Multiplex chromatin interactions with single-molecule precision

Landscape of the Epstein-Barr virus-host chromatin interactome and gene regulation

The three-dimensional (3D) chromatin structure of Epstein-Barr virus (EBV) within host cells and the underlying mechanisms of chromatin interaction and gene regulation, particularly those involving EBV's noncoding RNAs (ncRNAs), have remained incompletely characterized. In this study, we employed state-of-the-art techniques of 3D genome mapping, including protein-associated chromatin interaction analysis with paired-end tag sequencing (ChIA-PET), RNA-associated chromatin interaction technique (RDD), and super-resolution microscopy, to delineate the spatial architecture of EBV in human lymphoblastoid cells. We systematically analyzed EBV-to-EBV (E-E), EBV-to-host (E-H), and host-to-host (H-H) interactions linked to host proteins and EBV RNAs. Our findings reveal that EBV utilizes host CCCTC-binding factor (CTCF) and RNA polymerase II (RNAPII) to form distinct chromatin contact domains (CCDs) and RNAPII-associated interaction domains (RAIDs). The anchors of these chromatin domains serve as platforms for extensive interactions with host chromatin, thus modulating host gene expression. Notably, EBV ncRNAs, especially Epstein-Barr-encoded RNAs (EBERs), target and interact with less accessible regions of host chromatin to repress a subset of genes via the inhibition of RNAPII-associated chromatin loops. This process involves the cofactor nucleolin (NCL) and its RNA recognition motifs, and depletion of either NCL or EBERs alters expression of genes crucial for host infection control, immune response, and cell cycle regulation. These findings unveil a sophisticated interplay between EBV and host chromatin.

Discovery of therapeutic targets in cardiovascular diseases using high-throughput chromosome conformation capture (Hi-C)

Epigenetic changes have been associated with several cardiovascular diseases. In recent years, epigenetic inheritance based on spatial changes has gradually attracted attention. Alterations in three-dimensional chromatin structures have been shown to regulate gene expression and influence disease onset and progression. High-throughput Chromosome Conformation Capture (Hi-C) is a powerful method to detect spatial chromatin conformation changes. Since its development, Hi-C technology has been widely adopted for discovering novel therapeutic targets in cardiovascular research. In this review, we summarize key targets identified by Hi-C in cardiovascular diseases and discuss their potential implications for epigenetic therapy.

Reconstruction of diploid higher-order human 3D genome interactions from noisy Pore-C data using Dip3D

Differential high-order chromatin interactions between homologous chromosomes affect many biological processes. Traditional chromatin conformation capture genome analysis methods mainly identify two-way interactions and cannot provide comprehensive haplotype information, especially for low-heterozygosity organisms such as human. Here, we present a pipeline of methods to delineate diploid high-order chromatin interactions from noisy Pore-C outputs. We trained a previously published single-nucleotide variant (SNV)-calling deep learning model, Clair3, on Pore-C data to achieve superior SNV calling, applied a filtering strategy to tag reads for haplotypes and established a haplotype imputation strategy for high-order concatemers. Learning the haplotype characteristics of high-order concatemers from high-heterozygosity mouse allowed us to devise a progressive haplotype imputation strategy, which improved the haplotype-informative Pore-C contact rate 14.1-fold to 76% in the HG001 cell line. Overall, the diploid three-dimensional (3D) genome interactions we derived using Dip3D surpassed conventional methods in noise reduction and contact distribution uniformity, with better haplotype-informative contact density and genomic coverage rates. Dip3D identified previously unresolved haplotype high-order interactions, in addition to an understanding of their relationship with allele-specific expression, such as in X-chromosome inactivation. These results lead us to conclude that Dip3D is a robust pipeline for the high-quality reconstruction of diploid high-order 3D genome interactions.

Deciphering single-cell genomic architecture: insights into cellular heterogeneity and regulatory dynamics

BACKGROUND

The genomic architecture of eukaryotes exhibits dynamic spatial and temporal changes, enabling cellular processes critical for maintaining viability and functional diversity. Recent advances in sequencing technologies have facilitated the dissection of genomic architecture and functional activity at single-cell resolution, moving beyond the averaged signals typically derived from bulk cell analyses.

MAIN BODY

The advent of single-cell genomics and epigenomics has yielded transformative insights into cellular heterogeneity, behavior, and biological complexity with unparalleled genomic resolution and reproducibility. This review summarizes recent progress in the characterization of genomic architecture at the single-cell level, emphasizing the impact of structural variation and chromatin organization on gene regulatory networks and cellular identity.

CONCLUSION

Future directions in single-cell genomics and high-resolution epigenomic methodologies are explored, focusing on emerging challenges and potential impacts on the understanding of cellular states, regulatory dynamics, and the intricate mechanisms driving cellular function and diversity. Future perspectives on the challenges and potential implications of single-cell genomics, along with high-resolution genomic and epigenomic technologies for understanding cellular states and regulatory dynamics, are also discussed.

Chromatin architecture mapping by multiplex proximity tagging

Chromatin plays a pivotal role in genome expression, maintenance, and replication. To better understand chromatin organization, we developed a novel proximity-tagging method which assigns unique DNA barcodes to molecules that associate in 3D space. Using this method - Proximity Copy Paste (PCP) - we mapped the connectivity of individual nucleosomes in Saccharomyces cerevisiae. By analyzing nucleosome positions and spacing on single molecule fibers, we show that chromatin is predominantly organized into regularly spaced nucleosome arrays that can be positioned or delocalized. Basic features of nucleosome arrays are generally explained by gene size and transcription. PCP can also map long-range, multi-way interactions and we provide the first direct evidence supporting a model that metaphase chromosomes are compacted by cohesin loop clustering. Analyzing single-molecule nuclease footprinting data we define distinct chromatin states within a mixed population to show that non-canonical nucleosomes, notably Overlapping-Di-Nucleosomes (OLDN) are a stable feature of chromatin. PCP is a versatile method allowing the detection of the connectivity of individual molecules locally and over large distance to be mapped at high-resolution in a single experiment.

ParSite is a multicolor DNA labeling system that allows for simultaneous imaging of triple genomic loci in living cells

The organization of the human genome in space and time is critical for transcriptional regulation and cell fate determination. However, robust methods for tracking genome organization or genomic interactions over time in living cells are lacking. Here, we developed a multicolor DNA labeling system, ParSite, to simultaneously track triple genomic loci in the U2OS cells. The tricolor ParSite system is derived from the T. thermophilus ParB/ParSc (TtParB/ParSc) system by rational design. We mutated the interface between TtParB and ParSc and generated a new pair of TtParBm and ParSm for genomic DNA labeling. The insertions of 16 base-pair palindromic ParSc and ParSm into genomic loci allow dual-color DNA imaging in living cells. A pair of genomic loci labeled by ParSite could be colocalized with p53-binding protein 1 (53BP1) in response to CRISPR/Cas9-mediated double-strand breaks (DSBs). The ParSite permits tracking promoter and terminator dynamics of the APP gene, which spans 290 kilobases in length. Intriguingly, the hybrid ParS (ParSh) of half-ParSc and half-ParSm enables for the visualization of a third locus independent of ParSc or ParSm. We simultaneously labeled 3 loci with a genomic distance of 36, 89, and 352 kilobases downstream the C3 repeat locus, respectively. In sum, the ParSite is a robust DNA labeling system for tracking multiple genomic loci in space and time in living cells.

Epigenomic and 3D genomic mapping reveals developmental dynamics and subgenomic asymmetry of transcriptional regulatory architecture in allotetraploid cotton

Although epigenetic modification has long been recognized as a vital force influencing gene regulation in plants, the dynamics of chromatin structure implicated in the intertwined transcriptional regulation of duplicated genes in polyploids have yet to be understood. Here, we document the dynamic organization of chromatin structure in two subgenomes of allotetraploid cotton (Gossypium hirsutum) by generating 3D genomic, epigenomic and transcriptomic datasets from 12 major tissues/developmental stages covering the life cycle. We systematically identify a subset of genes that are closely associated with specific tissue functions. Interestingly, these genes exhibit not only higher tissue specificity but also a more pronounced homoeologous bias. We comprehensively elucidate the intricate process of subgenomic collaboration and divergence across various tissues. A comparison among subgenomes in the 12 tissues reveals widespread differences in the reorganization of 3D genome structures, with the Dt subgenome exhibiting a higher extent of dynamic chromatin status than the At subgenome. Moreover, we construct a comprehensive atlas of putative functional genome elements and discover that 37 cis-regulatory elements (CREs) have selection signals acquired during domestication and improvement. These data and analyses are publicly available to the research community through a web portal. In summary, this study provides abundant resources and depicts the regulatory architecture of the genome, which thereby facilitates the understanding of biological processes and guides cotton breeding.

Mapping the 3D genome architecture

The spatial organization of the genome plays a critical role in regulating gene expression, cellular differentiation, and genome stability. This review provides an in-depth examination of the methodologies, computational tools, and frameworks developed to map the three-dimensional (3D) architecture of the genome, focusing on both ligation-based and ligation-free techniques. We also explore the limitations of these methods, including biases introduced by restriction enzyme digestion and ligation inefficiencies, and compare them to more recent ligation-free approaches such as Genome Architecture Mapping (GAM) and Split-Pool Recognition of Interactions by Tag Extension (SPRITE). These techniques offer unique insights into higher-order chromatin structures by bypassing ligation steps, thus enabling the capture of complex multi-way interactions that are often challenging to resolve with traditional methods. Furthermore, we discuss the integration of chromatin interaction data with other genomic layers through multimodal approaches, including recent advances in single-cell technologies like sci-HiC and scSPRITE, which help unravel the heterogeneity of chromatin architecture in development and disease.

Unraveling the three-dimensional (3D) genome architecture in Neurodevelopmental Disorders (NDDs)

The human genome, comprising millions of pairs of bases, serves as the blueprint of life, encoding instructions for cellular processes. However, genomes are not merely linear sequences; rather, the complex of DNA and histones, known as chromatin, exhibits complex organization across various levels, which profoundly influence gene expression and cellular function. Central to understanding genome organization is the emerging field of three-dimensional (3D) genome studies. Utilizing advanced techniques such as Hi-C, researchers have unveiled non-random dispositions of genomic elements, highlighting their importance in transcriptional regulation and disease mechanisms. Topologically Associating Domains (TADs), that demarcate regions of chromatin with preferential internal interactions, play crucial roles in gene regulation and are increasingly implicated in various diseases such as cancer and schizophrenia. However, their role in Neurodevelopmental Disorders (NDDs) remains poorly understood. Here, we focus on TADs and 3D conservation across the evolution and between cell types in NDDs. The investigation into genome organization and its impact on disease has led to significant breakthroughs in understanding NDDs etiology such ASD (Autism Spectrum Disorder). By elucidating the wide spectrum of ASD manifestations, researchers aim to uncover the underlying genetic and epigenetic factors contributing to its heterogeneity. Moreover, studies linking TAD disruption to NDDs underscore the importance of spatial genome organization in maintaining proper brain development and function. In summary, this review highlights the intricate interplay between genome organization, transcriptional control, and disease pathology, shedding light on fundamental biological processes and offering insights into the mechanisms underlying NDDs like ASD.

Permeable TAD boundaries and their impact on genome-associated functions

TAD boundaries are genomic elements that separate biological processes in neighboring domains by blocking DNA loops that are formed through Cohesin-mediated loop extrusion. Most TAD boundaries consist of arrays of binding sites for the CTCF protein, whose interaction with the Cohesin complex blocks loop extrusion. TAD boundaries are not fully impermeable though and allow a limited amount of inter-TAD loop formation. Based on the reanalysis of Nano-C data, a multicontact Chromosome Conformation Capture assay, we propose a model whereby clustered CTCF binding sites promote the successive stalling of Cohesin and subsequent dissociation from the chromatin. A fraction of Cohesin nonetheless achieves boundary read-through. Due to a constant rate of Cohesin dissociation elsewhere in the genome, the maximum length of inter-TAD loops is restricted though. We speculate that the DNA-encoded organization of stalling sites regulates TAD boundary permeability and discuss implications for enhancer-promoter loop formation and other genomic processes.

Extrachromosomal DNA Associates with Nuclear Condensates and Reorganizes Chromatin Structures to Enhance Oncogenic Transcription

Extrachromosomal, circular DNA (ecDNA) is a prevalent oncogenic alteration in cancer genomes, often associated with aggressive tumor behavior and poor patient outcome. While previous studies proposed a chromatin-based mobile enhancer model for ecDNA-driven oncogenesis, its precise mechanism and impact remains unclear across diverse cancer types. Our study, utilizing advanced multi-omics profiling, epigenetic editing, and imaging approaches in three cancer models, reveals that ecDNA hubs are an integrated part of nuclear condensates and exhibit cancer-type specific chromatin connectivity. Epigenetic silencing of the ecDNA-specific regulatory modules or chemically disrupting liquid-liquid phase separation breaks down ecDNA hubs, displaces MED1 co-activator binding, inhibits oncogenic transcription, and promotes cell death. These findings substantiate the trans -activator function of ecDNA and underscore a structural mechanism driving oncogenesis. This refined understanding expands our views of oncogene regulation and opens potential avenues for novel therapeutic strategies in cancer treatment.

3D chromatin structures associated with ncRNA roX2 for hyperactivation and coactivation across the entire X chromosome

The three-dimensional (3D) organization of chromatin within the nucleus is crucial for gene regulation. However, the 3D architectural features that coordinate the activation of an entire chromosome remain largely unknown. We introduce an omics method, RNA-associated chromatin DNA-DNA interactions, that integrates RNA polymerase II (RNAPII)-mediated regulome with stochastic optical reconstruction microscopy to investigate the landscape of noncoding RNA roX2-associated chromatin topology for gene equalization to achieve dosage compensation. Our findings reveal that roX2 anchors to the target gene transcription end sites (TESs) and spreads in a distinctive boot-shaped configuration, promoting a more open chromatin state for hyperactivation. Furthermore, roX2 arches TES to transcription start sites to enhance transcriptional loops, potentially facilitating RNAPII convoying and connecting proximal promoter-promoter transcriptional hubs for synergistic gene regulation. These TESs cluster as roX2 compartments, surrounded by inactive domains for coactivation of multiple genes within the roX2 territory. In addition, roX2 structures gradually form and scaffold for stepwise coactivation in dosage compensation.

Fly Me to the Micron: Microtechnologies for Drosophila Research

Multicellular model organisms, such as Drosophila melanogaster (fruit fly), are frequently used in a myriad of biological research studies due to their biological significance and global standardization. However, traditional tools used in these studies generally require manual handling, subjective phenotyping, and bulk treatment of the organisms, resulting in laborious experimental protocols with limited accuracy. Advancements in microtechnology over the course of the last two decades have allowed researchers to develop automated, high-throughput, and multifunctional experimental tools that enable novel experimental paradigms that would not be possible otherwise. We discuss recent advances in microtechnological systems developed for small model organisms using D. melanogaster as an example. We critically analyze the state of the field by comparing the systems produced for different applications. Additionally, we suggest design guidelines, operational tips, and new research directions based on the technical and knowledge gaps in the literature. This review aims to foster interdisciplinary work by helping engineers to familiarize themselves with model organisms while presenting the most recent advances in microengineering strategies to biologists.

Regulating epithelial-mesenchymal plasticity from 3D genome organization

Epithelial-mesenchymal transition (EMT) is a dynamic process enabling polarized epithelial cells to acquire mesenchymal features implicated in development and carcinoma progression. As our understanding evolves, it is clear the reversible execution of EMT arises from complex epigenomic regulation involving histone modifications and 3-dimensional (3D) genome structural changes, leading to a cascade of transcriptional events. This review summarizes current knowledge on chromatin organization in EMT, with a focus on hierarchical structures of the 3D genome and chromatin accessibility changes.

Effects of super-enhancers in cancer metastasis: mechanisms and therapeutic targets

Metastasis remains the principal cause of cancer-related lethality despite advancements in cancer treatment. Dysfunctional epigenetic alterations are crucial in the metastatic cascade. Among these, super-enhancers (SEs), emerging as new epigenetic regulators, consist of large clusters of regulatory elements that drive the high-level expression of genes essential for the oncogenic process, upon which cancer cells develop a profound dependency. These SE-driven oncogenes play an important role in regulating various facets of metastasis, including the promotion of tumor proliferation in primary and distal metastatic organs, facilitating cellular migration and invasion into the vasculature, triggering epithelial-mesenchymal transition, enhancing cancer stem cell-like properties, circumventing immune detection, and adapting to the heterogeneity of metastatic niches. This heavy reliance on SE-mediated transcription delineates a vulnerable target for therapeutic intervention in cancer cells. In this article, we review current insights into the characteristics, identification methodologies, formation, and activation mechanisms of SEs. We also elaborate the oncogenic roles and regulatory functions of SEs in the context of cancer metastasis. Ultimately, we discuss the potential of SEs as novel therapeutic targets and their implications in clinical oncology, offering insights into future directions for innovative cancer treatment strategies.

Chromatin image-driven modelling

The challenge of modelling the spatial conformation of chromatin remains an open problem. While multiple data-driven approaches have been proposed, each has limitations. This work introduces two image-driven modelling methods based on the Molecular Dynamics Flexible Fitting (MDFF) approach: the force method and the correlational method. Both methods have already been used successfully in protein modelling. We propose a novel way to employ them for building chromatin models directly from 3D images. This approach is termed image-driven modelling. Additionally, we introduce the initial structure generator, a tool designed to generate optimal starting structures for the proposed algorithms. The methods are versatile and can be applied to various data types, with minor modifications to accommodate new generation imaging techniques.

Single-cell mapping of cell-type specific chromatin architecture in the central nervous system

Determining how chromatin is structured in the nucleus is critical to studying its role in gene regulation. Recent advances in the analysis of single-cell chromatin architecture have considerably improved our understanding of cell-type-specific chromosome conformation and nuclear architecture. In this review, we discuss the methods used for analysis of 3D chromatin conformation, including sequencing-based methods, imaging-based techniques, and computational approaches. We further review the application of these methods in the study of the role of chromatin topology in neural development and disorders.

Statistical modeling and significance estimation of multi-way chromatin contacts with HyperloopFinder

Recent advances in chromatin conformation capture technologies, such as SPRITE and Pore-C, have enabled the detection of simultaneous contacts among multiple chromatin loci. This has made it possible to investigate the cooperative transcriptional regulation involving multiple genes and regulatory elements at the resolution of a single molecule. However, these technologies are unavoidably subject to the random polymer looping effect and technical biases, making it challenging to distinguish genuine regulatory relationships directly from random polymer interactions. Here, we present HyperloopFinder, a method for identifying regulatory multi-way chromatin contacts (hyperloops) by jointly modeling the random polymer looping effect and technical biases to estimate the statistical significance of multi-way contacts. The results show that our model can accurately estimate the expected interaction frequency of multi-way contacts based on the distance distribution of pairwise contacts, revealing that most multi-way contacts can be formed by randomly linking the pairwise contacts adjacent to each other. Moreover, we observed the spatial colocalization of the interaction sites of hyperloops from image-based data. Our results also revealed that hyperloops can function as scaffolds for the cooperation among multiple genes and regulatory elements. In summary, our work contributes novel insights into higher-order chromatin structures and functions and has the potential to enhance our understanding of transcriptional regulation and other cellular processes.

Tracking pairwise genomic loci by the ParB-ParS and Noc-NBS systems in living cells

The dynamics of genomic loci pairs and their interactions are essential for transcriptional regulation and genome organization. However, a robust method for tracking pairwise genomic loci in living cells is lacking. Here we developed a multicolor DNA labeling system, mParSpot (multicolor ParSpot), to track pairs of genomic loci and their interactions in living cells. The mParSpot system is derived from the ParB/ParS in the parABS system and Noc/NBS in its paralogous nucleoid occlusion system. The insertion of 16 base-pair palindromic ParSs or NBSs into the genomic locus allows the cognate binding protein ParB or Noc to spread kilobases of DNA around ParSs or NBSs for loci-specific visualization. We tracked two loci with a genomic distance of 53 kilobases and measured their spatial distance over time. Using the mParSpot system, we labeled the promoter and terminator of the MSI2 gene span 423 kb and measured their spatial distance. We also tracked the promoter and terminator dynamics of the MUC4 gene in living cells. In sum, the mParSpot is a robust and sensitive DNA labeling system for tracking genomic interactions in space and time under physiological or pathological contexts.

Characterizing nascent transcription patterns of PROMPTs, eRNAs, and readthrough transcripts in the ENCODE4 deeply profiled cell lines

Arising as co-products of canonical gene expression, transcription-associated lincRNAs, such as promoter upstream transcripts (PROMPTs), enhancer RNAs (eRNAs), and readthrough (RT) transcripts, are often regarded as byproducts of transcription, although they may be important for the expression of nearby genes. We identified regions of nascent expression of these lincRNA in 16 human cell lines using Bru-seq techniques, and found distinctly regulated patterns of PROMPT, eRNA, and RT transcription using the diverse biochemical approaches in the ENCODE4 deeply profiled cell lines collection. Transcription of these lincRNAs was influenced by sequence-specific features and the local or 3D chromatin landscape. However, these sequence and chromatin features do not describe the full spectrum of lincRNA expression variability we identify, highlighting the complexity of their regulation. This may suggest that transcription-associated lincRNAs are not merely byproducts, but rather that the transcript itself, or the act of its transcription, is important for genomic function.

Interpretable online network dictionary learning for inferring long-range chromatin interactions

Dictionary learning (DL), implemented via matrix factorization (MF), is commonly used in computational biology to tackle ubiquitous clustering problems. The method is favored due to its conceptual simplicity and relatively low computational complexity. However, DL algorithms produce results that lack interpretability in terms of real biological data. Additionally, they are not optimized for graph-structured data and hence often fail to handle them in a scalable manner. In order to address these limitations, we propose a novel DL algorithm called online convex network dictionary learning (online cvxNDL). Unlike classical DL algorithms, online cvxNDL is implemented via MF and designed to handle extremely large datasets by virtue of its online nature. Importantly, it enables the interpretation of dictionary elements, which serve as cluster representatives, through convex combinations of real measurements. Moreover, the algorithm can be applied to data with a network structure by incorporating specialized subnetwork sampling techniques. To demonstrate the utility of our approach, we apply cvxNDL on 3D-genome RNAPII ChIA-Drop data with the goal of identifying important long-range interaction patterns (long-range dictionary elements). ChIA-Drop probes higher-order interactions, and produces data in the form of hypergraphs whose nodes represent genomic fragments. The hyperedges represent observed physical contacts. Our hypergraph model analysis has the objective of creating an interpretable dictionary of long-range interaction patterns that accurately represent global chromatin physical contact maps. Through the use of dictionary information, one can also associate the contact maps with RNA transcripts and infer cellular functions. To accomplish the task at hand, we focus on RNAPII-enriched ChIA-Drop data from Drosophila Melanogaster S2 cell lines. Our results offer two key insights. First, we demonstrate that online cvxNDL retains the accuracy of classical DL (MF) methods while simultaneously ensuring unique interpretability and scalability. Second, we identify distinct collections of proximal and distal interaction patterns involving chromatin elements shared by related processes across different chromosomes, as well as patterns unique to specific chromosomes. To associate the dictionary elements with biological properties of the corresponding chromatin regions, we employ Gene Ontology (GO) enrichment analysis and perform multiple RNA coexpression studies.

Advances in the multimodal analysis of the 3D chromatin structure and gene regulation

Recent studies have demonstrated that the three-dimensional conformation of the chromatin plays a crucial role in gene regulation, with aberrations potentially leading to various diseases. Advanced methodologies have revealed a link between the chromatin conformation and biological function. This review divides these methodologies into sequencing-based and imaging-based methodologies, tracing their development over time. We particularly highlight innovative techniques that facilitate the simultaneous mapping of RNAs, histone modifications, and proteins within the context of the 3D architecture of chromatin. This multimodal integration substantially improves our ability to establish a robust connection between the spatial arrangement of molecular components in the nucleus and their functional roles. Achieving a comprehensive understanding of gene regulation requires capturing diverse data modalities within individual cells, enabling the direct inference of functional relationships between these components. In this context, imaging-based technologies have emerged as an especially promising approach for gathering spatial information across multiple components in the same cell.

3C methods in cancer research: recent advances and future prospects

In recent years, Hi-C technology has revolutionized cancer research by elucidating the mystery of three-dimensional chromatin organization and its role in gene regulation. This paper explored the impact of Hi-C advancements on cancer research by delving into high-resolution techniques, such as chromatin loops, structural variants, haplotype phasing, and extrachromosomal DNA (ecDNA). Distant regulatory elements interact with their target genes through chromatin loops. Structural variants contribute to the development and progression of cancer. Haplotype phasing is crucial for understanding allele-specific genomic rearrangements and somatic clonal evolution in cancer. The role of ecDNA in driving oncogene amplification and drug resistance in cancer cells has also been revealed. These innovations offer a deeper understanding of cancer biology and the potential for personalized therapies. Despite these advancements, challenges, such as the accurate mapping of repetitive sequences and precise identification of structural variants, persist. Integrating Hi-C with multiomics data is key to overcoming these challenges and comprehensively understanding complex cancer genomes. Thus, Hi-C is a powerful tool for guiding precision medicine in cancer research and treatment.

Single-cell multiplex chromatin and RNA interactions in ageing human brain

Dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA1-3. Chromatin complex compositions change during cellular differentiation and ageing, and are expected to be highly heterogeneous among terminally differentiated single cells4-7. Here we introduce the multinucleic acid interaction mapping in single cells (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression and RNA-chromatin associations within individual nuclei. When applied to 14 human frontal cortex samples from older donors, MUSIC delineated diverse cortical cell types and states. We observed that nuclei exhibiting fewer short-range chromatin interactions were correlated with both an 'older' transcriptomic signature and Alzheimer's disease pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci and a promoter tends to be that in which these cis expression quantitative trait loci specifically affect the expression of their target gene. In addition, female cortical cells exhibit highly heterogeneous interactions between XIST non-coding RNA and chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploration of chromatin architecture and transcription at cellular resolution in complex tissues.

Multifaceted roles of cohesin in regulating transcriptional loops

Cohesin is required for chromatin loop formation. However, its precise role in regulating gene transcription remains largely unknown. We investigated the relationship between cohesin and RNA Polymerase II (RNAPII) using single-molecule mapping and live-cell imaging methods in human cells. Cohesin-mediated transcriptional loops were highly correlated with those of RNAPII and followed the direction of gene transcription. Depleting RAD21, a subunit of cohesin, resulted in the loss of long-range (>100 kb) loops between distal (super-)enhancers and promoters of cell-type-specific genes. By contrast, the short-range (<50 kb) loops were insensitive to RAD21 depletion and connected genes that are mostly housekeeping. This result explains why only a small fraction of genes are affected by the loss of long-range chromatin interactions due to cohesin depletion. Remarkably, RAD21 depletion appeared to up-regulate genes located in early initiation zones (EIZ) of DNA replication, and the EIZ signals were amplified drastically without RAD21. Our results revealed new mechanistic insights of cohesin's multifaceted roles in establishing transcriptional loops, preserving long-range chromatin interactions for cell-specific genes, and maintaining timely order of DNA replication.

Single-cell multiplex chromatin and RNA interactions in aging human brain

The dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA (caRNA) 1-3. Chromatin complex compositions change during cellular differentiation and aging, and are expected to be highly heterogeneous among terminally differentiated single cells 4-7. Here we introduce the Multi-Nucleic Acid Interaction Mapping in Single Cell (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression, and RNA-chromatin associations within individual nuclei. Applied to 14 human frontal cortex samples from elderly donors, MUSIC delineates diverse cortical cell types and states. We observed the nuclei exhibiting fewer short-range chromatin interactions are correlated with an "older" transcriptomic signature and with Alzheimer's pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci (cis eQTLs) and a promoter tends to be the cell type where these cis eQTLs specifically affect their target gene's expression. Additionally, the female cortical cells exhibit highly heterogeneous interactions between the XIST non-coding RNA and Chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploring chromatin architecture and transcription at cellular resolution in complex tissues.

Computational methods for analysing multiscale 3D genome organization

Recent progress in whole-genome mapping and imaging technologies has enabled the characterization of the spatial organization and folding of the genome in the nucleus. In parallel, advanced computational methods have been developed to leverage these mapping data to reveal multiscale three-dimensional (3D) genome features and to provide a more complete view of genome structure and its connections to genome functions such as transcription. Here, we discuss how recently developed computational tools, including machine-learning-based methods and integrative structure-modelling frameworks, have led to a systematic, multiscale delineation of the connections among different scales of 3D genome organization, genomic and epigenomic features, functional nuclear components and genome function. However, approaches that more comprehensively integrate a wide variety of genomic and imaging datasets are still needed to uncover the functional role of 3D genome structure in defining cellular phenotypes in health and disease.

Spatial chromatin accessibility sequencing resolves high-order spatial interactions of epigenomic markers

As the genome is organized into a three-dimensional structure in intracellular space, epigenomic information also has a complex spatial arrangement. However, most epigenetic studies describe locations of methylation marks, chromatin accessibility regions, and histone modifications in the horizontal dimension. Proper spatial epigenomic information has rarely been obtained. In this study, we designed spatial chromatin accessibility sequencing (SCA-seq) to resolve the genome conformation by capturing the epigenetic information in single-molecular resolution while simultaneously resolving the genome conformation. Using SCA-seq, we are able to examine the spatial interaction of chromatin accessibility (e.g. enhancer-promoter contacts), CpG island methylation, and spatial insulating functions of the CCCTC-binding factor. We demonstrate that SCA-seq paves the way to explore the mechanism of epigenetic interactions and extends our knowledge in 3D packaging of DNA in the nucleus.

A Lightweight Framework For Chromatin Loop Detection at the Single-Cell Level

Single-cell Hi-C (scHi-C) has made it possible to analyze chromatin organization at the single-cell level. However, scHi-C experiments generate inherently sparse data, which poses a challenge for loop calling methods. The existing approach performs significance tests across the imputed dense contact maps, leading to substantial computational overhead and loss of information at the single-cell level. To overcome this limitation, a lightweight framework called scGSLoop is proposed, which sets a new paradigm for scHi-C loop calling by adapting the training and inferencing strategies of graph-based deep learning to leverage the sequence features and 1D positional information of genomic loci. With this framework, sparsity is no longer a challenge, but rather an advantage that the model leverages to achieve unprecedented computational efficiency. Compared to existing methods, scGSLoop makes more accurate predictions and is able to identify more loops that have the potential to play regulatory roles in genome functioning. Moreover, scGSLoop preserves single-cell information by identifying a distinct group of loops for each individual cell, which not only enables an understanding of the variability of chromatin looping states between cells, but also allows scGSLoop to be extended for the investigation of multi-connected hubs and their underlying mechanisms.

Technological advances in probing 4D genome organization

The last two decades of work on chromosome conformation in eukaryotic nuclei have revealed a complex and highly regulated hierarchy of architectural features, from self-associating domains and compartmental interactions to locus-specific loops. Recent findings have shown that these structures are dynamic and heterogeneous, with emerging insights into the factors that shape them and implications for the control of transcription and other nuclear processes. Here, we review the latest advances in the DNA sequencing- and microscopy-based technologies for probing these features in space and time (4D) and discuss how they have been combined with complementary approaches such as genetic perturbations, protein and RNA measurements, and modeling to gain mechanistic insights about genome regulation across space and time.

scNanoHi-C: a single-cell long-read concatemer sequencing method to reveal high-order chromatin structures within individual cells

The high-order three-dimensional (3D) organization of regulatory genomic elements provides a topological basis for gene regulation, but it remains unclear how multiple regulatory elements across the mammalian genome interact within an individual cell. To address this, herein, we developed scNanoHi-C, which applies Nanopore long-read sequencing to explore genome-wide proximal high-order chromatin contacts within individual cells. We show that scNanoHi-C can reliably and effectively profile 3D chromatin structures and distinguish structure subtypes among individual cells. This method could also be used to detect genomic variations, including copy-number variations and structural variations, as well as to scaffold the de novo assembly of single-cell genomes. Notably, our results suggest that extensive high-order chromatin structures exist in active chromatin regions across the genome, and multiway interactions between enhancers and their target promoters were systematically identified within individual cells. Altogether, scNanoHi-C offers new opportunities to investigate high-order 3D genome structures at the single-cell level.

ScSmOP: a universal computational pipeline for single-cell single-molecule multiomics data analysis

Single-cell multiomics techniques have been widely applied to detect the key signature of cells. These methods have achieved a single-molecule resolution and can even reveal spatial localization. These emerging methods provide insights elucidating the features of genomic, epigenomic and transcriptomic heterogeneity in individual cells. However, they have given rise to new computational challenges in data processing. Here, we describe Single-cell Single-molecule multiple Omics Pipeline (ScSmOP), a universal pipeline for barcode-indexed single-cell single-molecule multiomics data analysis. Essentially, the C language is utilized in ScSmOP to set up spaced-seed hash table-based algorithms for barcode identification according to ligation-based barcoding data and synthesis-based barcoding data, followed by data mapping and deconvolution. We demonstrate high reproducibility of data processing between ScSmOP and published pipelines in comprehensive analyses of single-cell omics data (scRNA-seq, scATAC-seq, scARC-seq), single-molecule chromatin interaction data (ChIA-Drop, SPRITE, RD-SPRITE), single-cell single-molecule chromatin interaction data (scSPRITE) and spatial transcriptomic data from various cell types and species. Additionally, ScSmOP shows more rapid performance and is a versatile, efficient, easy-to-use and robust pipeline for single-cell single-molecule multiomics data analysis.

Multi-feature clustering of CTCF binding creates robustness for loop extrusion blocking and Topologically Associating Domain boundaries

Topologically Associating Domains (TADs) separate vertebrate genomes into insulated regulatory neighborhoods that focus genome-associated processes. TADs are formed by Cohesin-mediated loop extrusion, with many TAD boundaries consisting of clustered binding sites of the CTCF insulator protein. Here we determine how this clustering of CTCF binding contributes to the blocking of loop extrusion and the insulation between TADs. We identify enrichment of three features of CTCF binding at strong TAD boundaries, consisting of strongly bound and closely spaced CTCF binding peaks, with a further enrichment of DNA-binding motifs within these peaks. Using multi-contact Nano-C analysis in cells with normal and perturbed CTCF binding, we establish that individual CTCF binding sites contribute to the blocking of loop extrusion, but in an incomplete manner. When clustered, individual CTCF binding sites thus create a stepwise insulation between neighboring TADs. Based on these results, we propose a model whereby multiple instances of temporal loop extrusion blocking create strong insulation between TADs.

EpiMCI: Predicting Multi-Way Chromatin Interactions from Epigenomic Signals

The recently emerging high-throughput Pore-C (HiPore-C) can identify whole-genome high-order chromatin multi-way interactions with an ultra-high output, contributing to deciphering three-dimensional (3D) genome organization. However, it also brings new challenges to relevant data analysis. To alleviate this problem, we proposed the EpiMCI, a model for multi-way chromatin interaction prediction based on a hypergraph neural network with epigenomic signals as the input. The EpiMCI integrated separate hyperedge representations with coupling hyperedge information and obtained AUCs of 0.981 and 0.984 in the GM12878 and K562 datasets, respectively, which outperformed the current available method. Moreover, the EpiMCI can be applied to denoise the HiPore-C data and improve the data quality efficiently. Furthermore, the vertex embeddings extracted from the EpiMCI reflected the global chromatin architecture accurately. The principal component analysis suggested that it was well aligned with the activities of genomic regions at the chromatin compartment level. Taken together, the EpiMCI can accurately predict multi-way chromatin interactions and can be applied to studies relying on chromatin architecture.

Spatial and temporal organization of the genome: Current state and future aims of the 4D nucleome project

The four-dimensional nucleome (4DN) consortium studies the architecture of the genome and the nucleus in space and time. We summarize progress by the consortium and highlight the development of technologies for (1) mapping genome folding and identifying roles of nuclear components and bodies, proteins, and RNA, (2) characterizing nuclear organization with time or single-cell resolution, and (3) imaging of nuclear organization. With these tools, the consortium has provided over 2,000 public datasets. Integrative computational models based on these data are starting to reveal connections between genome structure and function. We then present a forward-looking perspective and outline current aims to (1) delineate dynamics of nuclear architecture at different timescales, from minutes to weeks as cells differentiate, in populations and in single cells, (2) characterize cis-determinants and trans-modulators of genome organization, (3) test functional consequences of changes in cis- and trans-regulators, and (4) develop predictive models of genome structure and function.

Evaluating the role of the nuclear microenvironment in gene function by population-based modeling

The nuclear folding of chromosomes relative to nuclear bodies is an integral part of gene function. Here, we demonstrate that population-based modeling-from ensemble Hi-C data-provides a detailed description of the nuclear microenvironment of genes and its role in gene function. We define the microenvironment by the subnuclear positions of genomic regions with respect to nuclear bodies, local chromatin compaction, and preferences in chromatin compartmentalization. These structural descriptors are determined in single-cell models, thereby revealing the structural variability between cells. We demonstrate that the microenvironment of a genomic region is linked to its functional potential in gene transcription, replication, and chromatin compartmentalization. Some chromatin regions feature a strong preference for a single microenvironment, due to association with specific nuclear bodies in most cells. Other chromatin shows high structural variability, which is a strong indicator of functional heterogeneity. Moreover, we identify specialized nuclear microenvironments, which distinguish chromatin in different functional states and reveal a key role of nuclear speckles in chromosome organization. We demonstrate that our method produces highly predictive three-dimensional genome structures, which accurately reproduce data from a variety of orthogonal experiments, thus considerably expanding the range of Hi-C data analysis.

Activation, decommissioning, and dememorization: enhancers in a life cycle

Spatiotemporal regulation of cell type-specific gene expression is essential to convert a zygote into a complex organism that contains hundreds of distinct cell types. A class of cis-regulatory elements called enhancers, which have the potential to enhance target gene transcription, are crucial for precise gene expression programs during development. Following decades of research, many enhancers have been discovered and how enhancers become activated has been extensively studied. However, the mechanisms underlying enhancer silencing are less well understood. We review current understanding of enhancer decommissioning and dememorization, both of which enable enhancer silencing. We highlight recent progress from genome-wide perspectives that have revealed the life cycle of enhancers and how its dynamic regulation underlies cell fate transition, development, cell regeneration, and epigenetic reprogramming.

An upgraded method of high-throughput chromosome conformation capture (Hi-C 3.0) in cotton (Gossypium spp.)

High-throughput chromosome conformation capture (Hi-C) technology has been applied to explore the chromatin interactions and shed light on the biological functions of three-dimensional genomic features. However, it remains challenging to guarantee the high quality of Hi-C library in plants and hence the reliable capture of chromatin structures, especially loops, due to insufficient fragmentation and low efficiency of proximity ligations. To overcome these deficiencies, we optimized the parameters of the Hi-C protocol, principally the cross-linking agents and endonuclease fragmentation strategy. The double cross-linkers (FA+DSG) and double restriction enzymes (DpnII+DdeI) were utilized. Thus, a systematic in situ Hi-C protocol was designed using plant tissues embedded with comprehensive quality controls to monitor the library construction. This upgraded method, termed Hi-C 3.0, was applied to cotton leaves for trial. In comparison with the conventional Hi-C 2.0, Hi-C 3.0 can obtain more than 50% valid contacts at a given sequencing depth to improve the signal-to-noise ratio. Hi-C 3.0 can furthermore enhance the capturing of loops almost as twice as that of Hi-C 2.0. In addition, Hi-C 3.0 showed higher efficiency of compartment detection and identified compartmentalization more accurately. In general, Hi-C 3.0 contributes to the advancement of the Hi-C method in plants by promoting its capability on decoding the chromatin organization.

New discoveries in the field of metabolism by applying single-cell and spatial omics

Single-cell multi-Omics (SCM-Omics) and spatial multi-Omics (SM-Omics) technologies provide state-of-the-art methods for exploring the composition and function of cell types in tissues/organs. Since its emergence in 2009, single-cell RNA sequencing (scRNA-seq) has yielded many groundbreaking new discoveries. The combination of this method with the emergence and development of SM-Omics techniques has been a pioneering strategy in neuroscience, developmental biology, and cancer research, especially for assessing tumor heterogeneity and T-cell infiltration. In recent years, the application of these methods in the study of metabolic diseases has also increased. The emerging SCM-Omics and SM-Omics approaches allow the molecular and spatial analysis of cells to explore regulatory states and determine cell fate, and thus provide promising tools for unraveling heterogeneous metabolic processes and making them amenable to intervention. Here, we review the evolution of SCM-Omics and SM-Omics technologies, and describe the progress in the application of SCM-Omics and SM-Omics in metabolism-related diseases, including obesity, diabetes, nonalcoholic fatty liver disease (NAFLD) and cardiovascular disease (CVD). We also conclude that the application of SCM-Omics and SM-Omics approaches can help resolve the molecular mechanisms underlying the pathogenesis of metabolic diseases in the body and facilitate therapeutic measures for metabolism-related diseases. This review concludes with an overview of the current status of this emerging field and the outlook for its future.

Advancements in Focal Amplification Detection in Tumor/Liquid Biopsies and Emerging Clinical Applications

Focal amplifications (FAs) are crucial in cancer research due to their significant diagnostic, prognostic, and therapeutic implications. FAs manifest in various forms, such as episomes, double minute chromosomes, and homogeneously staining regions, arising through different mechanisms and mainly contributing to cancer cell heterogeneity, the leading cause of drug resistance in therapy. Numerous wet-lab, mainly FISH, PCR-based assays, next-generation sequencing, and bioinformatics approaches have been set up to detect FAs, unravel the internal structure of amplicons, assess their chromatin compaction status, and investigate the transcriptional landscape associated with their occurrence in cancer cells. Most of them are tailored for tumor samples, even at the single-cell level. Conversely, very limited approaches have been set up to detect FAs in liquid biopsies. This evidence suggests the need to improve these non-invasive investigations for early tumor detection, monitoring disease progression, and evaluating treatment response. Despite the potential therapeutic implications of FAs, such as, for example, the use of HER2-specific compounds for patients with ERBB2 amplification, challenges remain, including developing selective and effective FA-targeting agents and understanding the molecular mechanisms underlying FA maintenance and replication. This review details a state-of-the-art of FA investigation, with a particular focus on liquid biopsies and single-cell approaches in tumor samples, emphasizing their potential to revolutionize the future diagnosis, prognosis, and treatment of cancer patients.

HiCLift: a fast and efficient tool for converting chromatin interaction data between genome assemblies

MOTIVATION

With the continuous effort to improve the quality of human reference genome and the generation of more and more personal genomes, the conversion of genomic coordinates between genome assemblies is critical in many integrative and comparative studies. While tools have been developed for such task for linear genome signals such as ChIP-Seq, no tool exists to convert genome assemblies for chromatin interaction data, despite the importance of three-dimensional genome organization in gene regulation and disease.

RESULTS

Here, we present HiCLift, a fast and efficient tool that can convert the genomic coordinates of chromatin contacts such as Hi-C and Micro-C from one assembly to another, including the latest T2T-CHM13 genome. Comparing with the strategy of directly remapping raw reads to a different genome, HiCLift runs on average 42 times faster (hours vs. days), while outputs nearly identical contact matrices. More importantly, as HiCLift does not need to remap the raw reads, it can directly convert human patient sample data, where the raw sequencing reads are sometimes hard to acquire or not available.

AVAILABILITY AND IMPLEMENTATION

HiCLift is publicly available at https://github.com/XiaoTaoWang/HiCLift.

Analysis of super-enhancer using machine learning and its application to medical biology

The analysis of super-enhancers (SEs) has recently attracted attention in elucidating the molecular mechanisms of cancer and other diseases. SEs are genomic structures that strongly induce gene expression and have been reported to contribute to the overexpression of oncogenes. Because the analysis of SEs and integrated analysis with other data are performed using large amounts of genome-wide data, artificial intelligence technology, with machine learning at its core, has recently begun to be utilized. In promoting precision medicine, it is important to consider information from SEs in addition to genomic data; therefore, machine learning technology is expected to be introduced appropriately in terms of building a robust analysis platform with a high generalization performance. In this review, we explain the history and principles of SE, and the results of SE analysis using state-of-the-art machine learning and integrated analysis with other data are presented to provide a comprehensive understanding of the current status of SE analysis in the field of medical biology. Additionally, we compared the accuracy between existing machine learning methods on the benchmark dataset and attempted to explore the kind of data preprocessing and integration work needed to make the existing algorithms work on the benchmark dataset. Furthermore, we discuss the issues and future directions of current SE analysis.

Appressoria Formation in Phytopathogenic Fungi Suppressed by Antimicrobial Peptides and Hybrid Peptides from Black Soldier Flies

Antimicrobial peptides (AMPs) from black solider flies (Hermetia illucens, BSF) exhibiting broad-spectrum antimicrobial activity are the most promising green substitutes for preventing the infection of phytopathogenic fungi; therefore, AMPs have been a focal topic of research. Recently, many studies have focused on the antibacterial activities of BSF AMPs against animal pathogens; however, currently, their antifungal activities against phytopathogenic fungi remain unclear. In this study, 7 AMPs selected from 34 predicted AMPs based on BSF metagenomics were artificially synthesized. When conidia from the hemibiotrophic phytopathogenic fungi Magnaporthe oryzae and Colletotrichum acutatum were treated with the selected AMPs, three selected AMPs-CAD1, CAD5, and CAD7-showed high appressorium formation inhibited by lengthened germ tubes. Additionally, the MIC₅₀ concentrations of the inhibited appressorium formations were 40 μM, 43 μM, and 43 μM for M. oryzae, while 51 μM, 49 μM, and 44 μM were observed for C. acutatum, respectively. A tandem hybrid AMP named CAD-Con comprising CAD1, CAD5, and CAD7 significantly enhanced antifungal activities, and the MIC₅₀ concentrations against M. oryzae and C. acutatum were 15 μM and 22 μM, respectively. In comparison with the wild type, they were both significantly reduced in terms of virulence when infection assays were performed using the treated conidia of M. oryzae or C. acutatum by CAD1, CAD5, CAD7, or CAD-Con. Meanwhile, their expression levels of CAD1, CAD5, and CAD7 could also be activated and significantly increased after the BSF larvae were treated with the conidia of M. oryzae or C. acutatum, respectively. To our knowledge, the antifungal activities of BSF AMPs against plant pathogenic fungi, which help us to seek potential AMPs with antifungal activities, provide proof of the effectiveness of green control strategies for crop production.

Single-cell detection of primary transcripts, their genomic loci and nuclear factors by 3D immuno-RNA/DNA FISH in T cells

Over the past decades, it has become increasingly clear that higher order chromatin folding and organization within the nucleus is involved in the regulation of genome activity and serves as an additional epigenetic mechanism that modulates cellular functions and gene expression programs in diverse biological processes. In particular, dynamic allelic interactions and nuclear locations can be of functional importance during the process of lymphoid differentiation and the regulation of immune responses. Analyses of the proximity between chromatin and/or nuclear regions can be performed on populations of cells with high-throughput sequencing approaches such as chromatin conformation capture ("3C"-based) or DNA adenine methyltransferase identification (DamID) methods, or, in individual cells, by the simultaneous visualization of genomic loci, their primary transcripts and nuclear compartments within the 3-dimensional nuclear space using Fluorescence In Situ Hybridization (FISH) and immunostaining. Here, we present a detailed protocol to simultaneously detect nascent RNA transcripts (3D RNA FISH), their genomic loci (3D DNA FISH) and/or their chromosome territories (CT paint DNA FISH) combined with the antibody-based detection of various nuclear factors (immunofluorescence). We delineate the application and effectiveness of this robust and reproducible protocol in several murine T lymphocyte subtypes (from differentiating thymic T cells, to activated splenic and peripheral T cells) as well as other murine cells, including embryonic stem cells, B cells, megakaryocytes and macrophages.

3D enhancer-promoter interactions and multi-connected hubs: Organizational principles and functional roles

The spatiotemporal control of gene expression is dependent on the activity of cis-acting regulatory sequences, called enhancers, which regulate target genes over variable genomic distances and, often, by skipping intermediate promoters, suggesting mechanisms that control enhancer-promoter communication. Recent genomics and imaging technologies have revealed highly complex enhancer-promoter interaction networks, whereas advanced functional studies have started interrogating the forces behind the physical and functional communication among multiple enhancers and promoters. In this review, we first summarize our current understanding of the factors involved in enhancer-promoter communication, with a particular focus on recent papers that have revealed new layers of complexities to old questions. In the second part of the review, we focus on a subset of highly connected enhancer-promoter "hubs" and discuss their potential functions in signal integration and gene regulation, as well as the putative factors that might determine their dynamics and assembly.

The 3D genome and its impacts on human health and disease

Eukaryotic genomes are highly compacted in the cell nucleus. Two loci separated by a long linear distance can be brought into proximity in space through DNA-binding proteins and RNAs, which contributes profoundly to the regulation of gene expression. Recent technology advances have enabled the development and application of the chromosome conformation capture (3C) technique and a host of 3C-based methods that enable genome-scale investigations into changes in chromatin high-order structures during diverse physiological processes and diseases. In this review, we introduce 3C-based technologies and discuss how they can be utilized to glean insights into the impacts of three-dimensional (3D) genome organization in normal physiological and disease processes.

Women’s contribution in understanding how topoisomerases, supercoiling, and transcription control genome organization

One of the biggest paradoxes in biology is that human genome is roughly 2 m long, while the nucleus containing it is almost one million times smaller. To fit into the nucleus, DNA twists, bends and folds into several hierarchical levels of compaction. Still, DNA has to maintain a high degree of accessibility to be readily replicated and transcribed by proteins. How compaction and accessibility co-exist functionally in human cells is still a matter of debate. Here, we discuss how the torsional stress of the DNA helix acts as a buffer, regulating both chromatin compaction and accessibility. We will focus on chromatin supercoiling and on the emerging role of topoisomerases as pivotal regulators of genome organization. We will mainly highlight the major breakthrough studies led by women, with the intention of celebrating the work of this group that remains a minority within the scientific community.

High-throughput Pore-C reveals the single-allele topology and cell type-specificity of 3D genome folding

Canonical three-dimensional (3D) genome structures represent the ensemble average of pairwise chromatin interactions but not the single-allele topologies in populations of cells. Recently developed Pore-C can capture multiway chromatin contacts that reflect regional topologies of single chromosomes. By carrying out high-throughput Pore-C, we reveal extensive but regionally restricted clusters of single-allele topologies that aggregate into canonical 3D genome structures in two human cell types. We show that fragments in multi-contact reads generally coexist in the same TAD. In contrast, a concurrent significant proportion of multi-contact reads span multiple compartments of the same chromatin type over megabase distances. Synergistic chromatin looping between multiple sites in multi-contact reads is rare compared to pairwise interactions. Interestingly, the single-allele topology clusters are cell type-specific even inside highly conserved TADs in different types of cells. In summary, HiPore-C enables global characterization of single-allele topologies at an unprecedented depth to reveal elusive genome folding principles.

3D genomics and its applications in precision medicine

Three-dimensional (3D) genomics is an emerging discipline that studies the three-dimensional structure of chromatin and the three-dimensional and functions of genomes. It mainly studies the three-dimensional conformation and functional regulation of intranuclear genomes, such as DNA replication, DNA recombination, genome folding, gene expression regulation, transcription factor regulation mechanism, and the maintenance of three-dimensional conformation of genomes. Self-chromosomal conformation capture (3C) technology has been developed, and 3D genomics and related fields have developed rapidly. In addition, chromatin interaction analysis techniques developed by 3C technologies, such as paired-end tag sequencing (ChIA-PET) and whole-genome chromosome conformation capture (Hi-C), enable scientists to further study the relationship between chromatin conformation and gene regulation in different species. Thus, the spatial conformation of plant, animal, and microbial genomes, transcriptional regulation mechanisms, interaction patterns of chromosomes, and the formation mechanism of spatiotemporal specificity of genomes are revealed. With the help of new experimental technologies, the identification of key genes and signal pathways related to life activities and diseases is sustaining the rapid development of life science, agriculture, and medicine. In this paper, the concept and development of 3D genomics and its application in agricultural science, life science, and medicine are introduced, which provides a theoretical basis for the study of biological life processes.

A prolific and robust whole-genome genotyping method using PCR amplification via primer-template mismatched annealing

Whole-genome genotyping methods are important for breeding. However, it has been challenging to develop a robust method for simultaneous foreground and background genotyping that can easily be adapted to different genes and species. In our study, we accidently discovered that in adapter ligation-mediated PCR, the amplification by primer-template mismatched annealing (PTMA) along the genome could generate thousands of stable PCR products. Based on this observation, we consequently developed a novel method for simultaneous foreground and background integrated genotyping by sequencing (FBI-seq) using one specific primer, in which foreground genotyping is performed by primer-template perfect annealing (PTPA), while background genotyping employs PTMA. Unlike DNA arrays, multiple PCR, or genome target enrichments, FBI-seq requires little preliminary work for primer design and synthesis, and it is easily adaptable to different foreground genes and species. FBI-seq therefore provides a prolific, robust, and accurate method for simultaneous foreground and background genotyping to facilitate breeding in the post-genomics era.