Computer vision for pattern detection in chromosome contact maps

Quantitative spatial analysis of bacterial transcriptome and chromosome structural data with GRATIOSA: application to twin-supercoiled domain distribution

While classical models of transcriptional regulation focus on transcription factors binding at promoters, gene expression is also influenced by chromosome organization. Understanding this spatial regulation strongly benefits from integrated and quantitative spatial analyses of genome-scale data such as RNA-Seq and ChIP-Seq. We introduce Genome Regulation Analysis Tool Incorporating Organization and Spatial Architecture (GRATIOSA), a Python package making such combined analyses more systematic and reproducible. While current software focuses on initial analysis steps (read mapping and counting), GRATIOSA proposes an integrated framework for subsequent analyses, providing a broad range of spatially resolved quantitative data analyses, comparisons, and representations. Several tutorials illustrate applications across diverse species for typical tasks involving RNA-Seq, ChIP-Seq, and processed Hi-C data. We also use the software to quantitatively assess the validity and extension of the twin-supercoiled domain model in Escherichia coli genome-wide transcription, using recent topoisomerase ChIP-Seq data. We show that topoisomerases are locally recruited specifically by the 40% most highly expressed transcription units, with magnitudes correlating with expression levels. The recruitment of topoisomerase I extends to around 10 kb upstream, whereas DNA gyrase is recruited at least 30 kb downstream of transcription units, with subtle requirements for each enzyme depending on the orientation and expression level.

Unraveling the three-dimensional genome structure using machine learning

The study of chromatin interactions has advanced considerably with technologies such as high-throughput chromosome conformation capture (Hi-C) sequencing, providing a genome-wide view of physical interactions within the nucleus. These techniques have revealed the existence of hierarchical chromatin structures such as compartments, topologically associating domains (TADs), and chromatin loops, which are crucial in genome organization and regulation. However, identifying and analyzing these structural features require advanced computational methods. In recent years, machine learning approaches, particularly deep learning, have emerged as powerful tools for detecting and analyzing structural information. In this review, we present an overview of various machine learning-based techniques for determining chromosomal organization. Starting with the progress in predicting interactions from DNA sequences, we describe methods for identifying various hierarchical structures from Hi-C data. Additionally, we present advances in enhancing the chromosome contact frequency map resolution to overcome the limitations of Hi-C data. Finally, we identify the remaining challenges and propose potential solutions and future directions. [BMB Reports 2025; 58(5): 203-208].

Unveiling Multi-Scale Architectural Features in Single-Cell Hi-C Data Using scCAFE

Single-cell Hi-C (scHi-C) has provided unprecedented insights into the heterogeneity of 3D genome organization. However, its sparse and noisy nature poses challenges for computational analyses, such as chromatin architectural feature identification. Here, scCAFE is introduced, which is a deep learning model for the multi-scale detection of architectural features at the single-cell level. scCAFE provides a unified framework for annotating chromatin loops, TAD-like domains (TLDs), and compartments across individual cells. This model outperforms previous scHi-C loop calling methods and delivers accurate predictions of TLDs and compartments that are biologically consistent with previous studies. The resulting single-cell annotations also offer a measure to characterize the heterogeneity of different levels of architectural features across cell types. This heterogeneity is then leveraged to identify a series of marker loop anchors, demontrating the potential of the 3D genome data to annotate cell identities without the aid of simultaneously sequenced omics data. Overall, scCAFE not only serves as a useful tool for analyzing single-cell genomic architecture, but also paves the way for precise cell-type annotations solely based on 3D genome features.

CGLoop: a neural network framework for chromatin loop prediction

BACKGROUND

Chromosomes of species exhibit a variety of high-dimensional organizational features, and chromatin loops, which are fundamental structures in the three-dimensional (3D) structure of the genome. Chromatin loops are visible speckled patterns on Hi-C contact matrix generated by chromosome conformation capture methods. The chromatin loops play an important role in gene expression, and predicting the chromatin loops generated during whole genome interactions is crucial for a deeper understanding of the 3D genome structure and function.

RESULTS

Here, we propose CGLoop, a deep learning based neural network framework that detects chromatin loops in Hi-C contact matrix. CGLoop combines the convolutional neural network (CNN) with Convolutional Block Attention Module (CBAM) and the Bidirectional Gated Recurrent Unit (BiGRU) to capture important features related to chromatin loops by comprehensively analyzing the Hi-C contact matrix, enabling the prediction of candidate chromatin loops. And CGLoop employs a density based clustering method to filter the candidate chromatin loops predicted by the neural network model. Finally, we compared CGloop with other chromatin loops prediction methods on several cell line including GM12878, K562, IMR90, and mESC. The code is available from https://github.com/wllwuliliwll/CGLoop .

CONCLUSIONS

The experimental results show that, loops predicted by CGLoop show high APA scores and there is an enrichment of multiple transcription factors and binding proteins at the predicted loops anchors, which outperforms other methods in terms of accuracy and validity of chromatin loops prediction.

CCCTC-binding factor N-terminal domain regulates clustered protocadherin gene expression by enhancing cohesin processivity

CTCF (CCCTC-binding factor) instructs 3D genome folding by anchoring or forestalling cohesin loop extrusion, but the exact mechanism remains obscure. Here, using clustered protocadherins (cPcdh) as model genes, we report that CTCF assists or facilitates cohesin loop extrusion by enhancing its processivity. Specifically, we show that, compared with the Pcdh α and γ gene clusters, the Pcdhβ cluster is greatly affected upon CTCFY226A/F228A mutation in the N-terminal domain. Given the long-range distance of the Pcdhβ cluster from the distal enhancer, this finding has interesting implications in CTCF regulation of cohesin processivity along the linear chromatin during DNA loop extrusion. In particular, the effect on cohesin processivity upon CTCFY226A/F228A mutation is conspicuously similar to that of WAPL overexpression, suggesting that, in contrast to the general view of blocking or forestalling cohesin, CTCF may actually enhance or facilitate cohesin loop extrusion during 3D genome folding. We conclude that CTCF enhances cohesin enrichments via the N-terminal YDF motif in clustered protocadherin genes in a genomic-distance biased manner.

A Paradigm of Computer Vision and Deep Learning Empowers the Strain Screening and Bioprocess Detection

High-performance strain and corresponding fermentation process are essential for achieving efficient biomanufacturing. However, conventional offline detection methods for products are cumbersome and less stable, hindering the "Test" module in the operation of "Design-Build-Test-Learn" cycle for strain screening and fermentation process optimization. This study proposed and validated an innovative research paradigm combining computer vision with deep learning to facilitate efficient strain selection and effective fermentation process optimization. A practical framework was developed for gentamicin C1a titer as a proof-of-concept, using computer vision to extract different color space components across various cultivation systems. Subsequently, by integrating data preprocessing with algorithm design, a prediction model was developed using 1D-CNN model with Z-score preprocessing, achieving a correlation coefficient (R2) of 0.9862 for gentamicin C1a. Furthermore, this model was successfully applied for high-yield strain screening and real-time monitoring of the fermentation process and extended to rapid detection of fluorescent protein expression in promoter library construction. The visual sensing research paradigm proposed in this study provides a theoretical framework and data support for the standardization and digital monitoring of color-changing bioprocesses.

Parasitic plasmids are anchored to inactive regions of eukaryotic chromosomes through a nucleosome signal

Natural plasmids are common in prokaryotes, but few have been documented in eukaryotes. The natural 2µ plasmid present in the yeast Saccharomyces cerevisiae is one of these best-characterized exceptions. This highly stable genetic element has coexisted with its host for millions of years, faithfully segregating at each cell division through a mechanism that remains unclear. Using proximity ligation methods (such as Hi-C, Micro-C) to map the contacts between 2µ plasmid and yeast chromosomes under dozens of different biological conditions, we found that the plasmid is tethered preferentially to regions with low transcriptional activity, often corresponding to long, inactive genes. These contacts do not depend on common chromosome-structuring factors, such as members of the structural maintenance of chromosome complexes (SMC) but depend on a nucleosome-encoded signal associated with RNA Pol II depletion. They appear stable throughout the cell cycle and can be established within minutes. This chromosome hitchhiking strategy may extend beyond the 2µ plasmid/S. cerevisiae pair, as suggested by the binding pattern of the natural eukaryotic plasmid Ddp5 along silent chromosome regions of the amoeba Dictyostelium discoideum.

B cell stimulation changes the structure and higher-order organization of the inactive X chromosome

X chromosome inactivation (XCI) equalizes X-linked gene expression between sexes. B cells exhibit dynamic XCI, with Xist RNA/heterochromatic marks absent on the inactive X (Xi) in naive B cells but returning following mitogenic stimulation. The impact of dynamic XCI on Xi structure and maintenance was previously unknown. Here, we find dosage compensation of the Xi with state-specific XCI escape genes in naive and in vitro-activated B cells. Allele-specific OligoPaints indicate similar Xi and active X (Xa) territories in B cells that are less compact than in fibroblasts. Allele-specific Hi-C reveals a lack of TAD-like structures on the Xi of naive B cells and stimulation-induced alterations in TAD-like boundary strength independent of gene expression. Notably, Xist deletion in B cells changes TAD boundaries and large-scale Xi compaction. Altogether, our results uncover B cell-specific Xi plasticity, which could underlie sex-biased biological mechanisms.

A common molecular mechanism underlying Cornelia de Lange and CHOPS syndromes

The cohesin protein complex is essential for the formation of topologically associating domains (TADs) and chromatin loops on interphase chromosomes.1,2,3,4,5 For the loading onto chromosomes, cohesin requires the cohesin loader complex formed by NIPBL6,7,8 and MAU2.9 Cohesin localizes at enhancers and gene promoters with NIPBL in mammalian cells10,11,12,13,14 and forms enhancer-promoter loops.15,16 Cornelia de Lange syndrome (CdLS) is a rare, genetically heterogeneous disorder affecting multiple organs and systems during development,17,18 caused by mutations in the cohesin loader NIPBL gene (>60% of patients),19,20,21,22,23 as well as in genes encoding cohesin, a chromatin regulator, BRD4, and cohesin-related factors.24,25,26,27 We also reported CHOPS syndrome that phenotypically overlaps with CdLS28,29 and is caused by gene mutations of a super elongation complex (SEC) core component, AFF4. Although these syndromes are associated with transcriptional dysregulation,24,28,30,31,32 the underlying mechanism remains unclear. In this study, we provide the first comprehensive analysis of chromosome architectural changes caused by these mutations using cell lines derived from CdLS and CHOPS syndrome patients. In both patient cells, we found a decrease in cohesin, NIPBL, BRD4, and acetylation of lysine 27 on histone H3 (H3K27ac)33,34,35 in most enhancers with enhancer-promoter loop attenuation. By contrast, TADs were maintained in both patient cells. These findings reveal a shared molecular mechanism in these syndromes and highlight unexpected roles for cohesin, cohesin loaders, and the SEC in maintaining the enhancer complexes. These complexes are crucial for recruiting transcriptional regulators, sustaining active histone modifications, and facilitating enhancer-promoter looping.

Chromosomal domain formation by archaeal SMC, a roadblock protein, and DNA structure

In eukaryotes, structural maintenance of chromosomes (SMC) complexes form topologically associating domains (TADs) by extruding DNA loops and being stalled by roadblock proteins. It remains unclear whether a similar mechanism of domain formation exists in prokaryotes. Using high-resolution chromosome conformation capture sequencing, we show that an archaeal homolog of the bacterial Smc-ScpAB complex organizes the genome of Thermococcus kodakarensis into TAD-like domains. We find that TrmBL2, a nucleoid-associated protein that forms a stiff nucleoprotein filament, stalls the T. kodakarensis SMC complex and establishes a boundary at the site-specific recombination site dif. TrmBL2 stalls the SMC complex at tens of additional non-boundary loci with lower efficiency. Intriguingly, the stalling efficiency is correlated with structural properties of underlying DNA sequences. Our study illuminates a eukaryotic-like mechanism of domain formation in archaea and a role of intrinsic DNA structure in large-scale genome organization.

Post-mitotic transcriptional activation and 3D regulatory interactions show locus- and differentiation-specific sensitivity to cohesin depletion

Prior studies showed that structural loops collapse upon acute cohesin depletion, while regulatory enhancer-promoter (E-P) loops largely persist, consistent with minimal transcriptional changes. However, these studies, conducted in asynchronous cells, could not resolve whether cohesin is required for the establishment of regulatory interactions and transcriptional activation during cell division or cell state transitions. To address this gap, we degraded RAD21, a core cohesin subunit, in naïve mouse embryonic stem cells (ESCs) transitioning from mitosis to G1 either in self-renewal condition or during differentiation toward formative pluripotency. Although most structural loops failed to be re-established without cohesin, about 35% of regulatory loops reformed at normal or higher frequencies. Cohesin-independent loops showed characteristics of strong active enhancers and promoters and a significant association with H3K27ac mitotic bookmarks. However, inhibition of CBP/p300 during mitotic exit did not impact these cohesin-independent interactions, suggesting the presence of complex compensatory mechanisms. At the transcriptional level, cohesin depletion induced only minor changes, supporting that post-mitotic transcriptional reactivation is largely independent of cohesin. The few genes with impaired reactivation were directly bound by RAD21 at their promoters, engaged in many structural loops, and located within strongly insulated TADs with low gene density. Importantly, degrading cohesin during the M-to-G1 transition in the presence of EpiLC differentiation signals revealed a larger group of susceptible genes, including key signature genes and transcription factors. Impaired activation of these genes was partly due to the failure to establish de novo EpiLC-specific interactions in the absence of cohesin. These experiments revealed locus-specific and context-specific dependencies between cohesin, E-P interactions, and transcription.

Sequence-dependent activity and compartmentalization of foreign DNA in a eukaryotic nucleus

In eukaryotes, DNA-associated protein complexes coevolve with genomic sequences to orchestrate chromatin folding. We investigate the relationship between DNA sequence and the spontaneous loading and activity of chromatin components in the absence of coevolution. Using bacterial genomes integrated into Saccharomyces cerevisiae, which diverged from yeast more than 2 billion years ago, we show that nucleosomes, cohesins, and associated transcriptional machinery can lead to the formation of two different chromatin archetypes, one transcribed and the other silent, independently of heterochromatin formation. These two archetypes also form on eukaryotic exogenous sequences, depend on sequence composition, and can be predicted using neural networks trained on the native genome. They do not mix in the nucleus, leading to a bipartite nuclear compartmentalization, reminiscent of the organization of vertebrate nuclei.

B cell stimulation changes the structure and higher-order organization of the inactive X chromosome

X Chromosome Inactivation (XCI) equalizes X-linked gene expression between sexes. B cells exhibit dynamic XCI, with Xist RNA/heterochromatic marks absent on the inactive X (Xi) in naive B cells but returning following mitogenic stimulation. The impact of dynamic XCI on Xi structure and maintenance was previously unknown. Here, we find dosage compensation of the Xi with state-specific XCI escape genes in naive and in vitro activated B cells. Allele-specific OligoPaints indicate similar Xi and Xa territories in B cells that are less compact than in fibroblasts. Allele-specific Hi-C reveals a lack of TAD-like structures on the Xi of naive B cells, and stimulation-induced alterations in TAD-like boundary strength independent of gene expression. Notably, Xist deletion in B cells changes TAD boundaries and large-scale Xi compaction. Altogether, our results uncover B cell-specific Xi plasticity which could underlie sex-biased biological mechanisms.

Convergent pairs of highly transcribed genes restrict chromatin looping in Dictyostelium discoideum

Dictyostelium discoideum is a unicellular slime mold, developing into a multicellular fruiting body upon starvation. Development is accompanied by large-scale shifts in gene expression program, but underlying features of chromatin spatial organization remain unknown. Here, we report that the Dictyostelium 3D genome is organized into positionally conserved, largely consecutive, non-hierarchical and weakly insulated loops at the onset of multicellular development. The transcription level within the loop interior tends to be higher than in adjacent regions. Loop interiors frequently contain functionally linked genes and genes which coherently change expression level during development. Loop anchors are predominantly positioned by the genes in convergent orientation. Results of polymer simulations and Hi-C-based observations suggest that the loop profile may arise from the interplay between transcription and extrusion-driven chromatin folding. In this scenario, a convergent gene pair serves as a bidirectional extrusion barrier or a 'diode' that controls passage of the cohesin extruder by relative transcription level of paired genes.

Promoter capture Hi-C identifies promoter-related loops and fountain structures in Arabidopsis

BACKGROUND

Promoters serve as key elements in the regulation of gene transcription. In mammals, loop interactions between promoters and enhancers increase the complexity of the promoter-based regulatory networks. However, the identification of enhancer-promoter or promoter-related loops in Arabidopsis remains incomplete.

RESULTS

Here, we use promoter capture Hi-C to identify promoter-related loops in Arabidopsis, which shows that gene body, proximal promoter, and intergenic regions can interact with promoters, potentially functioning as distal regulatory elements or enhancers. We find that promoter-related loops mainly repress gene transcription and are associated with ordered chromatin structures, such as topologically associating domains and fountains-chromatin structures not previously identified in Arabidopsis. Cohesin binds to the center of fountains and is involved in their formation. Moreover, fountain strength is positively correlated with the number of promoter-related loops, and the maintenance of these loops is linked to H3K4me3. In atxr3 mutants, which lack the major H3K4me3 methyltransferases in Arabidopsis, the number of promoter-related loops at fountains is reduced, leading to upregulation of fountain-regulated genes.

CONCLUSIONS

We identify promoter-related loops associated with ordered chromatin structures and reveal the molecular mechanisms involved in fountain formation and maintenance.

Footprint-C reveals transcription factor modes in local clusters and long-range chromatin interactions

The proximity ligation-based Hi-C and derivative methods are the mainstream tools to study genome-wide chromatin interactions. These methods often fragment the genome using enzymes functionally irrelevant to the interactions per se, restraining the efficiency in identifying structural features and the underlying regulatory elements. Here we present Footprint-C, which yields high-resolution chromatin contact maps built upon intact and genuine footprints protected by transcription factor (TF) binding. When analyzed at one-dimensional level, the billions of chromatin contacts from Footprint-C enable genome-wide analysis at single footprint resolution, and reveal preferential modes of local TF co-occupancy. At pairwise contact level, Footprint-C exhibits higher efficiency in identifying chromatin structural features when compared with other Hi-C methods, segregates chromatin interactions emanating from adjacent TF footprints, and uncovers multiway interactions involving different TFs. Altogether, Footprint-C results suggest that rich regulatory modes of TF may underlie both local residence and distal chromatin interactions, in terms of TF identity, valency, and conformational configuration.

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.

EMF1 functions as a 3D chromatin modulator in Arabidopsis

It is well known that genome organizers, like mammalian CCCTC-binding factor (CTCF) or Drosophila architectural proteins CP190 and BEAF-32, contribute to the three-dimensional (3D) organization of the genome and ensure normal gene transcription. However, bona fide genome organizers have not been identified in plants. Here, we show that EMBRYONIC FLOWER1 (EMF1) functions as a genome modulator in Arabidopsis. EMF1 interacts with the cohesin component SISTER CHROMATIN COHESION3 (SCC3), and both proteins are enriched at compartment domain (CD) boundaries. Accordingly, emf1 and scc3 show a strength decrease at the CD boundary in which these proteins colocalize. EMF1 maintains CD boundary strength, either independently or in cooperation with histone modifications. Moreover, EMF1 is required to maintain gene-resolution interactions and to block long-range aberrant chromatin loops. These data unveil a key role of EMF1 in regulating 3D chromatin structure.

Genome assembly of the southern pine beetle (Dendroctonus frontalis Zimmerman) reveals the origins of gene content reduction in Dendroctonus

Dendroctonus frontalis also known as southern pine beetle (SPB), is the most damaging insect forest pest in the southeastern United States. Genomic data are important to provide information on pest biology and to identify molecular targets to develop improved pest management approaches. Here, we produced a chromosome-level genome assembly of SPB using long-read sequencing data. Synteny analyses confirmed the conservation of the core Coleopteran Stevens elements and validated the bona fide SPB X chromosome. Transcriptomic data were used to obtain 39 588 transcripts corresponding to 13 354 putative protein-coding loci. Comparative analyses of gene content across 14 beetles and three other insects revealed several losses of conserved genes in the Dendroctonus clade and gene gains in SPB and Dendroctonus that were enriched for loci encoding membrane proteins and extracellular matrix proteins. While lineage-specific gene losses contributed to the gene content reduction observed in Dendroctonus, we also showed that widespread misannotation of transposable elements represents an important cause of the apparent gene expansion in several non-Dendroctonus species. Our findings uncovered distinctive features of the SPB gene complement and disentangled the role of biological and annotation-related factors contributing to gene content variation across beetles.

A Bioconductor/R Workflow for the Detection and Visualization of Differential Chromatin Loops

Background

Chromatin loops play a critical role in gene regulation by connecting regulatory loci and gene promoters. The identification of changes in chromatin looping between cell types or biological conditions is an important task for understanding gene regulation; however, the manipulation, statistical analysis, and visualization of data sets describing 3D chromatin structure is challenging due to the large and complex nature of the relevant data sets.

Methods

Here, we describe a workflow for identifying and visualizing differential chromatin loops from Hi-C data from two biological conditions using the 'mariner', 'DESeq2' and 'plotgardener' Bioconductor/R packages. The workflow assumes that Hi-C data has been processed into '.hic' or '.cool' files and that loops have been identified using an existing loop-calling algorithm.

Results

First, the 'mariner' package is used to merge redundant loop calls and extract interaction frequency counts. Next, 'DESeq2' is used to identify loops that exhibit differential contact frequencies between conditions. Finally, 'plotgardener' is used to visualize differential loops.

Conclusion

Chromatin interaction data is an important modality for understanding the mechanisms of transcriptional regulation. The workflow presented here outlines the use of 'mariner' as a tool to manipulate, extract, and aggregate chromatin interaction data, 'DESeq2' to perform differential analysis of these data across conditions, samples, and replicates, and 'plotgardener' to explore and visualize the results.

GrapHiC: An integrative graph based approach for imputing missing Hi-C reads

Hi-C experiments allow researchers to study and understand the 3D genome organization and its regulatory function. Unfortunately, sequencing costs and technical constraints severely restrict access to high-quality Hi-C data for many cell types. Existing frameworks rely on a sparse Hi-C dataset or cheaper-to-acquire ChIP-seq data to predict Hi-C contact maps with high read coverage. However, these methods fail to generalize to sparse or cross-cell-type inputs because they do not account for the contributions of epigenomic features or the impact of the structural neighborhood in predicting Hi-C reads. We propose GrapHiC, which combines Hi-C and ChIP-seq in a graph representation, allowing more accurate embedding of structural and epigenomic features. Each node represents a binned genomic region, and we assign edge weights using the observed Hi-C reads. Additionally, we embed ChIP-seq and relative positional information as node attributes, allowing our representation to capture structural neighborhoods and the contributions of proteins and their modifications for predicting Hi-C reads. We show that GrapHiC generalizes better than the current state-of-the-art on cross-cell-type settings and sparse Hi-C inputs. Moreover, we can utilize our framework to impute Hi-C reads even when no Hi-C contact map is available, thus making high-quality Hi-C data accessible for many cell types. Availability: https://github.com/rsinghlab/GrapHiC.

An extrinsic motor directs chromatin loop formation by cohesin

The ring-shaped cohesin complex topologically entraps two DNA molecules to establish sister chromatid cohesion. Cohesin also shapes the interphase chromatin landscape with wide-ranging implications for gene regulation, and cohesin is thought to achieve this by actively extruding DNA loops without topologically entrapping DNA. The 'loop extrusion' hypothesis finds motivation from in vitro observations-whether this process underlies in vivo chromatin loop formation remains untested. Here, using the budding yeast S. cerevisiae, we generate cohesin variants that have lost their ability to extrude DNA loops but retain their ability to topologically entrap DNA. Analysis of these variants suggests that in vivo chromatin loops form independently of loop extrusion. Instead, we find that transcription promotes loop formation, and acts as an extrinsic motor that expands these loops and defines their ultimate positions. Our results necessitate a re-evaluation of the loop extrusion hypothesis. We propose that cohesin, akin to sister chromatid cohesion establishment at replication forks, forms chromatin loops by DNA-DNA capture at places of transcription, thus unifying cohesin's two roles in chromosome segregation and interphase genome organisation.

Chromosome-level genome assembly of the bay scallop Argopecten irradians

The bay scallop, Argopecten irradians, is a species of major commercial, cultural, and ecological importance. It is endemic to the eastern coast of the United States, but has also been introduced to China, where it supports a significant aquaculture industry. Here, we provide an annotated chromosome-level reference genome assembly for the bay scallop, assembled using PacBio and Hi-C data. The total genome size is 845.9 Mb, distributed over 1,503 scaffolds with a scaffold N50 of 44.3 Mb. The majority (92.9%) of the assembled genome is contained within the 16 largest scaffolds, corresponding to the 16 chromosomes confirmed by Hi-C analysis. The assembly also includes the complete mitochondrial genome. Approximately 36.2% of the genome consists of repetitive elements. The BUSCO analysis showed a completeness of 96.2%. We identified 33,772 protein-coding genes. This genome assembly will be a valuable resource for future research on evolutionary dynamics, adaptive mechanisms, and will support genome-assisted breeding, contributing to the conservation and management of this iconic species in the face of environmental and pathogenic challenges.

A fast and adaptive detection framework for genome-wide chromatin loop mapping from Hi-C data

Chromatin loop identification plays an important role in molecular biology and 3D genomics research, as it constitutes a fundamental process in transcription and gene regulation. Such precise chromatin structures can be identified across genome-wide interaction matrices via Hi-C data analysis, which is essential for unraveling the intricacies of transcriptional regulation. Given the increasing number of genome-wide contact maps, derived from both in situ Hi-C and single-cell Hi-C experiments, there is a pressing need for efficient and resilient algorithms capable of processing data from diverse experiments rapidly and adaptively. Here, we propose YOLOOP, a novel detection-based framework that is different from the conventional paradigm. YOLOOP stands out for its speed, surpassing the performance of previous state-of-the-art (SOTA) chromatin loop detection methods. It achieves a 30-fold acceleration compared with classification-based methods, up to 20-fold acceleration compared with the SOTA kernel-based framework, and a fivefold acceleration compared with statistical algorithms. Furthermore, the proposed framework is capable of generalizing across various cell types, multiresolution Hi-C maps, and diverse experimental protocols. Compared with the existing paradigms, YOLOOP shows up to a 10% increase in recall and a 15% increase in F1-score, particularly noteworthy in the GM12878 cell line. YOLOOP also offers fast adaptability with straightforward fine-tuning, making it readily applicable to extremely sparse single-cell Hi-C contact maps. It maintains its exceptional speed, completing genome-wide detection at a 10 kb resolution for a single-cell contact map within 1 min and for a 900-cell-superimposed contact map within 3 min, enabling fast analysis of large-scale single-cell data.

TULIPs decorate the three-dimensional genome of PFA ependymoma

Posterior fossa group A (PFA) ependymoma is a lethal brain cancer diagnosed in infants and young children. The lack of driver events in the PFA linear genome led us to search its 3D genome for characteristic features. Here, we reconstructed 3D genomes from diverse childhood tumor types and uncovered a global topology in PFA that is highly reminiscent of stem and progenitor cells in a variety of human tissues. A remarkable feature exclusively present in PFA are type B ultra long-range interactions in PFAs (TULIPs), regions separated by great distances along the linear genome that interact with each other in the 3D nuclear space with surprising strength. TULIPs occur in all PFA samples and recur at predictable genomic coordinates, and their formation is induced by expression of EZHIP. The universality of TULIPs across PFA samples suggests a conservation of molecular principles that could be exploited therapeutically.

Mechanism of homology search expansion during recombinational DNA break repair in Saccharomyces cerevisiae

Homology search is a central step of DNA double-strand break (DSB) repair by homologous recombination (HR). How it operates in cells remains elusive. We developed a Hi-C-based methodology to map single-stranded DNA (ssDNA) contacts genome-wide in S. cerevisiae, which revealed two main homology search phases. Initial search conducted by short Rad51-ssDNA nucleoprotein filaments (NPFs) is confined in cis by cohesin-mediated chromatin loop folding. Progressive growth of stiff NPFs enables exploration of distant genomic sites. Long-range resection drives this transition from local to genome-wide search by increasing the probability of assembling extensive NPFs. DSB end-tethering promotes coordinated search by opposite NPFs. Finally, an autonomous genetic element on chromosome III engages the NPF, which stimulates homology search in its vicinity. This work reveals the mechanism of the progressive expansion of homology search that is orchestrated by chromatin organizers, long-range resection, end-tethering, and specialized genetic elements and that exploits the stiff NPF structure conferred by Rad51 oligomerization.

Spectral-based detection of chromatin loops in multiplexed super-resolution FISH data

Involved in mitotic condensation, interaction of transcriptional regulatory elements and isolation of structural domains, loop formation has become a paradigm in the deciphering of chromatin architecture and its functional role. Despite the emergence of increasingly powerful genome visualization techniques, the high variability in cell populations and the randomness of conformations still make loop detection a challenge. We introduce an approach for determining the presence and frequency of loops in a collection of experimental conformations obtained by multiplexed super-resolution imaging. Based on a spectral approach, in conjunction with neural networks, this method offers a powerful tool to detect loops in large experimental data sets, both at the population and single-cell levels. The method's performance is confirmed on experimental FISH data where Hi-C and other loop detection results are available. The method is then applied to recently published experimental data, where it provides a detailed and statistically quantified description of the global architecture of the chromosomal region under study.

Light control of three-dimensional chromatin organization in soybean

Higher-order chromatin structure is critical for regulation of gene expression. In plants, light profoundly affects the morphogenesis of emerging seedlings as well as global gene expression to ensure optimal adaptation to environmental conditions. However, the changes and functional significance of chromatin organization in response to light during seedling development are not well documented. We constructed Hi-C contact maps for the cotyledon, apical hook and hypocotyl of soybean subjected to dark and light conditions. The resulting high-resolution Hi-C contact maps identified chromosome territories, A/B compartments, A/B sub-compartments, TADs (Topologically Associated Domains) and chromatin loops in each organ. We observed increased chromatin compaction under light and we found that domains that switched from B sub-compartments in darkness to A sub-compartments under light contained genes that were activated during photomorphogenesis. At the local scale, we identified a group of TADs constructed by gene clusters consisting of different numbers of Small Auxin-Upregulated RNAs (SAURs), which exhibited strict co-expression in the hook and hypocotyl in response to light stimulation. In the hypocotyl, RNA polymerase II (RNAPII) regulated the transcription of a SAURs cluster under light via TAD condensation. Our results suggest that the 3D genome is involved in the regulation of light-related gene expression in a tissue-specific manner.

YY1-controlled regulatory connectivity and transcription are influenced by the cell cycle

Few transcription factors have been examined for their direct roles in physically connecting enhancers and promoters. Here acute degradation of Yin Yang 1 (YY1) in erythroid cells revealed its requirement for the maintenance of numerous enhancer-promoter loops, but not compartments or domains. Despite its reported ability to interact with cohesin, the formation of YY1-dependent enhancer-promoter loops does not involve stalling of cohesin-mediated loop extrusion. Integrating mitosis-to-G1-phase dynamics, we observed partial retention of YY1 on mitotic chromatin, predominantly at gene promoters, followed by rapid rebinding during mitotic exit, coinciding with enhancer-promoter loop establishment. YY1 degradation during the mitosis-to-G1-phase interval revealed a set of enhancer-promoter loops that require YY1 for establishment during G1-phase entry but not for maintenance in interphase, suggesting that cell cycle stage influences YY1's architectural function. Thus, as revealed here for YY1, chromatin architectural functions of transcription factors can vary in their interplay with CTCF and cohesin as well as by cell cycle stage.

SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model

Harnessing the power of single-cell genomics technologies, single-cell Hi-C (scHi-C) and its derived technologies provide powerful tools to measure spatial proximity between regulatory elements and their target genes in individual cells. Using a global background model, we propose SnapHiC-G, a computational method, to identify long-range enhancer-promoter interactions from scHi-C data. We applied SnapHiC-G to scHi-C datasets generated from mouse embryonic stem cells and human brain cortical cells. SnapHiC-G achieved high sensitivity in identifying long-range enhancer-promoter interactions. Moreover, SnapHiC-G can identify putative target genes for noncoding genome-wide association study (GWAS) variants, and the genetic heritability of neuropsychiatric diseases is enriched for single-nucleotide polymorphisms (SNPs) within SnapHiC-G-identified interactions in a cell-type-specific manner. In sum, SnapHiC-G is a powerful tool for characterizing cell-type-specific enhancer-promoter interactions from complex tissues and can facilitate the discovery of chromatin interactions important for gene regulation in biologically relevant cell types.

A continuum of zinc finger transcription factor retention on native chromatin underlies dynamic genome organization

Transcription factor (TF) residence on chromatin translates into quantitative transcriptional or structural outcomes on genome. Commonly used formaldehyde crosslinking fixes TF-DNA interactions cumulatively and compromises the measured occupancy level. Here we mapped the occupancy level of global or individual zinc finger TFs like CTCF and MAZ, in the form of highly resolved footprints, on native chromatin. By incorporating reinforcing perturbation conditions, we established S-score, a quantitative metric to proxy the continuum of CTCF or MAZ retention across different motifs on native chromatin. The native chromatin-retained CTCF sites harbor sequence features within CTCF motifs better explained by S-score than the metrics obtained from other crosslinking or native assays. CTCF retention on native chromatin correlates with local SUMOylation level, and anti-correlates with transcriptional activity. The S-score successfully delineates the otherwise-masked differential stability of chromatin structures mediated by CTCF, or by MAZ independent of CTCF. Overall, our study established a paradigm continuum of TF retention across binding sites on native chromatin, explaining the dynamic genome organization.

scGrapHiC: deep learning-based graph deconvolution for Hi-C using single cell gene expression

SUMMARY

Single-cell Hi-C (scHi-C) protocol helps identify cell-type-specific chromatin interactions and sheds light on cell differentiation and disease progression. Despite providing crucial insights, scHi-C data is often underutilized due to the high cost and the complexity of the experimental protocol. We present a deep learning framework, scGrapHiC, that predicts pseudo-bulk scHi-C contact maps using pseudo-bulk scRNA-seq data. Specifically, scGrapHiC performs graph deconvolution to extract genome-wide single-cell interactions from a bulk Hi-C contact map using scRNA-seq as a guiding signal. Our evaluations show that scGrapHiC, trained on seven cell-type co-assay datasets, outperforms typical sequence encoder approaches. For example, scGrapHiC achieves a substantial improvement of 23.2% in recovering cell-type-specific Topologically Associating Domains over the baselines. It also generalizes to unseen embryo and brain tissue samples. scGrapHiC is a novel method to generate cell-type-specific scHi-C contact maps using widely available genomic signals that enables the study of cell-type-specific chromatin interactions.

AVAILABILITY AND IMPLEMENTATION

The GitHub link: https://github.com/rsinghlab/scGrapHiC contains the source code of scGrapHiC and associated scripts to preprocess publicly available datasets to produce the results and visualizations we have discuss in this manuscript.

Enhancing Hi-C contact matrices for loop detection with Capricorn: a multiview diffusion model

MOTIVATION

High-resolution Hi-C contact matrices reveal the detailed three-dimensional architecture of the genome, but high-coverage experimental Hi-C data are expensive to generate. Simultaneously, chromatin structure analyses struggle with extremely sparse contact matrices. To address this problem, computational methods to enhance low-coverage contact matrices have been developed, but existing methods are largely based on resolution enhancement methods for natural images and hence often employ models that do not distinguish between biologically meaningful contacts, such as loops and other stochastic contacts.

RESULTS

We present Capricorn, a machine learning model for Hi-C resolution enhancement that incorporates small-scale chromatin features as additional views of the input Hi-C contact matrix and leverages a diffusion probability model backbone to generate a high-coverage matrix. We show that Capricorn outperforms the state of the art in a cross-cell-line setting, improving on existing methods by 17% in mean squared error and 26% in F1 score for chromatin loop identification from the generated high-coverage data. We also demonstrate that Capricorn performs well in the cross-chromosome setting and cross-chromosome, cross-cell-line setting, improving the downstream loop F1 score by 14% relative to existing methods. We further show that our multiview idea can also be used to improve several existing methods, HiCARN and HiCNN, indicating the wide applicability of this approach. Finally, we use DNA sequence to validate discovered loops and find that the fraction of CTCF-supported loops from Capricorn is similar to those identified from the high-coverage data. Capricorn is a powerful Hi-C resolution enhancement method that enables scientists to find chromatin features that cannot be identified in the low-coverage contact matrix.

AVAILABILITY AND IMPLEMENTATION

Implementation of Capricorn and source code for reproducing all figures in this paper are available at https://github.com/CHNFTQ/Capricorn.

Inhibiting AGTR1 reduces AML burden and protects the heart from cardiotoxicity in mouse models

Clinical treatment of acute myeloid leukemia (AML) largely relies on intensive chemotherapy. However, the application of chemotherapy is often hindered by cardiotoxicity. Patient sequence data revealed that angiotensin II receptor type 1 (AGTR1) is a shared target between AML and cardiovascular disease (CVD). We found that inhibiting AGTR1 sensitized AML to chemotherapy and protected the heart against chemotherapy-induced cardiotoxicity in a human AML cell-transplanted mouse model. These effects were regulated by the AGTR1-Notch1 axis in AML cells and cardiomyocytes from mice. In mouse cardiomyocytes, AGTR1 was hyperactivated by AML and chemotherapy. AML leukemogenesis increased the expression of the angiotensin-converting enzyme and led to increased production of angiotensin II, the ligand of AGTR1, in an MLL-AF9-driven AML mouse model. In this model, the AGTR1-Notch1 axis regulated a variety of genes involved with cell stemness and chemotherapy resistance. AML cell stemness was reduced after Agtr1a deletion in the mouse AML cell transplant model. Mechanistically, Agtr1a deletion decreased γ-secretase formation, which is required for transmembrane Notch1 cleavage and release of the Notch1 intracellular domain into the nucleus. Using multiomics, we identified AGTR1-Notch1 signaling downstream genes and found decreased binding between these gene sequences with Notch1 and chromatin enhancers, as well as increased binding with silencers. These findings describe an AML/CVD association that may be used to improve AML treatment.

Genome assembly of the southern pine beetle (Dendroctonus frontalis Zimmerman) reveals the origins of gene content reduction in Dendroctonus

Dendroctonus frontalis, also known as southern pine beetle (SPB), represents the most damaging forest pest in the southeastern United States. Strategies to predict, monitor and suppress SPB outbreaks have had limited success. Genomic data are critical to inform on pest biology and to identify molecular targets to develop improved management approaches. Here, we produced a chromosome-level genome assembly of SPB using long-read sequencing data. Synteny analyses confirmed the conservation of the core coleopteran Stevens elements and validated the bona fide SPB X chromosome. Transcriptomic data were used to obtain 39,588 transcripts corresponding to 13,354 putative protein-coding loci. Comparative analyses of gene content across 14 beetle and 3 other insects revealed several losses of conserved genes in the Dendroctonus clade and gene gains in SPB and Dendroctonus that were enriched for loci encoding membrane proteins and extracellular matrix proteins. While lineage-specific gene losses contributed to the gene content reduction observed in Dendroctonus, we also showed that widespread misannotation of transposable elements represents a major cause of the apparent gene expansion in several non-Dendroctonus species. Our findings uncovered distinctive features of the SPB gene complement and disentangled the role of biological and annotation-related factors contributing to gene content variation across beetles.

CD-Loop: a chromatin loop detection method based on the diffusion model

Motivation

In recent years, there have been significant advances in various chromatin conformation capture techniques, and annotating the topological structure from Hi-C contact maps has become crucial for studying the three-dimensional structure of chromosomes. However, the structure and function of chromatin loops are highly dynamic and diverse, influenced by multiple factors. Therefore, obtaining the three-dimensional structure of the genome remains a challenging task. Among many chromatin loop prediction methods, it is difficult to fully extract features from the contact map and make accurate predictions at low sequencing depths.

Results

In this study, we put forward a deep learning framework based on the diffusion model called CD-Loop for predicting accurate chromatin loops. First, by pre-training the input data, we obtain prior probabilities for predicting the classification of the Hi-C contact map. Then, by combining the denoising process based on the diffusion model and the prior probability obtained by pre-training, candidate loops were predicted from the input Hi-C contact map. Finally, CD-Loop uses a density-based clustering algorithm to cluster the candidate chromatin loops and predict the final chromatin loops. We compared CD-Loop with the currently popular methods, such as Peakachu, Chromosight, and Mustache, and found that in different cell types, species, and sequencing depths, CD-Loop outperforms other methods in loop annotation. We conclude that CD-Loop can accurately predict chromatin loops and reveal cell-type specificity. The code is available at https://github.com/wangyang199897/CD-Loop.

Open2C, Abdennur N, Abraham S, Fudenberg G, Flyamer IM, Galitsyna AA, Goloborodko A, Imakaev M, Oksuz BA, Venev SV, Xiao Y. Cooltools: Enabling high-resolution Hi-C analysis in Python

Chromosome conformation capture (3C) technologies reveal the incredible complexity of genome organization. Maps of increasing size, depth, and resolution are now used to probe genome architecture across cell states, types, and organisms. Larger datasets add challenges at each step of computational analysis, from storage and memory constraints to researchers' time; however, analysis tools that meet these increased resource demands have not kept pace. Furthermore, existing tools offer limited support for customizing analysis for specific use cases or new biology. Here we introduce cooltools (https://github.com/open2c/cooltools), a suite of computational tools that enables flexible, scalable, and reproducible analysis of high-resolution contact frequency data. Cooltools leverages the widely-adopted cooler format which handles storage and access for high-resolution datasets. Cooltools provides a paired command line interface (CLI) and Python application programming interface (API), which respectively facilitate workflows on high-performance computing clusters and in interactive analysis environments. In short, cooltools enables the effective use of the latest and largest genome folding datasets.

High resolution maps of chromatin reorganization through mouse meiosis reveal novel features of the 3D meiotic structure

When germ cells transition from the mitotic cycle into meiotic prophase I (MPI), chromosomes condense into an array of chromatin loops that are required to promote homolog pairing and genetic recombination. To identify the changes in chromosomal conformation, we isolated nuclei on a trajectory from spermatogonia to the end of MPI. At each stage along this trajectory, we built genomic interaction maps with the highest temporal and spatial resolution to date. The changes in chromatin folding coincided with a concurrent decline in mitotic cohesion and a rise in meiotic cohesin complexes. We found that the stereotypical large-scale A and B compartmentalization was lost during meiotic prophase I alongside the loss of topological associating domains (TADs). Still, local subcompartments were detected and maintained throughout meiosis. The enhanced Micro-C resolution revealed that, despite the loss of TADs, higher frequency contact sites between two loci were detectable during meiotic prophase I coinciding with CTCF bound sites. The pattern of interactions around these CTCF sites with their neighboring loci showed that CTCF sites were often anchoring the meiotic loops. Additionally, the localization of CTCF to the meiotic axes indicated that these anchors were at the base of loops. Strikingly, even in the face of the dramatic reconfiguration of interphase chromatin into a condensed loop-array, the interactions between regulatory elements remained well preserved. This establishes a potential mechanism for how the meiotic chromatin maintains active transcription within a highly structured genome. In summary, the high temporal and spatial resolution of these data revealed previously unappreciated aspects of mammalian meiotic chromatin organization.

Sister chromatid cohesion halts DNA loop expansion

Eukaryotic genomes are folded into DNA loops mediated by structural maintenance of chromosomes (SMC) complexes such as cohesin, condensin, and Smc5/6. This organization regulates different DNA-related processes along the cell cycle, such as transcription, recombination, segregation, and DNA repair. During the G2 stage, SMC-mediated DNA loops coexist with cohesin complexes involved in sister chromatid cohesion (SCC). However, the articulation between the establishment of SCC and the formation of SMC-mediated DNA loops along the chromatin remains unknown. Here, we show that SCC is indeed a barrier to cohesin-mediated DNA loop expansion along G2/M Saccharomyces cerevisiae chromosomes.

Comparative study on chromatin loop callers using Hi-C data reveals their effectiveness

BACKGROUND

Chromosome is one of the most fundamental part of cell biology where DNA holds the hierarchical information. DNA compacts its size by forming loops, and these regions house various protein particles, including CTCF, SMC3, H3 histone. Numerous sequencing methods, such as Hi-C, ChIP-seq, and Micro-C, have been developed to investigate these properties. Utilizing these data, scientists have developed a variety of loop prediction techniques that have greatly improved their methods for characterizing loop prediction and related aspects.

RESULTS

In this study, we categorized 22 loop calling methods and conducted a comprehensive study of 11 of them. Additionally, we have provided detailed insights into the methodologies underlying these algorithms for loop detection, categorizing them into five distinct groups based on their fundamental approaches. Furthermore, we have included critical information such as resolution, input and output formats, and parameters. For this analysis, we utilized the GM12878 Hi-C datasets at 5 KB, 10 KB, 100 KB and 250 KB resolutions. Our evaluation criteria encompassed various factors, including memory usages, running time, sequencing depth, and recovery of protein-specific sites such as CTCF, H3K27ac, and RNAPII.

CONCLUSION

This analysis offers insights into the loop detection processes of each method, along with the strengths and weaknesses of each, enabling readers to effectively choose suitable methods for their datasets. We evaluate the capabilities of these tools and introduce a novel Biological, Consistency, and Computational robustness score ( B C C score ) to measure their overall robustness ensuring a comprehensive evaluation of their performance.

Absence of chromosome axis protein recruitment prevents meiotic recombination chromosome-wide in the budding yeast Lachancea kluyveri

Meiotic recombination shows broad variations across species and along chromosomes and is often suppressed at and around genomic regions determining sexual compatibility such as mating type loci in fungi. Here, we show that the absence of Spo11-DSBs and meiotic recombination on Lakl0C-left, the chromosome arm containing the sex locus of the Lachancea kluyveri budding yeast, results from the absence of recruitment of the two chromosome axis proteins Red1 and Hop1, essential for proper Spo11-DSBs formation. Furthermore, cytological observation of spread pachytene meiotic chromosomes reveals that Lakl0C-left does not undergo synapsis. However, we show that the behavior of Lakl0C-left is independent of its particularly early replication timing and is not accompanied by any peculiar chromosome structure as detectable by Hi-C in this yet poorly studied yeast. Finally, we observed an accumulation of heterozygous mutations on Lakl0C-left and a sexual dimorphism of the haploid meiotic offspring, supporting a direct effect of this absence of meiotic recombination on L. kluyveri genome evolution and fitness. Because suppression of meiotic recombination on sex chromosomes is widely observed across eukaryotes, the mechanism for recombination suppression described here may apply to other species, with the potential to impact sex chromosome evolution.

Transcription-induced domains form the elementary constraining building blocks of bacterial chromosomes

Transcription generates local topological and mechanical constraints on the DNA fiber, leading to the generation of supercoiled chromosome domains in bacteria. However, the global impact of transcription on chromosome organization remains elusive, as the scale of genes and operons in bacteria remains well below the resolution of chromosomal contact maps generated using Hi-C (~5-10 kb). Here we combined sub-kb Hi-C contact maps and chromosome engineering to visualize individual transcriptional units. We show that transcriptional units form discrete three-dimensional transcription-induced domains that impose mechanical and topological constraints on their neighboring sequences at larger scales, modifying their localization and dynamics. These results show that transcriptional domains constitute primary building blocks of bacterial chromosome folding and locally impose structural and dynamic constraints.

Orchestrating chromosome conformation capture analysis with Bioconductor

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data structures, computational methods and visualization tools available in Bioconductor to investigate Hi-C, micro-C and other 3C-related data, in R. An online book ( https://bioconductor.org/books/OHCA/ ) further provides prospective end users with a number of workflows to process, import, analyze and visualize any type of chromosome conformation capture data.

ZNF143 deletion alters enhancer/promoter looping and CTCF/cohesin geometry

The transcription factor ZNF143 contains a central domain of seven zinc fingers in a tandem array and is involved in 3D genome construction. However, the mechanism by which ZNF143 functions in chromatin looping remains unclear. Here, we show that ZNF143 directionally recognizes a diverse range of genomic sites directly within enhancers and promoters and is required for chromatin looping between these sites. In addition, ZNF143 is located between CTCF and cohesin at numerous CTCF sites, and ZNF143 removal narrows the space between CTCF and cohesin. Moreover, genetic deletion of ZNF143, in conjunction with acute CTCF degradation, reveals that ZNF143 and CTCF collaborate to regulate higher-order topological chromatin organization. Finally, CTCF depletion enlarges direct ZNF143 chromatin looping. Thus, ZNF143 is recruited by CTCF to the CTCF sites to regulate CTCF/cohesin configuration and TAD (topologically associating domain) formation, whereas directional recognition of genomic DNA motifs directly by ZNF143 itself regulates promoter activity via chromatin looping.

Phage-inducible chromosomal minimalist islands (PICMIs), a novel family of small marine satellites of virulent phages

Phage satellites are bacterial genetic elements that co-opt phage machinery for their own dissemination. Here we identify a family of satellites, named Phage-Inducible Chromosomal Minimalist Islands (PICMIs), that are broadly distributed in marine bacteria of the family Vibrionaceae. A typical PICMI is characterized by reduced gene content, does not encode genes for capsid remodelling, and packages its DNA as a concatemer. PICMIs integrate in the bacterial host genome next to the fis regulator, and encode three core proteins necessary for excision and replication. PICMIs are dependent on virulent phage particles to spread to other bacteria, and protect their hosts from other competitive phages without interfering with their helper phage. Thus, our work broadens our understanding of phage satellites and narrows down the minimal number of functions necessary to hijack a tailed phage.

Chromosome architecture in an archaeal species naturally lacking structural maintenance of chromosomes proteins

Proteins in the structural maintenance of chromosomes (SMC) superfamily play key roles in chromosome organization and are ubiquitous across all domains of life. However, SMC proteins are notably absent in the Desulfurococcales of phylum Crenarchaeota. Intrigued by this observation, we performed chromosome conformation capture experiments in the model Desulfurococcales species Aeropyrum pernix. As in other archaea, we observe chromosomal interaction domains across the chromosome. The boundaries between chromosomal interaction domains show a dependence on transcription and translation for their definition. Importantly, however, we reveal an additional higher-order, bipartite organization of the chromosome-with a small high-gene-expression and self-interacting domain that is defined by transcriptional activity and loop structures. Viewing these data in the context of the distribution of SMC superfamily proteins in the Crenarchaeota, we suggest that the organization of the Aeropyrum genome represents an evolutionary antecedent of the compartmentalized architecture observed in the Sulfolobus lineage.

A Comprehensive Evaluation of Generalizability of Deep Learning-Based Hi-C Resolution Improvement Methods

Hi-C is a widely used technique to study the 3D organization of the genome. Due to its high sequencing cost, most of the generated datasets are of a coarse resolution, which makes it impractical to study finer chromatin features such as Topologically Associating Domains (TADs) and chromatin loops. Multiple deep learning-based methods have recently been proposed to increase the resolution of these datasets by imputing Hi-C reads (typically called upscaling). However, the existing works evaluate these methods on either synthetically downsampled datasets, or a small subset of experimentally generated sparse Hi-C datasets, making it hard to establish their generalizability in the real-world use case. We present our framework-Hi-CY-that compares existing Hi-C resolution upscaling methods on seven experimentally generated low-resolution Hi-C datasets belonging to various levels of read sparsities originating from three cell lines on a comprehensive set of evaluation metrics. Hi-CY also includes four downstream analysis tasks, such as TAD and chromatin loops recall, to provide a thorough report on the generalizability of these methods. We observe that existing deep learning methods fail to generalize to experimentally generated sparse Hi-C datasets, showing a performance reduction of up to 57%. As a potential solution, we find that retraining deep learning-based methods with experimentally generated Hi-C datasets improves performance by up to 31%. More importantly, Hi-CY shows that even with retraining, the existing deep learning-based methods struggle to recover biological features such as chromatin loops and TADs when provided with sparse Hi-C datasets. Our study, through the Hi-CY framework, highlights the need for rigorous evaluation in the future. We identify specific avenues for improvements in the current deep learning-based Hi-C upscaling methods, including but not limited to using experimentally generated datasets for training.

H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs

Polycomb Repressive Complex 2 (PRC2)-mediated histone H3K27 tri-methylation (H3K27me3) recruits canonical PRC1 (cPRC1) to maintain heterochromatin. In early development, polycomb-regulated genes are connected through long-range 3D interactions which resolve upon differentiation. Here, we report that polycomb looping is controlled by H3K27me3 spreading and regulates target gene silencing and cell fate specification. Using glioma-derived H3 Lys-27-Met (H3K27M) mutations as tools to restrict H3K27me3 deposition, we show that H3K27me3 confinement concentrates the chromatin pool of cPRC1, resulting in heightened 3D interactions mirroring chromatin architecture of pluripotency, and stringent gene repression that maintains cells in progenitor states to facilitate tumor development. Conversely, H3K27me3 spread in pluripotent stem cells, following neural differentiation or loss of the H3K36 methyltransferase NSD1, dilutes cPRC1 concentration and dissolves polycomb loops. These results identify the regulatory principles and disease implications of polycomb looping and nominate histone modification-guided distribution of reader complexes as an important mechanism for nuclear compartment organization.

Highlights

The confinement of H3K27me3 at PRC2 nucleation sites without its spreading correlates with increased 3D chromatin interactions.The H3K27M oncohistone concentrates canonical PRC1 that anchors chromatin loop interactions in gliomas, silencing developmental programs.Stem and progenitor cells require factors promoting H3K27me3 confinement, including H3K36me2, to maintain cPRC1 loop architecture.The cPRC1-H3K27me3 interaction is a targetable driver of aberrant self-renewal in tumor cells.

3D chromatin interactions involving Drosophila insulators are infrequent but preferential and arise before TADs and transcription

In mammals, insulators contribute to the regulation of loop extrusion to organize chromatin into topologically associating domains. In Drosophila the role of insulators in 3D genome organization is, however, under current debate. Here, we addressed this question by combining bioinformatics analysis and multiplexed chromatin imaging. We describe a class of Drosophila insulators enriched at regions forming preferential chromatin interactions genome-wide. Notably, most of these 3D interactions do not involve TAD borders. Multiplexed imaging shows that these interactions occur infrequently, and only rarely involve multiple genomic regions coalescing together in space in single cells. Finally, we show that non-border preferential 3D interactions enriched in this class of insulators are present before TADs and transcription during Drosophila development. Our results are inconsistent with insulators forming stable hubs in single cells, and instead suggest that they fine-tune existing 3D chromatin interactions, providing an additional regulatory layer for transcriptional regulation.

The shape of chromatin: insights from computational recognition of geometric patterns in Hi-C data

The three-dimensional organization of chromatin plays a crucial role in gene regulation and cellular processes like deoxyribonucleic acid (DNA) transcription, replication and repair. Hi-C and related techniques provide detailed views of spatial proximities within the nucleus. However, data analysis is challenging partially due to a lack of well-defined, underpinning mathematical frameworks. Recently, recognizing and analyzing geometric patterns in Hi-C data has emerged as a powerful approach. This review provides a summary of algorithms for automatic recognition and analysis of geometric patterns in Hi-C data and their correspondence with chromatin structure. We classify existing algorithms on the basis of the data representation and pattern recognition paradigm they make use of. Finally, we outline some of the challenges ahead and promising future directions.