Capturing chromosome conformation

3D genome organization and epigenetic regulation in autoimmune diseases

Three-dimensional (3D) genomics is an emerging field of research that investigates the relationship between gene regulatory function and the spatial structure of chromatin. Chromatin folding can be studied using chromosome conformation capture (3C) technology and 3C-based derivative sequencing technologies, including chromosome conformation capture-on-chip (4C), chromosome conformation capture carbon copy (5C), and high-throughput chromosome conformation capture (Hi-C), which allow scientists to capture 3D conformations from a single site to the entire genome. A comprehensive analysis of the relationships between various regulatory components and gene function also requires the integration of multi-omics data such as genomics, transcriptomics, and epigenomics. 3D genome folding is involved in immune cell differentiation, activation, and dysfunction and participates in a wide range of diseases, including autoimmune diseases. We describe hierarchical 3D chromatin organization in this review and conclude with characteristics of C-techniques and multi-omics applications of the 3D genome. In addition, we describe the relationship between 3D genome structure and the differentiation and maturation of immune cells and address how changes in chromosome folding contribute to autoimmune diseases.

HAT: Hypergraph analysis toolbox

Recent advances in biological technologies, such as multi-way chromosome conformation capture (3C), require development of methods for analysis of multi-way interactions. Hypergraphs are mathematically tractable objects that can be utilized to precisely represent and analyze multi-way interactions. Here we present the Hypergraph Analysis Toolbox (HAT), a software package for visualization and analysis of multi-way interactions in complex systems.

A multiple super-enhancer region establishes inter-TAD interactions and controls Hoxa function in cranial neural crest

Enhancer-promoter interactions preferentially occur within boundary-insulated topologically associating domains (TADs), limiting inter-TAD interactions. Enhancer clusters in linear proximity, termed super-enhancers (SEs), ensure high target gene expression levels. Little is known about SE topological regulatory impact during craniofacial development. Here, we identify 2232 genome-wide putative SEs in mouse cranial neural crest cells (CNCCs), 147 of which target genes establishing CNCC positional identity during face formation. In second pharyngeal arch (PA2) CNCCs, a multiple SE-containing region, partitioned into Hoxa Inter-TAD Regulatory Element 1 and 2 (HIRE1 and HIRE2), establishes long-range inter-TAD interactions selectively with Hoxa2, that is required for external and middle ear structures. HIRE2 deletion in a Hoxa2 haploinsufficient background results in microtia. HIRE1 deletion phenocopies the full homeotic Hoxa2 knockout phenotype and induces PA3 and PA4 CNCC abnormalities correlating with Hoxa2 and Hoxa3 transcriptional downregulation. Thus, SEs can overcome TAD insulation and regulate anterior Hoxa gene collinear expression in a CNCC subpopulation-specific manner during craniofacial development.

Determining chromatin architecture with Micro Capture-C

Micro Capture-C (MCC) is a chromatin conformation capture (3C) method for visualizing reproducible three-dimensional contacts of specified regions of the genome at base pair resolution. These methods are an established family of techniques that use proximity ligation to assay the topology of chromatin. MCC can generate data at substantially higher resolution than previous techniques through multiple refinements of the 3C method. Using a sequence agnostic nuclease, the maintenance of cellular integrity and full sequencing of the ligation junctions, MCC achieves subnucleosomal levels of resolution, which can be used to reveal transcription factor binding sites analogous to DNAse I footprinting. Gene dense regions, close-range enhancer-promoter contacts, individual enhancers within super-enhancers and multiple other types of loci or regulatory regions that were previously challenging to assay with conventional 3C techniques, are readily observed using MCC. MCC requires training in common molecular biology techniques and bioinformatics to perform the experiment and analyze the data. The protocol can be expected to be completed in a 3 week timeframe for experienced molecular biologists.

Identification of Mechanisms by Which Genetic Susceptibility Loci Influence Systemic Sclerosis Risk Using Functional Genomics in Primary T Cells and Monocytes

OBJECTIVE

Systemic sclerosis (SSc) is a complex autoimmune disease with a strong genetic component. However, most of the genes associated with the disease are still unknown because associated variants affect mostly noncoding intergenic elements of the genome. We used functional genomics to translate the genetic findings into a better understanding of the disease.

METHODS

Promoter capture Hi-C and RNA-sequencing experiments were performed in CD4+ T cells and CD14+ monocytes from 10 SSc patients and 5 healthy controls to link SSc-associated variants with their target genes, followed by differential expression and differential interaction analyses between cell types.

RESULTS

We linked SSc-associated loci to 39 new potential target genes and confirmed 7 previously known SSc-associated genes. We highlight novel causal genes, such as CXCR5, as the most probable candidate gene for the DDX6 locus. Some previously known SSc-associated genes, such as IRF8, STAT4, and CD247, showed cell type-specific interactions. We also identified 15 potential drug targets already in use in other similar immune-mediated diseases that could be repurposed for SSc treatment. Furthermore, we observed that interactions were directly correlated with the expression of important genes implicated in cell type-specific pathways and found evidence that chromatin conformation is associated with genotype.

CONCLUSION

Our study revealed potential causal genes for SSc-associated loci, some of them acting in a cell type-specific manner, suggesting novel biologic mechanisms that might mediate SSc pathogenesis.

Regulation of chromatin organization during animal regeneration

Activation of regeneration upon tissue damages requires the activation of many developmental genes responsible for cell proliferation, migration, differentiation, and tissue patterning. Ample evidence revealed that the regulation of chromatin organization functions as a crucial mechanism for establishing and maintaining cellular identity through precise control of gene transcription. The alteration of chromatin organization can lead to changes in chromatin accessibility and/or enhancer-promoter interactions. Like embryogenesis, each stage of tissue regeneration is accompanied by dynamic changes of chromatin organization in regeneration-responsive cells. In the past decade, many studies have been conducted to investigate the contribution of chromatin organization during regeneration in various tissues, organs, and organisms. A collection of chromatin regulators were demonstrated to play critical roles in regeneration. In this review, we will summarize the progress in the understanding of chromatin organization during regeneration in different research organisms and discuss potential common mechanisms responsible for the activation of regeneration response program.

Chromosome folding and prophage activation reveal specific genomic architecture for intestinal bacteria

BACKGROUND

Bacteria and their viruses, bacteriophages, are the most abundant entities of the gut microbiota, a complex community of microorganisms associated with human health and disease. In this ecosystem, the interactions between these two key components are still largely unknown. In particular, the impact of the gut environment on bacteria and their associated prophages is yet to be deciphered.

RESULTS

To gain insight into the activity of lysogenic bacteriophages within the context of their host genomes, we performed proximity ligation-based sequencing (Hi-C) in both in vitro and in vivo conditions on the 12 bacterial strains of the OMM12 synthetic bacterial community stably associated within mice gut (gnotobiotic mouse line OMM12). High-resolution contact maps of the chromosome 3D organization of the bacterial genomes revealed a wide diversity of architectures, differences between environments, and an overall stability over time in the gut of mice. The DNA contacts pointed at 3D signatures of prophages leading to 16 of them being predicted as functional. We also identified circularization signals and observed different 3D patterns between in vitro and in vivo conditions. Concurrent virome analysis showed that 11 of these prophages produced viral particles and that OMM12 mice do not carry other intestinal viruses.

CONCLUSIONS

The precise identification by Hi-C of functional and active prophages within bacterial communities will unlock the study of interactions between bacteriophages and bacteria across conditions (healthy vs disease). Video Abstract.

Nuclear genome organization in fungi: from gene folding to Rabl chromosomes

Comparative genomics has recently provided unprecedented insights into the biology and evolution of the fungal lineage. In the postgenomics era, a major research interest focuses now on detailing the functions of fungal genomes, i.e. how genomic information manifests into complex phenotypes. Emerging evidence across diverse eukaryotes has revealed that the organization of DNA within the nucleus is critically important. Here, we discuss the current knowledge on the fungal genome organization, from the association of chromosomes within the nucleus to topological structures at individual genes and the genetic factors required for this hierarchical organization. Chromosome conformation capture followed by high-throughput sequencing (Hi-C) has elucidated how fungal genomes are globally organized in Rabl configuration, in which centromere or telomere bundles are associated with opposite faces of the nuclear envelope. Further, fungal genomes are regionally organized into topologically associated domain-like (TAD-like) chromatin structures. We discuss how chromatin organization impacts the proper function of DNA-templated processes across the fungal genome. Nevertheless, this view is limited to a few fungal taxa given the paucity of fungal Hi-C experiments. We advocate for exploring genome organization across diverse fungal lineages to ensure the future understanding of the impact of nuclear organization on fungal genome function.

Development and Validation of Blood-Based Predictive Biomarkers for Response to PD-1/PD-L1 Checkpoint Inhibitors: Evidence of a Universal Systemic Core of 3D Immunogenetic Profiling across Multiple Oncological Indications

BACKGROUND

Unprecedented advantages in cancer treatment with immune checkpoint inhibitors (ICIs) remain limited to only a subset of patients. Systemic analyses of the regulatory 3D genome architecture linked to individual epigenetic and immunogenetic controls associated with tumour immune evasion mechanisms and immune checkpoint pathways reveal a highly prevalent molecular profile predictive of response to PD-1/PD-L1 ICIs. A clinical blood test based on a set of eight (8) 3D genomic biomarkers has been developed and validated on the basis of an observational trial to predict response to ICI therapy.

METHODS

The predictive eight biomarker set is derived from prospective observational clinical trials, representing 280 treatments with Pembrolizumab, Atezolizumab, Durvalumab, Nivolumab, and Avelumab in a broad range of indications: melanoma, lung, hepatocellular, renal, breast, bladder, colon, head and neck, bone, brain, lymphoma, prostate, vulvar, and cervical cancers.

RESULTS

The 3D genomic eight biomarker panel for response to immune checkpoint therapy achieved a high accuracy of 85%, sensitivity of 93%, and specificity of 82%.

CONCLUSIONS

This study demonstrates that a 3D genomic approach can be used to develop a predictive clinical assay for response to PD-1/PD-L1 checkpoint inhibition in cancer patients.

Characterization of Gene Regulatory Elements in Human Fetal Cortical Development: Enhancing Our Understanding of Neurodevelopmental Disorders and Evolution

The neocortex is the region that most distinguishes human brain from other mammals and primates [Annu Rev Genet. 2021 Nov;55(1):555-81]. Studying the development of human cortex is important in understanding the evolutionary changes occurring in humans relative to other primates, as well as in elucidating mechanisms underlying neurodevelopmental disorders. Cortical development is a highly regulated process, spatially and temporally coordinated by expression of essential transcriptional factors in response to signaling pathways [Neuron. 2019 Sep;103(6):980-1004]. Enhancers are the most well-understood cis-acting, non-protein-coding regulatory elements that regulate gene expression [Nat Rev Genet. 2014 Apr;15(4):272-86]. Importantly, given the conservation of both DNA sequence and molecular function of the majority of proteins across mammals [Genome Res. 2003 Dec;13(12):2507-18], enhancers [Science. 2015 Mar;347(6226):1155-9], which are far more divergent at the sequence level, likely account for the phenotypes that distinguish the human brain by changing the regulation of gene expression. In this review, we will revisit the conceptual framework of gene regulation during human brain development, as well as the evolution of technologies to study transcriptional regulation, with recent advances in genome biology that open a window allowing us to systematically characterize cis-regulatory elements in developing human brain [Hum Mol Genet. 2022 Oct;31(R1):R84-96]. We provide an update on work to characterize the suite of all enhancers in the developing human brain and the implications for understanding neuropsychiatric disorders. Finally, we discuss emerging therapeutic ideas that utilize our emerging knowledge of enhancer function.

When 3D genome changes cause disease: the impact of structural variations in congenital disease and cancer

Large structural variations (SV) are a class of mutations that have long been known to cause a wide range of genetic diseases, from rare congenital disease to cancer. Many of these SVs do not directly disrupt disease-related genes and determining causal genotype-phenotype relationships has been challenging to disentangle in the past. This has started to change with our increased understanding of the 3D genome folding. The pathophysiologies of the different types of genetic diseases influence the type of SVs observed and their genetic consequences, and how these are connected to 3D genome folding. We propose guiding principles for interpreting disease-associated SVs based on our current understanding of 3D chromatin architecture and the gene-regulatory and physiological mechanisms disrupted in disease.

Overview of Avian Sex Reversal

Sex determination and differentiation are processes by which a bipotential gonad adopts either a testicular or ovarian cell fate, and secondary sexual characteristics adopt either male or female developmental patterns. In birds, although genetic factors control the sex determination program, sex differentiation is sensitive to hormones, which can induce sex reversal when disturbed. Although these sex-reversed birds can form phenotypes opposite to their genotypes, none can experience complete sex reversal or produce offspring under natural conditions. Promising evidence indicates that the incomplete sex reversal is associated with cell autonomous sex identity (CASI) of avian cells, which is controlled by genetic factors. However, studies cannot clearly describe the regulatory mechanism of avian CASI and sex development at present, and these factors require further exploration. In spite of this, the abundant findings of avian sex research have provided theoretical bases for the progress of gender control technologies, which are being improved through interdisciplinary co-operation and will ultimately be employed in poultry production. In this review, we provide an overview of avian sex determination and differentiation and comprehensively summarize the research progress on sex reversal in birds, especially chickens. Importantly, we describe key issues faced by applying gender control systems in poultry production and chronologically summarize the development of avian sex control methods. In conclusion, this review provides unique perspectives for avian sex studies and helps scientists develop more advanced systems for sex regulation in birds.

LPAD: using network construction and label propagation to detect topologically associating domains from Hi-C data

With the development of chromosome conformation capture technique, the study of spatial conformation of a genome based on Hi-C technique has made a quantum leap. Previous studies reveal that genomes are folded into hierarchy of three-dimensional (3D) structures associated with topologically associating domains (TADs), and detecting TAD boundaries is of great significance in the chromosome-level analysis of 3D genome architecture. In this paper, we propose a novel TAD identification method, LPAD, which first extracts node correlations from global interactions of chromosomes based on the random walk with restart and then builds an undirected graph from Hi-C contact matrix. Next, LPAD designs a label propagation-based approach to discover communities and generates TADs. Experimental results verify the effectiveness and quality of TAD detections compared with existing methods. Furthermore, experimental evaluation of chromatin immunoprecipitation sequencing data shows that LPAD performs high enrichment of histone modifications remarkably nearby the TAD boundaries, and these results demonstrate LPAD's advantages on TAD identification accuracy.

Structural reorganization and relaxation dynamics of axially stressed chromosomes

Chromosomes endure mechanical stresses throughout the cell cycle; for example, resulting from the pulling of chromosomes by spindle fibers during mitosis or deformation of the nucleus during cell migration. The response to physical stress is closely related to chromosome structure and function. Micromechanical studies of mitotic chromosomes have revealed them to be remarkably extensible objects and informed early models of mitotic chromosome organization. We use a data-driven, coarse-grained polymer modeling approach to explore the relationship between the spatial organization of individual chromosomes and their emergent mechanical properties. In particular, we investigate the mechanical properties of our model chromosomes by axially stretching them. Simulated stretching led to a linear force-extension curve for small strain, with mitotic chromosomes behaving about 10-fold stiffer than interphase chromosomes. Studying their relaxation dynamics, we found that chromosomes are viscoelastic solids with a highly liquid-like, viscous behavior in interphase that becomes solid-like in mitosis. This emergent mechanical stiffness originates from lengthwise compaction, an effective potential capturing the activity of loop-extruding SMC complexes. Chromosomes denature under large strains via unraveling, which is characterized by opening of large-scale folding patterns. By quantifying the effect of mechanical perturbations on the chromosome's structural features, our model provides a nuanced understanding of in vivo mechanics of chromosomes.

Capturing the hierarchically assorted modules of protein-protein interactions in the organized nucleome

Nuclear proteins are major constituents and key regulators of nucleome topological organization and manipulators of nuclear events. To decipher the global connectivity of nuclear proteins and the hierarchically organized modules of their interactions, we conducted two rounds of cross-linking mass spectrometry (XL-MS) analysis, one of which followed a quantitative double chemical cross-linking mass spectrometry (in vivoqXL-MS) workflow, and identified 24,140 unique crosslinks in total from the nuclei of soybean seedlings. This in vivo quantitative interactomics enabled the identification of 5340 crosslinks that can be converted into 1297 nuclear protein-protein interactions (PPIs), 1220 (94%) of which were non-confirmative (or novel) nuclear PPIs compared with those in repositories. There were 250 and 26 novel interactors of histones and the nucleolar box C/D small nucleolar ribonucleoprotein complex, respectively. Modulomic analysis of orthologous Arabidopsis PPIs produced 27 and 24 master nuclear PPI modules (NPIMs) that contain the condensate-forming protein(s) and the intrinsically disordered region-containing proteins, respectively. These NPIMs successfully captured previously reported nuclear protein complexes and nuclear bodies in the nucleus. Surprisingly, these NPIMs were hierarchically assorted into four higher-order communities in a nucleomic graph, including genome and nucleolus communities. This combinatorial pipeline of 4C quantitative interactomics and PPI network modularization revealed 17 ethylene-specific module variants that participate in a broad range of nuclear events. The pipeline was able to capture both nuclear protein complexes and nuclear bodies, construct the topological architectures of PPI modules and module variants in the nucleome, and probably map the protein compositions of biomolecular condensates.

Structural changes in chromosomes driven by multiple condensin motors during mitosis

We create a computational framework that utilizes loop extrusion (LE) by multiple condensin I/II motors to predict changes in chromosome organization during mitosis. The theory accurately reproduces the experimental contact probability profiles for the mitotic chromosomes in HeLa and DT40 cells. The LE rate is smaller at the start of mitosis and increases as the cells approach metaphase. Condensin II-mediated mean loop size is about six times larger than loops because of condensin I. The loops, which overlap each other, are stapled to a central dynamically changing helical scaffold formed by the motors during the LE process. A polymer physics-based data-driven method that uses the Hi-C contact map as the only input shows that the helix is characterized as random helix perversions (RHPs) in which the handedness changes randomly along the scaffold. The theoretical predictions, which are testable using imaging experiments, do not contain any parameters.

hipFG: High-throughput harmonization and integration pipeline for functional genomics data

Preparing functional genomic (FG) data with diverse assay types and file formats for integration into analysis workflows that interpret genome-wide association and other studies is a significant and time-consuming challenge. Here we introduce hipFG, an automatically customized pipeline for efficient and scalable normalization of heterogenous FG data collections into standardized, indexed, rapidly searchable analysis-ready datasets while accounting for FG datatypes (e.g., chromatin interactions, genomic intervals, quantitative trait loci).

The magic of unraveling genome architecture and function

Over the last decades, technological breakthroughs in super-resolution microscopy have allowed us to reach molecular resolution and design experiments of unprecedented complexity. Investigating how chromatin is folded in 3D, from the nucleosome level up to the entire genome, is becoming possible by "magic" (imaging genomic), i.e., the combination of imaging and genomic approaches. This offers endless opportunities to delve into the relationship between genome structure and function. Here, we review recently achieved objectives and the conceptual and technical challenges the field of genome architecture is currently undertaking. We discuss what we have learned so far and where we are heading. We elucidate how the different super-resolution microscopy approaches and, more specifically, live-cell imaging have contributed to the understanding of genome folding. Moreover, we discuss how future technical developments could address remaining open questions.

Predicting enhancer-promoter interaction based on epigenomic signals

Introduction: The physical interactions between enhancers and promoters are often involved in gene transcriptional regulation. High tissue-specific enhancer-promoter interactions (EPIs) are responsible for the differential expression of genes. Experimental methods are time-consuming and labor-intensive in measuring EPIs. An alternative approach, machine learning, has been widely used to predict EPIs. However, most existing machine learning methods require a large number of functional genomic and epigenomic features as input, which limits the application to different cell lines. Methods: In this paper, we developed a random forest model, HARD (H3K27ac, ATAC-seq, RAD21, and Distance), to predict EPI using only four types of features. Results: Independent tests on a benchmark dataset showed that HARD outperforms other models with the fewest features. Discussion: Our results revealed that chromatin accessibility and the binding of cohesin are important for cell-line-specific EPIs. Furthermore, we trained the HARD model in the GM12878 cell line and performed testing in the HeLa cell line. The cross-cell-lines prediction also performs well, suggesting it has the potential to be applied to other cell lines.

Dynamic chromatin architectures provide insights into the genetics of cattle myogenesis

BACKGROUND

Sharply increased beef consumption is propelling the genetic improvement projects of beef cattle in China. Three-dimensional genome structure is confirmed to be an important layer of transcription regulation. Although genome-wide interaction data of several livestock species have already been produced, the genome structure states and its regulatory rules in cattle muscle are still limited.

RESULTS

Here we present the first 3D genome data in Longissimus dorsi muscle of fetal and adult cattle (Bos taurus). We showed that compartments, topologically associating domains (TADs), and loop undergo re-organization and the structure dynamics were consistent with transcriptomic divergence during muscle development. Furthermore, we annotated cis-regulatory elements in cattle genome during myogenesis and demonstrated the enrichments of promoter and enhancer in selection sweeps. We further validated the regulatory function of one HMGA2 intronic enhancer near a strong sweep region on primary bovine myoblast proliferation.

CONCLUSIONS

Our data provide key insights of the regulatory function of high order chromatin structure and cattle myogenic biology, which will benefit the progress of genetic improvement of beef cattle.

Dynamic chromatin conformation and accessibility changes mediate the spatial-specific gene regulatory network in Bombyx mori

Silk gland genes of Bombyx mori can have strict spatial expression patterns, which impact their functions and silk quality; however, our understanding of their regulation mechanisms is currently insufficient. To address this, the middle silk gland (MSG) and posterior silk gland (PSG) of the silkworm were investigated. Gene ontology annotation showed that spatially specific expressed genes were involved in the formation of H3k9me and chromatin topology. Chromatin conformation data generated by Hi-C showed that the topologically associated domain boundaries around FibL and Sericin1 genes were significantly different between MSG and PSG. Changes in chromatin conformation led to changes in chromatin activity, which significantly affected the expression of nearby genes in silkworm. Chromatin accessibility regions of MSG and PSG were analyzed using FAIRE-seq, and 1006 transcription factor motifs were identified in open chromatin regions. Furthermore, the spatial-specific expression patterns of silk gland genes were mainly associated with homeobox-contained transcription factors, such as POU-M2, which was specifically bound and relatively highly expressed in the MSG. The regulatory network mediated by POU-M2 regulated most of the spatial-specific expressed genes in MSG, such as ADH1. These results can aid in improving silk performance, optimizing silkworm breeding, and improving the gene spatial regulatory model research for insects.

Comparing chromatin contact maps at scale: methods and insights

Comparing chromatin contact maps is an essential step in quantifying how three-dimensional (3D) genome organization shapes development, evolution, and disease. However, no gold standard exists for comparing contact maps, and even simple methods often disagree. In this study, we propose novel comparison methods and evaluate them alongside existing approaches using genome-wide Hi-C data and 22,500 in silico predicted contact maps. We also quantify the robustness of methods to common sources of biological and technical variation, such as boundary size and noise. We find that simple difference-based methods such as mean squared error are suitable for initial screening, but biologically informed methods are necessary to identify why maps diverge and propose specific functional hypotheses. We provide a reference guide, codebase, and benchmark for rapidly comparing chromatin contact maps at scale to enable biological insights into the 3D organization of the genome.

Regulation and Immunotherapeutic Targeting of the Epigenome in Exhausted CD8 T Cell Responses

Exhaustion is a state of CD8 T cell differentiation that occurs in settings of chronic Ag such as tumors, chronic viral infection, and autoimmunity. Cellular differentiation is driven by a series of environmental signals that promote epigenetic landscapes that set transcriptomes needed for function. For CD8 T cells, the epigenome that underlies exhaustion is distinct from effector and memory cell differentiation, suggesting that signals early on set in motion a process where the epigenome is modified to promote a trajectory toward a dysfunctional state. Although we know many signals that promote exhaustion, putting this in the context of the epigenetic changes that occur during differentiation has been less clear. In this review, we aim to summarize the epigenetic changes associated with exhaustion in the context of signals that promote it, highlighting immunotherapeutic studies that support these observations or areas for future therapeutic opportunities.

Toward cis-regulation in soybean: a 3D genome scope

In eukaryotic cells, 3D genome plays an important role in the regulation of gene spatiotemporal expression, which is essential for the biological and developmental processes in a life cycle. In the past decade, the development of high-throughput technologies greatly enhances our ability to map the 3D genome organization, identifies multiple 3D genome structures, and investigates the functional role of 3D genome organization in gene regulation, which facilitates our understandings of cis-regulatory landscape and biological development. Comparing with the comprehensive analyses of 3D genome in mammals and model plants, the progress in soybean is much less. Future development and application of tools to precisely manipulate 3D genome structure at different levels will significantly strengthen the functional genome study and molecular breeding in soybean. Here, we review the recent progresses in 3D genome study and discuss future directions, which may help to improve soybean 3D functional genome study and molecular breeding.

The 3D genome and its impacts on human health and disease

Eukaryotic genomes are highly compacted in the cell nucleus. Two loci separated by a long linear distance can be brought into proximity in space through DNA-binding proteins and RNAs, which contributes profoundly to the regulation of gene expression. Recent technology advances have enabled the development and application of the chromosome conformation capture (3C) technique and a host of 3C-based methods that enable genome-scale investigations into changes in chromatin high-order structures during diverse physiological processes and diseases. In this review, we introduce 3C-based technologies and discuss how they can be utilized to glean insights into the impacts of three-dimensional (3D) genome organization in normal physiological and disease processes.

Survey of activation-induced genome architecture reveals a novel enhancer of Myc

The transcription factor Myc is critically important in driving cell proliferation, a function that is frequently dysregulated in cancer. To avoid this dysregulation Myc is tightly controlled by numerous layers of regulation. One such layer is the use of distal regulatory enhancers to drive Myc expression. Here, using chromosome conformation capture to examine B cells of the immune system in the first hours after their activation, we reveal a previously unidentified enhancer of Myc. The interactivity of this enhancer coincides with a dramatic, but discrete, spike in Myc expression 3 h post-activation. However, genetic deletion of this region, has little impact on Myc expression, Myc protein level or in vitro and in vivo cell proliferation. Examination of the enhancer deleted regulatory landscape suggests that enhancer redundancy likely sustains Myc expression. This work highlights not only the importance of temporally examining enhancers, but also the complexity and dynamics of the regulation of critical genes such as Myc.

Light-activated macromolecular phase separation modulates transcription by reconfiguring chromatin interactions

Biomolecular condensates participate in the regulation of gene transcription, yet the relationship between nuclear condensation and transcriptional activation remains elusive. Here, we devised a biotinylated CRISPR-dCas9-based optogenetic method, light-activated macromolecular phase separation (LAMPS), to enable inducible formation, affinity purification, and multiomic dissection of nuclear condensates at the targeted genomic loci. LAMPS-induced condensation at enhancers and promoters activates endogenous gene transcription by chromatin reconfiguration, causing increased chromatin accessibility and de novo formation of long-range chromosomal loops. Proteomic profiling of light-induced condensates by dCas9-mediated affinity purification uncovers multivalent interaction-dependent remodeling of macromolecular composition, resulting in the selective enrichment of transcriptional coactivators and chromatin structure proteins. Our findings support a model whereby the formation of nuclear condensates at native genomic loci reconfigures chromatin architecture and multiprotein assemblies to modulate gene transcription. Hence, LAMPS facilitates mechanistic interrogation of the relationship between nuclear condensation, genome structure, and gene transcription in living cells.

Fluorescence-based super-resolution-microscopy strategies for chromatin studies

Super-resolution microscopy (SRM) is a prime tool to study chromatin organisation at near biomolecular resolution in the native cellular environment. With fluorescent labels DNA, chromatin-associated proteins and specific epigenetic states can be identified with high molecular specificity. The aim of this review is to introduce the field of diffraction-unlimited SRM to enable an informed selection of the most suitable SRM method for a specific chromatin-related research question. We will explain both diffraction-unlimited approaches (coordinate-targeted and stochastic-localisation-based) and list their characteristic spatio-temporal resolutions, live-cell compatibility, image-processing, and ability for multi-colour imaging. As the increase in resolution, compared to, e.g. confocal microscopy, leads to a central role of the sample quality, important considerations for sample preparation and concrete examples of labelling strategies applicable to chromatin research are discussed. To illustrate how SRM-based methods can significantly improve our understanding of chromatin functioning, and to serve as an inspiring starting point for future work, we conclude with examples of recent applications of SRM in chromatin research.

Oncogenic epidermal growth factor receptor signal-induced histone deacetylation suppresses chemokine gene expression in human lung adenocarcinoma

Epidermal growth factor receptor (EGFR)-mutated (mt) lung adenocarcinoma (LA) is refractory to immune checkpoint inhibitors (ICIs). However, the mechanisms have not been fully elucidated. CD8+ T cell infiltration was significantly lower in EGFR-mt than in EGFR-wild-type LA, which was associated with suppression of chemokine expression. Since this T cell-deserted tumor microenvironment may lead to the refractoriness of ICIs against EGFR-mt LA, we investigated the mechanism by focusing on the regulation of chemokine expression. The expression of C-X-C motif ligand (CXCL) 9, 10 and 11, which constitute a gene cluster on chromosome 4, was suppressed under EGFR signaling. The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) revealed open chromatin peaks near this gene cluster following EGFR-tyrosine kinase inhibitor (TKI) treatment. The histone deacetylase (HDAC) inhibitor recovered the expression of CXCL9, 10 and 11 in EGFR-mt LA. Nuclear HDAC activity, as well as histone H3 deacetylation, were dependent on oncogenic EGFR signaling. Furthermore, the Cleavage Under Targets and Tagmentation (CUT & Tag) assay revealed a histone H3K27 acetylation peak at 15 kb upstream of CXCL11 after treatment with EGFR-TKI, which corresponded to one of the open chromatin peaks detected by ATAC-seq. The data suggest that EGFR-HDAC axis mediates silencing of the chemokine gene cluster through chromatin conformational change, which might be relevant to the ICI resistance by creating T cell-deserted tumor microenvironment. Targeting this axis may develop a new therapeutic strategy to overcome the ICI resistance of EGFR-mt LA.

Dynamics of nuclear architecture during early embryonic development and lessons from liveimaging

Nuclear organization has emerged as a potential key regulator of genome function. During development, the deployment of transcriptional programs must be tightly coordinated with cell division and is often accompanied by major changes in the repertoire of expressed genes. These transcriptional and developmental events are paralleled by changes in the chromatin landscape. Numerous studies have revealed the dynamics of nuclear organization underlying them. In addition, advances in live-imaging-based methodologies enable the study of nuclear organization with high spatial and temporal resolution. In this Review, we summarize the current knowledge of the changes in nuclear architecture in the early embryogenesis of various model systems. Furthermore, to highlight the importance of integrating fixed-cell and live approaches, we discuss how different live-imaging techniques can be applied to examine nuclear processes and their contribution to our understanding of transcription and chromatin dynamics in early development. Finally, we provide future avenues for outstanding questions in this field.

Regulation of loop extrusion on the interphase genome

In the human cell nucleus, dynamically organized chromatin is the substrate for gene regulation, DNA replication, and repair. A central mechanism of DNA loop formation is an ATPase motor cohesin-mediated loop extrusion. The cohesin complexes load and unload onto the chromosome under the control of other regulators that physically interact and affect motor activity. Regulation of the dynamic loading cycle of cohesin influences not only the chromatin structure but also genome-associated human disorders and aging. This review focuses on the recently spotlighted genome organizing factors and the mechanism by which their dynamic interactions shape the genome architecture in interphase.

The Foundational Data Initiative for Parkinson Disease: Enabling efficient translation from genetic maps to mechanism

The Foundational Data Initiative for Parkinson Disease (FOUNDIN-PD) is an international collaboration producing fundamental resources for Parkinson disease (PD). FOUNDIN-PD generated a multi-layered molecular dataset in a cohort of induced pluripotent stem cell (iPSC) lines differentiated to dopaminergic (DA) neurons, a major affected cell type in PD. The lines were derived from the Parkinson's Progression Markers Initiative study, which included participants with PD carrying monogenic PD variants, variants with intermediate effects, and variants identified by genome-wide association studies and unaffected individuals. We generated genetic, epigenetic, regulatory, transcriptomic, and longitudinal cellular imaging data from iPSC-derived DA neurons to understand molecular relationships between disease-associated genetic variation and proximate molecular events. These data reveal that iPSC-derived DA neurons provide a valuable cellular context and foundational atlas for modeling PD genetic risk. We have integrated these data into a FOUNDIN-PD data browser as a resource for understanding the molecular pathogenesis of PD.

High-throughput Pore-C reveals the single-allele topology and cell type-specificity of 3D genome folding

Canonical three-dimensional (3D) genome structures represent the ensemble average of pairwise chromatin interactions but not the single-allele topologies in populations of cells. Recently developed Pore-C can capture multiway chromatin contacts that reflect regional topologies of single chromosomes. By carrying out high-throughput Pore-C, we reveal extensive but regionally restricted clusters of single-allele topologies that aggregate into canonical 3D genome structures in two human cell types. We show that fragments in multi-contact reads generally coexist in the same TAD. In contrast, a concurrent significant proportion of multi-contact reads span multiple compartments of the same chromatin type over megabase distances. Synergistic chromatin looping between multiple sites in multi-contact reads is rare compared to pairwise interactions. Interestingly, the single-allele topology clusters are cell type-specific even inside highly conserved TADs in different types of cells. In summary, HiPore-C enables global characterization of single-allele topologies at an unprecedented depth to reveal elusive genome folding principles.

3D genomics and its applications in precision medicine

Three-dimensional (3D) genomics is an emerging discipline that studies the three-dimensional structure of chromatin and the three-dimensional and functions of genomes. It mainly studies the three-dimensional conformation and functional regulation of intranuclear genomes, such as DNA replication, DNA recombination, genome folding, gene expression regulation, transcription factor regulation mechanism, and the maintenance of three-dimensional conformation of genomes. Self-chromosomal conformation capture (3C) technology has been developed, and 3D genomics and related fields have developed rapidly. In addition, chromatin interaction analysis techniques developed by 3C technologies, such as paired-end tag sequencing (ChIA-PET) and whole-genome chromosome conformation capture (Hi-C), enable scientists to further study the relationship between chromatin conformation and gene regulation in different species. Thus, the spatial conformation of plant, animal, and microbial genomes, transcriptional regulation mechanisms, interaction patterns of chromosomes, and the formation mechanism of spatiotemporal specificity of genomes are revealed. With the help of new experimental technologies, the identification of key genes and signal pathways related to life activities and diseases is sustaining the rapid development of life science, agriculture, and medicine. In this paper, the concept and development of 3D genomics and its application in agricultural science, life science, and medicine are introduced, which provides a theoretical basis for the study of biological life processes.

Using QTL to Identify Genes and Pathways Underlying the Regulation and Production of Milk Components in Cattle

Milk is a complex liquid, and the concentrations of many of its components are under genetic control. Many genes and pathways are known to regulate milk composition, and the purpose of this review is to highlight how the discoveries of quantitative trait loci (QTL) for milk phenotypes can elucidate these pathways. The main body of this review focuses primarily on QTL discovered in cattle (Bos taurus) as a model species for the biology of lactation, and there are occasional references to sheep genetics. The following section describes a range of techniques that can be used to help identify the causative genes underlying QTL when the underlying mechanism involves the regulation of gene expression. As genotype and phenotype databases continue to grow and diversify, new QTL will continue to be discovered, and although proving the causality of underlying genes and variants remains difficult, these new data sets will further enhance our understanding of the biology of lactation.

Defining the separation landscape of topological domains for decoding consensus domain organization of the 3D genome

Topologically associating domains (TADs) have emerged as basic structural and functional units of genome organization and have been determined by many computational methods from Hi-C contact maps. However, the TADs obtained by different methods vary greatly, which makes the accurate determination of TADs a challenging issue and hinders subsequent biological analyses about their organization and functions. Obvious inconsistencies among the TADs identified by different methods indeed make the statistical and biological properties of TADs overly depend on the chosen method rather than on the data. To this end, we use the consensus structural information captured by these methods to define the TAD separation landscape for decoding the consensus domain organization of the 3D genome. We show that the TAD separation landscape could be used to compare domain boundaries across multiple cell types for discovering conserved and divergent topological structures, decipher three types of boundary regions with diverse biological features, and identify consensus TADs (ConsTADs). We illustrate that these analyses could deepen our understanding of the relationships between the topological domains and chromatin states, gene expression, and DNA replication timing.

The Nodewalk assay to quantitate chromatin fiber interactomes in very small cell populations

The chromosome conformation capture method and its derivatives, such as circularized chromosome conformation capture, carbon copy chromosome conformation capture, high-throughput chromosome conformation capture and capture high-throughput chromosome conformation capture, have pioneered our understanding of the principles of chromosome folding in the nucleus. These technical advances, however, cannot precisely quantitate interaction frequency in very small input samples. Here we describe a protocol for the Nodewalk assay, which is based on converting chromosome conformation capture DNA samples to RNA and subsequently to cDNA using strategically placed primers. This pipeline enables the quantitative analyses of chromatin fiber interactions without compromising its sensitivity down to <300 cells, making it suitable for MiSeq analyses of higher-order chromatin structures in biopsies, circulating tumor cells and transitional cell states, for example. Importantly, the quality of the Nodewalk sample can be assessed before sequencing to avoid unnecessary costs. Moreover, it enables analyses from hundreds of different restriction enzyme fragment viewpoints within the same initial small input sample to uncover complex, genome-wide networks. Following optimization of the different steps, the entire protocol can be completed within 2 weeks.

A maximum-entropy model to predict 3D structural ensembles of chromatin from pairwise distances with applications to interphase chromosomes and structural variants

The principles that govern the organization of genomes, which are needed for an understanding of how chromosomes are packaged and function in eukaryotic cells, could be deciphered if the three-dimensional (3D) structures are known. Recently, single-cell imaging techniques have been developed to determine the 3D coordinates of genomic loci in vivo. Here, we introduce a computational method (Distance Matrix to Ensemble of Structures, DIMES), based on the maximum entropy principle, with experimental pairwise distances between loci as constraints, to generate a unique ensemble of 3D chromatin structures. Using the ensemble of structures, we quantitatively account for the distribution of pairwise distances, three-body co-localization, and higher-order interactions. The DIMES method can be applied to both small and chromosome-scale imaging data to quantify the extent of heterogeneity and fluctuations in the shapes across various length scales. We develop a perturbation method in conjunction with DIMES to predict the changes in 3D structures from structural variations. Our method also reveals quantitative differences between the 3D structures inferred from Hi-C and those measured in imaging experiments. Finally, the physical interpretation of the parameters extracted from DIMES provides insights into the origin of phase separation between euchromatin and heterochromatin domains.

The GRN concept as a guide for evolutionary developmental biology

Organismal phenotypes result largely from inherited developmental programs, usually executed during embryonic and juvenile life stages. These programs are not blank slates onto which natural selection can draw arbitrary forms. Rather, the mechanisms of development play an integral role in shaping phenotypic diversity and help determine the evolutionary trajectories of species. Modern evolutionary biology must, therefore, account for these mechanisms in both theory and in practice. The gene regulatory network (GRN) concept represents a potent tool for achieving this goal whose utility has grown in tandem with advances in "omic" technologies and experimental techniques. However, while the GRN concept is widely utilized, it is often less clear what practical implications it has for conducting research in evolutionary developmental biology. In this Perspective, we attempt to provide clarity by discussing how experiments and projects can be designed in light of the GRN concept. We first map familiar biological notions onto the more abstract components of GRN models. We then review how diverse functional genomic approaches can be directed toward the goal of constructing such models and discuss current methods for functionally testing evolutionary hypotheses that arise from them. Finally, we show how the major steps of GRN model construction and experimental validation suggest generalizable workflows that can serve as a scaffold for project design. Taken together, the practical implications that we draw from the GRN concept provide a set of guideposts for studies aiming at unraveling the molecular basis of phenotypic diversity.

Translating non-coding genetic associations into a better understanding of immune-mediated disease

Genome-wide association studies have identified hundreds of genetic loci that are associated with immune-mediated diseases. Most disease-associated variants are non-coding, and a large proportion of these variants lie within enhancers. As a result, there is a pressing need to understand how common genetic variation might affect enhancer function and thereby contribute to immune-mediated (and other) diseases. In this Review, we first describe statistical and experimental methods to identify causal genetic variants that modulate gene expression, including statistical fine-mapping and massively parallel reporter assays. We then discuss approaches to characterise the mechanisms by which these variants modulate immune function, such as clustered regularly interspaced short palindromic repeats (CRISPR)-based screens. We highlight examples of studies that, by elucidating the effects of disease variants within enhancers, have provided important insights into immune function and uncovered key pathways of disease.

Examining the biological mechanisms of human mental disorders resulting from gene-environment interdependence using novel functional genomic approaches

We explore how functional genomics approaches that integrate datasets from human and non-human model systems can improve our understanding of the effect of gene-environment interplay on the risk for mental disorders. We start by briefly defining the G-E paradigm and its challenges and then discuss the different levels of regulation of gene expression and the corresponding data existing in humans (genome wide genotyping, transcriptomics, DNA methylation, chromatin modifications, chromosome conformational changes, non-coding RNAs, proteomics and metabolomics), discussing novel approaches to the application of these data in the study of the origins of mental health. Finally, we discuss the multilevel integration of diverse types of data. Advance in the use of functional genomics in the context of a G-E perspective improves the detection of vulnerabilities, informing the development of preventive and therapeutic interventions.

(Tn5-)FISH-based imaging in the era of 3D/spatial genomics

3D genomics mainly focuses on the 3D position of single genes at the cell level, while spatial genomics focuses more on the tissue level. In this exciting new era of 3D/spatial genomics, half-century old FISH and its derivative methods, including Tn5-FISH, play important roles. In this review, we introduce the Tn5-FISH we developed recently, and present six different applications published by our collaborators and us, based on (Tn5-)FISH, which can be either general BAC clone-based FISH or Tn5-FISH. In these interesting cases, (Tn5-)FISH demonstrated its vigorous ability of targeting sub-chromosomal structures across different diseases and cell lines (leukemia, mESCs (mouse embryonic stem cells), and differentiation cell lines). Serving as an effective tool to image genomic structures at the kilobase level, Tn5-FISH holds great potential to detect chromosomal structures in a high-throughput manner, thus bringing the dawn for new discoveries in the great era of 3D/spatial genomics.

Chromosome Three-Dimensional Structure Reconstruction: An Iterative ShRec3D Algorithm

The three-dimensional (3D) structure of chromosomes is of great significance to ensure that the genome performs various functions (e.g., gene expression) correctly and replicates and separates correctly in mitosis. Since the emergence of Hi-C in 2009, a new experimental technique in molecular biology, researchers have been paying more and more attention to the reconstruction of chromosome 3D structure. To reconstruct the 3D structure of chromosomes based on Hi-C experimental data, many algorithms have been proposed, among which ShRec3D is one of the most outstanding. In this article, an iterative ShRec3D algorithm is presented to greatly improve the native ShRec3D algorithm. Experimental results show that our algorithm can significantly promote the performance of ShRec3D, and this improvement is applicable to almost all data noise range and signal coverage range, so it is universal.

High-Resolution 3D Genome Map of Brucella Chromosomes in Exponential and Stationary Phases

The three-dimensional (3D) genome structure of an organism or cell is highly relevant to its biological activities, but the availability of 3D genome information for bacteria, especially intracellular pathogens, is still limited. Here, we used Hi-C (high-throughput chromosome conformation capture) technology to determine the 3D chromosome structures of exponential- and stationary-phase Brucella melitensis at a 1-kb resolution. We observed that the contact heat maps of the two B. melitensis chromosomes contain a prominent diagonal and a secondary diagonal. Then, 79 chromatin interaction domains (CIDs) were detected at an optical density at 600 nm (OD600) of 0.4 (exponential phase), with the longest CID being 106 kb and the shortest being 12 kb. Moreover, we obtained 49,363 significant cis-interaction loci and 59,953 significant trans-interaction loci. Meanwhile, 82 CIDs of B. melitensis at an OD600 of 1.5 (stationary phase) were detected, with the longest CID being 94 kb and the shortest being 16 kb. In addition, 25,965 significant cis-interaction loci and 35,938 significant trans-interaction loci were obtained in this phase. Furthermore, we found that as the B. melitensis cells grew from the logarithmic to the plateau phase, the frequency of short-range interactions increased, while that of long-range interactions decreased. Finally, combined analysis of 3D genome and whole-genome transcriptome (RNA-seq) data revealed that the strength of short-range interactions in Chr1 is specifically and strongly correlated with gene expression. Overall, our study provides a global view of the chromatin interactions in the B. melitensis chromosomes, which will serve as a resource for further study of the spatial regulation of gene expression in Brucella. IMPORTANCE The spatial structure of chromatin plays important roles in normal cell functions and in the regulation of gene expression. Three-dimensional genome sequencing has been performed in many mammals and plants, but the availability of such data for bacteria, especially intracellular pathogens, is still limited. Approximately 10% of sequenced bacterial genomes contain more than one replicon. However, how multiple replicons are organized within bacterial cells, how they interact, and whether these interactions help to maintain or segregate these multipartite genomes are unresolved issues. Brucella is a Gram-negative, facultative intracellular, and zoonotic bacterium. Except for Brucella suis biovar 3, Brucella species have two chromosomes. Here, we applied Hi-C technology to determine the 3D genome structures of exponential- and stationary-phase Brucella melitensis chromosomes at a 1-kb resolution. Combined analysis of the 3D genome and RNA-seq data indicated that the strength of short-range interactions in B. melitensis Chr1 is specifically and strongly correlated with gene expression. Our study provides a resource to achieve a deeper understanding of the spatial regulation of gene expression in Brucella.

Computational approaches to understand transcription regulation in development

Gene regulatory networks (GRNs) serve as useful abstractions to understand transcriptional dynamics in developmental systems. Computational prediction of GRNs has been successfully applied to genome-wide gene expression measurements with the advent of microarrays and RNA-sequencing. However, these inferred networks are inaccurate and mostly based on correlative rather than causative interactions. In this review, we highlight three approaches that significantly impact GRN inference: (1) moving from one genome-wide functional modality, gene expression, to multi-omics, (2) single cell sequencing, to measure cell type-specific signals and predict context-specific GRNs, and (3) neural networks as flexible models. Together, these experimental and computational developments have the potential to significantly impact the quality of inferred GRNs. Ultimately, accurately modeling the regulatory interactions between transcription factors and their target genes will be essential to understand the role of transcription factors in driving developmental gene expression programs and to derive testable hypotheses for validation.

Evolutionarily distinct and sperm-specific supersized chromatin loops are marked by Helitron transposons in Xenopus tropicalis

Transposable elements (TEs) are abundant in metazoan genomes and have multifaceted effects on host fitness. However, the mechanisms underlying the functions of TEs are still not fully understood. Here, we combine Hi-C, ATAC-seq, and ChIP-seq assays to report the existence of multimegabase supersized loop (SSL) clusters in the Xenopus tropicalis sperm. We show that SSL anchors are inaccessible and devoid of the architectural protein CTCF, RNA polymerase II, and modified histones. Nearly all SSL anchors are marked by Helitrons, a class II DNA transposon. Molecular dynamics simulations indicate that SSL clusters are likely formed via a molecular agent-mediated chromatin condensation process. However, only slightly more SSL anchor-associated genes are expressed at late embryo development stages, suggesting that SSL anchors might only function in sperm. Our work shows an evolutionarily distinct and sperm-specific genome structure marked by a subset of Helitrons, whose establishment and function remain to be explored.

Evaluating the mouse neural precursor line, SN4741, as a suitable proxy for midbrain dopaminergic neurons

To overcome the ethical and technical limitations of in vivo human disease models, the broader scientific community frequently employs model organism-derived cell lines to investigate of disease mechanisms, pathways, and therapeutic strategies. Despite the widespread use of certain in vitro models, many still lack contemporary genomic analysis supporting their use as a proxy for the affected human cells and tissues. Consequently, it is imperative to determine how accurately and effectively any proposed biological surrogate may reflect the biological processes it is assumed to model. One such cellular surrogate of human disease is the established mouse neural precursor cell line, SN4741, which has been used to elucidate mechanisms of neurotoxicity in Parkinson disease for over 25 years. Here, we are using a combination of classic and contemporary genomic techniques - karyotyping, RT-qPCR, single cell RNA-seq, bulk RNA-seq, and ATAC-seq - to characterize the transcriptional landscape, chromatin landscape, and genomic architecture of this cell line, and evaluate its suitability as a proxy for midbrain dopaminergic neurons in the study of Parkinson disease. We find that SN4741 cells possess an unstable triploidy and consistently exhibits low expression of dopaminergic neuron markers across assays, even when the cell line is shifted to the non-permissive temperature that drives differentiation. The transcriptional signatures of SN4741 cells suggest that they are maintained in an undifferentiated state at the permissive temperature and differentiate into immature neurons at the non-permissive temperature; however, they may not be dopaminergic neuron precursors, as previously suggested. Additionally, the chromatin landscapes of SN4741 cells, in both the differentiated and undifferentiated states, are not concordant with the open chromatin profiles of ex vivo , mouse E15.5 forebrain- or midbrain-derived dopaminergic neurons. Overall, our data suggest that SN4741 cells may reflect early aspects of neuronal differentiation but are likely not a suitable a proxy for dopaminergic neurons as previously thought. The implications of this study extend broadly, illuminating the need for robust biological and genomic rationale underpinning the use of in vitro models of molecular processes.

Challenges and Opportunities for Clinical Cytogenetics in the 21st Century

The powerful utilities of current DNA sequencing technology question the value of developing clinical cytogenetics any further. By briefly reviewing the historical and current challenges of cytogenetics, the new conceptual and technological platform of the 21st century clinical cytogenetics is presented. Particularly, the genome architecture theory (GAT) has been used as a new framework to emphasize the importance of clinical cytogenetics in the genomic era, as karyotype dynamics play a central role in information-based genomics and genome-based macroevolution. Furthermore, many diseases can be linked to elevated levels of genomic variations within a given environment. With karyotype coding in mind, new opportunities for clinical cytogenetics are discussed to integrate genomics back into cytogenetics, as karyotypic context represents a new type of genomic information that organizes gene interactions. The proposed research frontiers include: 1. focusing on karyotypic heterogeneity (e.g., classifying non-clonal chromosome aberrations (NCCAs), studying mosaicism, heteromorphism, and nuclear architecture alteration-mediated diseases), 2. monitoring the process of somatic evolution by characterizing genome instability and illustrating the relationship between stress, karyotype dynamics, and diseases, and 3. developing methods to integrate genomic data and cytogenomics. We hope that these perspectives can trigger further discussion beyond traditional chromosomal analyses. Future clinical cytogenetics should profile chromosome instability-mediated somatic evolution, as well as the degree of non-clonal chromosomal aberrations that monitor the genomic system's stress response. Using this platform, many common and complex disease conditions, including the aging process, can be effectively and tangibly monitored for health benefits.

3D genome-selected microRNAs to improve Alzheimer's disease prediction

Introduction

Alzheimer's disease (AD) is a type of neurodegenerative disease that has no effective treatment in its late stage, making the early prediction of AD critical. There have been an increase in the number of studies indicating that miRNAs play an important role in neurodegenerative diseases including Alzheimer's disease via epigenetic modifications including DNA methylation. Therefore, miRNAs may serve as excellent biomarkers in early AD prediction.

Methods

Considering that the non-coding RNAs' activity may be linked to their corresponding DNA loci in the 3D genome, we collected the existing AD-related miRNAs combined with 3D genomic data in this study. We investigated three machine learning models in this work under leave-one-out cross-validation (LOOCV): support vector classification (SVC), support vector regression (SVR), and knearest neighbors (KNNs).

Results

The prediction results of different models demonstrated the effectiveness of incorporating 3D genome information into the AD prediction models.

Discussion

With the assistance of the 3D genome, we were able to train more accurate models by selecting fewer but more discriminatory miRNAs, as witnessed by several ML models. These interesting findings indicate that the 3D genome has great potential to play an important role in future AD research.

Conserved noncoding sequences correlate with distant gene contacts in Arabidopsis and Brassica

Physical contact between genes distant on chromosomes is a potentially important way for genes to coordinate their expressions. To investigate the potential importance of distant contacts, we performed high-throughput chromatin conformation capture (Hi-C) experiments on leaf nuclei isolated from Brassica rapa and Brassica oleracea. We then combined our results with published Hi-C data from Arabidopsis thaliana. We found that distant genes come into physical contact and do so preferentially between the proximal promoter of one gene and the downstream region of another gene. Genes with higher numbers of conserved noncoding sequences (CNSs) nearby were more likely to have contact with distant genes. With more CNSs came higher numbers of transcription factor binding sites and more histone modifications associated with the activity. In addition, for the genes we studied, distant contacting genes with CNSs were more likely to be transcriptionally coordinated. These observations suggest that CNSs may enrich active histone modifications and recruit transcription factors, correlating with distant contacts to ensure coordinated expression. This study advances our knowledge of gene contacts and provides insights into the relationship between CNSs and distant gene contacts in plants.