TADs and Their Borders: Free Movement or Building a Wall?

The human genome is segmented into topologically associating domains (TADs), but the role of this conserved organization during transient changes in gene expression is not known. Here we describe the distribution of progestin-induced chromatin modifications and changes in transcriptional activity over TADs in T47D breast cancer cells. Using ChIP-seq (chromatin immunoprecipitation combined with high-throughput sequencing), Hi-C (chromosome capture followed by high-throughput sequencing), and three-dimensional (3D) modeling techniques, we found that the borders of the ∼ 2000 TADs in these cells are largely maintained after hormone treatment and that up to 20% of the TADs could be considered as discrete regulatory units where the majority of the genes are either transcriptionally activated or repressed in a coordinated fashion. The epigenetic signatures of the TADs are homogeneously modified by hormones in correlation with the transcriptional changes. Hormone-induced changes in gene activity and chromatin remodeling are accompanied by differential structural changes for activated and repressed TADs, as reflected by specific and opposite changes in the strength of intra-TAD interactions within responsive TADs. Indeed, 3D modeling of the Hi-C data suggested that the structure of TADs was modified upon treatment. The differential responses of TADs to progestins and estrogens suggest that TADs could function as "regulons" to enable spatially proximal genes to be coordinately transcribed in response to hormones.

BackgroundGene expression has long been known to be influenced by the relative proximity of DNA regulatory elements. Topologically associating domains (TADs) are self-interacting genomic regions involved in regulating gene expression by controlling the proximity of these elements. Prior studies of TADs and their biological roles have revealed correlations between TAD changes and cellular differentiation. Here, we used Hi-C and RNA-seq data to correlate TCR-induced changes in TAD structure and gene expression in human CD4+ T cells.ResultsWe developed a pipeline, Differentially Expressed Gene Enrichment Finder (DEGEF), that identifies regions of differentially expressed gene enrichment. Using DEGEF, we found that TCR-regulated genes cluster non-uniformly across the genome and that these clusters preferentially localized in regions of TAD rearrangement. Interestingly, clusters of upregulated genes preferentially formed new Hi-C contacts compared to downregulated clusters, suggesting that TCR-activated CD4+ T cells may regulate genes by changing stimulatory contacts rather than inhibitory contacts.ConclusionsOur observations support a significant relationship between TAD rearrangements and changes in local gene expression. These findings indicate potentially important roles for TAD rearrangements in shaping their local regulatory environments and thus driving differential expression of nearby genes during CD4+ T cell activation. Moreover, they provide new insights into global mechanisms that regulate gene expression.

Animal interphase chromosomes are organized into topologically associating domains (TADs). How TADs are formed is not fully understood. Here, we combined high-throughput chromosome conformation capture and gene silencing to obtain insights into TAD dynamics in Xenopus tropicalis embryos. First, TAD establishment in X. tropicalis is similar to that in mice and flies and does not depend on zygotic genome transcriptional activation. This process is followed by further refinements in active and repressive chromatin compartments and the appearance of loops and stripes. Second, within TADs, higher self-interaction frequencies at one end of the boundary are associated with higher DNA occupancy of the architectural proteins CTCF and Rad21. Third, the chromatin remodeling factor ISWI is required for de novo TAD formation. Finally, TAD structures are variable in different tissues. Our work shows that X. tropicalis is a powerful model for chromosome architecture analysis and suggests that chromatin remodeling plays an essential role in de novo TAD establishment.

Eukaryotic genomes are organized within nuclei in three-dimensional space, forming structures such as loops, topologically associating domains (TADs), and chromosome territories. This 3D architecture impacts gene regulation and development, stress responses, and disease. However, current methods to infer these 3D structures from genomic data have multiple drawbacks, including varying outcomes depending on the resolution of the analysis and sequencing depth, qualitative outputs that limit statistical comparisons, and insufficient insight into structure frequency within samples. These challenges hinder rigorous comparisons of 3D properties across genomes, conditions, or species. To overcome these issues, we developed WaveTAD, a wavelet transform-based method that provides a resolution-free, probabilistic, and hierarchical description of 3D organization. WaveTAD generates TAD strengths, capturing the variable frequency of intrachromosomal interactions within samples, and shows increased accuracy and sensitivity over existing methods. We applied WaveTAD to multiple datasets from Drosophila, mouse, and humans to illustrate new biological insights that our more sensitive and quantitative approach provides, such as the widespread presence of embryonic 3D organization before zygotic genome activation, the effect of multiple CTCF units on the stability of loops and TADs, and the association between gene expression and TAD structures in COVID-19 patients or sex-specific transcription in Drosophila.

Mammalian genomes are partitioned into domains that replicate in a defined temporal order. These domains can replicate at similar times in all cell types (constitutive) or at cell type-specific times (developmental). Genome-wide chromatin conformation capture (Hi-C) has revealed sub-megabase topologically associating domains (TADs), which are the structural counterparts of replication domains. Hi-C also segregates inter-TAD contacts into defined 3D spatial compartments that align precisely to genome-wide replication timing profiles. Determinants of the replication-timing program are re-established during early G1 phase of each cell cycle and lost in G2 phase, but it is not known when TAD structure and inter-TAD contacts are re-established after their elimination during mitosis. Here, we use multiplexed 4C-seq to study dynamic changes in chromatin organization during early G1. We find that both establishment of TADs and their compartmentalization occur during early G1, within the same time frame as establishment of the replication-timing program. Once established, this 3D organization is preserved either after withdrawal into quiescence or for the remainder of interphase including G2 phase, implying 3D structure is not sufficient to maintain replication timing. Finally, we find that developmental domains are less well compartmentalized than constitutive domains and display chromatin properties that distinguish them from early and late constitutive domains. Overall, this study uncovers a strong connection between chromatin re-organization during G1, establishment of replication timing, and its developmental control.

Most publicly accessible single-cell Hi-C data are sparse and cannot reach a higher resolution. Therefore, learning latent representations (bin-specific embeddings) of sparse single-cell Hi-C matrices would provide us with a novel way of mining valuable information hidden in the limited number of single-cell Hi-C contacts. We present scHiCEmbed, an unsupervised computational method for learning bin-specific embeddings of single-cell Hi-C data, and the computational system is applied to the tasks of 3D structure reconstruction of whole genomes and detection of topologically associating domains (TAD). The only input of scHiCEmbed is a raw or scHiCluster-imputed single-cell Hi-C matrix. The main process of scHiCEmbed is to embed each node/bin in a higher dimensional space using graph auto-encoders. The learned n-by-3 bin-specific embedding/latent matrix is considered the final reconstructed 3D genome structure. For TAD detection, we use constrained hierarchical clustering on the latent matrix to classify bins: S_Dbw is used to determine the optimal number of clusters, and each cluster is considered as one potential TAD. Our reconstructed 3D structures for individual chromatins at different cell stages reveal the expanding process of chromatins during the cell cycle. We observe that the TADs called from single-cell Hi-C data are not shared across individual cells and that the TAD boundaries called from raw or imputed single-cell Hi-C are significantly different from those called from bulk Hi-C, confirming the cell-to-cell variability in terms of TAD definitions. The source code for scHiCEmbed is publicly available, and the URL can be found in the conclusion section.

Topologically associated domains (TADs) represent essential units constituting chromatin’s intricate three-dimensional spatial organization. TADs are stably present across cell types and species, and their influence on vital biological processes, such as gene expression, DNA replication, and chromosomal translocation, underscores their significance. Accordingly, the identification of TADs within the Hi-C interaction matrix is a key point in three-dimensional genomics. TADs manifest as contiguous blocks along the diagonal of the Hi-C interaction matrix, which are characterized by dense interactions within blocks and sparse interactions between blocks. An optimization method is proposed to enhance Hi-C interaction matrix data using the empirical mode decomposition method, which requires no prior knowledge and adaptively decomposes Hi-C data into a sum of multiple eigenmodal functions via exploiting the inherent characteristics of variations in the input Hi-C data. We identify TADs within the optimized data and compared the results with five commonly used TAD detection methods, namely the Directionality Index (DI), Interaction Isolation (IS), HiCKey, HiCDB, and TopDom. The results demonstrate the universality and efficiency of the proposed method, highlighting its potential as a valuable tool in TAD identification.

Genomic DNA is folded into loops and topologically associating domains (TADs), which serve important structural and regulatory roles. It has been proposed that these genomic structures are formed by a loop extrusion process, which is mediated by structural maintenance of chromosomes (SMC) protein complexes. Recent single-molecule studies have shown that the SMC complexes condensin and cohesin are indeed able to extrude DNA into loops. In this Review, we discuss how the loop extrusion hypothesis can explain key features of genome architecture; cellular functions of loop extrusion, such as separation of replicated DNA molecules, facilitation of enhancer-promoter interactions and immunoglobulin gene recombination; and what is known about the mechanism of loop extrusion and its regulation, for example, by chromatin boundaries that depend on the DNA binding protein CTCF. We also discuss how the loop extrusion hypothesis has led to a paradigm shift in our understanding of both genome architecture and the functions of SMC complexes.

BackgroundHi-C data have been widely used to reconstruct chromosomal three-dimensional (3D) structures. One of the key limitations of Hi-C is the unclear relationship between spatial distance and the number of Hi-C contacts. Many methods used a fixed parameter when converting the number of Hi-C contacts to wish distances. However, a single parameter cannot properly explain the relationship between wish distances and genomic distances or the locations of topologically associating domains (TADs).ResultsWe have addressed one of the key issues of using Hi-C data, that is, the unclear relationship between spatial distances and the number of Hi-C contacts, which is crucial to understand significant biological functions, such as the enhancer-promoter interactions. Specifically, we developed a new method to infer this converting parameter and pairwise Euclidean distances based on the topology of the Hi-C complex network (HiCNet). The inferred distances were modeled by clustering coefficient and multiple other types of constraints. We found that our inferred distances between bead-pairs within the same TAD were apparently smaller than those distances between bead-pairs from different TADs. Our inferred distances had a higher correlation with fluorescence in situ hybridization (FISH) data, fitted the localization patterns of Xist transcripts on DNA, and better matched 156 pairs of protein-enabled long-range chromatin interactions detected by ChIA-PET. Using the inferred distances and another round of optimization, we further reconstructed 40 kb high-resolution 3D chromosomal structures of mouse male ES cells. The high-resolution structures successfully illustrate TADs and DNA loops (peaks in Hi-C contact heatmaps) that usually indicate enhancer-promoter interactions.ConclusionsWe developed a novel method to infer the wish distances between DNA bead-pairs from Hi-C contacts. High-resolution 3D structures of chromosomes were built based on the newly-inferred wish distances. This whole process has been implemented as a tool named HiCNet, which is publicly available at http://dna.cs.miami.edu/HiCNet/.

Topologically associating domains (TADs) are fundamental units of 3D genomes and play essential roles in gene regulation. Hi-C data suggests a hierarchical organization of TADs. Accurately annotating nested TADs from Hi-C data remains challenging, both in terms of the precise identification of boundaries and the correct inference of hierarchies. While domain boundary is relatively well conserved across cells, few approaches have taken advantage of this fact. Here, we present RobusTAD to annotate TAD hierarchies. It incorporates additional Hi-C data to refine boundaries annotated from the study sample. RobusTAD outperforms existing tools at boundary and domain annotation across several benchmarking tasks.

The complete DNA sequencing of the entire human genome, or better known as the Human Genome Project, concluded in 2003. Ever since then, many headways have been made to better understand the organization of the human genome. There are many levels of organizations of the genome, its most basic unit, the nucleosome, which consists of DNA wrapped around histone proteins. Some of the higher levels of organization include tetranucleosomes, which consists of several nucleosomes, and topological associating domains (TADs), which are regions in the genome that self-interact more frequently with themselves compared to outside the TAD. In particular, TADs have been relatively new to the scene; there are currently no experimentally validated TADs. Furthermore, disruption of TAD boundaries are associated with several diseases like cancer. Nevertheless, there are currently many methods to call TADs, all of which are not based on a rigorous topological mathematical model. The HodgeRank algorithm, based on the Hodge decomposition theorem, gives us an avenue to quantify these self-interactions. The HodgeRank algorithm was previously used to rank imcomplete or imbalanced data from several e-commerce sites and movies from Netflix. We first show that HodgeRank can also be used to successfully quantify the ``curvedness'' of different biomolecules, such as modelling the protein folding process and comparing biomolecules of different scales and complexities. We then turn our attention back to Hi-C data, which encompasses TADs/TAD regions. We show that under a suitable metric, HodgeRank can be used to quantify the self-interactions within each TAD region of Chromosome 10, each of these regions generated by an existing TAD calling method. Solar power, a renewable source of energy, plays a significant role in allowing us to reduce our dependence on fossil fuels. Solar cells allow us to harness solar power by converting light energy from the Sun to electrical power through the photovoltaic effect, where light energy excites an electron, allowing it to reach a higher energy state. One of the types of materials that are used to make these solar cells are hybrid organic-inorganic perovskites (HOIPs). Not only have HOIPs been projected to be one of the most cost-effective options for future solar cells, its efficiency levels have risen from 5% to 25% in the last decade. Current machine learning-based perovskite designs rely heavily on the prediction of the bandgap of HOIPs. We show that the PerSpect-ML model, which is based on the generation of machine learning features using the eigenvalues of the Hodge Laplacian matrices, and previously applied to protein-ligand binding affinity prediction to great success, can be applied to the prediction of the bandgap of a comprehensive data set of hybrid organic-inorganic perovskites. We show that the resulting machine learning model not only significantly reduces the computational costs of current models, but also is superior in terms of overall predictive ability.

ABSTRACTMammalian genomes are folded into spatial domains, which regulate gene expression by modulating enhancer-promoter contacts. Here, we review recent studies on the structure and function of Topologically Associating Domains (TADs) and chromatin loops. We discuss how loop extrusion models can explain TAD formation and evidence that TADs are formed by the ring-shaped protein complex, cohesin, and that TAD boundaries are established by the DNA-binding protein, CTCF. We discuss our recent genomic, biochemical and single-molecule imaging studies on CTCF and cohesin, which suggest that TADs and chromatin loops are dynamic structures. We highlight complementary polymer simulation studies and Hi-C studies employing acute depletion of CTCF and cohesin, which also support such a dynamic model. We discuss the limitations of each approach and conclude that in aggregate the available evidence argues against stable loops and supports a model where TADs are dynamic structures that continually form and break throughout the cell cycle.

Topologically associating domains (TADs) are the most fundamental elements and significant structures of the eukaryotic genome. Currently, algorithms have been developed to find the TADs. But few algorithms are reported to compare the similarity of TADs between genomes. In this study, mice Hi-C sequencing data of four contrasts were enrolled. Seventeen algorithms, including BPscore, Jaccard index (JI) distance, VI distance, image hash, image subtraction, image variance, and so on, were used to quantify the genomic similarity of TADs. Image subtraction, Euclidean distance, and Manhattan distance were significantly better for TAD difference detection than the others. Deferent Hash (dHash) with the best zoom size ranked the second, followed by improved Hamming distance algorithm and JI distance. Advantages and disadvantages of various algorithms for quantifying the similarity of TADs were compared. Our work could provide the fundament for TADs comparison.

Genome-wide chromosome conformation capture (Hi-C) has revealed the organization of chromatin into topologically associating domains (TADs) and loops, which are thought to help regulate genome functions. TADs and loops are understood as the result of DNA extrusion mediated by the cohesin complex. However, despite recent efforts, direct visualization and quantification of this process in single cells remains an open challenge. Here, we use polymer simulations and dedicated analysis methods to explore if, and under which conditions, DNA loop extrusion can be detected and quantitatively characterized by imaging pairs of fluorescently labeled loci located near loop or TAD anchors in fixed or living cells. We find that under realistic conditions, extrusion can be detected and the frequency of loop formation can be quantified from fixed cell images alone, while the lifetime of loops and the speed of extrusion can be estimated from dynamic live-cell data. Our delineation of appropriate imaging conditions and the proposed analytical methods lay the groundwork for a systematic quantitative characterization of loop extrusion in fixed or living cells.

Studying the three-dimensional structure of chromosomes is an emerging field flourishing in recent years because of rapid development of experimental approaches for studying chromosomal contacts. This has led to numerous studies providing results of segmentation of chromosome sequences of different species into so-called topologically associating domains (TADs). As the number of such studies grows steadily and many of them make claims about the perceived differences between TAD structures observed in different conditions, there is a growing need for good measures of similarity (or dissimilarity) between such segmentations. We provide here a bipartite (BP) score, which is a relatively simple distance metric based on the bipartite matching between two segmentations. In this article, we provide the rationale behind choosing specifically this function and show its results on several different data sets, both simulated and experimental. We show that not only the BP score is a proper metric satisfying the triangle inequality, but also that it is providing good granularity of scores for typical situations occurring between different TAD segmentations. We also introduce local variant of the BP metric and show that in actual comparisons between experimental data sets, the local BP score is correlating with the observed changes in gene expression and genome methylation. In summary, we consider the BP score a good foundation for analyzing the dynamics of chromosome structures. The methodology we present in this study could be used by many researchers in their ongoing analyses, making it a popular and useful tool.