user-selected region on screen within seconds, using a deep-learning model; 3) reconstructing local Hi-C map surrounding user-provided SVs and generating publication-quality figures; 4) detecting enhancer hijacking events for any user-suggested regions on screen. In addition, EagleC Explorer can also incorporate other genomic tracks such as RNA-Seq or ChIP-Seq to facilitate scientists for integrative data analysis and making novel discoveries.

Linked-read based analysis of the medulloblastoma genome

Introduction

Medulloblastoma is the most common type of malignant pediatric brain tumor with group 4 medulloblastomas (G4 MBs) accounting for 40% of cases. However, the molecular mechanisms that underlie this subgroup are still poorly understood. Point mutations are detected in a large number of genes at low incidence per gene while the detection of complex structural variants in recurrently affected genes typically requires the application of long-read technologies.

Methods

Here, we applied linked-read sequencing, which combines the long-range genome information of long-read sequencing with the high base pair accuracy of short read sequencing and very low sample input requirements.

Results

We demonstrate the detection of complex structural variants and point mutations in these tumors, and, for the first time, the detection of extrachromosomal DNA (ecDNA) with linked-reads. We provide further evidence for the high heterogeneity of somatic mutations in G4 MBs and add new complex events associated with it.

Discussion

We detected several enhancer-hijacking events, an ecDNA containing the MYCN gene, and rare structural rearrangements, such a chromothripsis in a G4 medulloblastoma, chromoplexy involving 8 different chromosomes, a TERT gene rearrangement, and a PRDM6 duplication.

Chromosome conformation capture technologies as tools to detect structural variations and their repercussion in chromatin 3D configuration

3D genome organization regulates gene expression in different physiological and pathological contexts. Characterization of chromatin structure at different scales has provided information about how the genome organizes in the nuclear space, from chromosome territories, compartments of euchromatin and heterochromatin, topologically associated domains to punctual chromatin loops between genomic regulatory elements and gene promoters. In recent years, chromosome conformation capture technologies have also been used to characterize structural variations (SVs) de novo in pathological conditions. The study of SVs in cancer, has brought information about transcriptional misregulation that relates directly to the incidence and prognosis of the disease. For example, gene fusions have been discovered arising from chromosomal translocations that upregulate oncogenes expression, and other types of SVs have been described that alter large genomic regions encompassing many genes. However, studying SVs in 2D cannot capture all their regulatory implications in the genome. Recently, several bioinformatic tools have been developed to identify and classify SVs from chromosome conformation capture data and clarify how they impact chromatin structure in 3D, resulting in transcriptional misregulation. Here, we review recent literature concerning bioinformatic tools to characterize SVs from chromosome conformation capture technologies and exemplify their vast potential to rebuild the 3D landscape of genomes in cancer. The study of SVs from the 3D perspective can produce essential information about drivers, molecular targets, and disease evolution.

Probabilistic establishment of speckle-associated inter-chromosomal interactions

Inter-chromosomal interactions play a crucial role in genome organization, yet the organizational principles remain elusive. Here, we introduce a novel computational method to systematically characterize inter-chromosomal interactions using in situ Hi-C results from various cell types. Our method successfully identifies two apparently hub-like inter-chromosomal contacts associated with nuclear speckles and nucleoli, respectively. Interestingly, we discover that nuclear speckle-associated inter-chromosomal interactions are highly cell-type invariant with a marked enrichment of cell-type common super-enhancers (CSEs). Validation using DNA Oligopaint fluorescence in situ hybridization (FISH) shows a strong but probabilistic interaction behavior between nuclear speckles and CSE-harboring genomic regions. Strikingly, we find that the likelihood of speckle-CSE associations can accurately predict two experimentally measured inter-chromosomal contacts from Hi-C and Oligopaint DNA FISH. Our probabilistic establishment model well describes the hub-like structure observed at the population level as a cumulative effect of summing individual stochastic chromatin-speckle interactions. Lastly, we observe that CSEs are highly co-occupied by MAZ binding and MAZ depletion leads to significant disorganization of speckle-associated inter-chromosomal contacts. Taken together, our results propose a simple organizational principle of inter-chromosomal interactions mediated by MAZ-occupied CSEs.

Influence of human peripheral blood samples preprocessing on the quality of Hi-C libraries

The genome-wide variant of the chromatin conformation capture technique (Hi-C) is a powerful tool for revealing patterns of genome spatial organization, as well as for understanding the effects of their disturbance on disease development. In addition, Hi-C can be used to detect chromosomal rearrangements, including balanced translocations and inversions. The use of the Hi-C method for the detection of chromosomal rearrangements is becoming more widespread. Modern high-throughput methods of genome analysis can effectively reveal point mutations and unbalanced chromosomal rearrangements. However, their sensitivity for determining translocations and inversions remains rather low. The storage of whole blood samples can affect the amount and integrity of genomic DNA, and it can distort the results of subsequent analyses if the storage was not under proper conditions. The Hi-C method is extremely demanding on the input material. The necessary condition for successfully applying Hi-C and obtaining high-quality data is the preservation of the spatial chromatin organization within the nucleus. The purpose of this study was to determine the optimal storage conditions of blood samples for subsequent Hi-C analysis. We selected 10 different conditions for blood storage and sample processing. For each condition, we prepared and sequenced Hi-C libraries. The quality of the obtained data was compared. As a result of the work, we formulated the requirements for the storage and processing of samples to obtain high-quality Hi-C data. We have established the minimum volume of blood sufficient for conducting Hi-C analysis. In addition, we have identified the most suitable methods for isolation of peripheral blood mononuclear cells and their long-term storage. The main requirement we have formulated is not to freeze whole blood.

Genomic structural variation: A complex but important driver of human evolution

Structural variants (SVs)-including duplications, deletions, and inversions of DNA-can have significant genomic and functional impacts but are technically difficult to identify and assay compared with single-nucleotide variants. With the aid of new genomic technologies, it has become clear that SVs account for significant differences across and within species. This phenomenon is particularly well-documented for humans and other primates due to the wealth of sequence data available. In great apes, SVs affect a larger number of nucleotides than single-nucleotide variants, with many identified SVs exhibiting population and species specificity. In this review, we highlight the importance of SVs in human evolution by (1) how they have shaped great ape genomes resulting in sensitized regions associated with traits and diseases, (2) their impact on gene functions and regulation, which subsequently has played a role in natural selection, and (3) the role of gene duplications in human brain evolution. We further discuss how to incorporate SVs in research, including the strengths and limitations of various genomic approaches. Finally, we propose future considerations in integrating existing data and biospecimens with the ever-expanding SV compendium propelled by biotechnology advancements.

Hi-C analysis of genomic contacts revealed karyotype abnormalities in chicken HD3 cell line

BACKGROUND

Karyotype abnormalities are frequent in immortalized continuous cell lines either transformed or derived from primary tumors. Chromosomal rearrangements can cause dramatic changes in gene expression and affect cellular phenotype and behavior during in vitro culture. Structural variations of chromosomes in many continuous mammalian cell lines are well documented, but chromosome aberrations in cell lines from other vertebrate models often remain understudied. The chicken LSCC-HD3 cell line (HD3), generated from erythroid precursors, was used as an avian model for erythroid differentiation and lineage-specific gene expression. However, karyotype abnormalities in the HD3 cell line were not assessed. In the present study, we applied high-throughput chromosome conformation capture to analyze 3D genome organization and to detect chromosome rearrangements in the HD3 cell line.

RESULTS

We obtained Hi-C maps of genomic interactions for the HD3 cell line and compared A/B compartments and topologically associating domains between HD3 and several other cell types. By analysis of contact patterns in the Hi-C maps of HD3 cells, we identified more than 25 interchromosomal translocations of regions ≥ 200 kb on both micro- and macrochromosomes. We classified most of the observed translocations as unbalanced, leading to the formation of heteromorphic chromosomes. In many cases of microchromosome rearrangements, an entire microchromosome together with other macro- and microchromosomes participated in the emergence of a derivative chromosome, resembling "chromosomal fusions'' between acrocentric microchromosomes. Intrachromosomal inversions, deletions and duplications were also detected in HD3 cells. Several of the identified simple and complex chromosomal rearrangements, such as between GGA2 and GGA1qter; GGA5, GGA4p and GGA7p; GGA4q, GGA6 and GGA19; and duplication of the sex chromosome GGAW, were confirmed by FISH.

CONCLUSIONS

In the erythroid progenitor HD3 cell line, in contrast to mature and immature erythrocytes, the genome is organized into distinct topologically associating domains. The HD3 cell line has a severely rearranged karyotype with most of the chromosomes engaged in translocations and can be used in studies of genome structure-function relationships. Hi-C proved to be a reliable tool for simultaneous assessment of the spatial genome organization and chromosomal aberrations in karyotypes of birds with a large number of microchromosomes.

In it for the long run: perspectives on exploiting long-read sequencing in livestock for population scale studies of structural variants

Studies have demonstrated that structural variants (SV) play a substantial role in the evolution of species and have an impact on Mendelian traits in the genome. However, unlike small variants (< 50 bp), it has been challenging to accurately identify and genotype SV at the population scale using short-read sequencing. Long-read sequencing technologies are becoming competitively priced and can address several of the disadvantages of short-read sequencing for the discovery and genotyping of SV. In livestock species, analysis of SV at the population scale still faces challenges due to the lack of resources, high costs, technological barriers, and computational limitations. In this review, we summarize recent progress in the characterization of SV in the major livestock species, the obstacles that still need to be overcome, as well as the future directions in this growing field. It seems timely that research communities pool resources to build global population-scale long-read sequencing consortiums for the major livestock species for which the application of genomic tools has become cost-effective.

Hi-C Analysis to Identify Genome-Wide Chromatin Structural Aberration in Cancer

Hi-C is a method that analyzes genome-wide chromatin structure using next-generation sequencer. Chromatin structure is crucial for regulating transcription or replication, and Hi-C has revealed the hierarchical chromatin structures, such as loop, domain , and compartment structures. Aberrant alteration of these structures causes disease, and a number of structural aberrations in cancer cells have been reported recently. Besides, Hi-C can identify chromosome rearrangements that frequently occurred in cancer. Therefore, Hi-C is a powerful technique to analyze epigenomic and genomic aberrations in tumorigenesis. Here we will introduce the basic protocol of Hi-C in experimental and analytical aspects.

Structural variants drive context-dependent oncogene activation in cancer

Higher-order chromatin structure is important for the regulation of genes by distal regulatory sequences^1,2. Structural variants (SVs) that alter three-dimensional (3D) genome organization can lead to enhancer-promoter rewiring and human disease, particularly in the context of cancer³. However, only a small minority of SVs are associated with altered gene expression^4,5, and it remains unclear why certain SVs lead to changes in distal gene expression and others do not. To address these questions, we used a combination of genomic profiling and genome engineering to identify sites of recurrent changes in 3D genome structure in cancer and determine the effects of specific rearrangements on oncogene activation. By analysing Hi-C data from 92 cancer cell lines and patient samples, we identified loci affected by recurrent alterations to 3D genome structure, including oncogenes such as MYC, TERT and CCND1. By using CRISPR-Cas9 genome engineering to generate de novo SVs, we show that oncogene activity can be predicted by using 'activity-by-contact' models that consider partner region chromatin contacts and enhancer activity. However, activity-by-contact models are only predictive of specific subsets of genes in the genome, suggesting that different classes of genes engage in distinct modes of regulation by distal regulatory elements. These results indicate that SVs that alter 3D genome organization are widespread in cancer genomes and begin to illustrate predictive rules for the consequences of SVs on oncogene activation.

Algorithmic considerations when analysing capture Hi-C data

Chromosome conformation capture methodologies have provided insight into the effect of 3D genomic architecture on gene regulation. Capture Hi-C (CHi-C) is a recent extension of Hi-C that improves the effective resolution of chromatin interactions by enriching for defined regions of biological relevance. The varying targeting efficiency between capture regions, however, introduces bias not present in conventional Hi-C, making analysis more complicated. Here we consider salient features of an algorithm that should be considered in evaluating the performance of a program used to analyse CHi-C data in order to infer meaningful interactions. We use the program CHICAGO to analyse promoter capture Hi-C data generated on 28 different cell lines as a case study.

Unraveling the Structural Variations of Early-Stage Mycosis Fungoides—CD3 Based Purification and Third Generation Sequencing as Novel Tools for the Genomic Landscape in CTCL

Mycosis fungoides (MF) is the most common cutaneous T-cell lymphoma (CTCL). At present, knowledge of genetic changes in early-stage MF is insufficient. Additionally, low tumor cell fraction renders calling of copy-number variations as the predominant mutations in MF challenging, thereby impeding further investigations. We show that enrichment of T cells from a biopsy of a stage I MF patient greatly increases tumor fraction. This improvement enables accurate calling of recurrent MF copy-number variants such as ARID1A and CDKN2A deletion and STAT5 amplification, undetected in the unprocessed biopsy. Furthermore, we demonstrate that application of long-read nanopore sequencing is especially useful for the structural variant rich CTCL. We detect the structural variants underlying recurrent MF copy-number variants and show phasing of multiple breakpoints into complex structural variant haplotypes. Additionally, we record multiple occurrences of templated insertion structural variants in this sample. Taken together, this study suggests a workflow to make the early stages of MF accessible for genetic analysis, and indicates long-read sequencing as a major tool for genetic analysis for MF.

Structural variations in cancer and the 3D genome

Structural variations (SVs) affect more of the cancer genome than any other type of somatic genetic alteration but difficulties in detecting and interpreting them have limited our understanding. Clinical cancer sequencing also increasingly aims to detect SVs, leading to a widespread necessity to interpret their biological and clinical relevance. Recently, analyses of large whole-genome sequencing data sets revealed features that impact rates of SVs across the genome in different cancers. A striking feature has been the extent to which, in both their generation and their influence on the selective fitness of cancer cells, SVs are more specific to individual cancer types than other genetic alterations such as single-nucleotide variants. This Perspective discusses how the folding of the 3D genome, and differences in its folding across cell types, affect observed SV rates in different cancer types as well as how SVs can impact cancer cell fitness.

Translocation detection from Hi-C data via scan statistics

Recent Hi-C technology enables more comprehensive chromosomal conformation research, including the detection of structural variations, especially translocations. In this paper, we formulate the inter-chromosomal translocation detection as a problem of scan clustering in a spatial point process. We then develop TranScan, a new translocation detection method through scan statistics with the control of false discovery. The simulation shows that TranScan is more powerful than an existing sophisticated scan clustering method, especially under strong signal situations. Evaluation of TranScan against current translocation detection methods on realistic breakpoint simulations generated from real data suggests better discriminative power under the receiver operating characteristic curve. Power analysis also highlights TranScan's consistent outperformance when sequencing depth and heterozygosity rate is varied. Comparatively, Type I error rate is lowest when evaluated using a karyotypically normal cell line. Both the simulation and real data analysis indicate that TranScan has great potentials in inter-chromosomal translocation detection using Hi-C data. This article is protected by copyright. All rights reserved.

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.

EagleC: A deep-learning framework for detecting a full range of structural variations from bulk and single-cell contact maps

The Hi-C technique has been shown to be a promising method to detect structural variations (SVs) in human genomes. However, algorithms that can use Hi-C data for a full-range SV detection have been severely lacking. Current methods can only identify interchromosomal translocations and long-range intrachromosomal SVs (>1 Mb) at less-than-optimal resolution. Therefore, we develop EagleC, a framework that combines deep-learning and ensemble-learning strategies to predict a full range of SVs at high resolution. We show that EagleC can uniquely capture a set of fusion genes that are missed by whole-genome sequencing or nanopore. Furthermore, EagleC also effectively captures SVs in other chromatin interaction platforms, such as HiChIP, Chromatin interaction analysis with paired-end tag sequencing (ChIA-PET), and capture Hi-C. We apply EagleC in more than 100 cancer cell lines and primary tumors and identify a valuable set of high-quality SVs. Last, we demonstrate that EagleC can be applied to single-cell Hi-C and used to study the SV heterogeneity in primary tumors.

Directed yeast genome evolution by controlled introduction of trans-chromosomic structural variations

Naturally occurring structural variations (SVs) are a considerable source of genomic variation that can reshape the 3D architecture of chromosomes. Controllable methods aimed at introducing the complex SVs and their related molecular mechanisms have remained farfetched. In this study, an SV-prone yeast strain was developed using Synthetic Chromosome Rearrangement and Modification by LoxP-mediated Evolution (SCRaMbLE) technology with two synthetic chromosomes, namely synV and synX. The biosynthesis of astaxanthin is used as a readout and a proof of concept for the application of SVs in industries. Our findings showed that complex SVs, including a pericentric inversion and a trans-chromosome translocation between synV and synX, resulted in two neo-chromosomes and a 2.7-fold yield of astaxanthin. Also, genetic targets were mapped, which resulted in a higher astaxanthin yield, thus demonstrating the SVs' ability to reorganize genetic information along the chromosomes. The rational design of trans-chromosome translocation and pericentric inversion enabled precise induction of these phenomena. Collectively, this study provides an effective tool to not only accelerate the directed genome evolution but also to reveal the mechanistic insight of complex SVs for altering phenotypes.

Computational analysis of cancer genome sequencing data

Distilling biologically meaningful information from cancer genome sequencing data requires comprehensive identification of somatic alterations using rigorous computational methods. As the amount and complexity of sequencing data have increased, so has the number of tools for analysing them. Here, we describe the main steps involved in the bioinformatic analysis of cancer genomes, review key algorithmic developments and highlight popular tools and emerging technologies. These tools include those that identify point mutations, copy number alterations, structural variations and mutational signatures in cancer genomes. We also discuss issues in experimental design, the strengths and limitations of sequencing modalities and methodological challenges for the future.

Somatic structural variant formation is guided by and influences genome architecture

The occurrence and formation of genomic structural variants (SVs) is known to be influenced by the 3D chromatin architecture, but the extent and magnitude have been challenging to study. Here, we apply Hi-C to study chromatin organization before and after induction of chromothripsis in human cells. We use Hi-C to manually assemble the derivative chromosomes following the occurrence of massive complex rearrangements, which allows us to study the sources of SV formation and their consequences on gene regulation. We observe an action–reaction interplay whereby the 3D chromatin architecture directly impacts the location and formation of SVs. In turn, the SVs reshape the chromatin organization to alter the local topologies, replication timing, and gene regulation in cis. We show that SVs have a strong tendency to occur between similar chromatin compartments and replication timing regions. Moreover, we find that SVs frequently occur at 3D loop anchors, that SVs can cause a switch in chromatin compartments and replication timing, and that this is a major source of SV-mediated effects on nearby gene expression changes. Finally, we provide evidence for a general mechanistic bias of the 3D chromatin on SV occurrence using data from more than 2700 patient-derived cancer genomes.

HolistIC: leveraging Hi-C and whole genome shotgun sequencing for double minute chromosome discovery

MOTIVATION

Double minute (DM) chromosomes are acentric extrachromosomal DNA artifacts that are frequently observed in the cells of numerous cancers. They are highly amplified and contain oncogenes and drug-resistance genes, making their presence a challenge for effective cancer treatment. Algorithmic discovery of DM can potentially improve bench-derived therapies for cancer treatment. A hindrance to this task is that DMs evolve, yielding circular chromatin that shares segments from progenitor DMs. This creates DMs with overlapping amplicon coordinates. Existing DM discovery algorithms use whole genome shotgun sequencing (WGS) in isolation, which can potentially incorrectly classify DMs that share overlapping coordinates.

RESULTS

In this study, we describe an algorithm called 'HolistIC' that can predict DMs in tumor genomes by integrating WGS and Hi-C sequencing data. The consolidation of these sources of information resolves ambiguity in DM amplicon prediction that exists in DM prediction with WGS data used in isolation. We implemented and tested our algorithm on the tandem Hi-C and WGS datasets of three cancer datasets and a simulated dataset. Results on the cancer datasets demonstrated HolistIC's ability to predict DMs from Hi-C and WGS data in tandem. The results on the simulated data showed the HolistIC can accurately distinguish DMs that have overlapping amplicon coordinates, an advance over methods that predict extrachromosomal amplification using WGS data in isolation.

AVAILABILITY AND IMPLEMENTATION

Our software, named 'HolistIC', is available at http://www.github.com/mhayes20/HolistIC.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Analysis of Hi-C Data for Discovery of Structural Variations in Cancer

Structural variations (SVs) are large genomic rearrangements that can be challenging to identify with current short read sequencing technology due to various confounding factors such as existence of genomic repeats and complex SV structures. Hi-C breakfinder is the first computational tool that utilizes the technology of high-throughput chromatin conformation capture assay (Hi-C) to systematically identify SVs, without being interfered by regular confounding factors. SVs change the spatial distance of genomic regions and cause discontinuous signals in Hi-C, which are difficult to analyze by routine informatics practice. Here we provide step-by-step guidance for how to identify SVs using Hi-C data and how to reconstruct Hi-C maps in the presence of SVs.

Regulation of epigenetic homeostasis in uveal melanoma and retinoblastoma

Uveal melanoma (UM) and retinoblastoma (RB), which cause blindness and even death, are the most frequently observed primary intraocular malignancies in adults and children, respectively. Epigenetic studies have shown that changes in the epigenome contribute to the rapid progression of both UM and RB following classic genetic changes. The loss of epigenetic homeostasis plays an important role in oncogenesis by disrupting the normal patterns of gene expression. The targetable nature of epigenetic modifications provides a unique opportunity to optimize treatment paradigms and establish new therapeutic options for both UM and RB with these aberrant epigenetic modifications. We aimed to review the research findings regarding relevant epigenetic changes in UM and RB. Herein, we 1) summarize the literature, with an emphasis on epigenetic alterations, including DNA methylation, histone modifications, RNA modifications, noncoding RNAs and an abnormal chromosomal architecture; 2) elaborate on the regulatory role of epigenetic modifications in biological processes during tumorigenesis; and 3) propose promising therapeutic candidates for epigenetic targets and update the list of epigenetic drugs for the treatment of UM and RB. In summary, we endeavour to depict the epigenetic landscape of primary intraocular malignancy tumorigenesis and provide potential epigenetic targets in the treatment of these tumours.

Hi-C detects genomic structural variants in peripheral blood of pediatric leukemia patients

B-cell acute lymphoblastic leukemia (B-ALL) is often driven by chromosome translocations that result in recurrent and well-studied gene fusions. Currently, fluorescent in-situ hybridization probes are employed to detect candidate translocations in bone marrow samples from B-ALL patients. Recently Hi-C, a sequencing-based technique originally designed to reconstruct the three-dimensional architecture of the nuclear genome, was shown to effectively recognize structural variants. Here, we demonstrate that Hi-C can be used as a genome-wide assay to detect translocations and other structural variants of potential clinical interest. Structural variants were identified in both bone marrow and peripheral blood samples, including an ETV6-RUNX1 translocation present in one pediatric B-ALL patient. Our report provides proof-of-principle that Hi-C could be an effective strategy to globally detect driver structural variants in B-ALL peripheral blood specimens, reducing the need for invasive bone marrow biopsies and candidate-based clinical tests.

Resolving complex structures at oncovirus integration loci with conjugate graph

Oncovirus integrations cause copy number variations and complex structural variations (SVs) on host genomes. However, the understanding of how inserted viral DNA impacts the local genome remains limited. The linear structure of the oncovirus integrated local genomic map (LGM) will lay the foundations to understand how oncovirus integrations emerge and compromise the host genome's functioning. We propose a conjugate graph model to reconstruct the rearranged LGM at integrated loci. Simulation tests prove the reliability and credibility of the algorithm. Applications of the algorithm to whole-genome sequencing data of human papillomavirus (HPV) and hepatitis B virus (HBV)-infected cancer samples gained biological insights on oncovirus integrations. We observed four affection patterns of oncovirus integrations from the HPV and HBV-integrated cancer samples, including the coding-frame truncation, hyper-amplification of tumor gene, the viral cis-regulation inserted at the single intron and at the intergenic region. We found that the focal duplicates and host SVs are frequent in the HPV-integrated LGMs, while the focal deletions are prevalent in HBV-integrated LGMs. Furthermore, with the results yields from our method, we found the enhanced microhomology-mediated end joining might lead to both HPV and HBV integrations and conjectured that the HPV integrations might mainly occur during the DNA replication process. The conjugate graph algorithm code and LGM construction pipeline, available at https://github.com/deepomicslab/FuseSV.

Synergistic alterations in the multilevel chromatin structure anchor dysregulated genes in small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive form of lung cancer that uniquely changes the chromosomal structure, although the basis of aberrant gene expression in SCLC remains largely unclear. Topologically associated domains (TADs) are structural and functional units of the human genome. Genetic and epigenetic alterations in the cancer genome can lead to the disruption of TAD boundaries and may cause gene dysregulation. To understand the potential regulatory role of this process in SCLC, we developed the TAD boundary alteration-related gene identification in tumors (TARGET) computational framework, which enables the systematic identification of candidate dysregulated genes associated with altered TAD boundaries. Using TARGET to compare gene expression profiles between SCLC and normal human lung fibroblast cell lines, we identified >100 genes in this category, of which 24 were further verified in samples from patients with SCLC using NanoString. The analysis revealed synergistic chromatin structure alteration at the A/B compartment and TAD boundary levels that underlies aberrant gene expression in SCLC. TARGET is a novel and powerful tool that can be used to explore the relationship of chromatin structure alteration to gene dysregulation related to SCLC tumorigenesis, progression, and prognosis.

Major Reorganization of Chromosome Conformation During Muscle Development in Pig

The spatial organization of the genome in the nucleus plays a crucial role in eukaryotic cell functions, yet little is known about chromatin structure variations during late fetal development in mammals. We performed in situ high-throughput chromosome conformation capture (Hi-C) sequencing of DNA from muscle samples of pig fetuses at two late stages of gestation. Comparative analysis of the resulting Hi-C interaction matrices between both groups showed widespread differences of different types. First, we discovered a complex landscape of stable and group-specific Topologically Associating Domains (TADs). Investigating the nuclear partition of the chromatin into transcriptionally active and inactive compartments, we observed a genome-wide fragmentation of these compartments between 90 and 110 days of gestation. Also, we identified and characterized the distribution of differential cis- and trans-pairwise interactions. In particular, trans-interactions at chromosome extremities revealed a mechanism of telomere clustering further confirmed by 3D Fluorescence in situ Hybridization (FISH). Altogether, we report major variations of the three-dimensional genome conformation during muscle development in pig, involving several levels of chromatin remodeling and structural regulation.

Genomic and transcriptomic analyses reveal a tandem amplification unit of 11 genes and mutations in mismatch repair genes in methotrexate-resistant HT-29 cells

DHFR gene amplification is commonly present in methotrexate (MTX)-resistant colon cancer cells and acute lymphoblastic leukemia. In this study, we proposed an integrative framework to characterize the amplified region by using a combination of single-molecule real-time sequencing, next-generation optical mapping, and chromosome conformation capture (Hi-C). We identified an amplification unit spanning 11 genes, from the DHFR gene to the ATP6AP1L gene position, with high adjusted interaction frequencies on chromosome 5 (~2.2 Mbp) and a twenty-fold tandemly amplified region, and novel inversions at the start and end positions of the amplified region as well as frameshift insertions in most of the MSH and MLH genes were detected. These mutations might stimulate chromosomal breakage and cause the dysregulation of mismatch repair. Characterizing the tandem gene-amplified unit may be critical for identifying the mechanisms that trigger genomic rearrangements. These findings may provide new insight into the mechanisms underlying the amplification process and the evolution of drug resistance.

Sequencing a large region of DNA containing many surplus copies of genes linked to drug resistance in colon cancer cells may illuminate how these genomic rearrangements arise. Such regions of gene amplification are highly repetitive, making them impossible to sequence using ordinary methods, and little is known about how they are generated. Using advanced methods, Jeong-Sun Seo at Seoul National University Bundang Hospital in South Korea and co-workers sequenced a region of gene amplification in colon cancer cells. The amplified region was approximately 20 times the length of that in healthy cells and contained many copies of an eleven-gene segment, including a gene implicated in drug resistance. The region also contained mutations in chromosomal repair genes which would disrupt repair pathways. These results illuminate the genetic changes that lead to gene amplification and drug resistance in cancer cells.

Spatial genome architecture and the emergence of malignancy

Human chromosomes are large spatially and hierarchically structured entities, the integrity of which needs to be preserved throughout the lifespan of the cell and in conjunction with cell cycle progression. Preservation of chromosomal structure is important for proper deployment of cell type-specific gene expression programs. Thus, aberrations in the integrity and structure of chromosomes will predictably lead to disease, including cancer. Here, we provide an updated standpoint with respect to chromatin misfolding and the emergence of various cancer types. We discuss recent studies implicating the disruption of topologically associating domains, switching between active and inactive compartments, rewiring of promoter-enhancer interactions in malignancy as well as the effects of single nucleotide polymorphisms in non-coding regions involved in long-range regulatory interactions. In light of these findings, we argue that chromosome conformation studies may now also be useful for patient diagnosis and drug target discovery.

Genome reconstruction and haplotype phasing using chromosome conformation capture methodologies

Genomic analysis of individuals or organisms is predicated on the availability of high-quality reference and genotype information. With the rapidly dropping costs of high-throughput DNA sequencing, this is becoming readily available for diverse organisms and for increasingly large populations of individuals. Despite these advances, there are still aspects of genome sequencing that remain challenging for existing sequencing methods. This includes the generation of long-range contiguity during genome assembly, identification of structural variants in both germline and somatic tissues, the phasing of haplotypes in diploid organisms and the resolution of genome sequence for organisms derived from complex samples. These types of information are valuable for understanding the role of genome sequence and genetic variation on genome function, and numerous approaches have been developed to address them. Recently, chromosome conformation capture (3C) experiments, such as the Hi-C assay, have emerged as powerful tools to aid in these challenges for genome reconstruction. We will review the current use of Hi-C as a tool for aiding in genome sequencing, addressing the applications, strengths, limitations and potential future directions for the use of 3C data in genome analysis. We argue that unique features of Hi-C experiments make this data type a powerful tool to address challenges in genome sequencing, and that future integration of Hi-C data with alternative sequencing assays will facilitate the continuing revolution in genomic analysis and genome sequencing.

Randomness in Cancer Breakpoint Prediction

Cancer genomes are susceptible to multiple rearrangements by deleting, inserting, and translocating genomic regions. Recently, the problem of finding determinants of breakpoint formations was approached with machine learning methods; however, unlike cancer point mutations, breakpoint prediction appeared to be a more difficult task, and various machine learning models did not achieve high prediction power often slightly exceeding the threshold of random guessing. This raised the question of whether the breakpoints are random noise in cancer mutagenesis or there exist determinants in structural mutagenesis. In the present study, we investigated randomness in cancer breakpoint genome distributions through the power of machine learning models to predict breakpoint hot spots. We divided all cancer types into three groups by degree of randomness in their breakpoint formation. We tested different density thresholds and explored the bias in hot spot definition. We also compared prediction of hot spots versus individual breakpoints. We found that hot spots are considerably better predicted than individual breakpoints; however, some individual breakpoints can also be predicted with a satisfactory power, and thus, it is not proper to filter them from analyses. We demonstrated that positive-unlabeled learning can provide insights into insufficiency of cancer data sets, which are not always reflected by data set sizes. Overall, the present results support the view that cancer breakpoint landscape can be represented by predictable dense breakpoint regions and scattered individual breakpoints, which are not all random noise, but some are generated by detectable mechanism.

Mapping chromatin accessibility and active regulatory elements reveals pathological mechanisms in human gliomas

Chromatin structure and accessibility, and combinatorial binding of transcription factors to regulatory elements in genomic DNA control transcription. Genetic variations in genes encoding histones, epigenetics-related enzymes or modifiers affect chromatin structure/dynamics and result in alterations in gene expression contributing to cancer development or progression. Gliomas are brain tumors frequently associated with epigenetics-related gene deregulation. We perform whole-genome mapping of chromatin accessibility, histone modifications, DNA methylation patterns and transcriptome analysis simultaneously in multiple tumor samples to unravel epigenetic dysfunctions driving gliomagenesis. Based on the results of the integrative analysis of the acquired profiles, we create an atlas of active enhancers and promoters in benign and malignant gliomas. We explore these elements and intersect with Hi-C data to uncover molecular mechanisms instructing gene expression in gliomas.

Robust detection of translocations in lymphoma FFPE samples using targeted locus capture-based sequencing

In routine diagnostic pathology, cancer biopsies are preserved by formalin-fixed, paraffin-embedding (FFPE) procedures for examination of (intra-) cellular morphology. Such procedures inadvertently induce DNA fragmentation, which compromises sequencing-based analyses of chromosomal rearrangements. Yet, rearrangements drive many types of hematolymphoid malignancies and solid tumors, and their manifestation is instructive for diagnosis, prognosis, and treatment. Here, we present FFPE-targeted locus capture (FFPE-TLC) for targeted sequencing of proximity-ligation products formed in FFPE tissue blocks, and PLIER, a computational framework that allows automated identification and characterization of rearrangements involving selected, clinically relevant, loci. FFPE-TLC, blindly applied to 149 lymphoma and control FFPE samples, identifies the known and previously uncharacterized rearrangement partners. It outperforms fluorescence in situ hybridization (FISH) in sensitivity and specificity, and shows clear advantages over standard capture-NGS methods, finding rearrangements involving repetitive sequences which they typically miss. FFPE-TLC is therefore a powerful clinical diagnostics tool for accurate targeted rearrangement detection in FFPE specimens.

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.

Large-scale reconstruction of chromatin structures of maize temperate and tropical inbred lines

Maize is a model plant species often used for genetics and genomics research because of its genetic diversity. There are prominent morphological, genetic, and epigenetic variations between tropical and temperate maize lines. However, the genome-wide chromatin conformations of these two maize types remain unexplored. We applied a Hi-C approach to compare the genome-wide chromatin interactions between temperate inbred line D132 and tropical line CML288. A reconstructed maize three-dimensional genome model revealed the spatial segregation of the global A and B compartments. The A compartments contain enriched genes and active epigenome marks, whereas the B compartments are gene-poor, transcriptionally silent chromatin regions. Whole-genome analyses indicated that the global A compartment content of CML288 was 3.12% lower than that of D132. Additionally, global and A/B sub-compartments were associated with differential gene expression and epigenetic changes between two inbred lines. About 25.3% of topologically associating domains (TADs) were determined to be associated with complex domain-level modifications that induced transcriptional changes, indicative of a large-scale reorganization of chromatin structures between the inbred maize lines. Furthermore, differences in chromatin interactions between the two lines correlated with epigenetic changes. These findings provide a solid foundation for the wider plant community to further investigate the genome-wide chromatin structures in other plant species.

Next-generation sequencing for constitutional variants in the clinical laboratory, 2021 revision: a technical standard of the American College of Medical Genetics and Genomics (ACMG)

Next-generation sequencing (NGS) technologies are now established in clinical laboratories as a primary testing modality in genomic medicine. These technologies have reduced the cost of large-scale sequencing by several orders of magnitude. It is now cost-effective to analyze an individual with disease-targeted gene panels, exome sequencing, or genome sequencing to assist in the diagnosis of a wide array of clinical scenarios. While clinical validation and use of NGS in many settings is established, there are continuing challenges as technologies and the associated informatics evolve. To assist clinical laboratories with the validation of NGS methods and platforms, the ongoing monitoring of NGS testing to ensure quality results, and the interpretation and reporting of variants found using these technologies, the American College of Medical Genetics and Genomics (ACMG) has developed the following technical standards.

A cookbook for DNase Hi-C

Background

The Hi-C technique is widely employed to study the 3-dimensional chromatin architecture and to assemble genomes. The conventional in situ Hi-C protocol employs restriction enzymes to digest chromatin, which results in nonuniform genomic coverage. Using sequence-agnostic restriction enzymes, such as DNAse I, could help to overcome this limitation.

Results

In this study, we compare different DNAse Hi-C protocols and identify the critical steps that significantly affect the efficiency of the protocol. In particular, we show that the SDS quenching strategy strongly affects subsequent chromatin digestion. The presence of biotinylated oligonucleotide adapters may lead to ligase reaction by-products, which can be avoided by rational design of the adapter sequences. Moreover, the use of nucleotide-exchange enzymes for biotin fill-in enables simultaneous labelling and repair of DNA ends, similar to the conventional Hi-C protocol. These improvements simplify the protocol, making it less expensive and time-consuming.

Conclusions

We propose a new robust protocol for the preparation of DNAse Hi-C libraries from cultured human cells and blood samples supplemented with experimental controls and computational tools for the evaluation of library quality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13072-021-00389-5.

An Empirical Bayes approach for the identification of long-range chromosomal interaction from Hi-C data

Hi-C experiments have become very popular for studying the 3D genome structure in recent years. Identification of long-range chromosomal interaction, i.e., peak detection, is crucial for Hi-C data analysis. But it remains a challenging task due to the inherent high dimensionality, sparsity and the over-dispersion of the Hi-C count data matrix. We propose EBHiC, an empirical Bayes approach for peak detection from Hi-C data. The proposed framework provides flexible over-dispersion modeling by explicitly including the "true" interaction intensities as latent variables. To implement the proposed peak identification method (via the empirical Bayes test), we estimate the overall distributions of the observed counts semiparametrically using a Smoothed Expectation Maximization algorithm, and the empirical null based on the zero assumption. We conducted extensive simulations to validate and evaluate the performance of our proposed approach and applied it to real datasets. Our results suggest that EBHiC can identify better peaks in terms of accuracy, biological interpretability, and the consistency across biological replicates. The source code is available on Github (https://github.com/QiZhangStat/EBHiC).

SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information

Topologically associating domains (TADs) are the organizational units of chromosome structures. TADs can contain TADs, thus forming a hierarchy. TAD hierarchies can be inferred from Hi-C data through coding trees. However, the current method for computing coding trees is not optimal. In this paper, we propose optimal algorithms for this computation. In comparison with seven state-of-art methods using two public datasets, from GM12878 and IMR90 cells, SuperTAD shows a significant enrichment of structural proteins around detected boundaries and histone modifications within TADs and displays a high consistency between various resolutions of identical Hi-C matrices.