Stripenn detects architectural stripes from chromatin conformation data using computer vision

Recipes and ingredients for deep learning models of 3D genome folding

Three-dimensional genome folding plays roles in gene regulation and disease. In this review, we compare and contrast recent deep learning models for predicting genome contact maps. We survey preprocessing, architecture, training, evaluation, and interpretation methods, highlighting the capabilities and limitations of different models. In each area, we highlight challenges, opportunities, and potential future directions for genome-folding models.

Improved cohesin HiChIP protocol and bioinformatic analysis for robust detection of chromatin loops and stripes

Chromosome Conformation Capture (3 C) methods, including Hi-C (a high-throughput variation of 3 C), detect pairwise interactions between DNA regions, enabling the reconstruction of chromatin architecture in the nucleus. HiChIP is a modification of the Hi-C experiment that includes a chromatin immunoprecipitation (ChIP) step, allowing genome-wide identification of chromatin contacts mediated by a protein of interest. In mammalian cells, cohesin protein complex is one of the major players in the establishment of chromatin loops. We present an improved cohesin HiChIP experimental protocol. Using comprehensive bioinformatic analysis, we show that a dual chromatin fixation method compared to the standard formaldehyde-only method, results in a substantially better signal-to-noise ratio, increased ChIP efficiency and improved detection of chromatin loops and architectural stripes. Additionally, we propose an automated pipeline called nf-HiChIP ( https://github.com/SFGLab/hichip-nf-pipeline ) for processing HiChIP samples starting from raw sequencing reads data and ending with a set of significant chromatin interactions (loops), which allows efficient and timely analysis of multiple samples in parallel, without requiring additional ChIP-seq experiments. Finally, using advanced approaches for biophysical modelling and stripe calling we generate accurate loop extrusion polymer models for a region of interest and provide a detailed picture of architectural stripes, respectively.

Significance in scale space for Hi-C data

MOTIVATION

Hi-C technology has been developed to profile genome-wide chromosome conformation. So far Hi-C data have been generated from a large compendium of different cell types and different tissue types. Among different chromatin conformation units, chromatin loops were found to play a key role in gene regulation across different cell types. While many different loop calling algorithms have been developed, most loop callers identified shared loops as opposed to cell-type-specific loops.

RESULTS

We propose SSSHiC, a new loop calling algorithm based on significance in scale space, which can be used to understand data at different levels of resolution. By applying SSSHiC to neuronal and glial Hi-C data, we detected more loops that are potentially engaged in cell-type-specific gene regulation. Compared with other loop callers, such as Mustache, these loops were more frequently anchored to gene promoters of cellular marker genes and had better APA scores. Therefore, our results suggest that SSSHiC can effectively capture loops that contain more gene regulatory information.

AVAILABILITY AND IMPLEMENTATION

The Hi-C data used in this study can be accessed through the PsychENCODE Knowledge Portal at https://www.synapse.org/#! Synapse: syn21760712. The code utilized for Curvature SSS cited in this study is available at https://github.com/jsmarron/MarronMatlabSoftware/blob/master/Matlab9/Matlab9Combined.zip. All custom code used in this research can be found in the GitHub repository: https://github.com/jerryliu01998/HiC. The code has also been submitted to Code Ocean with the doi: 10.24433/CO.1912913.v1.

Memory CD4+ T cells sequentially restructure their 3D genome during stepwise activation

Background

CD4+ T cells are a highly differentiated cell type that maintain enough transcriptomic plasticity to cycle between activated and memory statuses. How the 1D chromatin state and 3D chromatin architecture support this plasticity is under intensive investigation.

Methods

Here, we wished to test a commercially available in situ Hi-C kit (Arima Genomics Inc.) to establish whether published performance on limiting cell numbers from clonal cell lines copies across to a primary immune cell type. We achieved comparable contact matrices from 50,000, 250,000, and 1,000,000 memory CD4+ T-cell inputs. We generated multiple Hi-C and RNA-seq libraries from the same biological blood donors under three separate conditions: unstimulated fresh ex vivo, IL-2-only stimulated, and T cell receptor (TCR)+CD28+IL-2-stimulated, conferring increasingly stronger activation signals. We wished to capture the magnitude and progression of 3D chromatin shifts and correlate these to expression changes under the two stimulations.

Results

Although some genome organization changes occurred concomitantly with changes in gene expression, at least as many changes occurred without corresponding changes in expression. Counter to the hypothesis that topologically associated domains (TADs) are largely invariant structures providing a scaffold for dynamic looping contacts between enhancers and promotors, we found that there were at least as many dynamic TAD changes. Stimulation with IL-2 alone triggered many changes in genome organization, and many of these changes were strengthened by additional TCR and CD28 co-receptor stimulation.

Conclusions

This suggests a stepwise process whereby mCD4+ T cells undergo sequential buildup of 3D architecture induced by distinct or combined stimuli likely to "prime" or "deprime" them for expression responses to subsequent TCR-antigen ligation or additional cytokine stimulation.

Cis-regulatory chromatin contacts form de novo in the absence of loop extrusion

NIPBL promotes chromatin loop extrusion by the cohesin complex until it stalls at convergently oriented CTCF sites, leading to the formation of structural loops. However, to what extent loop extrusion contributes to the establishment vs maintenance of cis-regulatory element (CRE) connectivity is poorly understood. Here, we explored the de novo establishment of chromatin folding patterns at the mitosis-to-G1-phase transition upon acute NIPBL loss. NIPBL depletion primarily impaired the formation of cohesion-mediated structural loops with NIPBL dependence being proportional to loop length. In contrast, the majority of CRE loops were established independently of loop extrusion regardless of length. However, NIPBL depletion slowed the re-formation of CRE loops with weak enhancers. Transcription of genes at NIPBL-independent loop anchors was activated normally in the absence of NIPBL. In sum, establishment of most regulatory contacts and gene transcription following mitotic exit is independent of loop extrusion.

EXPRESSO: a multi-omics database to explore multi-layered 3D genomic organization

The three-dimensional (3D) organization of the human genome plays a crucial role in gene regulation. EXPloration of Regulatory Epigenome with Spatial and Sequence Observations (EXPRESSO) is a novel multi-omics database for exploration and visualization of multi-layered 3D genomic features across 46 different human tissues. Integrating 1360 3D genomic datasets (Hi-C, HiChIP, ChIA-PET) and 842 1D genomic and transcriptomic datasets (ChIP-seq, ATAC-seq, RNA-seq) from the same biosample, EXPRESSO provides a comprehensive resource for studying the interplay between 3D genome architecture and transcription regulation. This database offers diverse 3D genomic feature types (compartments, contact matrix, contact domains, stripes as diagonal lines extending from a genomic locus in contact matrix, chromatin loops, etc.) and user-friendly interface for both data exploration and download. Other key features include REpresentational State Transfer application programming interfaces for programmatic access, advanced visualization tools for 3D genomic features and web-based applications that correlate 3D genomic features with gene expression and epigenomic modifications. By providing extensive datasets and tools, EXPRESSO aims to deepen our understanding of 3D genomic architecture and its implications for human health and disease, serving as a vital resource for the research community. EXPRESSO is freely available at https://expresso.sustech.edu.cn.

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.

Mapping the 3D genome architecture

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

Overcoming artificial structures in resolution-enhanced Hi-C data by signal decomposition and multi-scale attention

Computational enhancement is an important strategy for inferring high-resolution features from genome-wide chromosome conformation capture (Hi-C) data, which typically have limited resolution. Deep learning has been highly successful in this task but we show that it creates prevalent artificial structures in the enhanced data due to the need to divide the large contact matrix into small patches. In addition, previous deep learning methods largely focus on local patterns, which cannot fully capture the complexity of Hi-C data. Here we propose Smooth, High-resolution, and Accurate Reconstruction of Patterns (SHARP) for enhancing Hi-C data. It uses the novel approach of decomposing the data into three types of signals, due to one-dimensional proximity, contiguous domains, and other fine structures, and applies deep learning only to the third type of signals, such that enhancement of the first two is unaffected by the patches. For the deep learning part, SHARP uses both local and global attention mechanisms to capture multi-scale contextual information. We compare SHARP with state-of-the-art methods extensively, including application to data from new samples and another species, and show that SHARP has superior performance in terms of resolution enhancement accuracy, avoiding creation of artificial structures, identifying significant interactions, and enrichment in chromatin states.

Dynamic chromatin architecture identifies new autoimmune-associated enhancers for IL2 and novel genes regulating CD4+ T cell activation

Genome-wide association studies (GWAS) have identified hundreds of genetic signals associated with autoimmune disease. The majority of these signals are located in non-coding regions and likely impact cis-regulatory elements (cRE). Because cRE function is dynamic across cell types and states, profiling the epigenetic status of cRE across physiological processes is necessary to characterize the molecular mechanisms by which autoimmune variants contribute to disease risk. We localized risk variants from 15 autoimmune GWAS to cRE active during TCR-CD28 co-stimulation of naïve human CD4+ T cells. To characterize how dynamic changes in gene expression correlate with cRE activity, we measured transcript levels, chromatin accessibility, and promoter-cRE contacts across three phases of naive CD4+ T cell activation using RNA-seq, ATAC-seq, and HiC. We identified ~1200 protein-coding genes physically connected to accessible disease-associated variants at 423 GWAS signals, at least one-third of which are dynamically regulated by activation. From these maps, we functionally validated a novel stretch of evolutionarily conserved intergenic enhancers whose activity is required for activation-induced IL2 gene expression in human and mouse, and is influenced by autoimmune-associated genetic variation. The set of genes implicated by this approach are enriched for genes controlling CD4+ T cell function and genes involved in human inborn errors of immunity, and we pharmacologically validated eight implicated genes as novel regulators of T cell activation. These studies directly show how autoimmune variants and the genes they regulate influence processes involved in CD4+ T cell proliferation and activation.

Computational methods for analysing multiscale 3D genome organization

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

BRWD1 orchestrates small pre-B cell chromatin topology by converting static to dynamic cohesin

Lymphocyte development consists of sequential and mutually exclusive cell states of proliferative selection and antigen receptor gene recombination. Transitions between each state require large, coordinated changes in epigenetic landscapes and transcriptional programs. How this occurs remains unclear. Here we demonstrate that in small pre-B cells, the lineage and stage-specific epigenetic reader bromodomain and WD repeat-containing protein 1 (BRWD1) reorders three-dimensional chromatin topology to affect the transition between proliferative and gene recombination molecular programs. BRWD1 regulated the switch between poised and active enhancers interacting with promoters, and coordinated this switch with Igk locus contraction. BRWD1 did so by converting chromatin-bound static to dynamic cohesin competent to mediate long-range looping. ATP-depletion revealed cohesin conversion to be the main energetic mechanism dictating dynamic chromatin looping. Our findings provide a new mechanism of cohesin regulation and reveal how cohesin function can be dictated by lineage contextual mechanisms to facilitate specific cell fate transitions.

Three-way contact analysis characterizes the higher order organization of the Tcra locus

The generation of highly diverse antigen receptors in T and B lymphocytes relies on V(D)J recombination. The enhancer Eα has been implicated in regulating the accessibility of Vα and Jα genes through long-range interactions during rearrangements of the T-cell antigen receptor gene Tcra. However, direct evidence for Eα physically mediating the interaction of Vα and Jα genes is still lacking. In this study, we utilized the 3C-HTGTS assay, a chromatin interaction technique based on 3C, to analyze the higher order chromatin structure of the Tcra locus. Our analysis revealed the presence of sufficient information in the 3C-HTGTS data to detect multiway contacts. Three-way contact analysis of the Tcra locus demonstrated the co-occurrence of the proximal Jα genes, Vα genes and Eα in CD4+CD8+ double-positive thymocytes. Notably, the INT2-TEAp loop emerged as a prominent structure likely to be responsible for bringing the proximal Jα genes and the Vα genes into proximity. Moreover, the enhancer Eα utilizes this loop to establish physical proximity with the proximal Vα gene region. This study provides insights into the higher order chromatin structure of the Tcra locus, shedding light on the spatial organization of chromatin and its impact on V(D)J recombination.

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.

Golnaz Vahedi: My environment enables me to achieve impossible goals

Golnaz Vahedi is an associate professor of genetics at the Perelman School of Medicine, University of Pennsylvania. Golnaz runs a multidisciplinary lab that uses cutting-edge computational and experimental approaches to understand the molecular mechanisms by which genomic information in immune cells is interpreted in normal development and during immune-mediated diseases. We talked about her diverse scientific background, the benefits of integrating molecular biology and immunology, and the importance of staying positive in academia.

High-throughput Oligopaint screen identifies druggable 3D genome regulators

The human genome functions as a three-dimensional chromatin polymer, driven by a complex collection of chromosome interactions1-3. Although the molecular rules governing these interactions are being quickly elucidated, relatively few proteins regulating this process have been identified. Here, to address this gap, we developed high-throughput DNA or RNA labelling with optimized Oligopaints (HiDRO)-an automated imaging pipeline that enables the quantitative measurement of chromatin interactions in single cells across thousands of samples. By screening the human druggable genome, we identified more than 300 factors that influence genome folding during interphase. Among these, 43 genes were validated as either increasing or decreasing interactions between topologically associating domains. Our findings show that genetic or chemical inhibition of the ubiquitous kinase GSK3A leads to increased long-range chromatin looping interactions in a genome-wide and cohesin-dependent manner. These results demonstrate the importance of GSK3A signalling in nuclear architecture and the use of HiDRO for identifying mechanisms of spatial genome organization.

Quantitative control of Ets1 dosage by a multi-enhancer hub promotes Th1 cell differentiation and protects from allergic inflammation

Multi-enhancer hubs are spatial clusters of enhancers present across numerous developmental programs. Here, we studied the functional relevance of these three-dimensional structures in T cell biology. Mathematical modeling identified a highly connected multi-enhancer hub at the Ets1 locus, comprising a noncoding regulatory element that was a hotspot for sequence variation associated with allergic disease in humans. Deletion of this regulatory element in mice revealed that the multi-enhancer connectivity was dispensable for T cell development but required for CD4+ T helper 1 (Th1) differentiation. These mice were protected from Th1-mediated colitis but exhibited overt allergic responses. Mechanistically, the multi-enhancer hub controlled the dosage of Ets1 that was required for CTCF recruitment and assembly of Th1-specific genome topology. Our findings establish a paradigm wherein multi-enhancer hubs control cellular competence to respond to an inductive cue through quantitative control of gene dosage and provide insight into how sequence variation within noncoding elements at the Ets1 locus predisposes individuals to allergic responses.

snHiC: a complete and simplified snakemake pipeline for grouped Hi-C data analysis

Summary

Genome-wide chromosome conformation capture (Hi-C) is a technique that allows the study of 3D genome organization. Despite being widely used, analysis of Hi-C data is technically challenging and involves several time-consuming steps that often require manual involvement making it error prone, potentially affecting data reproducibility. In order to facilitate and simplify these analyses we implemented snHiC, a snakemake-based pipeline that allows for the generation of contact matrices at multiple resolutions in one single run, aggregation of individual samples into user-specified groups, detection of domains, compartments, loops and stripes and performance of differential compartment and chromatin interaction analyses.

Availability and implementation

Source code is freely available at https://github.com/sebastian-gregoricchio/snHiC. A yaml-formatted file (snHiC/workflow/envs/snHiC_conda_env_stable.yaml) is available to build a compatible conda environment.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Multiscale 3D genome organization underlies ILC2 ontogenesis and allergic airway inflammation

Innate lymphoid cells (ILCs) are well-characterized immune cells that play key roles in host defense and tissue homeostasis. Yet, how the three-dimensional (3D) genome organization underlies the development and functions of ILCs is unknown. Herein, we carried out an integrative analysis of the 3D genome structure, chromatin accessibility and gene expression in mature ILCs. Our results revealed that the local 3D configuration of the genome is rewired specifically at loci associated with ILC biology to promote their development and functional differentiation. Importantly, we demonstrated that the ontogenesis of ILC2s and the progression of allergic airway inflammation are determined by a unique local 3D configuration of the region containing the ILC-lineage-defining factor Id2, which is characterized by multiple interactions between the Id2 promoter and distal regulatory elements bound by the transcription factors GATA-3 and RORα, unveiling the mechanism whereby the Id2 expression is specifically controlled in group 2 ILCs.

StripeDiff: Model-based algorithm for differential analysis of chromatin stripe

Multiple recent studies revealed stripes as an architectural feature of three-dimensional chromatin and found stripes connected to epigenetic regulation of transcription. Whereas a couple of tools are available to define stripes in a single sample, there is yet no reported method to quantitatively measure the dynamic change of each stripe between samples. Here, we developed StripeDiff, a bioinformatics tool that delivers a set of statistical methods to detect differential stripes between samples. StripeDiff showed optimal performance in both simulation data analysis and real Hi-C data analysis. Applying StripeDiff to 12 sets of Hi-C data revealed new insights into the connection between change of chromatin stripe and change of chromatin modification, transcriptional regulation, and cell differentiation. StripeDiff will be a robust tool for the community to facilitate understanding of stripes and their function in numerous biological models.

MoDLE: high-performance stochastic modeling of DNA loop extrusion interactions

DNA loop extrusion emerges as a key process establishing genome structure and function. We introduce MoDLE, a computational tool for fast, stochastic modeling of molecular contacts from DNA loop extrusion capable of simulating realistic contact patterns genome wide in a few minutes. MoDLE accurately simulates contact maps in concordance with existing molecular dynamics approaches and with Micro-C data and does so orders of magnitude faster than existing approaches. MoDLE runs efficiently on machines ranging from laptops to high performance computing clusters and opens up for exploratory and predictive modeling of 3D genome structure in a wide range of settings.

CTCF-CTCF loops and intra-TAD interactions show differential dependence on cohesin ring integrity

The ring-like cohesin complex mediates sister-chromatid cohesion by encircling pairs of sister chromatids. Cohesin also extrudes loops along chromatids. Whether the two activities involve similar mechanisms of DNA engagement is not known. We implemented an experimental approach based on isolated nuclei carrying engineered cleavable RAD21 proteins to precisely control cohesin ring integrity so that its role in chromatin looping could be studied under defined experimental conditions. This approach allowed us to identify cohesin complexes with distinct biochemical, and possibly structural, properties that mediate different sets of chromatin loops. When RAD21 is cleaved and the cohesin ring is opened, cohesin complexes at CTCF sites are released from DNA and loops at these elements are lost. In contrast, cohesin-dependent loops within chromatin domains that are not anchored at pairs of CTCF sites are more resistant to RAD21 cleavage. The results show that the cohesin complex mediates loops in different ways depending on the genomic context and suggests that it undergoes structural changes as it dynamically extrudes and encounters CTCF sites.

TCF-1 promotes chromatin interactions across topologically associating domains in T cell progenitors

The high mobility group (HMG) transcription factor TCF-1 is essential for early T cell development. Although in vitro biochemical assays suggest that HMG proteins can serve as architectural elements in the assembly of higher-order nuclear organization, the contribution of TCF-1 on the control of three-dimensional (3D) genome structures during T cell development remains unknown. Here, we investigated the role of TCF-1 in 3D genome reconfiguration. Using gain- and loss-of-function experiments, we discovered that the co-occupancy of TCF-1 and the architectural protein CTCF altered the structure of topologically associating domains in T cell progenitors, leading to interactions between previously insulated regulatory elements and target genes at late stages of T cell development. The TCF-1-dependent gain in long-range interactions was linked to deposition of active enhancer mark H3K27ac and recruitment of the cohesin-loading factor NIPBL at active enhancers. These data indicate that TCF-1 has a role in controlling global genome organization during T cell development.