Capturing chromosome conformation

Functional genomic assays to annotate enhancer-promoter interactions genome wide

Enhancers are pivotal for regulating gene transcription that occurs at promoters. Identification of the interacting enhancer-promoter pairs and understanding the mechanisms behind how they interact and how enhancers modulate transcription can provide fundamental insight into gene regulatory networks. Recently, advances in high-throughput methods in three major areas-chromosome conformation capture assay, such as Hi-C to study basic chromatin architecture, ectopic reporter experiments such as self-transcribing active regulatory region sequencing (STARR-seq) to quantify promoter and enhancer activity, and endogenous perturbations such as clustered regularly interspaced short palindromic repeat interference (CRISPRi) to identify enhancer-promoter compatibility-have further our knowledge about transcription. In this review, we will discuss the major method developments and key findings from these assays.

Normalization and de-noising of single-cell Hi-C data with BandNorm and scVI-3D

Single-cell high-throughput chromatin conformation capture methodologies (scHi-C) enable profiling of long-range genomic interactions. However, data from these technologies are prone to technical noise and biases that hinder downstream analysis. We develop a normalization approach, BandNorm, and a deep generative modeling framework, scVI-3D, to account for scHi-C specific biases. In benchmarking experiments, BandNorm yields leading performances in a time and memory efficient manner for cell-type separation, identification of interacting loci, and recovery of cell-type relationships, while scVI-3D exhibits advantages for rare cell types and under high sparsity scenarios. Application of BandNorm coupled with gene-associating domain analysis reveals scRNA-seq validated sub-cell type identification.

Biomolecular Topology: Modelling and Analysis

With the great advancement of experimental tools, a tremendous amount of biomolecular data has been generated and accumulated in various databases. The high dimensionality, structural complexity, the nonlinearity, and entanglements of biomolecular data, ranging from DNA knots, RNA secondary structures, protein folding configurations, chromosomes, DNA origami, molecular assembly, to others at the macromolecular level, pose a severe challenge in their analysis and characterization. In the past few decades, mathematical concepts, models, algorithms, and tools from algebraic topology, combinatorial topology, computational topology, and topological data analysis, have demonstrated great power and begun to play an essential role in tackling the biomolecular data challenge. In this work, we introduce biomolecular topology, which concerns the topological problems and models originated from the biomolecular systems. More specifically, the biomolecular topology encompasses topological structures, properties and relations that are emerged from biomolecular structures, dynamics, interactions, and functions. We discuss the various types of biomolecular topology from structures (of proteins, DNAs, and RNAs), protein folding, and protein assembly. A brief discussion of databanks (and databases), theoretical models, and computational algorithms, is presented. Further, we systematically review related topological models, including graphs, simplicial complexes, persistent homology, persistent Laplacians, de Rham-Hodge theory, Yau-Hausdorff distance, and the topology-based machine learning models.

Constricted migration is associated with stable 3D genome structure differences in cancer cells

To spread from a localized tumor, metastatic cancer cells must squeeze through constrictions that cause major nuclear deformations. Since chromosome structure affects nucleus stiffness, gene regulation, and DNA repair, here, we investigate the relationship between 3D genome structure and constricted migration in cancer cells. Using melanoma (A375) cells, we identify phenotypic differences in cells that have undergone multiple rounds of constricted migration. These cells display a stably higher migration efficiency, elongated morphology, and differences in the distribution of Lamin A/C and heterochromatin. Hi-C experiments reveal differences in chromosome spatial compartmentalization specific to cells that have passed through constrictions and related alterations in expression of genes associated with migration and metastasis. Certain features of the 3D genome structure changes, such as a loss of B compartment interaction strength, are consistently observed after constricted migration in clonal populations of A375 cells and in MDA-MB-231 breast cancer cells. Our observations suggest that consistent types of chromosome structure changes are induced or selected by passage through constrictions and that these may epigenetically encode stable differences in gene expression and cellular migration phenotype.

Transcriptional enhancers at 40: evolution of a viral DNA element to nuclear architectural structures

Gene regulation by transcriptional enhancers is the dominant mechanism driving cell type- and signal-specific transcriptional diversity in metazoans. However, over four decades since the original discovery, how enhancers operate in the nuclear space remains largely enigmatic. Recent multidisciplinary efforts combining real-time imaging, genome sequencing, and biophysical strategies provide insightful but conflicting models of enhancer-mediated gene control. Here, we review the discovery and progress in enhancer biology, emphasizing the recent findings that acutely activated enhancers assemble regulatory machinery as mesoscale architectural structures with distinct physical properties. These findings help formulate novel models that explain several mysterious features of the assembly of transcriptional enhancers and the mechanisms of spatial control of gene expression.

The Epstein-Barr Virus Enhancer Interaction Landscapes in Virus-Associated Cancer Cell Lines

Epstein-Barr virus (EBV) persists in human cells as episomes. EBV episomes are chromatinized and their 3D conformation varies greatly in cells expressing different latency genes. We used HiChIP, an assay which combines genome-wide chromatin conformation capture followed by deep sequencing (Hi-C) and chromatin immunoprecipitation (ChIP), to interrogate the EBV episome 3D conformation in different cancer cell lines. In an EBV-transformed lymphoblastoid cell line (LCL) GM12878 expressing type III EBV latency genes, abundant genomic interactions were identified by H3K27ac HiChIP. A strong enhancer was located near the BILF2 gene and looped to multiple genes around BALFs loci. Perturbation of the BILF2 enhancer by CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) altered the expression of BILF2 enhancer-linked genes, including BARF0 and BALF2, suggesting that this enhancer regulates the expression of linked genes. H3K27ac ChIP followed by deep sequencing (ChIP-seq) identified several strong EBV enhancers in T/NK (natural killer) lymphoma cells that express type II EBV latency genes. Extensive intragenomic interactions were also found which linked enhancers to target genes. A strong enhancer at BILF2 also looped to the BALF loci. CRISPRi also validated the functional connection between BILF2 enhancer and BARF1 gene. In contrast, H3K27ac HiChIP found significantly fewer intragenomic interactions in type I EBV latency gene-expressing primary effusion lymphoma (PEL) cell lines. These data provided new insight into the regulation of EBV latency gene expression in different EBV-associated tumors. IMPORTANCE EBV is the first human DNA tumor virus identified, discovered over 50 years ago. EBV causes ~200,000 cases of various cancers each year. EBV-encoded oncogenes, noncoding RNAs, and microRNAs (miRNAs) can promote cell growth and survival and suppress senescence. Regulation of EBV gene expression is very complex. The viral C promoter regulates the expression of all EBV nuclear antigens (EBNAs), some of which are very far away from the C promoter. Another way by which the virus activates remote gene expression is through DNA looping. In this study, we describe the viral genome looping patterns in various EBV-associated cancer cell lines and identify important EBV enhancers in these cells. This study also identified novel opportunities to perturb and eventually control EBV gene expression in these cancer cells.

Interpretation of the role of germline and somatic non-coding mutations in cancer: expression and chromatin conformation informed analysis

BACKGROUND

There has been extensive scrutiny of cancer driving mutations within the exome (especially amino acid altering mutations) as these are more likely to have a clear impact on protein functions, and thus on cell biology. However, this has come at the neglect of systematic identification of regulatory (non-coding) variants, which have recently been identified as putative somatic drivers and key germline risk factors for cancer development. Comprehensive understanding of non-coding mutations requires understanding their role in the disruption of regulatory elements, which then disrupt key biological functions such as gene expression.

MAIN BODY

We describe how advancements in sequencing technologies have led to the identification of a large number of non-coding mutations with uncharacterized biological significance. We summarize the strategies that have been developed to interpret and prioritize the biological mechanisms impacted by non-coding mutations, focusing on recent annotation of cancer non-coding variants utilizing chromatin states, eQTLs, and chromatin conformation data.

CONCLUSION

We believe that a better understanding of how to apply different regulatory data types into the study of non-coding mutations will enhance the discovery of novel mechanisms driving cancer.

ParticleChromo3D: a Particle Swarm Optimization algorithm for chromosome 3D structure prediction from Hi-C data

Background

The three-dimensional (3D) structure of chromatin has a massive effect on its function. Because of this, it is desirable to have an understanding of the 3D structural organization of chromatin. To gain greater insight into the spatial organization of chromosomes and genomes and the functions they perform, chromosome conformation capture (3C) techniques, particularly Hi-C, have been developed. The Hi-C technology is widely used and well-known because of its ability to profile interactions for all read pairs in an entire genome. The advent of Hi-C has greatly expanded our understanding of the 3D genome, genome folding, gene regulation and has enabled the development of many 3D chromosome structure reconstruction methods.

Results

Here, we propose a novel approach for 3D chromosome and genome structure reconstruction from Hi-C data using Particle Swarm Optimization (PSO) approach called ParticleChromo3D. This algorithm begins with a grouping of candidate solution locations for each chromosome bin, according to the particle swarm algorithm, and then iterates its position towards a global best candidate solution. While moving towards the optimal global solution, each candidate solution or particle uses its own local best information and a randomizer to choose its path. Using several metrics to validate our results, we show that ParticleChromo3D produces a robust and rigorous representation of the 3D structure for input Hi-C data. We evaluated our algorithm on simulated and real Hi-C data in this work. Our results show that ParticleChromo3D is more accurate than most of the existing algorithms for 3D structure reconstruction.

Conclusions

Our results also show that constructed ParticleChromo3D structures are very consistent, hence indicating that it will always arrive at the global solution at every iteration. The source code for ParticleChromo3D, the simulated and real Hi-C datasets, and the models generated for these datasets are available here: https://github.com/OluwadareLab/ParticleChromo3D

Rearrangement of T Cell genome architecture regulates GVHD

WAPL, cohesin's DNA release factor, regulates three-dimensional (3D) chromatin architecture. The 3D chromatin structure and its relevance to mature T cell functions is not well understood. We show that in vivo lymphopenic expansion, and alloantigen-driven proliferation, alters the 3D structure and function of the genome in mature T cells. Conditional deletion of WAPL, cohesin's DNA release factor, in T cells reduced long-range genomic interactions and altered chromatin A/B compartments and interactions within topologically associating domains (TADs) of the chromatin in T cells at baseline. WAPL deficiency in T cells reduced loop extensions, changed expression of cell cycling genes and reduced proliferation following in vitro and in vivo stimulation, and reduced severity of graft-versus-host disease (GVHD) following experimental allogeneic hematopoietic stem cell transplantation. These data collectively characterize 3D genomic architecture of T cells in vivo and demonstrate biological and clinical implications for its disruption by cohesin release factor WAPL.

The Neuroepigenome: Implications of Chemical and Physical Modifications of Genomic DNA in Schizophrenia

Schizophrenia is a chronic mental illness with a substantial genetic component. To unfold the complex etiology of schizophrenia, it is important to understand the interplay between genetic and nongenetic factors. Genetic factors involve variation in the DNA sequences of protein-coding genes, which directly contribute to phenotypic traits, and variation in noncoding sequences, which comprise 98% of the genome and contain DNA elements known to play a role in regulating gene expression. The epigenome refers to the chemical modifications on both DNA and the structural proteins that package DNA into the nucleus, which together regulate gene expression in specific cell types, conditions, and developmental stages. The dynamic nature of the epigenome makes it an ideal tool to investigate the relationship between inherited genetic mutations associated with schizophrenia and altered gene regulation throughout the course of brain development. In this review, we focus on the current understanding of the role of epigenetic marks and their three-dimensional nuclear organization in the developmental trajectory of distinct brain cell types to decipher the complex gene regulatory mechanisms that are disrupted in schizophrenia.

Clinical application of advanced multi-omics tumor profiling: Shaping precision oncology of the future

Next-generation DNA sequencing technology has dramatically advanced clinical oncology through the identification of therapeutic targets and molecular biomarkers, leading to the personalization of cancer treatment with significantly improved outcomes for many common and rare tumor entities. More recent developments in advanced tumor profiling now enable dissection of tumor molecular architecture and the functional phenotype at cellular and subcellular resolution. Clinical translation of high-resolution tumor profiling and integration of multi-omics data into precision treatment, however, pose significant challenges at the level of prospective validation and clinical implementation. In this review, we summarize the latest advances in multi-omics tumor profiling, focusing on spatial genomics and chromatin organization, spatial transcriptomics and proteomics, liquid biopsy, and ex vivo modeling of drug response. We analyze the current stages of translational validation of these technologies and discuss future perspectives for their integration into precision treatment.

Natural and Experimental Rewiring of Gene Regulatory Regions

The successful development and ongoing functioning of complex organisms depend on the faithful execution of the genetic code. A critical step in this process is the correct spatial and temporal expression of genes. The highly orchestrated transcription of genes is controlled primarily by cis-regulatory elements: promoters, enhancers, and insulators. The medical importance of this key biological process can be seen by the frequency with which mutations and inherited variants that alter cis-regulatory elements lead to monogenic and complex diseases and cancer. Here, we provide an overview of the methods available to characterize and perturb gene regulatory circuits. We then highlight mechanisms through which regulatory rewiring contributes to disease, and conclude with a perspective on how our understanding of gene regulation can be used to improve human health.

Causality in transcription and genome folding: Insights from X inactivation

The spatial organization of genomes is becoming increasingly understood. In mammals, where it is most investigated, this organization ties in with transcription, so an important research objective is to understand whether gene activity is a cause or a consequence of genome folding in space. In this regard, the phenomena of X-chromosome inactivation and reactivation open a unique window of investigation because of the singularities of the inactive X chromosome. Here we focus on the cause-consequence nexus between genome conformation and transcription and explain how recent results about the structural changes associated with inactivation and reactivation of the X chromosome shed light on this problem.

KLF4 recruits SWI/SNF to increase chromatin accessibility and reprogram the endothelial enhancer landscape under laminar shear stress

Physiologic laminar shear stress (LSS) induces an endothelial gene expression profile that is vasculo-protective. In this report, we delineate how LSS mediates changes in the epigenetic landscape to promote this beneficial response. We show that under LSS, KLF4 interacts with the SWI/SNF nucleosome remodeling complex to increase accessibility at enhancer sites that promote the expression of homeostatic endothelial genes. By combining molecular and computational approaches we discover enhancers that loop to promoters of KLF4- and LSS-responsive genes that stabilize endothelial cells and suppress inflammation, such as BMPR2, SMAD5, and DUSP5. By linking enhancers to genes that they regulate under physiologic LSS, our work establishes a foundation for interpreting how non-coding DNA variants in these regions might disrupt protective gene expression to influence vascular disease.

Identification of a polycomb responsive region in human HoxA cluster and its long-range interaction with polycomb enriched genomic regions

Polycomb and Trithorax group proteins (PcG, TrxG) epigenetically regulate developmental genes. These proteins bind with specific DNA elements, the Polycomb Response Element (PRE). Apart from mutations in polycomb/ trithorax proteins, altered cis-elements like PRE underlie the modified function and thus disease etiology. PREs are well studied in Drosophila, while only a few human PREs have been reported. We have identified a polycomb responsive DNA element, hPRE-HoxA3, in the intron of the HoxA3 gene. The hPRE-HoxA3 represses luciferase reporter activity in a PcG-dependent manner. The endogenous hPRE-HoxA3 element recruits PcG proteins and is enriched with repressive H3K27me3 marks, demonstrating that hPRE-HoxA3 is a part of the PcG-dependent gene regulatory network. Furthermore, it interacts with D11-12, the well-known PRE in the human Hox cluster. hPRE-Hox3 is a part of the 3-dimensional chromosomal domain organization as it is involved in the long-range interaction with other PcG enriched regions of Hox A, B, C, and D clusters.

Monocytes acquire prostate cancer specific chromatin conformations upon indirect co-culture with prostate cancer cells

Background

Three-dimensional chromosome loop conformations are powerful regulators of gene expression. These chromosome conformations can be detected both in tumour and in circulating cells and have significant disease biomarker potential. We have recently detected specific chromosome conformations in circulating cells of patients with prostate cancer (PCa) which were similar to ones found in their primary tumours, however, the possibility of horizontal transfer of chromosome conformations was not studied previously.

Methods

Human monocytes (U937) were co-cultured in Boyden chambers through 0.4 uM membrane with or without PC-3 human PCa cells or their conditioned media and a custom DNA microarray for 900,000 chromosomal loops covering all coding loci and non-coding RNA genes was performed on each part of the co-culture system.

Results

We have detected 684 PC-3 cell-specific chromosome conformations across the whole genome that were absent in naïve monocytes but appeared in monocytes co-cultured with PC-3 cells or with PC-3-conditioned media. Comparing PC3-specific conformations to the ones we have previously detected in systemic circulation of high-risk PCa patients revealed 9 positive loops present in both settings.

Conclusions

Our results demonstrate for the first time a proof of concept for horizontal transfer of chromosome conformations without direct cell-cell contact. This carries high clinical relevance as we have previously observed chromatin conformations in circulating cells of patients with melanoma and PCa similar to ones in their primary tumours. These changes can be used as highly specific biomarkers for diagnosis and prognosis. Further studies are required to elucidate the specific mechanism of chromosome conformations transfer and its clinical significance in particular diseases.

HULC targets the IGF1R-PI3K-AKT axis in trans to promote breast cancer metastasis and cisplatin resistance

Insulin-like growth factor I receptor (IGF1R) is frequently upregulated in breast cancer. Due to its intrinsic tyrosine kinase activity, aberrant activation of the IGF1R signaling axis may enhance tumor cell proliferation and cancer stemness, causing tumor relapse, metastasis and resistance to chemotherapy. We utilized a chromatin RNA in situ reverse transcription (CRIST) approach to characterize molecular factors that regulate the IGF1R network. We identified lncRNA HULC (Highly Upregulated in Liver Cancer) as a key trans-regulator of IGF1R in breast cancer cells. Loss of HULC suppressed the expression of IGF1R and the activation of its downstream PI3K/AKT pathway, while HULC overexpression activated the axis in breast cancer cells. Using a transcription-associated trap (RAT) assay, we demonstrated that HULC functioned as a nuclear lncRNA and epigenetically activated IGF1R by directly binding to the intragenic regulatory elements of the gene, orchestrating intrachromosomal interactions, and promoting histone H3K9 acetylation. The activated HULC-IGF1R/PI3K/AKT pathway mediated tumor resistance to cisplatin through the increased expression of cancer stemness markers, including NANOG, SOX2, OCT4, CD44 and ALDH1A1. In immunodeficient mice, stimulation of the HULC-IGF1R pathway promoted tumor metastasis. These data suggest that HULC may be a new epigenetic target for IGF1R axis-targeted therapeutic intervention.

Coming full circle: On the origin and evolution of the looping model for enhancer-promoter communication

In mammalian organisms, enhancers can regulate transcription from great genomic distances. How enhancers affect distal gene expression has been a major question in the field of gene regulation. One model to explain how enhancers communicate with their target promoters, the chromatin looping model, posits that enhancers and promoters come in close spatial proximity to mediate communication. Chromatin looping has been broadly accepted as a means for enhancer-promoter communication, driven by accumulating in vitro and in vivo evidence. The genome is now known to be folded into a complex 3D arrangement, created and maintained in part by the interplay of the Cohesin complex and the DNA-binding protein CTCF. In the last few years, however, doubt over the relationship between looping and transcriptional activation has emerged, driven by studies finding that only a modest number of genes are perturbed with acute degradation of looping machinery components. In parallel, newer models describing distal enhancer action have also come to prominence. In this article, we explore the emergence and development of the looping model as a means for enhancer-promoter communication and review the contrasting evidence between historical gene-specific and current global data for the role of chromatin looping in transcriptional regulation. We also discuss evidence for alternative models to chromatin looping and their support in the literature. We suggest that, while there is abundant evidence for chromatin looping as a major mechanism for enhancer function, enhancer-promoter communication is likely mediated by more than one mechanism in an enhancer- and context-dependent manner.

The relevance of chromatin architecture to genome rearrangements in Drosophila

DNA within chromosomes in the nucleus is non-randomly organized into chromosome territories, compartments and topologically associated domains (TADs). Chromosomal rearrangements have the potential to alter chromatin organization and modify gene expression leading to selection against these structural variants. Drosophila pseudoobscura has a wealth of naturally occurring gene arrangements that were generated by overlapping inversion mutations caused by two chromosomal breaks that rejoin the central region in reverse order. Unlike humans, Drosophila inversion heterozygotes do not have negative effects associated with crossing over during meiosis because males use achiasmate mechanisms for proper segregation, and aberrant recombinant meiotic products generated in females are lost in polar bodies. As a result, Drosophila populations are found to harbour extensive inversion polymorphisms. It is not clear, however, whether chromatin architecture constrains which inversions breakpoints persist in populations. We mapped the breakpoints of seven inversions in D. pseudoobscura to the TAD map to determine if persisting inversion breakpoints are more likely to occur at boundaries between TADs. Our results show that breakpoints occur at TAD boundaries more than expected by chance. Some breakpoints may alter gene expression within TADs supporting the hypothesis that position effects contribute to inversion establishment. This article is part of the theme issue 'Genomic architecture of supergenes: causes and evolutionary consequences'.

Long non-coding RNA tumor protein 73 antisense RNA 1 influences an interaction between lysine demethylase 5A and promoter of tumor protein 73 to enhance the malignancy of colorectal cancer

Colorectal cancer (CRC) is one of the leading causes of cancer-related death worldwide. The aim of the present study was to explore the expression level of tumor protein 73 (TP73) in highly malignant CRC tumors and how the long non-coding RNA tumor protein 73 antisense RNA 1 (TP73-AS1) influences that transcription. We found that TP73-AS1 was highly expressed in malignant CRC samples in The Cancer Genome Atlas (TCGA) database. We also demonstrated TP73-AS1 was expressed in thirty samples of CRC tissues collected from China Medical University patients as well as in HCT116, RKO and SW480 CRC cell lines but not in HCoEpiC or CCD-18Co normal colon cells. Only wild-type TP73-AS1, but not any of its alternate splicing isoforms, was positively correlated with tumor malignancy. TP73-AS1 transcripts were shown to be located in cell nuclei especially in close proximity to the TP73 promoter in CRC cells, but not in normal colon cells. In addition, an interaction between lysine demethylase 5A (KDM5A) and TP73-AS1 in CRC cells, but not normal colon cells, and KDM5A localization on the TP73 promoter were influenced by TP73-AS1. Interestingly, the H3K4me3 level on the TP73 promoter was reduced, but was elevated by TP73-AS1 knockdown in CRC cells. In conclusion, these results suggest a novel epigenetic role of TP73-AS1 on histone demethylation that influences TP73 transcription, and shed light on malignancy in CRC.

Polycomb-lamina antagonism partitions heterochromatin at the nuclear periphery

The genome can be divided into two spatially segregated compartments, A and B, which partition active and inactive chromatin states. While constitutive heterochromatin is predominantly located within the B compartment near the nuclear lamina, facultative heterochromatin marked by H3K27me3 spans both compartments. How epigenetic modifications, compartmentalization, and lamina association collectively maintain heterochromatin architecture remains unclear. Here we develop Lamina-Inducible Methylation and Hi-C (LIMe-Hi-C) to jointly measure chromosome conformation, DNA methylation, and lamina positioning. Through LIMe-Hi-C, we identify topologically distinct sub-compartments with high levels of H3K27me3 and differing degrees of lamina association. Inhibition of Polycomb repressive complex 2 (PRC2) reveals that H3K27me3 is essential for sub-compartment segregation. Unexpectedly, PRC2 inhibition promotes lamina association and constitutive heterochromatin spreading into H3K27me3-marked B sub-compartment regions. Consistent with this repositioning, genes originally marked with H3K27me3 in the B compartment, but not the A compartment, remain largely repressed, suggesting that constitutive heterochromatin spreading can compensate for H3K27me3 loss at a transcriptional level. These findings demonstrate that Polycomb sub-compartments and their antagonism with lamina association are fundamental features of genome structure. More broadly, by jointly measuring nuclear position and Hi-C contacts, our study demonstrates how compartmentalization and lamina association represent distinct but interdependent modes of heterochromatin regulation.

DNA methylation differences during development distinguish sympatric morphs of Arctic charr (Salvelinus alpinus)

Changes in DNA methylation in specific coding or non-coding regions can influence development and potentially divergence in traits within species and groups. While the impact of epigenetic variation on developmental pathways associated with evolutionary divergence is the focus of intense investigation, few studies have looked at recently diverged systems. Phenotypic diversity between closely related populations of Arctic charr (Salvelinus alpinus), which diverged within the last 10 000 years, offers an interesting ecological model to address such effects. Using bisulfite sequencing, we studied general DNA methylation patterns during development in the four sympatric morphs of Arctic charr from Lake Thingvallavatn. The data revealed strong differences between developmental timepoints and between morphs (mainly along the benthic - limnetic axis), both at single CpG sites and in 1,000bp-regions. Genes located close to differentially methylated CpG sites were involved in nucleosome assembly, regulation of osteoclast differentiation, and cell-matrix adhesion. Differentially methylated regions were enriched in tRNA and rRNA sequences, and half of them were located close to transcription start sites. The expression of 14 genes showing methylation differences over time or between morphs was further investigated by qPCR and nine of these were found to be differentially expressed between morphs. Four genes (ARHGEF37-like, H3-like, MPP3 and MEGF9) showed a correlation between methylation and expression. Lastly, histone gene clusters displayed interesting methylation differences between timepoints and morphs, as well as intragenic methylation variation. The results presented here provide a motivation for further studies on the contribution of epigenetic traits, such as DNA methylation, to phenotypic diversity and developmental mechanisms.

Application of the 3C Method to Study the Developmental Genes in Drosophila Larvae

A transition from one developmental stage to another is accompanied by activation of developmental programs and corresponding gene ensembles. Changes in the spatial conformation of the corresponding loci are associated with this activation and can be investigated with the help of the Chromosome Conformation Capture (3C) methodology. Application of 3C to specific developmental stages is a sophisticated task. Here, we describe the use of the 3C method to study the spatial organization of developmental loci in Drosophila larvae. We critically analyzed the existing protocols and offered our own solutions and the optimized protocol to overcome limitations. To demonstrate the efficiency of our procedure, we studied the spatial organization of the developmental locus Dad in 3rd instar Drosophila larvae. Differences in locus conformation were found between embryonic cells and living wild-type larvae. We also observed the establishment of novel regulatory interactions in the presence of an adjacent transgene upon activation of its expression in larvae. Our work fills the gap in the application of the 3C method to Drosophila larvae and provides a useful guide for establishing 3C on an animal model.

Uncovering the statistical physics of 3D chromosomal organization using data-driven modeling

In recent years, much effort has been devoted to understanding the three-dimensional (3D) organization of the genome and how genomic structure mediates nuclear function. The development of experimental techniques that combine DNA proximity ligation with high-throughput sequencing, such as Hi-C, have substantially improved our knowledge about chromatin organization. Numerous experimental advancements, not only utilizing DNA proximity ligation but also high-resolution genome imaging (DNA tracing), have required theoretical modeling to determine the structural ensembles consistent with such data. These 3D polymer models of the genome provide an understanding of the physical mechanisms governing genome architecture. Here, we present an overview of the recent advances in modeling the ensemble of 3D chromosomal structures by employing the maximum entropy approach combined with polymer physics. Particularly, we discuss the minimal chromatin model (MiChroM) along with the "maximum entropy genomic annotations from biomarkers associated with structural ensembles" (MEGABASE) model, which have been remarkably successful in the accurate modeling of chromosomes consistent with both Hi-C and DNA-tracing data.

StackEPI: identification of cell line-specific enhancer-promoter interactions based on stacking ensemble learning

Background

Understanding the regulatory role of enhancer–promoter interactions (EPIs) on specific gene expression in cells contributes to the understanding of gene regulation, cell differentiation, etc., and its identification has been a challenging task. On the one hand, using traditional wet experimental methods to identify EPIs often means a lot of human labor and time costs. On the other hand, although the currently proposed computational methods have good recognition effects, they generally require a long training time.

Results

In this study, we studied the EPIs of six human cell lines and designed a cell line-specific EPIs prediction method based on a stacking ensemble learning strategy, which has better prediction performance and faster training speed, called StackEPI. Specifically, by combining different encoding schemes and machine learning methods, our prediction method can extract the cell line-specific effective information of enhancer and promoter gene sequences comprehensively and in many directions, and make accurate recognition of cell line-specific EPIs. Ultimately, the source code to implement StackEPI and experimental data involved in the experiment are available at https://github.com/20032303092/StackEPI.git.

Conclusions

The comparison results show that our model can deliver better performance on the problem of identifying cell line-specific EPIs and outperform other state-of-the-art models. In addition, our model also has a more efficient computation speed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04821-9.

EPIXplorer: A web server for prediction, analysis and visualization of enhancer-promoter interactions

Long distance enhancers can physically interact with promoters to regulate gene expression through formation of enhancer-promoter (E-P) interactions. Identification of E-P interactions is also important for profound understanding of normal developmental and disease-associated risk variants. Although the state-of-art predictive computation methods facilitate the identification of E-P interactions to a certain extent, currently there is no efficient method that can meet various requirements of usage. Here we developed EPIXplorer, a user-friendly web server for efficient prediction, analysis and visualization of E-P interactions. EPIXplorer integrates 9 robust predictive algorithms, supports multiple types of 3D contact data and multi-omics data as input. The output from EPIXplorer is scored, fully annotated by regulatory elements and risk single-nucleotide polymorphisms (SNPs). In addition, the Visualization and Downstream module provide further functional analysis, all the output files and high-quality images are available for download. Together, EPIXplorer provides a user-friendly interface to predict the E-P interactions in an acceptable time, as well as understand how the genome-wide association study (GWAS) variants influence disease pathology by altering DNA looping between enhancers and the target gene promoters. EPIXplorer is available at https://www.csuligroup.com/EPIXplorer.

Chromatin Hubs: A biological and computational outlook

This review discusses our current understanding of chromatin biology and bioinformatics under the unifying concept of “chromatin hubs.” The first part reviews the biology of chromatin hubs, including chromatin–chromatin interaction hubs, chromatin hubs at the nuclear periphery, hubs around macromolecules such as RNA polymerase or lncRNAs, and hubs around nuclear bodies such as the nucleolus or nuclear speckles. The second part reviews existing computational methods, including enhancer–promoter interaction prediction, network analysis, chromatin domain callers, transcription factory predictors, and multi-way interaction analysis. We introduce an integrated model that makes sense of the existing evidence. Understanding chromatin hubs may allow us (i) to explain long-unsolved biological questions such as interaction specificity and redundancy of mechanisms, (ii) to develop more realistic kinetic and functional predictions, and (iii) to explain the etiology of genomic disease.

Regulation of 3D Organization and Its Role in Cancer Biology

Three-dimensional (3D) genomics is the frontier field in the post-genomics era, its foremost content is the relationship between chromatin spatial conformation and regulation of gene transcription. Cancer biology is a complex system resulting from genetic alterations in key tumor oncogenes and suppressor genes for cell proliferation, DNA replication, cell differentiation, and homeostatic functions. Although scientific research in recent decades has revealed how the genome sequence is mutated in many cancers, high-order chromosomal structures involved in the development and fate of cancer cells represent a crucial but rarely explored aspect of cancer genomics. Hence, dissection of the 3D genome conformation of cancer helps understand the unique epigenetic patterns and gene regulation processes that distinguish cancer biology from normal physiological states. In recent years, research in tumor 3D genomics has grown quickly. With the rapid progress of 3D genomics technology, we can now better determine the relationship between cancer pathogenesis and the chromatin structure of cancer cells. It is becoming increasingly explicit that changes in 3D chromatin structure play a vital role in controlling oncogene transcription. This review focuses on the relationships between tumor gene expression regulation, tumor 3D chromatin structure, and cancer phenotypic plasticity. Furthermore, based on the functional consequences of spatial disorganization in the cancer genome, we look forward to the clinical application prospects of 3D genomic biomarkers.

Epigenetic Regulation of Inflammatory Signaling and Inflammation-Induced Cancer

Epigenetics comprise a diverse array of reversible and dynamic modifications to the cell’s genome without implicating any DNA sequence alterations. Both the external environment surrounding the organism, as well as the internal microenvironment of cells and tissues, contribute to these epigenetic processes that play critical roles in cell fate specification and organismal development. On the other hand, dysregulation of epigenetic activities can initiate and sustain carcinogenesis, which is often augmented by inflammation. Chronic inflammation, one of the major hallmarks of cancer, stems from proinflammatory cytokines that are secreted by tumor and tumor-associated cells in the tumor microenvironment. At the same time, inflammatory signaling can establish positive and negative feedback circuits with chromatin to modulate changes in the global epigenetic landscape. In this review, we provide an in-depth discussion of the interconnected crosstalk between epigenetics and inflammation, specifically how epigenetic mechanisms at different hierarchical levels of the genome control inflammatory gene transcription, which in turn enact changes within the cell’s epigenomic profile, especially in the context of inflammation-induced cancer.

Genes Possessing the Most Frequent DNA DSBs Are Highly Associated with Development and Cancers, and Essentially Overlap with the rDNA-Contacting Genes

Double-strand DNA breakes (DSBs) are the most deleterious and widespread examples of DNA damage. They inevitably originate from endogenous mechanisms in the course of transcription, replication, and recombination, as well as from different exogenous factors. If not properly repaired, DSBs result in cell death or diseases. Genome-wide analysis of DSBs has revealed the numerous endogenous DSBs in human chromosomes. However, until now, it has not been clear what kind of genes are preferentially subjected to breakage. We performed a genetic and epigenetic analysis of the most frequent DSBs in HEK293T cells. Here, we show that they predominantly occur in the active genes controlling differentiation, development, and morphogenesis. These genes are highly associated with cancers and other diseases. About one-third of the genes possessing frequent DSBs correspond to rDNA-contacting genes. Our data suggest that a specific set of active genes controlling morphogenesis are the main targets of DNA breakage in human cells, although there is a specific set of silent genes controlling metabolism that also are enriched in DSBs. We detected this enrichment by different activators and repressors of transcription at DSB target sites, as well breakage at promoters. We propose that both active transcription and silencing of genes give a propensity for DNA breakage. These results have implications for medicine and gene therapy.

Contribution of Immunoglobulin Enhancers to B Cell Nuclear Organization

B cells undergo genetic rearrangements at immunoglobulin gene (Ig) loci during B cell maturation. First V(D)J recombination occurs during early B cell stages followed by class switch recombination (CSR) and somatic hypermutation (SHM) which occur during mature B cell stages. Given that RAG1/2 induces DNA double strand breaks (DSBs) during V(D)J recombination and AID (Activation-Induced Deaminase) leads to DNA modifications (mutations during SHM or DNA DSBs during CSR), it is mandatory that IgH rearrangements be tightly regulated to avoid any mutations or translocations within oncogenes. Ig loci contain various cis-regulatory elements that are involved in germline transcription, chromatin modifications or RAG/AID recruitment. Ig cis-regulatory elements are increasingly recognized as being involved in nuclear positioning, heterochromatin addressing and chromosome loop regulation. In this review, we examined multiple data showing the critical interest of studying Ig gene regulation at the whole nucleus scale. In this context, we highlighted the essential function of Ig gene regulatory elements that now have to be considered as nuclear organizers in B lymphocytes.

TADfit is a multivariate linear regression model for profiling hierarchical chromatin domains on replicate Hi-C data

Topologically associating domains (TADs) are fundamental building blocks of three dimensional genome, and organized into complex hierarchies. Identifying hierarchical TADs on Hi-C data helps to understand the relationship between genome architectures and gene regulation. Herein we propose TADfit, a multivariate linear regression model for profiling hierarchical chromatin domains, which tries to fit the interaction frequencies in Hi-C contact matrix with and without replicates using all-possible hierarchical TADs, and the significant ones can be determined by the regression coefficients obtained with the help of an online learning solver called Follow-The-Regularized-Leader (FTRL). Beyond the existing methods, TADfit has an ability to handle multiple contact matrix replicates and find partially overlapping TADs on them, which helps to find the comprehensive underlying TADs across replicates from different experiments. The comparative results tell that TADfit has better accuracy and reproducibility, and the hierarchical TADs called by it exhibit a reasonable biological relevance.

De novo assembly provides new insights into the evolution of Elaeagnus angustifolia L

BACKGROUND

Elaeagnus angustifolia L. is a deciduous tree in the family Elaeagnaceae. It is widely used to study abiotic stress tolerance in plants and to improve desertification-affected land because of its ability to withstand diverse types of environmental stress, such as drought, salt, cold, and wind. However, no studies have examined the mechanisms underlying the resistance of E. angustifolia to environmental stress and its adaptive evolution.

METHODS

Here, we used PacBio, Hi-C, resequencing, and RNA-seq to construct the genome and transcriptome of E. angustifolia and explore its adaptive evolution.

RESULTS

The reconstructed genome of E. angustifolia was 526.80 Mb, with a contig N50 of 12.60 Mb and estimated divergence time of 84.24 Mya. Gene family expansion and resequencing analyses showed that the evolution of E. angustifolia was closely related to environmental conditions. After exposure to salt stress, GO pathway analysis showed that new genes identified from the transcriptome were related to ATP-binding, metal ion binding, and nucleic acid binding.

CONCLUSION

The genome sequence of E. angustifolia could be used for comparative genomic analyses of Elaeagnaceae family members and could help elucidate the mechanisms underlying the response of E. angustifolia to drought, salt, cold, and wind stress. Generally, these results provide new insights that could be used to improve desertification-affected land.

Hodge theory-based biomolecular data analysis

Hodge theory reveals the deep intrinsic relations of differential forms and provides a bridge between differential geometry, algebraic topology, and functional analysis. Here we use Hodge Laplacian and Hodge decomposition models to analyze biomolecular structures. Different from traditional graph-based methods, biomolecular structures are represented as simplicial complexes, which can be viewed as a generalization of graph models to their higher-dimensional counterparts. Hodge Laplacian matrices at different dimensions can be generated from the simplicial complex. The spectral information of these matrices can be used to study intrinsic topological information of biomolecular structures. Essentially, the number (or multiplicity) of k-th dimensional zero eigenvalues is equivalent to the k-th Betti number, i.e., the number of k-th dimensional homology groups. The associated eigenvectors indicate the homological generators, i.e., circles or holes within the molecular-based simplicial complex. Furthermore, Hodge decomposition-based HodgeRank model is used to characterize the folding or compactness of the molecular structures, in particular, the topological associated domain (TAD) in high-throughput chromosome conformation capture (Hi-C) data. Mathematically, molecular structures are represented in simplicial complexes with certain edge flows. The HodgeRank-based average/total inconsistency (AI/TI) is used for the quantitative measurements of the folding or compactness of TADs. This is the first quantitative measurement for TAD regions, as far as we know.

IGF2: Development, Genetic and Epigenetic Abnormalities

In the 30 years since the first report of parental imprinting in insulin-like growth factor 2 (Igf2) knockout mouse models, we have learnt much about the structure of this protein, its role and regulation. Indeed, many animal and human studies involving innovative techniques have shed light on the complex regulation of IGF2 expression. The physiological roles of IGF-II have also been documented, revealing pleiotropic tissue-specific and developmental-stage-dependent action. Furthermore, in recent years, animal studies have highlighted important interspecies differences in IGF-II function, gene expression and regulation. The identification of human disorders due to impaired IGF2 gene expression has also helped to elucidate the major role of IGF-II in growth and in tumor proliferation. The Silver-Russell and Beckwith-Wiedemann syndromes are the most representative imprinted disorders, as they constitute both phenotypic and molecular mirrors of IGF2-linked abnormalities. The characterization of patients with either epigenetic or genetic defects altering IGF2 expression has confirmed the central role of IGF-II in human growth regulation, particularly before birth, and its effects on broader body functions, such as metabolism or tumor susceptibility. Given the long-term health impact of these rare disorders, it is important to understand the consequences of IGF2 defects in these patients.

The era of 3D and spatial genomics

Over a decade ago the advent of high-throughput chromosome conformation capture (Hi-C) sparked a new era of 3D genomics. Since then the number of methods for mapping the 3D genome has flourished, enabling an ever-increasing understanding of how DNA is packaged in the nucleus and how the spatiotemporal organization of the genome orchestrates its vital functions. More recently, the next generation of spatial genomics technologies has begun to reveal how genome sequence and 3D genome organization vary between cells in their tissue context. We summarize how the toolkit for charting genome topology has evolved over the past decade and discuss how new technological developments are advancing the field of 3D and spatial genomics.

Hi-C embedded polymer model of Escherichia coli reveals the origin of heterogeneous subdiffusion in chromosomal loci

Underneath its apparently simple architecture, the circular chromosome of Escherichia coli is known for displaying complex dynamics in its cytoplasm, with past investigations hinting at inherently diverse mobilities of chromosomal loci across the genome. To decipher its origin, we simulate the dynamics of genome-wide spectrum of E. coli chromosomal loci, via integrating its experimentally derived Hi-C interaction matrix within a polymer-based model. Our analysis demonstrates that, while the dynamics of the chromosome is subdiffusive in a viscoelastic media, the diffusion constants are strongly dependent of chromosomal loci coordinates and diffusive exponents (α) are widely heterogenous with α ≈ 0.36-0.60. The loci-dependent heterogeneous dynamics and mean first-passage times of interloci encounter were found to be modulated via genetically distant interloci communications and is robust even in the presence of active, ATP-dependent noises. Control investigations reveal that the absence of Hi-C-derived interactions in the model would have abolished the traits of heterogeneous loci diffusion, underscoring the key role of loci-specific genetically distant interaction in modulating the underlying heterogeneity of the loci diffusion.

Sister chromatid-sensitive Hi-C to map the conformation of replicated genomes

Chromosome conformation capture (Hi-C) techniques map the 3D organization of entire genomes. How sister chromatids fold in replicated chromosomes, however, cannot be determined with conventional Hi-C because of the identical DNA sequences of sister chromatids. Here, we present a protocol for sister chromatid-sensitive Hi-C (scsHi-C) that enables the distinction of DNA contacts within individual sister chromatids (cis sister contacts) from those between sister chromatids (trans sister contacts), thereby allowing investigation of the organization of replicated genomes. scsHi-C is based on live-cell labeling of nascent DNA by the synthetic nucleoside 4-thio-thymidine (4sT), which incorporates into a distinct DNA strand on each sister chromatid because of semi-conservative DNA replication. After purification of genomic DNA and in situ Hi-C library preparation, 4sT is chemically converted into 5-methyl-cytosine in the presence of OsO4/NH4Cl to introduce T-to-C signature point mutations on 4sT-labeled DNA. The Hi-C library is then sequenced, and ligated fragments are assigned to sister chromatids on the basis of strand orientation and the presence of signature mutations. The ensemble of scsHi-C contacts thereby represents genome-wide contact probabilities within and across sister chromatids. scsHi-C can be completed in 2 weeks, has been successfully applied in HeLa cells and can potentially be established for any cell type that allows proper cell cycle synchronization and incorporation of sufficient amounts of 4sT. The genome-wide maps of replicated chromosomes detected by scsHi-C enable investigation of the molecular mechanisms shaping sister chromatid topologies and the relevance of sister chromatid conformation in crucial processes like DNA repair, mitotic chromosome formation and potentially other biological processes.

Epigenetic regulation of T cell exhaustion

Chronic antigen stimulation during viral infections and cancer can lead to T cell exhaustion, which is characterized by reduced effector function and proliferation, and the expression of inhibitory immune checkpoint receptors. Recent studies have demonstrated that T cell exhaustion results in wholescale epigenetic remodeling that confers phenotypic stability to these cells and prevents T cell reinvigoration by checkpoint blockade. Here, we review foundational technologies to profile the epigenome at multiple scales, including mapping the locations of transcription factors and histone modifications, DNA methylation and three-dimensional genome conformation. We discuss how these technologies have elucidated the development and epigenetic regulation of exhausted T cells and functional implications across viral infection, cancer, autoimmunity and engineered T cell therapies. Finally, we cover emerging multi-omic and genome engineering technologies, current and upcoming opportunities to apply these to T cell exhaustion, and therapeutic opportunities for T cell engineering in the clinic.

Building regulatory landscapes reveals that an enhancer can recruit cohesin to create contact domains, engage CTCF sites and activate distant genes

Developmental gene expression is often controlled by distal regulatory DNA elements called enhancers. Distant enhancer action is restricted to structural chromosomal domains that are flanked by CTCF-associated boundaries and formed through cohesin chromatin loop extrusion. To better understand how enhancers, genes and CTCF boundaries together form structural domains and control expression, we used a bottom-up approach, building series of active regulatory landscapes in inactive chromatin. We demonstrate here that gene transcription levels and activity over time reduce with increased enhancer distance. The enhancer recruits cohesin to stimulate domain formation and engage flanking CTCF sites in loop formation. It requires cohesin exclusively for the activation of distant genes, not of proximal genes, with nearby CTCF boundaries supporting efficient long-range enhancer action. Our work supports a dual activity model for enhancers: its classic role of stimulating transcription initiation and elongation from target gene promoters and a role of recruiting cohesin for the creation of chromosomal domains, the engagement of CTCF sites in chromatin looping and the activation of distal target genes.

DeepLUCIA: predicting tissue-specific chromatin loops using Deep Learning-based Universal Chromatin Interaction Annotator

MOTIVATION

The importance of chromatin loops in gene regulation is broadly accepted. There are mainly two approaches to predict chromatin loops: transcription factor (TF) binding-dependent approach and genomic variation-based approach. However, neither of these approaches provides an adequate understanding of gene regulation in human tissues. To address this issue, we developed a deep learning-based chromatin loop prediction model called DeepLUCIA (Deep Learning-based Universal Chromatin Interaction Annotator).

RESULTS

Although DeepLUCIA does not use TF binding profile data which previous TF binding-dependent methods critically rely on, its prediction accuracies are comparable to those of the previous TF binding-dependent methods. More importantly, DeepLUCIA enables the tissue-specific chromatin loop predictions from tissue-specific epigenomes that cannot be handled by genomic variation-based approach. We demonstrated the utility of the DeepLUCIA by predicting several novel target genes of SNPs identified in genome-wide association studies targeting Brugada syndrome, COVID-19 severity, and age-related macular degeneration.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Erythroid Cell Research: 3D Chromatin, Transcription Factors and Beyond

Studies of the regulatory networks and signals controlling erythropoiesis have brought important insights in several research fields of biology and have been a rich source of discoveries with far-reaching implications beyond erythroid cells biology. The aim of this review is to highlight key recent discoveries and show how studies of erythroid cells bring forward novel concepts and refine current models related to genome and 3D chromatin organization, signaling and disease, with broad interest in life sciences.

3D or Not 3D: Shaping the Genome during Development

One of the most fundamental questions in developmental biology is how one fertilized cell can give rise to a fully mature organism and how gene regulation governs this process. Precise spatiotemporal gene expression is required for development and is believed to be achieved through a complex interplay of sequence-specific information, epigenetic modifications, trans-acting factors, and chromatin folding. Here we review the role of chromatin folding during development, the mechanisms governing 3D genome organization, and how it is established in the embryo. Furthermore, we discuss recent advances and debated questions regarding the contribution of the 3D genome to gene regulation during organogenesis. Finally, we describe the mechanisms that can reshape the 3D genome, including disease-causing structural variations and the emerging view that transposable elements contribute to chromatin organization.

Balance of osmotic pressures determines the nuclear-to-cytoplasmic volume ratio of the cell

The volume of the cell nucleus varies across cell types and species and is commonly thought to be determined by the size of the genome and degree of chromatin compaction. However, this notion has been challenged over the years by much experimental evidence. Here, we consider the physical condition of mechanical force balance as a determining condition of the nuclear volume and use quantitative, order-of-magnitude analysis to estimate the forces from different sources of nuclear and cytoplasmic pressure. Our estimates suggest that the dominant pressure within the nucleus and cytoplasm of nonstriated muscle cells originates from the osmotic pressure of proteins and RNA molecules that are localized to the nucleus or cytoplasm by out-of-equilibrium, active nucleocytoplasmic transport rather than from chromatin or its associated ions. This motivates us to formulate a physical model for the ratio of the cell and nuclear volumes in which osmotic pressures of localized proteins determine the relative volumes. In accordance with unexplained observations that are a century old, our model predicts that the ratio of the cell and nuclear volumes is a constant, robust to a wide variety of biochemical and biophysical manipulations, and is changed only if gene expression or nucleocytoplasmic transport is modulated.

Spatial Features and Functional Implications of Plant 3D Genome Organization

The advent of high-throughput sequencing-based methods for chromatin conformation, accessibility, and immunoprecipitation assays has been a turning point in 3D genomics. Altogether, these new tools have been pushing upward the interpretation of pioneer cytogenetic evidence for a higher order in chromatin packing. Here, we review the latest development in our understanding of plant spatial genome structures and different levels of organization and discuss their functional implications. Then, we spotlight the complexity of organellar (i.e., mitochondria and plastids) genomes and discuss their 3D packing into nucleoids. Finally, we propose unaddressed research axes to investigate functional links between chromatin-like dynamics and transcriptional regulation within organellar nucleoids.

Chromosome organization through the cell cycle at a glance

Genome organization and the three-dimensional folding of chromosomes are now seen as major contributors to nearly all nuclear functions including gene regulation, replication and repair. Recent studies have shown that in addition to the dramatic metamorphoses in chromosome conformation associated with entry to, and exit from mitosis, chromosomes undergo continual conformational changes throughout interphase with differential dynamics in loop structure, topological domains, compartments and lamina-associated domains. Understanding and accounting for these cell-cycle-dependent conformational changes is essential for the interpretation of data from a growing array of powerful molecular techniques to investigate genome conformation function, and to identify the molecules and mechanisms that drive chromosome conformational changes. In this Cell Science at a Glance article and the accompanying poster, we review Hi-C and microscopy studies describing cell-cycle-dependent conformational changes in chromosome structure.

Persistent spectral simplicial complex-based machine learning for chromosomal structural analysis in cellular differentiation

The three-dimensional (3D) chromosomal structure plays an essential role in all DNA-templated processes, including gene transcription, DNA replication and other cellular processes. Although developing chromosome conformation capture (3C) methods, such as Hi-C, which can generate chromosomal contact data characterized genome-wide chromosomal structural properties, understanding 3D genomic nature-based on Hi-C data remains lacking. Here, we propose a persistent spectral simplicial complex (PerSpectSC) model to describe Hi-C data for the first time. Specifically, a filtration process is introduced to generate a series of nested simplicial complexes at different scales. For each of these simplicial complexes, its spectral information can be calculated from the corresponding Hodge Laplacian matrix. PerSpectSC model describes the persistence and variation of the spectral information of the nested simplicial complexes during the filtration process. Different from all previous models, our PerSpectSC-based features provide a quantitative global-scale characterization of chromosome structures and topology. Our descriptors can successfully classify cell types and also cellular differentiation stages for all the 24 types of chromosomes simultaneously. In particular, persistent minimum best characterizes cell types and Dim (1) persistent multiplicity best characterizes cellular differentiation. These results demonstrate the great potential of our PerSpectSC-based models in polymeric data analysis.

Computational Approaches for Understanding Sequence Variation Effects on the 3D Genome Architecture

Decoding how genomic sequence and its variations affect 3D genome architecture is indispensable for understanding the genetic architecture of various traits and diseases. The 3D genome organization can be significantly altered by genome variations and in turn impact the function of the genomic sequence. Techniques for measuring the 3D genome architecture across spatial scales have opened up new possibilities for understanding how the 3D genome depends upon the genomic sequence and how it can be altered by sequence variations. Computational methods have become instrumental in analyzing and modeling the sequence effects on 3D genome architecture, and recent development in deep learning sequence models have opened up new opportunities for studying the interplay between sequence variations and the 3D genome. In this review, we focus on computational approaches for both the detection and modeling of sequence variation effects on the 3D genome, and we discuss the opportunities presented by these approaches. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.