Gene regulation in the third dimension

Network-wide risk convergence in gene co-expression identifies reproducible genetic hubs of schizophrenia risk

The omnigenic model posits that genetic risk for traits with complex heritability involves cumulative effects of peripheral genes on mechanistic "core genes," suggesting that in a network of genes, those closer to clusters including core genes should have higher GWAS signals. In gene co-expression networks, we confirmed that GWAS signals accumulate in genes more connected to risk-enriched gene clusters, highlighting across-network risk convergence. This was strongest in adult psychiatric disorders, especially schizophrenia (SCZ), spanning 70% of network genes, suggestive of super-polygenic architecture. In snRNA-seq cell type networks, SCZ risk convergence was strongest in L2/L3 excitatory neurons. We prioritized genes most connected to SCZ-GWAS genes, which showed robust association to a CRISPRa measure of PGC3 regulation and were consistently identified across several brain regions. Several genes, including dopamine-associated ones, were prioritized specifically in the striatum. This strategy thus retrieves current drug targets and can be used to prioritize other potential drug targets.

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

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

A global transcriptional activator involved in the iron homeostasis in cyanobacteria

Cyanobacteria use a series of adaptation strategies and a complicated regulatory network to maintain intracellular iron (Fe) homeostasis. Here, a global activator named IutR has been identified through three-dimensional chromosome organization and transcriptome analysis in a model cyanobacterium Synechocystis sp. PCC 6803. Inactivation of all three homologous IutR-encoding genes resulted in an impaired tolerance of Synechocystis to Fe deficiency and loss of the responses of Fe uptake-related genes to Fe-deplete conditions. Protein-promoter interaction assays confirmed the direct binding of IutR with the promoters of genes related to Fe uptake, and chromatin immunoprecipitation sequencing analysis further revealed that in addition to Fe uptake, IutR could regulate many other physiological processes involved in intracellular Fe homeostasis. These results proved that IutR is an important transcriptional activator, which is essential for cyanobacteria to induce Fe-deficiency response genes. This study provides in-depth insights into the complicated Fe-deficient signaling network and the molecular mechanism of cyanobacteria adaptation to Fe-deficient environments.

A Constitutive Heterochromatic Region Shapes Genome Organization and Impacts Gene Expression in Neurospora crassa

Genome organization is essential for proper function, including gene expression. In metazoan genome organization, chromatin loops and Topologically Associated Domains (TADs) facilitate local gene clustering, while chromosomes form distinct nuclear territories characterized by compartmentalization of silent heterochromatin at the nuclear periphery and active euchromatin in the nucleus center. A similar hierarchical organization occurs in the fungus Neurospora crassa where its seven chromosomes form a Rabl conformation, where heterochromatic centromeres and telomeres independently cluster at the nuclear membrane, while interspersed heterochromatic loci in Neurospora aggregate across megabases of linear genomic distance for forming TAD-like structures. However, the role of individual heterochromatic loci in normal genome organization and function is unknown. Here, we examined the genome organization of a Neurospora strain harboring a ∼47.4 kilobase facultative (temporarily silent) heterochromatic region deletion, as well as the genome organization of a strain deleted of a 110.6 kilobase permanently silent constitutive heterochromatic region. While the facultative heterochromatin deletion had little effect on local chromatin structure, the constitutive heterochromatin deletion altered local TAD-like structures, gene expression, and the predicted 3D genome structure by qualitatively repositioning genes into the nucleus center. Our work elucidates the role of individual heterochromatic regions for genome organization and function.

Stratifying TAD boundaries pinpoints focal genomic regions of regulation, damage, and repair

Advances in chromatin mapping have exposed the complex chromatin hierarchical organization in mammals, including topologically associating domains (TADs) and their substructures, yet the functional implications of this hierarchy in gene regulation and disease progression are not fully elucidated. Our study delves into the phenomenon of shared TAD boundaries, which are pivotal in maintaining the hierarchical chromatin structure and regulating gene activity. By integrating high-resolution Hi-C data, chromatin accessibility, and DNA double-strand breaks (DSBs) data from various cell lines, we systematically explore the complex regulatory landscape at high-level TAD boundaries. Our findings indicate that these boundaries are not only key architectural elements but also vibrant hubs, enriched with functionally crucial genes and complex transcription factor binding site-clustered regions. Moreover, they exhibit a pronounced enrichment of DSBs, suggesting a nuanced interplay between transcriptional regulation and genomic stability. Our research provides novel insights into the intricate relationship between the 3D genome structure, gene regulation, and DNA repair mechanisms, highlighting the role of shared TAD boundaries in maintaining genomic integrity and resilience against perturbations. The implications of our findings extend to understanding the complexities of genomic diseases and open new avenues for therapeutic interventions targeting the structural and functional integrity of TAD boundaries.

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.

Hi-BDiSCO: folding 3D mesoscale genome structures from Hi-C data using brownian dynamics

The structure and dynamics of the eukaryotic genome are intimately linked to gene regulation and transcriptional activity. Many chromosome conformation capture experiments like Hi-C have been developed to detect genome-wide contact frequencies and quantify loop/compartment structures for different cellular contexts and time-dependent processes. However, a full understanding of these events requires explicit descriptions of representative chromatin and chromosome configurations. With the exponentially growing amount of data from Hi-C experiments, many methods for deriving 3D structures from contact frequency data have been developed. Yet, most reconstruction methods use polymer models with low resolution to predict overall genome structure. Here we present a Brownian Dynamics (BD) approach termed Hi-BDiSCO for producing 3D genome structures from Hi-C and Micro-C data using our mesoscale-resolution chromatin model based on the Discrete Surface Charge Optimization (DiSCO) model. Our approach integrates reconstruction with chromatin simulations at nucleosome resolution with appropriate biophysical parameters. Following a description of our protocol, we present applications to the NXN, HOXC, HOXA and Fbn2 mouse genes ranging in size from 50 to 100 kb. Such nucleosome-resolution genome structures pave the way for pursuing many biomedical applications related to the epigenomic regulation of chromatin and control of human disease.

Histone deacetylation and cytosine methylation compartmentalize heterochromatic regions in the genome organization of Neurospora crassa

Chromosomes must correctly fold in eukaryotic nuclei for proper genome function. Eukaryotic organisms hierarchically organize their genomes, including in the fungus Neurospora crassa, where chromatin fiber loops compact into Topologically Associated Domain-like structures formed by heterochromatic region aggregation. However, insufficient data exist on how histone posttranslational modifications (PTMs), including acetylation, affect genome organization. In Neurospora, the HCHC complex [composed of the proteins HDA-1, CDP-2 (Chromodomain Protein-2), Heterochromatin Protein-1, and CHAP (CDP-2 and HDA-1 Associated Protein)] deacetylates heterochromatic nucleosomes, as loss of individual HCHC members increases centromeric acetylation, and alters the methylation of cytosines in DNA. Here, we assess whether the HCHC complex affects genome organization by performing Hi-C in strains deleted of the cdp-2 or chap genes. CDP-2 loss increases intra- and interchromosomal heterochromatic region interactions, while loss of CHAP decreases heterochromatic region compaction. Individual HCHC mutants exhibit different patterns of histone PTMs genome-wide, as CDP-2 deletion increases heterochromatic H4K16 acetylation, yet smaller heterochromatic regions lose H3K9 trimethylation and gain interheterochromatic region interactions; CHAP loss produces minimal acetylation changes but increases heterochromatic H3K9me3 enrichment. Loss of both CDP-2 and the DIM-2 DNA methyltransferase causes extensive genome disorder as heterochromatic-euchromatic contacts increase despite additional H3K9me3 enrichment. Our results highlight how the increased cytosine methylation in HCHC mutants ensures genome compartmentalization when heterochromatic regions become hyperacetylated without HDAC activity.

Histone deacetylation and cytosine methylation compartmentalize heterochromatic regions in the genome organization of Neurospora crassa

Chromosomes must correctly fold in eukaryotic nuclei for proper genome function. Eukaryotic organisms hierarchically organize their genomes, including in the fungus Neurospora crassa, where chromatin fiber loops compact into Topologically Associated Domain (TAD)-like structures formed by heterochromatic region aggregation. However, insufficient data exists on how histone post-translational modifications, including acetylation, affect genome organization. In Neurospora, the HCHC complex (comprised of the proteins HDA-1, CDP-2, HP1, and CHAP) deacetylates heterochromatic nucleosomes, as loss of individual HCHC members increases centromeric acetylation and alters the methylation of cytosines in DNA. Here, we assess if the HCHC complex affects genome organization by performing Hi-C in strains deleted of the cdp-2 or chap genes. CDP-2 loss increases intra- and inter-chromosomal heterochromatic region interactions, while loss of CHAP decreases heterochromatic region compaction. Individual HCHC mutants exhibit different patterns of histone post-translational modifications genome-wide: without CDP-2, heterochromatic H4K16 acetylation is increased, yet smaller heterochromatic regions lose H3K9 trimethylation and gain inter-heterochromatic region interactions; CHAP loss produces minimal acetylation changes but increases heterochromatic H3K9me3 enrichment. Loss of both CDP-2 and the DIM-2 DNA methyltransferase causes extensive genome disorder, as heterochromatic-euchromatic contacts increase despite additional H3K9me3 enrichment. Our results highlight how the increased cytosine methylation in HCHC mutants ensures genome compartmentalization when heterochromatic regions become hyperacetylated without HDAC activity.

IChrom-Deep: An Attention-Based Deep Learning Model for Identifying Chromatin Interactions

Identification of chromatin interactions is crucial for advancing our knowledge of gene regulation. However, due to the limitations of high-throughput experimental techniques, there is an urgent need to develop computational methods for predicting chromatin interactions. In this study, we propose a novel attention-based deep learning model, termed IChrom-Deep, to identify chromatin interactions using sequence features and genomic features. The experimental results based on the datasets of three cell lines demonstrate that the IChrom-Deep achieves satisfactory performance and is superior to the previous methods. We also investigate the effect of DNA sequence and associated features and genomic features on chromatin interactions, and highlight the applicable scenarios of some features, such as sequence conservation and distance. Moreover, we identify a few genomic features that are extremely important across different cell lines, and IChrom-Deep achieves comparable performance with only these significant genomic features versus using all genomic features. It is believed that IChrom-Deep can serve as a useful tool for future studies that seek to identify chromatin interactions.

Enhancer Coamplification and Hijacking Promote Oncogene Expression in Liposarcoma

SIGNIFICANCE

Comprehensive profiling of the enhancer landscape and 3D genome structure in liposarcoma identifies extensive enhancer-oncogene coamplification and enhancer hijacking events, deepening the understanding of how oncogenes are regulated in cancer.

HiC-GNN: A generalizable model for 3D chromosome reconstruction using graph convolutional neural networks

Chromosome conformation capture (3 C) is a method of measuring chromosome topology in terms of loci interaction. The Hi-C method is a derivative of 3 C that allows for genome-wide quantification of chromosome interaction. From such interaction data, it is possible to infer the three-dimensional (3D) structure of the underlying chromosome. In this paper, we developed a novel method, HiC-GNN, for predicting the 3D structures of chromosomes from Hi-C data. HiC-GNN is unique from other methods for chromosome structure prediction in that the models learned by HiC-GNN can be generalized to data that is distinct from the training data. This aspect of HiC-GNN allows models that were trained on one Hi-C contact map to be used for inference on entirely different maps. To the authors' knowledge, this generalizing capability is not present in any existing methods. HiC-GNN uses a node embedding algorithm and a graph neural network to predict the 3D coordinates of each genomic loci from the corresponding Hi-C contact data. Unlike other methods, our algorithm allows for the storage of pre-trained parameters, thus enabling prediction on data that is entirely different from the training data. We show that our method can accurately generalize a single model across Hi-C resolutions, multiple restriction enzymes, and multiple cell populations while maintaining reconstruction accuracy across three Hi-C datasets. Our algorithm outperforms the state-of-the-art methods in accuracy of prediction and runtime and introduces a novel method for 3D structure prediction from Hi-C data. All our source codes and data are available at https://github.com/OluwadareLab/HiC-GNN.

A review and performance evaluation of clustering frameworks for single-cell Hi-C data

The three-dimensional genome structure plays a key role in cellular function and gene regulation. Single-cell Hi-C (high-resolution chromosome conformation capture) technology can capture genome structure information at the cell level, which provides the opportunity to study how genome structure varies among different cell types. Recently, a few methods are well designed for single-cell Hi-C clustering. In this manuscript, we perform an in-depth benchmark study of available single-cell Hi-C data clustering methods to implement an evaluation system for multiple clustering frameworks based on both human and mouse datasets. We compare eight methods in terms of visualization and clustering performance. Performance is evaluated using four benchmark metrics including adjusted rand index, normalized mutual information, homogeneity and Fowlkes-Mallows index. Furthermore, we also evaluate the eight methods for the task of separating cells at different stages of the cell cycle based on single-cell Hi-C data.

MCIBox: a toolkit for single-molecule multi-way chromatin interaction visualization and micro-domains identification

The emerging ligation-free three-dimensional (3D) genome mapping technologies can identify multiplex chromatin interactions with single-molecule precision. These technologies not only offer new insight into high-dimensional chromatin organization and gene regulation, but also introduce new challenges in data visualization and analysis. To overcome these challenges, we developed MCIBox, a toolkit for multi-way chromatin interaction (MCI) analysis, including a visualization tool and a platform for identifying micro-domains with clustered single-molecule chromatin complexes. MCIBox is based on various clustering algorithms integrated with dimensionality reduction methods that can display multiplex chromatin interactions at single-molecule level, allowing users to explore chromatin extrusion patterns and super-enhancers regulation modes in transcription, and to identify single-molecule chromatin complexes that are clustered into micro-domains. Furthermore, MCIBox incorporates a two-dimensional kernel density estimation algorithm to identify micro-domains boundaries automatically. These micro-domains were stratified with distinctive signatures of transcription activity and contained different cell-cycle-associated genes. Taken together, MCIBox represents an invaluable tool for the study of multiple chromatin interactions and inaugurates a previously unappreciated view of 3D genome structure.

CLNN-loop: a deep learning model to predict CTCF-mediated chromatin loops in the different cell lines and CTCF-binding sites (CBS) pair types

MOTIVATION

Three-dimensional (3D) genome organization is of vital importance in gene regulation and disease mechanisms. Previous studies have shown that CTCF-mediated chromatin loops are crucial to studying the 3D structure of cells. Although various experimental techniques have been developed to detect chromatin loops, they have been found to be time-consuming and costly. Nowadays, various sequence-based computational methods can capture significant features of 3D genome organization and help predict chromatin loops. However, these methods have low performance and poor generalization ability in predicting chromatin loops.

RESULTS

Here, we propose a novel deep learning model, called CLNN-loop, to predict chromatin loops in different cell lines and CTCF-binding sites (CBS) pair types by fusing multiple sequence-based features. The analysis of a series of examinations based on the datasets in the previous study shows that CLNN-loop has satisfactory performance and is superior to the existing methods in terms of predicting chromatin loops. In addition, we apply the SHAP framework to interpret the predictions of different models, and find that CTCF motif and sequence conservation are important signs of chromatin loops in different cell lines and CBS pair types.

AVAILABILITY AND IMPLEMENTATION

The source code of CLNN-loop is freely available at https://github.com/HaoWuLab-Bioinformatics/CLNN-loop and the webserver of CLNN-loop is freely available at http://hwclnn.sdu.edu.cn.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

VvSUN may act in the auxin pathway to regulate fruit shape in grape

Fruit shape is an essential agronomic feature in many crops. We identified and functionally characterized an auxin pathway-related gene, VvSUN. VvSUN, which belongs to the SUN/IQ67-DOMAIN (IQD) family, localizes to the plasma membrane and chloroplast and may be involved in controlling fruit shape through auxin. It is highly expressed in the ovary, and the expression level 1 week before the anthesis stage is positively correlated with the fruit shape index. Functional analyses illustrated that VvSUN gene overexpression in tomato and tobacco plants changed fruit/pod shape. The VvSUN promoter directly bound to VvARF6 in yeast and activated ß-glucuronidase (GUS) activity by indole-3-acetic acid (IAA) treatments in grapevine leaves, indicating that VvSUN functions are in coordination with auxin. Further analysis of 35S::VvSUN transgenic tomato ovaries showed that the fruit shape changes caused by VvSUN were predominantly caused by variations in cell number in longitudinal directions by regulating endogenous auxin levels via polar transport and/or auxin signal transduction process variations. Moreover, enrichment of the 35S::VvSUN transgenic tomato differentially expressed genes was found in a variety of biological processes, including primary metabolic process, transmembrane transport, calcium ion binding, cytoskeletal protein binding, tubulin binding, and microtubule-based movement. Using weighted gene co-expression network analysis (WGCNA), we confirmed that this plant hormone signal transduction may play a crucial role in controlling fruit shape. As a consequence, it is possible that VvSUN acts as a hub gene, altering cellular auxin levels and the plant hormone signal transduction pathway, which plays a role in cell division patterns, leading to anisotropic growth of the ovary and, ultimately, an elongated fruit shape.

Chromatin architecture in addiction circuitry identifies risk genes and potential biological mechanisms underlying cigarette smoking and alcohol use traits

Cigarette smoking and alcohol use are among the most prevalent substances used worldwide and account for a substantial proportion of preventable morbidity and mortality, underscoring the public health significance of understanding their etiology. Genome-wide association studies (GWAS) have successfully identified genetic variants associated with cigarette smoking and alcohol use traits. However, the vast majority of risk variants reside in non-coding regions of the genome, and their target genes and neurobiological mechanisms are unknown. Chromosomal conformation mappings can address this knowledge gap by charting the interaction profiles of risk-associated regulatory variants with target genes. To investigate the functional impact of common variants associated with cigarette smoking and alcohol use traits, we applied Hi-C coupled MAGMA (H-MAGMA) built upon cortical and newly generated midbrain dopaminergic neuronal Hi-C datasets to GWAS summary statistics of nicotine dependence, cigarettes per day, problematic alcohol use, and drinks per week. The identified risk genes mapped to key pathways associated with cigarette smoking and alcohol use traits, including drug metabolic processes and neuronal apoptosis. Risk genes were highly expressed in cortical glutamatergic, midbrain dopaminergic, GABAergic, and serotonergic neurons, suggesting them as relevant cell types in understanding the mechanisms by which genetic risk factors influence cigarette smoking and alcohol use. Lastly, we identified pleiotropic genes between cigarette smoking and alcohol use traits under the assumption that they may reveal substance-agnostic, shared neurobiological mechanisms of addiction. The number of pleiotropic genes was ~26-fold higher in dopaminergic neurons than in cortical neurons, emphasizing the critical role of ascending dopaminergic pathways in mediating general addiction phenotypes. Collectively, brain region- and neuronal subtype-specific 3D genome architecture helps refine neurobiological hypotheses for smoking, alcohol, and general addiction phenotypes by linking genetic risk factors to their target genes.

The genome organization of Neurospora crassa at high resolution uncovers principles of fungal chromosome topology

The eukaryotic genome must be precisely organized for its proper function, as genome topology impacts transcriptional regulation, cell division, replication, and repair, among other essential processes. Disruptions to human genome topology can lead to diseases, including cancer. The advent of chromosome conformation capture with high-throughput sequencing (Hi-C) to assess genome organization has revolutionized the study of nuclear genome topology; Hi-C has elucidated numerous genomic structures, including chromosomal territories, active/silent chromatin compartments, Topologically Associated Domains, and chromatin loops. While low-resolution heatmaps can provide important insights into chromosomal level contacts, high-resolution Hi-C datasets are required to reveal folding principles of individual genes. Of particular interest are high-resolution chromosome conformation datasets of organisms modeling the human genome. Here, we report the genome topology of the fungal model organism Neurospora crassa at a high resolution. Our composite Hi-C dataset, which merges 2 independent datasets generated with restriction enzymes that monitor euchromatin (DpnII) and heterochromatin (MseI), along with our DpnII/MseI double digest dataset, provide exquisite detail for both the conformation of entire chromosomes and the folding of chromatin at the resolution of individual genes. Within constitutive heterochromatin, we observe strong yet stochastic internal contacts, while euchromatin enriched with either activating or repressive histone post-translational modifications associates with constitutive heterochromatic regions, suggesting intercompartment contacts form to regulate transcription. Consistent with this, a strain with compromised heterochromatin experiences numerous changes in gene expression. Our high-resolution Neurospora Hi-C datasets are outstanding resources to the fungal community and provide valuable insights into higher organism genome topology.

StackTADB: a stacking-based ensemble learning model for predicting the boundaries of topologically associating domains (TADs) accurately in fruit flies

Chromosome is composed of many distinct chromatin domains, referred to variably as topological domains or topologically associating domains (TADs). The domains are stable across different cell types and highly conserved across species, thus these chromatin domains have been considered as the basic units of chromosome folding and regarded as an important secondary structure in chromosome organization. However, the identification of TAD boundaries is still a great challenge due to the high cost and low resolution of Hi-C data or experiments. In this study, we propose a novel ensemble learning framework, termed as StackTADB, for predicting the boundaries of TADs. StackTADB integrates four base classifiers including Random Forest, Logistic Regression, K-NearestNeighbor and Support Vector Machine. From the analysis of a series of examinations on the data set in the previous study, it is concluded that StackTADB has optimal performance in six metrics, AUC, Accuracy, MCC, Precision, Recall and F1 score, and it is superior to the existing methods. In addition, the comparison of the performance of multiple features shows that Kmers-based features play an essential role in predicting TADs boundaries of fruit flies, and we also apply the SHapley Additive exPlanations (SHAP) framework to interpret the predictions of StackTADB to identify the reason why Kmers-based features are vital. The experimental results show that the subsequences matching the BEAF-32 motif play a crucial role in predicting the boundaries of TADs. The source code is freely available at https://github.com/HaoWuLab-Bioinformatics/StackTADB and the webserver of StackTADB is freely available at http://hwtad.sdu.edu.cn:8002/StackTADB.

spatzie: an R package for identifying significant transcription factor motif co-enrichment from enhancer–promoter interactions

Genomic interactions provide important context to our understanding of the state of the genome. One question is whether specific transcription factor interactions give rise to genome organization. We introduce spatzie, an R package and a website that implements statistical tests for significant transcription factor motif cooperativity between enhancer–promoter interactions. We conducted controlled experiments under realistic simulated data from ChIP-seq to confirm spatzie is capable of discovering co-enriched motif interactions even in noisy conditions. We then use spatzie to investigate cell type specific transcription factor cooperativity within recent human ChIA-PET enhancer–promoter interaction data. The method is available online at https://spatzie.mit.edu.

Normalization of Chromosome Contact Maps: Matrix Balancing and Visualization

Over the last decade, genomic proximity ligation approaches have reshaped our vision of chromosomes 3D organizations, from bacteria nucleoids to larger eukaryotic genomes. The different protocols (3Cseq, Hi-C, TCC, MicroC [XL], Hi-CO, etc.) rely on common steps (chemical fixation digestion, ligation…) to detect pairs of genomic positions in close proximity. The most common way to represent these data is a matrix, or contact map, which allows visualizing the different chromatin structures (compartments, loops, etc.) that can be associated to other signals such as transcription, protein occupancy, etc. as well as, in some instances, to biological functions.In this chapter we present and discuss the filtering of the events recovered in proximity ligation experiments as well as the application of the balancing normalization procedure on the resulting contact map. We also describe a computational tool for visualizing normalized contact data dubbed Scalogram.The different processes described here are illustrated and supported by the laboratory custom-made scripts pooled into "hicstuff," an open-access python package accessible on github ( https://github.com/koszullab/hicstuff ).

Mapping nucleosome and chromatin architectures: A survey of computational methods

With ever-growing genomic sequencing data, the data variabilities and the underlying biases of the sequencing technologies pose significant computational challenges ranging from the need for accurately detecting the nucleosome positioning or chromatin interaction to the need for developing normalization methods to eliminate systematic biases. This review mainly surveys the computational methods for mapping the higher-resolution nucleosome and higher-order chromatin architectures. While a detailed discussion of the underlying algorithms is beyond the scope of our survey, we have discussed the methods and tools that can detect the nucleosomes in the genome, then demonstrated the computational methods for identifying 3D chromatin domains and interactions. We further illustrated computational approaches for integrating multi-omics data with Hi-C data and the advance of single-cell (sc)Hi-C data analysis. Our survey provides a comprehensive and valuable resource for biomedical scientists interested in studying nucleosome organization and chromatin structures as well as for computational scientists who are interested in improving upon them.

Epigenetics and tissue immunity-Translating environmental cues into functional adaptations

There is an increasing appreciation that many innate and adaptive immune cell subsets permanently reside within non-lymphoid organs, playing a critical role in tissue homeostasis and defense. The best characterized are macrophages and tissue-resident T lymphocytes that work in concert with organ structural cells to generate appropriate immune responses and are functionally shaped by organ-specific environmental cues. The interaction of tissue epithelial, endothelial and stromal cells is also required to attract, differentiate, polarize and maintain organ immune cells in their tissue niche. All of these processes require dynamic regulation of cellular transcriptional programmes, with epigenetic mechanisms playing a critical role, including DNA methylation and post-translational histone modifications. A failure to appropriately regulate immune cell transcription inevitably results in inadequate or inappropriate immune responses and organ pathology. Here, with a focus on the mammalian kidney, an organ which generates differing regional environmental cues (including hypersalinity and hypoxia) due to its physiological functions, we will review the basic concepts of tissue immunity, discuss the technologies available to profile epigenetic modifications in tissue immune cells, including those that enable single-cell profiling, and consider how these mechanisms influence the development, phenotype, activation and function of different tissue immune cell subsets, as well as the immunological function of structural cells.

Four-Dimensional Chromosome Structure Prediction

Chromatin conformation plays an important role in a variety of genomic processes, including genome replication, gene expression, and gene methylation. Hi-C data is frequently used to analyze structural features of chromatin, such as AB compartments, topologically associated domains, and 3D structural models. Recently, the genomics community has displayed growing interest in chromatin dynamics. Here, we present 4DMax, a novel method, which uses time-series Hi-C data to predict dynamic chromosome conformation. Using both synthetic data and real time-series Hi-C data from processes, such as induced pluripotent stem cell reprogramming and cardiomyocyte differentiation, we construct smooth four-dimensional models of individual chromosomes. These predicted 4D models effectively interpolate chromatin position across time, permitting prediction of unknown Hi-C contact maps at intermittent time points. Furthermore, 4DMax correctly recovers higher order features of chromatin, such as AB compartments and topologically associated domains, even at time points where Hi-C data is not made available to the algorithm. Contact map predictions made using 4DMax outperform naïve numerical interpolation in 87.7% of predictions on the induced pluripotent stem cell dataset. A/B compartment profiles derived from 4DMax interpolation showed higher similarity to ground truth than at least one profile generated from a neighboring time point in 100% of induced pluripotent stem cell experiments. Use of 4DMax may alleviate the cost of expensive Hi-C experiments by interpolating intermediary time points while also providing valuable visualization of dynamic chromatin changes.

Neural differentiation of glioblastoma cell lines via a herpes simplex virus thymidine kinase/ganciclovir system driven by a glial fibrillary acidic protein promoter

Glioblastoma is a malignant brain tumor with poor prognosis that rapidly acquires resistance to available clinical treatments. The herpes simplex virus thymidine kinase/ganciclovir (HSVtk/GCV) system produces the selective elimination of HSVtk-positive cells and is a candidate for preclinical testing against glioblastoma via its ability to regulate proliferation and differentiation. Therefore, in this study, we aimed to establish a plasmid encoding the HSVtk/GCV system driven by a glial fibrillary acidic protein (GFAP) promoter and verify its possibility of neural differentiation of glioblastoma cell line under the GCV challenge. Four stable clones-N2A-pCMV-HSVtk, N2A-pGFAP-HSVtk, U251-pCMV-HSVtk, and U251-pGFAP-HSVtk-were established from neuronal N2A and glioblastoma U251 cell lines. In vitro GCV sensitivity was assessed by MTT assay for monitoring time- and dosage-dependent cytotoxicity. The capability for neural differentiation in stable glioblastoma clones during GCV treatment was assessed by performing immunocytochemistry for nestin, GFAP, and βIII-tubulin. Under GFAP promoter control, the U251 stable clone exhibited GCV sensitivity, while the neuronal N2A clones were nonreactive. During GCV treatment, cells underwent apoptosis on day 3 and dying cells were identified after day 5. Nestin was increasingly expressed in surviving cells, indicating that the population of neural stem-like cells was enriched. Lower levels of GFAP expression were detected in surviving cells. Furthermore, βIII-tubulin-positive neuron-like cells were identified after GCV treatment. This study established pGFAP-HSVtk-P2A-EGFP plasmids that successfully ablated GFAP-positive glioblastoma cells, but left neuronal N2A cells intact. These data suggest that the neural differentiation of glioblastoma cells can be promoted by treatment with the HSVtk/GCV system.

A plug and play microfluidic platform for standardized sensitive low-input chromatin immunoprecipitation

Epigenetic profiling by chromatin immunoprecipitation followed by sequencing (ChIP-seq) has become a powerful tool for genome-wide identification of regulatory elements, for defining transcriptional regulatory networks, and for screening for biomarkers. However, the ChIP-seq protocol for low-input samples is laborious and time-consuming and suffers from experimental variation, resulting in poor reproducibility and low throughput. Although prototypic microfluidic ChIP-seq platforms have been developed, these are poorly transferable as they require sophisticated custom-made equipment and in-depth microfluidic and ChIP expertise, while lacking parallelization. To enable standardized, automated ChIP-seq profiling of low-input samples, we constructed microfluidic PDMS-based plates capable of performing 24 sensitive ChIP reactions within 30 min of hands-on time and 4.5 h of machine-running time. These disposable plates can be conveniently loaded into a widely available controller for pneumatics and thermocycling. In light of the plug and play (PnP) ChIP plates and workflow, we named our procedure PnP-ChIP-seq. We show high-quality ChIP-seq on hundreds to a few thousand of cells for all six post-translational histone modifications that are included in the International Human Epigenome Consortium set of reference epigenomes. PnP-ChIP-seq robustly detects epigenetic differences on promoters and enhancers between naive and more primed mouse embryonic stem cells (mESCs). Furthermore, we used our platform to generate epigenetic profiles of rare subpopulations of mESCs that resemble the two-cell stage of embryonic development. PnP-ChIP-seq allows nonexpert laboratories worldwide to conveniently run robust, standardized ChIP-seq, whereas its high throughput, consistency, and sensitivity pave the way toward large-scale profiling of precious sample types such as rare subpopulations of cells or biopsies.

In search of lost time: Enhancers as modulators of timing in lymphocyte development and differentiation

Proper timing of gene expression is central to lymphocyte development and differentiation. Lymphocytes often delay gene activation for hours to days after the onset of signaling components, which act on the order of seconds to minutes. Such delays play a prominent role during the intricate choreography of developmental events and during the execution of an effector response. Though a number of mechanisms are sufficient to explain timing at short timescales, it is not known how timing delays are implemented over long timescales that may span several cell generations. Based on the literature, we propose that a class of cis-regulatory elements, termed "timing enhancers," may explain how timing delays are controlled over these long timescales. By considering chromatin as a kinetic barrier to state switching, the timing enhancer model explains experimentally observed dynamics of gene expression where other models fall short. In this review, we elaborate on features of the timing enhancer model and discuss the evidence for its generality throughout development and differentiation. We then discuss potential molecular mechanisms underlying timing enhancer function. Finally, we explore recent evidence drawing connections between timing enhancers and genetic risk for immunopathology. We argue that the timing enhancer model is a useful framework for understanding how cis-regulatory elements control the central dimension of timing in lymphocyte biology.

MOLECULAR MEDICINE: Found in Translation

Studies of the major hemoglobin disorders, β-thalassemia and sickle cell disease (SCD), have laid a foundation for molecular medicine. While enormous progress has been made in understanding gene structure and regulation, translating molecular insights to therapy for the many individuals affected with these disorders has been challenging. Advances in three activities have recently converged to bring novel genetic and potentially curative treatments to clinical trials. First, improved lentiviral vectors for gene transfer into hematopoietic stem cells have revived somatic gene therapy for blood disorders. Second, elucidation of regulatory factors and mechanisms that control the normal developmental switch from fetal to adult hemoglobin has provided a route to reactivation of the fetal form for therapy. Third, revolutionary methods of gene engineering permit molecular insights to be leveraged for patients. Here I review how the promise of molecular medicine to bring transformative treatments to the clinical arena is finally being realized.

ASHIC: hierarchical Bayesian modeling of diploid chromatin contacts and structures

The recently developed Hi-C technique has been widely applied to map genome-wide chromatin interactions. However, current methods for analyzing diploid Hi-C data cannot fully distinguish between homologous chromosomes. Consequently, the existing diploid Hi-C analyses are based on sparse and inaccurate allele-specific contact matrices, which might lead to incorrect modeling of diploid genome architecture. Here we present ASHIC, a hierarchical Bayesian framework to model allele-specific chromatin organizations in diploid genomes. We developed two models under the Bayesian framework: the Poisson-multinomial (ASHIC-PM) model and the zero-inflated Poisson-multinomial (ASHIC-ZIPM) model. The proposed ASHIC methods impute allele-specific contact maps from diploid Hi-C data and simultaneously infer allelic 3D structures. Through simulation studies, we demonstrated that ASHIC methods outperformed existing approaches, especially under low coverage and low SNP density conditions. Additionally, in the analyses of diploid Hi-C datasets in mouse and human, our ASHIC-ZIPM method produced fine-resolution diploid chromatin maps and 3D structures and provided insights into the allelic chromatin organizations and functions. To summarize, our work provides a statistically rigorous framework for investigating fine-scale allele-specific chromatin conformations. The ASHIC software is publicly available at https://github.com/wmalab/ASHIC.

Chromatin Interaction Changes during the iPSC-NPC Model to Facilitate the Study of Biologically Significant Genes Involved in Differentiation

Given the difficulties of obtaining diseased cells, differentiation of neurons from patient-specific human induced pluripotent stem cells (iPSCs) with neural progenitor cells (NPCs) as intermediate precursors is of great interest. While cellular and transcriptomic changes during the differentiation process have been tracked, little attention has been given to examining spatial re-organization, which has been revealed to control gene regulation in various cells. To address the regulatory mechanism by 3D chromatin structure during neuronal differentiation, we examined the changes that take place during differentiation process using two cell types that are highly valued in the study of neurodegenerative disease - iPSCs and NPCs. In our study, we used Hi-C, a derivative of chromosome conformation capture that enables unbiased, genome-wide analysis of interaction frequencies in chromatin. We showed that while topologically associated domains remained mostly the same during differentiation, the presence of differential interacting regions in both cell types suggested that spatial organization affects gene regulation of both pluripotency maintenance and neuroectodermal differentiation. Moreover, closer analysis of promoter-promoter pairs suggested that cell fate specification is under the control of cis-regulatory elements. Our results are thus a resourceful addition in benchmarking differentiation protocols and also provide a greater appreciation of NPCs, the common precursors from which required neurons for applications in neurodegenerative diseases such as Parkinson's disease, Alzheimer's disease, schizophrenia and spinal cord injuries are utilized.

Latest Advances for the Sleeping Beauty Transposon System: 23 Years of Insomnia but Prettier than Ever: Refinement and Recent Innovations of the Sleeping Beauty Transposon System Enabling Novel, Nonviral Genetic Engineering Applications

The Sleeping Beauty transposon system is a nonviral DNA transfer tool capable of efficiently mediating transposition-based, stable integration of DNA sequences of choice into eukaryotic genomes. Continuous refinements of the system, including the emergence of hyperactive transposase mutants and novel approaches in vectorology, greatly improve upon transposition efficiency rivaling viral-vector-based methods for stable gene insertion. Current developments, such as reversible transgenesis and proof-of-concept RNA-guided transposition, further expand on possible applications in the future. In addition, innate advantages such as lack of preferential integration into genes reduce insertional mutagenesis-related safety concerns while comparably low manufacturing costs enable widespread implementation. Accordingly, the system is recognized as a powerful and versatile tool for genetic engineering and is playing a central role in an ever-expanding number of gene and cell therapy clinical trials with the potential to become a key technology to meet the growing demand for advanced therapy medicinal products.

GSDB: a database of 3D chromosome and genome structures reconstructed from Hi-C data

Advances in the study of chromosome conformation capture technologies, such as Hi-C technique - capable of capturing chromosomal interactions in a genome-wide scale - have led to the development of three-dimensional chromosome and genome structure reconstruction methods from Hi-C data. The three dimensional genome structure is important because it plays a role in a variety of important biological activities such as DNA replication, gene regulation, genome interaction, and gene expression. In recent years, numerous Hi-C datasets have been generated, and likewise, a number of genome structure construction algorithms have been developed.

In this work, we outline the construction of a novel Genome Structure Database (GSDB) to create a comprehensive repository that contains 3D structures for Hi-C datasets constructed by a variety of 3D structure reconstruction tools. The GSDB contains over 50,000 structures from 12 state-of-the-art Hi-C data structure prediction algorithms for 32 Hi-C datasets.

GSDB functions as a centralized collection of genome structures which will enable the exploration of the dynamic architectures of chromosomes and genomes for biomedical research. GSDB is accessible at http://sysbio.rnet.missouri.edu/3dgenome/GSDB

Cancer systems immunology

Tumor immunology is undergoing a renaissance due to the recent profound clinical successes of tumor immunotherapy. These advances have coincided with an exponential growth in the development of -omics technologies. Armed with these technologies and their associated computational and modeling toolsets, systems biologists have turned their attention to tumor immunology in an effort to understand the precise nature and consequences of interactions between tumors and the immune system. Such interactions are inherently multivariate, spanning multiple time and size scales, cell types, and organ systems, rendering systems biology approaches particularly amenable to their interrogation. While in its infancy, the field of 'Cancer Systems Immunology' has already influenced our understanding of tumor immunology and immunotherapy. As the field matures, studies will move beyond descriptive characterizations toward functional investigations of the emergent behavior that govern tumor-immune responses. Thus, Cancer Systems Immunology holds incredible promise to advance our ability to fight this disease.

ZEAMAP, a Comprehensive Database Adapted to the Maize Multi-Omics Era

As one of the most extensively cultivated crops, maize (Zea mays L.) has been extensively studied by researchers and breeders for over a century. With advances in high-throughput detection of various omics data, a wealth of multi-dimensional and multi-omics information has been accumulated for maize and its wild relative, teosinte. Integration of this information has the potential to accelerate genetic research and generate improvements in maize agronomic traits. To this end, we constructed ZEAMAP, a comprehensive database incorporating multiple reference genomes, annotations, comparative genomics, transcriptomes, open chromatin regions, chromatin interactions, high-quality genetic variants, phenotypes, metabolomics, genetic maps, genetic mapping loci, population structures, and populational DNA methylation signals within maize inbred lines. ZEAMAP is user friendly, with the ability to interactively integrate, visualize, and cross-reference multiple different omics datasets.

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Functional annotations and comparative genomics of maize and teosinte genomes

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Multi-omics data generated from the same maize inbred lines panel

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Interactive tools to query, cross-refer, and visualize the omics data

Inferring Spatial Organization of Individual Topologically Associated Domains via Piecewise Helical Model

The recently developed Hi-C technology enables a genome-wide view of chromosome spatial organizations, and has shed deep insights into genome structure and genome function. However, multiple sources of uncertainties make downstream data analysis and interpretation challenging. Specifically, statistical models for inferring three-dimensional (3D) chromosomal structure from Hi-C data are far from their maturity. Most existing methods are highly over-parameterized, lacking clear interpretations, and sensitive to outliers. In this study, we propose a parsimonious, easy to interpret, and robust piecewise helical model for the inference of 3D chromosomal structure of individual topologically associated domain from Hi-C data. When applied to a real Hi-C dataset, the piecewise helical model not only achieves much better model fitting than existing models, but also reveals that geometric properties of chromatin spatial organization are closely related to genome function.

The chromatin bound proteome of the human malaria parasite

Proteins interacting with DNA are fundamental for mediating processes such as gene expression, DNA replication and maintenance of genome integrity. Accumulating evidence suggests that the chromatin of apicomplexan parasites, such as Plasmodium falciparum, is highly organized, and this structure provides an epigenetic mechanism for transcriptional regulation. To investigate how parasite chromatin structure is being regulated, we undertook comparative genomics analysis using 12 distinct eukaryotic genomes. We identified conserved and parasite-specific chromatin-associated domains (CADs) and proteins (CAPs). We then used the chromatin enrichment for proteomics (ChEP) approach to experimentally capture CAPs in P. falciparum. A topological scoring analysis of the proteomics dataset revealed stage-specific enrichments of CADs and CAPs. Finally, we characterized, two candidate CAPs: a conserved homologue of the structural maintenance of chromosome 3 protein and a homologue of the crowded-like nuclei protein, a plant-like protein functionally analogous to animal nuclear lamina proteins. Collectively, our results provide a comprehensive overview of CAPs in apicomplexans, and contribute to our understanding of the complex molecular components regulating chromatin structure and genome architecture in these deadly parasites.

Invited Review: Epigenetics in neurodevelopment

Neural development requires the orchestration of dynamic changes in gene expression to regulate cell fate decisions. This regulation is heavily influenced by epigenetics, heritable changes in gene expression not directly explained by genomic information alone. An understanding of the complexity of epigenetic regulation is rapidly emerging through the development of novel technologies that can assay various features of epigenetics and gene regulation. Here, we provide a broad overview of several commonly investigated modes of epigenetic regulation, including DNA methylation, histone modifications, noncoding RNAs, as well as epitranscriptomics that describe modifications of RNA, in neurodevelopment and diseases. Rather than functioning in isolation, it is being increasingly appreciated that these various modes of gene regulation are dynamically interactive and coordinate the complex nature of neurodevelopment along multiple axes. Future work investigating these interactions will likely utilize 'multi-omic' strategies that assay cell fate dynamics in a high-dimensional and high-throughput fashion. Novel human neurodevelopmental models including iPSC and cerebral organoid systems may provide further insight into human-specific features of neurodevelopment and diseases.

Supramolecular multilayer organization of chromosomes: possible functional roles of planar chromatin in gene expression and DNA replication and repair

Experimental evidence indicates that the chromatin filament is self-organized into a multilayer planar structure that is densely stacked in metaphase and unstacked in interphase. This chromatin organization is unexpected, but it is shown that diverse supramolecular assemblies, including dinoflagellate chromosomes, are multilayered. The mechanical strength of planar chromatin protects the genome integrity, even when double-strand breaks are produced. Here, it is hypothesized that the chromatin filament in the loops and topologically associating domains is folded within the thin layers of the multilaminar chromosomes. It is also proposed that multilayer chromatin has two states: inactive when layers are stacked and active when layers are unstacked. Importantly, the well-defined topology of planar chromatin may facilitate DNA replication without entanglements and DNA repair by homologous recombination.

Role of nucleosome positioning in 3D chromatin organization and loop formation

We present a physics-based polymer model that can investigate 3D organization of chromatin accounting for DNA elasticity, DNA-bending due to nucleosomes, and 1D organization of nucleosomes along DNA. We find that the packing density of chromatin oscillates between densities corresponding to highly folded and extended configurations as we change the nucleosome organization (length of linker DNA). We compute the looping probability of chromatin and show that the presence of nucleosomes increases the looping probability of the chain compared to that of a bare DNA. We also show that looping probability has a large variability depending on the nature of nucleosome organization and density of linker histones.

A computational method to predict topologically associating domain boundaries combining histone Marks and sequence information

Background

The three-dimensional (3D) structure of chromatins plays significant roles during cell differentiation and development. Hi-C and other 3C-based technologies allow us to look deep into the chromatin architectures. Many studies have suggested that topologically associating domains (TAD), as the structure and functional unit, are conserved across different organs. However, our understanding about the underlying mechanism of the TAD boundary formation is still limited.

Results

We developed a computational method, TAD–Lactuca, to infer this structure by taking the contextual information of the epigenetic modification signals and the primary DNA sequence information on the genome. TAD–Lactuca is found stable in the case of multi-resolutions and different datasets. It could achieve high accuracy and even outperforms the state-of-art methods when the sequence patterns were incorporated. Moreover, several transcript factor binding motifs, besides the well-known CCCTC-binding factor (CTCF) motif, were found significantly enriched on the boundaries.

Conclusions

We provided a low cost, effective method to predict TAD boundaries. Above results suggested the incorporation of sequence features could significantly improve the performance. The sequence motif enrichment analysis indicates several gene regulation motifs around the boundaries, which is consistent with TADs may serve as the functional units of gene regulation and implies the sequence patterns would be important in chromatin folding.

High resolution discovery of chromatin interactions

Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) is a method for the genome-wide de novo discovery of chromatin interactions. Existing computational methods typically fail to detect weak or dynamic interactions because they use a peak-calling step that ignores paired-end linkage information. We have developed a novel computational method called Chromatin Interaction Discovery (CID) to overcome this limitation with an unbiased clustering approach for interaction discovery. CID outperforms existing chromatin interaction detection methods with improved sensitivity, replicate consistency, and concordance with other chromatin interaction datasets. In addition, CID also outperforms other methods in discovering chromatin interactions from HiChIP data. We expect that the CID method will be valuable in characterizing 3D chromatin interactions and in understanding the functional consequences of disease-associated distal genetic variations.

Integrated genome-wide methylation and expression analyses reveal functional predictors of response to antidepressants

Major depressive disorder (MDD) is primarily treated with antidepressants, yet many patients fail to respond adequately, and identifying antidepressant response biomarkers is thus of clinical significance. Some hypothesis-driven investigations of epigenetic markers for treatment response have been previously made, but genome-wide approaches remain unexplored. Healthy participants (n = 112) and MDD patients (n = 211) between 18-60 years old were recruited for an 8-week trial of escitalopram treatment. Responders and non-responders were identified using differential Montgomery-Åsberg Depression Rating Scale scores before and after treatment. Genome-wide DNA methylation and gene expression analyses were assessed using the Infinium MethylationEPIC Beadchip and HumanHT-12 v4 Expression Beadchip, respectively, on pre-treatment peripheral blood DNA and RNA samples. Differentially methylated positions (DMPs) located in regions of differentially expressed genes between responders (n = 82) and non-responders (n = 95) were identified, and technically validated using a targeted sequencing approach. Three DMPs located in the genes CHN2 (cg23687322, p = 0.00043 and cg06926818, p = 0.0014) and JAK2 (cg08339825, p = 0.00021) were the most significantly associated with mRNA expression changes and subsequently validated. Replication was then conducted with non-responders (n = 76) and responders (n = 71) in an external cohort that underwent a similar antidepressant trial. One CHN2 site (cg06926818; p = 0.03) was successfully replicated. Our findings indicate that differential methylation at CpG sites upstream of the CHN2 and JAK2 TSS regions are possible peripheral predictors of antidepressant treatment response. Future studies can provide further insight on robustness of our candidate biomarkers, and greater characterization of functional components.

Epigenomics: Technologies and Applications

The advent of high-throughput epigenome mapping technologies has ushered in a new era of multiomics where powerful tools can now delineate and record different layers of genomic output. Integrating various components of the epigenome from these multiomics measurements allows the interrogation of cellular heterogeneity in addition to the discovery of molecular connectivity maps between the genome and its functional output. Mapping of chromatin accessibility dynamics and higher-order chromatin structure has enabled new levels of understanding of cell fate decisions, identity, and function in normal development, physiology, and disease. We provide a perspective on the progress of the epigenomics field and applications and anticipate an even greater revolution in our understanding of the human epigenome for years to come.

Cross-linker mediated compaction and local morphologies in a model chromosome

Chromatin and associated proteins constitute the highly folded structure of chromosomes. We consider a self-avoiding polymer model of the chromatin, segments of which may get cross-linked via protein binders that repel each other. The binders cluster together via the polymer mediated attraction, in turn, folding the polymer. Using molecular dynamics simulations, and a mean field description, we explicitly demonstrate the continuous nature of the folding transition, characterized by unimodal distributions of the polymer size across the transition. At the transition point the chromatin size and cross-linker clusters display large fluctuations, and a maximum in their negative cross-correlation, apart from a critical slowing down. Along the transition, we distinguish the local chain morphologies in terms of topological loops, inter-loop gaps, and zippering. The topologies are dominated by simply connected loops at the criticality, and by zippering in the folded phase.

NETWORK MODELLING OF TOPOLOGICAL DOMAINS USING HI-C DATA

Chromosome conformation capture experiments such as Hi-C are used to map the three-dimensional spatial organization of genomes. One specific feature of the 3D organization is known as topologically associating domains (TADs), which are densely interacting, contiguous chromatin regions playing important roles in regulating gene expression. A few algorithms have been proposed to detect TADs. In particular, the structure of Hi-C data naturally inspires application of community detection methods. However, one of the drawbacks of community detection is that most methods take exchangeability of the nodes in the network for granted; whereas the nodes in this case, that is, the positions on the chromosomes, are not exchangeable. We propose a network model for detecting TADs using Hi-C data that takes into account this nonexchangeability. in addition, our model explicitly makes use of cell-type specific CTCF binding sites as biological covariates and can be used to identify conserved TADs across multiple cell types. The model leads to a likelihood objective that can be efficiently optimized via relaxation. We also prove that when suitably initialized, this model finds the underlying TAD structure with high probability. using simulated data, we show the advantages of our method and the caveats of popular community detection methods, such as spectral clustering, in this application. Applying our method to real Hi-C data, we demonstrate the domains identified have desirable epigenetic features and compare them across different cell types.

Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa

Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness1, affecting 0.9-4% of women and 0.3% of men2-4, with twin-based heritability estimates of 50-60%5. Mortality rates are higher than those in other psychiatric disorders6, and outcomes are unacceptably poor7. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI)8,9 and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.

Reorganization of 3D genome structure may contribute to gene regulatory evolution in primates

A growing body of evidence supports the notion that variation in gene regulation plays a crucial role in both speciation and adaptation. However, a comprehensive functional understanding of the mechanisms underlying regulatory evolution remains elusive. In primates, one of the crucial missing pieces of information towards a better understanding of regulatory evolution is a comparative annotation of interactions between distal regulatory elements and promoters. Chromatin conformation capture technologies have enabled genome-wide quantifications of such distal 3D interactions. However, relatively little comparative research in primates has been done using such technologies. To address this gap, we used Hi-C to characterize 3D chromatin interactions in induced pluripotent stem cells (iPSCs) from humans and chimpanzees. We also used RNA-seq to collect gene expression data from the same lines. We generally observed that lower-order, pairwise 3D genomic interactions are conserved in humans and chimpanzees, but higher order genomic structures, such as topologically associating domains (TADs), are not as conserved. Inter-species differences in 3D genomic interactions are often associated with gene expression differences between the species. To provide additional functional context to our observations, we considered previously published chromatin data from human stem cells. We found that inter-species differences in 3D genomic interactions, which are also associated with gene expression differences between the species, are enriched for both active and repressive marks. Overall, our data demonstrate that, as expected, an understanding of 3D genome reorganization is key to explaining regulatory evolution.

The way in which a genome folds affects the regulation of gene expression. This is often due to loops in the three-dimensional structure that bring linearly distant genes and regulatory elements into close proximity. Most studies examining three-dimensional structure genome-wide are limited to a single species. In this study, we compared three-dimensional structure in the genomes of induced pluripotent stem cells from humans and chimpanzees. We collected gene expression data from the same samples, which allowed us to assess the contribution of three-dimensional chromatin conformation to gene regulatory evolution in primates. Our results demonstrate that gene expression differences between the species may often be mediated by differences in three-dimensional genomic interactions. Our data also suggest that large-scale chromatin structures (i.e. topologically associating domains, TADs) are not well conserved in their placement across species. We hope the analytical paradigms we present here could serve as a basis for future comparative studies of three-dimensional genome organization, elucidating the putative functional regulatory loci driving speciation.

Long Noncoding RNAs in Host-Pathogen Interactions

Long noncoding RNAs (lncRNAs) are key molecules that regulate gene expression in a variety of organisms. LncRNAs can drive different transcriptional and post-transcriptional events that impact cellular functions. Recent studies have identified many lncRNAs associated with immune cell development and activation; however, an understanding of their functional role in host immunity to infection is just emerging. Here, we provide a detailed and updated review of the functional roles of lncRNAs in regulating mammalian immune responses during host-pathogen interactions, because these functions may be either beneficial or detrimental to the host. With increased mechanistic insight into the roles of lncRNAs, it may be possible to design and/or improve lncRNA-based therapies to treat a variety of infectious and inflammatory diseases.

An Overview of Methods for Reconstructing 3-D Chromosome and Genome Structures from Hi-C Data

Over the past decade, methods for predicting three-dimensional (3-D) chromosome and genome structures have proliferated. This has been primarily due to the development of high-throughput, next-generation chromosome conformation capture (3C) technologies, which have provided next-generation sequencing data about chromosome conformations in order to map the 3-D genome structure. The introduction of the Hi-C technique-a variant of the 3C method-has allowed researchers to extract the interaction frequency (IF) for all loci of a genome at high-throughput and at a genome-wide scale. In this review we describe, categorize, and compare the various methods developed to map chromosome and genome structures from 3C data-particularly Hi-C data. We summarize the improvements introduced by these methods, describe the approach used for method evaluation, and discuss how these advancements shape the future of genome structure construction.