Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective.

Treatment failure for the lethal brain tumor glioblastoma (GBM) is attributed to intratumoral heterogeneity and tumor evolution. We utilized 3D neuronavigation during surgical resection to acquire samples representing the whole tumor mapped by 3D spatial coordinates. Integrative tissue and single-cell analysis revealed sources of genomic, epigenomic, and microenvironmental intratumoral heterogeneity and their spatial patterning. By distinguishing tumor-wide molecular features from those with regional specificity, we inferred GBM evolutionary trajectories from neurodevelopmental lineage origins and initiating events such as chromothripsis to emergence of genetic subclones and spatially restricted activation of differential tumor and microenvironmental programs in the core, periphery, and contrast-enhancing regions. Our work depicts GBM evolution and heterogeneity from a 3D whole-tumor perspective, highlights potential therapeutic targets that might circumvent heterogeneity-related failures, and establishes an interactive platform enabling 360° visualization and analysis of 3D spatial patterns for user-selected genes, programs, and other features across whole GBM tumors.

Identifying cis Elements for Spatiotemporal Control of Mammalian DNA Replication.

The temporal order of DNA replication (replication timing [RT]) is highly coupled with genome architecture, but cis-elements regulating either remain elusive. We created a series of CRISPR-mediated deletions and inversions of a pluripotency-associated topologically associating domain (TAD) in mouse ESCs. CTCF-associated domain boundaries were dispensable for RT. CTCF protein depletion weakened most TAD boundaries but had no effect on RT or A/B compartmentalization genome-wide. By contrast, deletion of three intra-TAD CTCF-independent 3D contact sites caused a domain-wide early-to-late RT shift, an A-to-B compartment switch, weakening of TAD architecture, and loss of transcription. The dispensability of TAD boundaries and the necessity of these "early replication control elements" (ERCEs) was validated by deletions and inversions at additional domains. Our results demonstrate that discrete cis-regulatory elements orchestrate domain-wide RT, A/B compartmentalization, TAD architecture, and transcription, revealing fundamental principles linking genome structure and function.

SATB2 organizes the 3D genome architecture of cognition in cortical neurons.

The DNA-binding protein SATB2 is genetically linked to human intelligence. We studied its influence on the three-dimensional (3D) epigenome by mapping chromatin interactions and accessibility in control versus SATB2-deficient cortical neurons. We find that SATB2 affects the chromatin looping between enhancers and promoters of neuronal-activity-regulated genes, thus influencing their expression. It also alters A/B compartments, topologically associating domains, and frequently interacting regions. Genes linked to SATB2-dependent 3D genome changes are implicated in highly specialized neuronal functions and contribute to cognitive ability and risk for neuropsychiatric and neurodevelopmental disorders. Non-coding DNA regions with a SATB2-dependent structure are enriched for common variants associated with educational attainment, intelligence, and schizophrenia. Our data establish SATB2 as a cell-type-specific 3D genome modulator, which operates both independently and in cooperation with CCCTC-binding factor (CTCF) to set up the chromatin landscape of pyramidal neurons for cognitive processes.

A B-Cell-Specific Enhancer Orchestrates Nuclear Architecture to Generate a Diverse Antigen Receptor Repertoire.

The genome is organized into topologically associated domains (TADs) that enclose smaller subTADs. Here, we identify and characterize an enhancer that is located in the middle of the V gene region of the immunoglobulin kappa light chain (Igκ) locus that becomes active preceding the stage at which this locus undergoes V(D)J recombination. This enhancer is a hub of long-range chromatin interactions connecting subTADs in the V gene region with the recombination center at the J genes. Deletion of this element results in a highly altered long-range chromatin interaction pattern across the locus and, importantly, affects individual V gene utilization locus-wide. These results indicate the existence of an enhancer-dependent framework in the Igκ locus and further suggest that the composition of the diverse antibody repertoire is regulated in a subTAD-specific manner. This enhancer thus plays a structural role in orchestrating the proper folding of the Igκ locus in preparation for V(D)J recombination.

HiC-ACT: improved detection of chromatin interactions from Hi-C data via aggregated Cauchy test.

Genome-wide chromatin conformation capture technologies such as Hi-C are commonly employed to study chromatin spatial organization. In particular, to identify statistically significant long-range chromatin interactions from Hi-C data, most existing methods such as Fit-Hi-C/FitHiC2 and HiCCUPS assume that all chromatin interactions are statistically independent. Such an independence assumption is reasonable at low resolution (e.g., 40 kb bin) but is invalid at high resolution (e.g., 5 or 10 kb bins) because spatial dependency of neighboring chromatin interactions is non-negligible at high resolution. Our previous hidden Markov random field-based methods accommodate spatial dependency but are computationally intensive. It is urgent to develop approaches that can model spatial dependence in a computationally efficient and scalable manner. Here, we develop HiC-ACT, an aggregated Cauchy test (ACT)-based approach, to improve the detection of chromatin interactions by post-processing results from methods assuming independence. To benchmark the performance of HiC-ACT, we re-analyzed deeply sequenced Hi-C data from a human lymphoblastoid cell line, GM12878, and mouse embryonic stem cells (mESCs). Our results demonstrate advantages of HiC-ACT in improving sensitivity with controlled type I error. By leveraging information from neighboring chromatin interactions, HiC-ACT enhances the power to detect interactions with lower signal-to-noise ratio and similar (if not stronger) epigenetic signatures that suggest regulatory roles. We further demonstrate that HiC-ACT peaks show higher overlap with known enhancers than Fit-Hi-C/FitHiC2 peaks in both GM12878 and mESCs. HiC-ACT, effectively a summary statistics-based approach, is computationally efficient (∼6 min and ∼2 GB memory to process 25,000 pairwise interactions).

MCIBox: a toolkit for single-molecule multi-way chromatin interaction visualization and micro-domains identification.

The emerging ligation-free three-dimensional (3D) genome mapping technologies can identify multiplex chromatin interactions with single-molecule precision. These technologies not only offer new insight into high-dimensional chromatin organization and gene regulation, but also introduce new challenges in data visualization and analysis. To overcome these challenges, we developed MCIBox, a toolkit for multi-way chromatin interaction (MCI) analysis, including a visualization tool and a platform for identifying micro-domains with clustered single-molecule chromatin complexes. MCIBox is based on various clustering algorithms integrated with dimensionality reduction methods that can display multiplex chromatin interactions at single-molecule level, allowing users to explore chromatin extrusion patterns and super-enhancers regulation modes in transcription, and to identify single-molecule chromatin complexes that are clustered into micro-domains. Furthermore, MCIBox incorporates a two-dimensional kernel density estimation algorithm to identify micro-domains boundaries automatically. These micro-domains were stratified with distinctive signatures of transcription activity and contained different cell-cycle-associated genes. Taken together, MCIBox represents an invaluable tool for the study of multiple chromatin interactions and inaugurates a previously unappreciated view of 3D genome structure.

Hi-C sequencing unravels dynamic three-dimensional chromatin interactions in muntjac lineage: insights from chromosome fusions in Fea's muntjac genome.

Eukaryotes have varying numbers and structures of characteristic chromosomes across lineages or species. The evolutionary trajectory of species may have been affected by spontaneous genome rearrangements. Chromosome fusion drastically alters karyotypes. However, the mechanisms and consequences of chromosome fusions, particularly in muntjac species, are poorly understood. Recent research-based advancements in three-dimensional (3D) genomics, particularly high-throughput chromatin conformation capture (Hi-C) sequencing, have allowed for the identification of chromosome fusions and provided mechanistic insights into three muntjac species: Muntiacus muntjak, M. reevesi, and M. crinifrons. This study aimed to uncover potential genome rearrangement patterns in the threatened species Fea's muntjac (Muntiacus feae), which have not been previously examined for such characteristics. Deep Hi-C sequencing (31.42 × coverage) was performed to reveal the 3D chromatin architecture of the Fea's muntjac genome. Patterns of repeated chromosome fusions that were potentially mediated by high-abundance transposable elements were identified. Comparative Hi-C maps demonstrated linkage homology between the sex chromosomes in Fea's muntjac and autosomes in M. reevesi, indicating that fusions may have played a crucial role in the evolution of the sex chromosomes of the lineage. The species-level dynamics of topologically associated domains (TADs) suggest that TAD organization could be altered by differential chromosome interactions owing to repeated chromosome fusions. However, research on the effect of TADs on muntjac genome evolution is insufficient. This study generated Hi-C data for the Fea's muntjac, providing a genomic resource for future investigations of the evolutionary patterns of chromatin conformation at the chromosomal level.

Towards Development of the 4C-Based Method Detecting Interactions of Plasmid DNA with Host Genome.

Chromosome conformation capture techniques have revolutionized our understanding of chromatin architecture and dynamics at the genome-wide scale. In recent years, these methods have been applied to a diverse array of species, revealing fundamental principles of chromosomal organization. However, structural organization of the extrachromosomal entities, like viral genomes or plasmids, and their interactions with the host genome, remain relatively underexplored. In this work, we introduce an enhanced 4C-protocol tailored for probing plasmid DNA interactions. We design specific plasmid vector and optimize protocol to allow high detection rate of contacts between the plasmid and host DNA.

Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes.

Gene-based tests are valuable techniques for identifying genetic factors in complex traits. Here, we propose a gene-based testing framework that incorporates data on long-range chromatin interactions, several recent technical advances for region-based tests, and leverages the knockoff framework for synthetic genotype generation for improved gene discovery. Through simulations and applications to genome-wide association studies (GWAS) and whole-genome sequencing data for multiple diseases and traits, we show that the proposed test increases the power over state-of-the-art gene-based tests in the literature, identifies genes that replicate in larger studies, and can provide a more narrow focus on the possible causal genes at a locus by reducing the confounding effect of linkage disequilibrium. Furthermore, our results show that incorporating genetic variation in distal regulatory elements tends to improve power over conventional tests. Results for UK Biobank and BioBank Japan traits are also available in a publicly accessible database that allows researchers to query gene-based results in an easy fashion.

Super-Enhancers and Their Parts: From Prediction Efforts to Pathognomonic Status.

Super-enhancers (SEs) are regions of the genome that play a crucial regulatory role in gene expression by promoting large-scale transcriptional responses in various cell types and tissues. Recent research suggests that alterations in super-enhancer activity can contribute to the development and progression of various disorders. The aim of this research is to explore the multifaceted roles of super-enhancers in gene regulation and their significant implications for understanding and treating complex diseases. Here, we study and summarise the classification of super-enhancer constituents, their possible modes of interaction, and cross-regulation, including super-enhancer RNAs (seRNAs). We try to investigate the opportunity of SE dynamics prediction based on the hierarchy of enhancer single elements (enhancers) and their aggregated action. To further our understanding, we conducted an in silico experiment to compare and differentiate between super-enhancers and locus-control regions (LCRs), shedding light on the enigmatic relationship between LCRs and SEs within the human genome. Particular attention is paid to the classification of specific mechanisms and their diversity, exemplified by various oncological, cardiovascular, and immunological diseases, as well as an overview of several anti-SE therapies. Overall, the work presents a comprehensive analysis of super-enhancers across different diseases, aiming to provide insights into their regulatory roles and may act as a rationale for future clinical interventions targeting these regulatory elements.

Chrom-Lasso: a lasso regression-based model to detect functional interactions using Hi-C data.

Hi-C is a genome-wide assay based on Chromosome Conformation Capture and high-throughput sequencing to decipher 3D chromatin organization in the nucleus. However, computational methods to detect functional interactions utilizing Hi-C data face challenges including the correction for various sources of biases and the identification of functional interactions with low counts of interacting fragments. We present Chrom-Lasso, a lasso linear regression model that removes complex biases assumption-free and identifies functional interacting loci with increased power by combining information of local reads distribution surrounding the area of interest. We showed that interacting regions identified by Chrom-Lasso are more enriched for 5C validated interactions and functional GWAS hits than that of GOTHiC and Fit-Hi-C. To further demonstrate the ability of Chrom-Lasso to detect interactions of functional importance, we performed time-series Hi-C and RNA-seq during T cell activation and exhaustion. We showed that the dynamic changes in gene expression and chromatin interactions identified by Chrom-Lasso were largely concordant with each other. Finally, we experimentally confirmed Chrom-Lasso's finding that Erbb3 was co-regulated with distinct neighboring genes at different states during T cell activation. Our results highlight Chrom-Lasso's utility in detecting weak functional interaction between cis-regulatory elements, such as promoters and enhancers.

Revisiting Assessment of Computational Methods for Hi-C Data Analysis.

The performances of algorithms for Hi-C data preprocessing, the identification of topologically associating domains, and the detection of chromatin interactions and promoter-enhancer interactions have been mostly evaluated using semi-quantitative or synthetic data approaches, without utilizing the most recent methods, since 2017. In this study, we comprehensively evaluated 24 popular state-of-the-art methods for the complete end-to-end pipeline of Hi-C data analysis, using manually curated or experimentally validated benchmark datasets, including a CRISPR dataset for promoter-enhancer interaction validation. Our results indicate that, although no single method exhibited superior performance in all situations, HiC-Pro, DomainCaller, and Fit-Hi-C2 showed relatively balanced performances of most evaluation metrics for preprocessing, topologically associating domain identification, and chromatin interaction/promoter-enhancer interaction detection, respectively. The comprehensive comparison presented in this manuscript provides a reference for researchers to choose Hi-C analysis tools that best suit their needs.

FreeHi-C spike-in simulations for benchmarking differential chromatin interaction detection.

High-throughput genome-wide chromatin conformation capture assay (Hi-C) is routinely used to profile long-range genomic interactions and three-dimensional organization of genomes. A key application of Hi-C is the comparative analysis of genomic interactions across different time points, cellular conditions, or multiple stimuli. While operating characteristics of methods for Hi-C data processing such as normalization, pairwise interaction and higher-order organization detection have been relatively well studied, properties of methods for differential chromatin interaction detection are less investigated. We have recently developed FreeHi-C to enable data-driven non-parametric simulations from Hi-C experiments. Here, we extend FreeHi-C with a user/data-driven spike-in module to facilitate comparisons of differential chromatin interaction detection methods where the ground truth differential chromatin interactions are known under a wide variety of settings. We use FreeHi-C to benchmark four differential chromatin interaction detection methods, namely HiCcompare, multiHiCcompare, diffHic, and Selfish, using three comparative analysis settings with different sequencing depths and spike-in proportions. This comparison reveals distinguished performances in terms of the standard metrics such as the false discovery rate control, detection power, significance order, precision-recall curve, and receiver operating characteristic curve as well as overall genomic properties of the types of differential chromatin interactions detectable by each method. Furthermore, it highlights the lack of power for all methods in small replication settings.

Very long intergenic non-coding (vlinc) RNAs directly regulate multiple genes in cis and trans.

BACKGROUND: The majority of the human genome is transcribed in the form of long non-coding (lnc) RNAs. While these transcripts have attracted considerable interest, their molecular mechanisms of function and biological significance remain controversial. One of the main reasons behind this lies in the significant challenges posed by lncRNAs requiring the development of novel methods and concepts to unravel their functionality. Existing methods often lack cross-validation and independent confirmation by different methodologies and therefore leave significant ambiguity as to the authenticity of the outcomes. Nonetheless, despite all the caveats, it appears that lncRNAs may function, at least in part, by regulating other genes via chromatin interactions. Therefore, the function of a lncRNA could be inferred from the function of genes it regulates. In this work, we present a genome-wide functional annotation strategy for lncRNAs based on identification of their regulatory networks via the integration of three distinct types of approaches: co-expression analysis, mapping of lncRNA-chromatin interactions, and assaying molecular effects of lncRNA knockdowns obtained using an inducible and highly specific CRISPR/Cas13 system. RESULTS: We applied the strategy to annotate 407 very long intergenic non-coding (vlinc) RNAs belonging to a novel widespread subclass of lncRNAs. We show that vlincRNAs indeed appear to regulate multiple genes encoding proteins predominantly involved in RNA- and development-related functions, cell cycle, and cellular adhesion via a mechanism involving proximity between vlincRNAs and their targets in the nucleus. A typical vlincRNAs can be both a positive and negative regulator and regulate multiple genes both in trans and cis. Finally, we show vlincRNAs and their regulatory networks potentially represent novel components of DNA damage response and are functionally important for the ability of cancer cells to survive genotoxic stress. CONCLUSIONS: This study provides strong evidence for the regulatory role of the vlincRNA class of lncRNAs and a potentially important role played by these transcripts in the hidden layer of RNA-based regulation in complex biological systems.

Rhythms of the Genome: Circadian Dynamics from Chromatin Topology, Tissue-Specific Gene Expression, to Behavior.

Circadian rhythms in physiology and behavior evolved to resonate with daily cycles in the external environment. In mammals, organs orchestrate temporal physiology over the 24-h day, which requires extensive gene expression rhythms targeted to the right tissue. Although a core set of gene products oscillates across virtually all cell types, gene expression profiling across tissues over the 24-h day showed that rhythmic gene expression programs are tissue specific. We highlight recent progress in uncovering how the circadian clock interweaves with tissue-specific gene regulatory networks involving functions such as xenobiotic metabolism, glucose homeostasis, and sleep. This progress hinges on not only comprehensive experimental approaches but also computational methods for multivariate analysis of periodic functional genomics data. We emphasize dynamic chromatin interactions as a novel regulatory layer underlying circadian gene transcription, core clock functions, and ultimately behavior. Finally, we discuss perspectives on extending the knowledge of the circadian clock in animals to human chronobiology.

Transcriptional enhancers: from prediction to functional assessment on a genome-wide scale.

Enhancers are cis-regulatory sequences located distally to target genes. These sequences consolidate developmental and environmental cues to coordinate gene expression in a tissue-specific manner. Enhancer function and tissue specificity depend on the expressed set of transcription factors, which recognize binding sites and recruit cofactors that regulate local chromatin organization and gene transcription. Unlike other genomic elements, enhancers are challenging to identify because they function independently of orientation, are often distant from their promoters, have poorly defined boundaries, and display no reading frame. In addition, there are no defined genetic or epigenetic features that are unambiguously associated with enhancer activity. Over recent years there have been developments in both empirical assays and computational methods for enhancer prediction. We review genome-wide tools, CRISPR advancements, and high-throughput screening approaches that have improved our ability to both observe and manipulate enhancers in vitro at the level of primary genetic sequences, chromatin states, and spatial interactions. We also highlight contemporary animal models and their importance to enhancer validation. Together, these experimental systems and techniques complement one another and broaden our understanding of enhancer function in development, evolution, and disease.

BAT Hi-C maps global chromatin interactions in an efficient and economical way.

Chromosome Conformation Capture (3C)-based technologies, such as Hi-C, have represented a significant breakthrough in investigating the structure and function of higher-order genome architecture. However, the mapping of global chromatin interactions remains challenging across many biological conditions due to high background noise and financial constraints, especially for small laboratories. Here, we describe the Bridge linker-Alul-Tn5 Hi-C (BAT Hi-C) method, which is a simple and efficient method for delineating chromatin conformational features of mouse embryonic stem (mES) cells and uncover DNA loops. This protocol combines Alul fragmentation and biotinylated linker-mediated proximity ligation to obtain kilobase (kb) resolution with a marked increase in the amount of unique read pairs. The protocol also includes chromatin isolation to reduce background noise and Tn5 tagmentation to cut down on preparation time. Importantly, with only one-third sequencing depth, our method revealed the same spectrum of chromatin contacts as in situ Hi-C. BAT Hi-C is an economical (i.e., approximately $40 for library preparation) and straightforward (total hands-on time of 3 days) tool that is ideal for the in-depth analysis of long-range chromatin looping events in a genome-wide fashion.

Global analysis of histone modifications and long-range chromatin interactions revealed the differential cistrome changes and novel transcriptional players in human dilated cardiomyopathy.

BACKGROUND: Acetylation and methylation of histones alter the chromatin structure and accessibility that affect transcriptional regulators binding to enhancers and promoters. The binding of transcriptional regulators enables the interaction between enhancers and promoters, thus affecting gene expression. However, our knowledge of these epigenetic alternations in patients with heart failure remains limited. METHODS AND RESULTS: From the comprehensive analysis of major histone modifications, 3-dimensional chromatin interactions, and transcriptome in left ventricular (LV) tissues from dilated cardiomyopathy (DCM) patients and non-heart failure (NF) donors, differential active enhancer and promoter regions were identified between NF and DCM. Moreover, the genome-wide average promoter signal is significantly lower in DCM than in NF. Super-enhancer (SE) analysis revealed that fewer SEs were found in DCM LVs than in NF ones, and three unique SE-associated genes between NF and DCM were identified. Moreover, SEs are enriched within the genomic region associated with long-range chromatin interactions. The differential enhancer-promoter interactions were observed in the known heart failure gene loci and are correlated with the gene expression levels. Motif analysis identified known cardiac factors and possible novel players for DCM. CONCLUSIONS: We have established the cistrome of four histone modifications and chromatin interactome for enhancers and promoters in NF and DCM tissues. Differential histone modifications and enhancer-promoter interactions were found in DCM, which were associated with gene expression levels of a subset of disease-associated genes in human heart failure.

Short-range regulatory chromatin loops in plants.

In all eukaryotic organisms, gene expression correlates with the condensation state of the chromatin. Highly packed genome regions, known as heterochromatins, are associated with repressed loci, whereas euchromatic regions represent a relaxed state of the chromatin actively transcribed. However, even in these active regions, associations between chromatin domains dynamically modify genome topology and alter gene expression. Long-range interaction within and between chromosomes determines chromatin domains that help to coordinate transcriptional events. On the other hand, short-range chromatin interactions emerged as dynamic mechanisms regulating the expression of specific loci. Our current capacity to decipher genome topology at high resolution allowed us to identify numerous cases of short-range regulatory chromatin interactions, which are reviewed in this Insight article.

NR2F2 Orphan Nuclear Receptor is Involved in Estrogen Receptor Alpha-Mediated Transcriptional Regulation in Luminal A Breast Cancer Cells.

Nuclear Receptor Subfamily 2 Group F Member 2 (NR2F2) is a member of the steroid/thyroid hormone receptor superfamily with a crucial role in organogenesis, angiogenesis, cardiovascular development and tumorigenesis. However, there is limited knowledge about the cistrome and transcriptome of NR2F2 in breast cancer. In this study, we mapped the regulatory mechanism by NR2F2 using functional genomic methods. To investigate the clinical significance of NR2F2 in breast cancer, The Cancer Genome Atlas (TCGA) data were used. These results show that a high NR2F2 is associated with better survival of a specific subset of patients, namely those with luminal A breast cancer. Therefore, genome-wide NR2F2 and estrogen receptor alpha (ERα) binding sites were mapped in luminal A breast cancer cells using chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq), revealing that most NR2F2 overlap with ERα that are co-occupied by forkhead box A1 (FOXA1) and GATA binding protein 3 (GATA3) in active enhancer regions. NR2F2 overlaps with highly frequent ERα chromatin interactions, which are essential for the formation of ERα-bound super-enhancers. In the process of the transcriptome profiling of NR2F2-depleted breast cancer cells such differentially expressed genes have been identified that are involved in endocrine therapy resistance and are also ERα target genes. Overall, these findings demonstrate that the NR2F2 nuclear receptor has a key role in ERα-mediated transcription and it can offer a potential therapeutic target in patients with luminal A breast cancer.