Enhancer-promoter communication: unraveling enhancer strength and positioning within a given topologically associating domain (TAD)
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ABSTRACT:
SUBMITTER: Giaimo B
PROVIDER: S-EPMC9374741 | biostudies-literature | 2022 Jan
REPOSITORIES: biostudies-literature
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Project description:Topologically associating domains (TADs) are chromatin domains in the eukaryotic genome. TADs often comprise several sub-TADs. The boundaries of TADs and sub-TADs are enriched in CTCF, an architectural protein. Deletion of CTCF-binding motifs at one boundary disrupts the domains, often resulting in a transcriptional decrease in genes inside the domains. However, it is not clear how TAD and sub-TAD affect each other in the domain formation. Unaffected gene transcription was observed in the β-globin locus when one boundary of TAD or sub-TAD was destroyed. Here, we disrupted β-globin TAD and sub-TAD by deleting CTCF motifs at both boundaries in MEL/ch11 cells. Disruption of TAD impaired sub-TAD, but sub-TAD disruption did not affect TAD. Both TAD and sub-TAD disruption compromised the β-globin transcription, accompanied by the loss of enhancer-promoter interactions. However, histone H3 occupancy and H3K27ac were largely maintained across the β-globin locus. Genome-wide analysis showed that putative enhancer-promoter interactions and gene transcription were decreased by the disruption of CTCF-mediated topological domains in neural progenitor cells. Collectively, our results indicate that there is unequal relationship between TAD and sub-TAD formation. TAD is likely not sufficient for gene transcription, and, therefore, sub-TAD appears to be required. TAD-dependently formed sub-TADs are considered to provide chromatin environments for enhancer-promoter interactions enabling gene transcription.
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Project description:Whole-genome sequencing (WGS) studies of autism spectrum disorder (ASD) have demonstrated the roles of rare promoter de novo variants (DNVs). However, most promoter DNVs in ASD are not located immediately upstream of known ASD genes. In this study analyzing WGS data of 5,044 ASD probands, 4,095 unaffected siblings, and their parents, we show that promoter DNVs within topologically associating domains (TADs) containing ASD genes are significantly and specifically associated with ASD. An analysis considering TADs as functional units identified specific TADs enriched for promoter DNVs in ASD and indicated that common variants in these regions also confer ASD heritability. Experimental validation using human induced pluripotent stem cells (iPSCs) showed that likely deleterious promoter DNVs in ASD can influence multiple genes within the same TAD, resulting in overall dysregulation of ASD-associated genes. These results highlight the importance of TADs and gene-regulatory mechanisms in better understanding the genetic architecture of ASD.
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Project description:Metazoan chromosomes are sequentially partitioned into topologically associating domains (TADs) and then into smaller sub-domains. One class of sub-domains, insulated neighborhoods, are proposed to spatially sequester and insulate the enclosed genes through self-association and chromatin looping. However, it has not been determined functionally whether promoter-enhancer interactions and gene regulation are broadly restricted to within these loops. Here, we employed published datasets from murine embryonic stem cells (mESCs) to identify insulated neighborhoods that confine promoter-enhancer interactions and demarcate gene regulatory regions. To directly address the functionality of these regions, we depleted estrogen-related receptor β (Esrrb), which binds the Mediator co-activator complex, to impair enhancers of genes within 222 insulated neighborhoods without causing mESC differentiation. Esrrb depletion reduces Mediator binding, promoter-enhancer looping, and expression of both nascent RNA and mRNA within the insulated neighborhoods without significantly affecting the flanking genes. Our data indicate that insulated neighborhoods represent functional regulons in mammalian genomes.
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Project description:Distinguishing between conserved and divergent regulatory mechanisms is essential for translating preclinical research from mice to humans, yet there is a lack of information about how evolutionary genome rearrangements affect the regulation of the immune response, a rapidly evolving system. The current model is topologically associating domains (TADs) are conserved between species, buffering evolutionary rearrangements and conserving long-range interactions within a TAD. However, we find that TADs frequently span evolutionary translocation and inversion breakpoints near genes with species-specific expression in immune cells, creating unique enhancer-promoter interactions exclusive to the mouse or human genomes. This includes TADs encompassing immune-related transcription factors, cytokines, and receptors. For example, we uncover an evolutionary rearrangement that created a shared LPS-inducible regulatory module between OASL and P2RX7 in human macrophages that is absent in mice. Therefore, evolutionary genome rearrangements disrupt TAD boundaries, enabling sequence-conserved enhancer elements from divergent genomic locations between species to create unique regulatory modules.
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Project description:Chromatin is a polymer complex of DNA and proteins that regulates gene expression. The three-dimensional (3D) structure and organization of chromatin controls DNA transcription and replication. High-throughput chromatin conformation capture techniques generate Hi-C maps that can provide insight into the 3D structure of chromatin. Hi-C maps can be represented as a symmetric matrix [Formula: see text], where each element represents the average contact probability or number of contacts between chromatin loci i and j. Previous studies have detected topologically associating domains (TADs), or self-interacting regions in [Formula: see text] within which the contact probability is greater than that outside the region. Many algorithms have been developed to identify TADs within Hi-C maps. However, most TAD identification algorithms are unable to identify nested or overlapping TADs and for a given Hi-C map there is significant variation in the location and number of TADs identified by different methods. We develop a novel method to identify TADs, KerTAD, using a kernel-based technique from computer vision and image processing that is able to accurately identify nested and overlapping TADs. We benchmark this method against state-of-the-art TAD identification methods on both synthetic and experimental data sets. We find that the new method consistently has higher true positive rates (TPR) and lower false discovery rates (FDR) than all tested methods for both synthetic and manually annotated experimental Hi-C maps. The TPR for KerTAD is also largely insensitive to increasing noise and sparsity, in contrast to the other methods. We also find that KerTAD is consistent in the number and size of TADs identified across replicate experimental Hi-C maps for several organisms. Thus, KerTAD will improve automated TAD identification and enable researchers to better correlate changes in TADs to biological phenomena, such as enhancer-promoter interactions and disease states.
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Project description:BackgroundRecent increasing evidence indicates that three-dimensional chromosome structure plays an important role in genomic function. Topologically associating domains (TADs) are self-interacting regions that have been shown to be a chromosomal structural unit. During evolution, these are conserved based on checking synteny block cross species. Are there common TAD patterns across species or cell lines?ResultsTo address the above question, we propose a novel task-TAD recognition-as opposed to traditional TAD identification. Specifically, we treat Hi-C maps as images, thus re-casting TAD recognition as image pattern recognition, for which we use a convolutional neural network and a residual neural network. In addition, we propose an elegant way to generate non-TAD data for binary classification. We demonstrate deep learning performance which is quite promising, AUC > 0.80, through cross-species and cell-type validation.ConclusionsTADs have been shown to be conserved during evolution. Interestingly, our results confirm that the TAD recognition model is practical across species, which indicates that TADs between human and mouse show common patterns from an image classification point of view. Our approach could be a new way to identify TAD variations or patterns among Hi-C maps. For example, TADs of two Hi-C maps are conserved if the two classification models are exchangeable.
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Project description:Topologically associating domains (TADs) are critical structural units in three-dimensional genome organization of mammalian genome. Dynamic reorganizations of TADs between health and disease states are associated with essential genome functions. However, computational methods for identifying reorganized TADs are still in the early stages of development. Here, we present DiffDomain, an algorithm leveraging high-dimensional random matrix theory to identify structurally reorganized TADs using high-throughput chromosome conformation capture (Hi-C) contact maps. Method comparison using multiple real Hi-C datasets reveals that DiffDomain outperforms alternative methods for false positive rates, true positive rates, and identifying a new subtype of reorganized TADs. Applying DiffDomain to Hi-C data from different cell types and disease states demonstrates its biological relevance. Identified reorganized TADs are associated with structural variations and epigenomic changes such as changes in CTCF binding sites. By applying to a single-cell Hi-C data from mouse neuronal development, DiffDomain can identify reorganized TADs between cell types with reasonable reproducibility using pseudo-bulk Hi-C data from as few as 100 cells per condition. Moreover, DiffDomain reveals differential cell-to-population variability and heterogeneous cell-to-cell variability in TADs. Therefore, DiffDomain is a statistically sound method for better comparative analysis of TADs using both Hi-C and single-cell Hi-C data.
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Project description:Topologically associating domains (TADs) have been proposed to be the basic unit of chromosome folding and have been shown to play key roles in genome organization and gene regulation. Several different tools are available for TAD prediction, but their properties have never been thoroughly assessed. In this manuscript, we compare the output of seven different TAD prediction tools on two published Hi-C data sets. TAD predictions varied greatly between tools in number, size distribution and other biological properties. Assessed against a manual annotation of TADs, individual TAD boundary predictions were found to be quite reliable, but their assembly into complete TAD structures was much less so. In addition, many tools were sensitive to sequencing depth and resolution of the interaction frequency matrix. This manuscript provides users and designers of TAD prediction tools with information that will help guide the choice of tools and the interpretation of their predictions.
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Project description:Genomes across a wide range of eukaryotic organisms fold into higher-order chromatin domains. Topologically associating domains (TADs) were originally discovered empirically in low-resolution Hi-C heat maps representing ensemble average interaction frequencies from millions of cells. Here, we discuss recent advances in high-resolution Hi-C, single-cell imaging experiments, and functional genetic studies, which provide an increasingly complex view of the genome's hierarchical structure-function relationship. On the basis of these new findings, we update the definitions of distinct classes of chromatin domains according to emerging knowledge of their structural, mechanistic and functional properties.
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