Single-cell DNA methylation and 3D genome architecture in the human brain

Human brain ancestral barcodes

Dynamic CpG methylation 'barcodes' were read from 15,000-21,000 single cells from three human male brains. To overcome sparse sequencing coverage, the barcode had ~31,000 rapidly fluctuating X-chromosome CpG sites (fCpGs), with at least 500 covered sites per cell and at least 30 common sites between cell pairs (average of ~48). Barcodes appear to start methylated and record mitotic ages because excitatory neurons and glial cells that emerge later in development were less methylated. Barcodes are different between most cells, with average pairwise differences (PWDs) of ~0.5 between cells. About 10 cell pairs per million were more closely related with PWDs <0.05. Barcodes appear to record ancestry and reconstruct trees where more related cells had similar phenotypes, albeit some pairs had phenotypic differences. Inhibitory neurons showed more evidence of tangential migration than excitatory neurons, with related cells in different cortical regions. fCpG barcodes become polymorphic during development and can distinguish between thousands of human cells.

Exploring the untapped potential of single-cell and spatial omics in plant biology

Advances in single-cell and spatial omics technologies have revolutionised biology by revealing the diverse molecular states of individual cells and their spatial organization within tissues. The field of plant biology has widely adopted single-cell transcriptome and chromatin accessibility profiling and spatial transcriptomics, which extend traditional cell biology and genomics analyses and provide unique opportunities to reveal molecular and cellular dynamics of tissues. Using these technologies, comprehensive cell atlases have been generated in several model plant species, providing valuable platforms for discovery and tool development. Other emerging technologies related to single-cell and spatial omics, such as multiomics, lineage tracing, molecular recording, and high-content genetic and chemical perturbation phenotyping, offer immense potential for deepening our understanding of plant biology yet remain underutilised due to unique technical challenges and resource availability. Overcoming plant-specific barriers, such as cell wall complexity and limited antibody resources, alongside community-driven efforts in developing more complete reference atlases and computational tools, will accelerate progress. The synergy between technological innovation and targeted biological questions is poised to drive significant discoveries, advancing plant science. This review highlights the current applications of single-cell and spatial omics technologies in plant research and introduces emerging approaches with the potential to transform the field.

Revisiting the Pathogenesis of X-Linked Adrenoleukodystrophy

BACKGROUND

X-ALD is a white matter (WM) disease caused by mutations in the ABCD1 gene encoding the transporter of very-long-chain fatty acids (VLCFAs) into peroxisomes. Strikingly, the same ABCD1 mutation causes either devastating brain inflammatory demyelination during childhood or, more often, progressive spinal cord axonopathy starting in middle-aged adults. The accumulation of undegraded VLCFA in glial cell membranes and myelin has long been thought to be the central mechanism of X-ALD.

METHODS

This review discusses studies in mouse and drosophila models that have modified our views of X-ALD pathogenesis.

RESULTS

In the Abcd1 knockout (KO) mouse that mimics the spinal cord disease, the late manifestations of axonopathy are rapidly reversed by ABCD1 gene transfer into spinal cord oligodendrocytes (OLs). In a peroxin-5 KO mouse model, the selective impairment of peroxisomal biogenesis in OLs achieves an almost perfect phenocopy of cerebral ALD. A drosophila knockout model revealed that VLCFA accumulation in glial myelinating cells causes the production of a toxic lipid able to poison axons and activate inflammatory cells. Other mouse models showed the critical role of OLs in providing energy substrates to axons. In addition, studies on microglial changing substates have improved our understanding of neuroinflammation.

CONCLUSIONS

Animal models supporting a primary role of OLs and axonal pathology and a secondary role of microglia allow us to revisit of X-ALD mechanisms. Beyond ABCD1 mutations, pathogenesis depends on unidentified contributors, such as genetic background, cell-specific epigenomics, potential environmental triggers, and stochasticity of crosstalk between multiple cell types among billions of glial cells and neurons.

Spatiotemporal 3D chromatin organization across multiple brain regions during human fetal development

Elucidating the regulatory mechanisms underlying the development of different brain regions in humans is essential for understanding advanced cognition and neuropsychiatric disorders. However, the spatiotemporal organization of three-dimensional (3D) chromatin structure and its regulatory functions across different brain regions remain poorly understood. Here, we generated an atlas of high-resolution 3D chromatin structure across six developing human brain regions, including the prefrontal cortex (PFC), primary visual cortex (V1), cerebellum (CB), subcortical corpus striatum (CS), thalamus (TL), and hippocampus (HP), spanning gestational weeks 11-26. We found that the spatial and temporal dynamics of 3D chromatin organization play a key role in regulating brain region development. We also identified H3K27ac-marked super-enhancers as key contributors to shaping brain region-specific 3D chromatin structures and gene expression patterns. Finally, we uncovered hundreds of neuropsychiatric GWAS SNP-linked genes, shedding light on critical molecules in various neuropsychiatric disorders. In summary, our findings provide important insights into the 3D chromatin regulatory mechanisms governing brain region-specific development and can serve as a valuable resource for advancing our understanding of neuropsychiatric disorders.

Neurodevelopmental hijacking of oligodendrocyte lineage programs drives glioblastoma infiltration

Glioblastoma (GBM) is an aggressive brain tumor with a highly invasive nature. Despite the clinical relevance of this behavior, the molecular underpinnings of infiltrating GBM cells in the peritumoral zone remain underexplored in patients. Here, we show that peritumoral progenitor-like GBM cells activate transcriptional programs associated with increased invasivity, synaptic activity, and NOTCH signaling. These cells spatially colocalize with neurons and exhibit an increased propensity for neuronal crosstalk. The epigenetic encoding of these infiltrative cells mirrors that of uncommitted oligodendrocyte progenitor cells (OPCs) in the developing human brain, a neurodevelopmental state marked by increased synaptic and migratory potential. Functional perturbation of a nominated regulatory factor, ZEB1, confirmed its role in maintaining the invasive and uncommitted developmental potential of infiltrative GBM cells. Our findings provide insights into the neurodevelopmental hijacking that drives GBM infiltration in patients, rationalizing further investigation into targeting differentiation potential as a therapeutic strategy.

Neuronal Circuit Evolution: From Development to Structure and Adaptive Significance

Neuronal circuits represent the functional units of the brain. Understanding how the circuits are generated to perform computations will help us understand how the brain functions. Nevertheless, neuronal circuits are not engineered, but have formed through millions of years of animal evolution. We posit that it is necessary to study neuronal circuit evolution to comprehensively understand circuit function. Here, we review our current knowledge regarding the mechanisms that underlie circuit evolution. First, we describe the possible genetic and developmental mechanisms that have contributed to circuit evolution. Then, we discuss the structural changes of circuits during evolution and how these changes affected circuit function. Finally, we try to put circuit evolution in an ecological context and assess the adaptive significance of specific examples. We argue that, thanks to the advent of new tools and technologies, evolutionary neurobiology now allows us to address questions regarding the evolution of circuitry and behavior that were unimaginable until very recently.

Tri-omic single-cell mapping of the 3D epigenome and transcriptome in whole mouse brains throughout the lifespan

Exploring the genomic basis of transcriptional programs has been a long-standing research focus. Here we report a single-cell method, ChAIR, to map chromatin accessibility, chromatin interactions and RNA expression simultaneously. After validating in cultured cells, we applied ChAIR to whole mouse brains and delineated the concerted dynamics of epigenome, three-dimensional (3D) genome and transcriptome during maturation and aging. In particular, gene-centric chromatin interactions and open chromatin states provided 3D epigenomic mechanism underlying cell-type-specific transcription and revealed spatially resolved specificity. Importantly, the composition of short-range and ultralong chromatin contacts in individual cells is remarkably correlated with transcriptional activity, open chromatin state and genome folding density. This genomic property, along with associated cellular properties, differs in neurons and non-neuronal cells across different anatomic regions throughout the lifespan, implying divergent nuclear mechano-genomic mechanisms at play in brain cells. Our results demonstrate ChAIR's robustness in revealing single-cell 3D epigenomic states of cell-type-specific transcription in complex tissues.

Transcription and epigenetic factor dynamics in neuronal activity-dependent gene regulation

Neuronal activity, including sensory-evoked and spontaneous firing, regulates the expression of a subset of genes known as activity-dependent genes. A key issue in this process is the activation and accumulation of transcription factors (TFs), which bind to cis-elements at specific enhancers and promoters, ultimately driving RNA synthesis through transcription machinery. Epigenetic factors such as histone modifiers also play a crucial role in facilitating the specific binding of TFs. Recent evidence from epigenome analyses and imaging studies have revealed intriguing mechanisms: the default chromatin structure at activity-dependent genes is formed independently of neuronal activity, while neuronal activity modulates spatiotemporal dynamics of TFs and their interactions with epigenetic factors (EFs). In this article we review new insights into activity-dependent gene regulation that affects brain development and plasticity.

Advances and applications in single-cell and spatial genomics

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.

Chimeric brain models: Unlocking insights into human neural development, aging, diseases, and cell therapies

Human-rodent chimeric brain models serve as a unique platform for investigating the pathophysiology of human cells within a living brain environment. These models are established by transplanting human tissue- or human pluripotent stem cell (hPSC)-derived macroglial, microglial, or neuronal lineage cells, as well as cerebral organoids, into the brains of host animals. This approach has opened new avenues for exploring human brain development, disease mechanisms, and regenerative processes. Here, we highlight recent advancements in using chimeric models to study human neural development, aging, and disease. Additionally, we explore the potential applications of these models for studying human glial cell-replacement therapies, studying in vivo human glial-to-neuron reprogramming, and harnessing single-cell omics and advanced functional assays to uncover detailed insights into human neurobiology. Finally, we discuss strategies to enhance the precision and translational relevance of these models, expanding their impact in stem cell and neuroscience research.

Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina

Most genetic risk variants linked to ocular diseases are non-protein coding and presumably contribute to disease through dysregulation of gene expression, however, deeper understanding of their mechanisms of action has been impeded by an incomplete annotation of the transcriptional regulatory elements across different retinal cell types. To address this knowledge gap, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome and 3D chromatin architecture in human retina, macula, and retinal pigment epithelium (RPE)/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 sub-classes of retinal cells. Comparative analysis of chromatin landscapes between human and mouse retina cells further revealed both evolutionarily conserved and divergent retinal gene-regulatory programs. Leveraging the rapid advancements in deep-learning techniques, we developed sequence-based predictors to interpret non-coding risk variants of retina diseases. Our study establishes retina-wide, single-cell transcriptome, epigenome, and 3D genome atlases, and provides a resource for studying the gene regulatory programs of the human retina and relevant diseases.

Human Body Single-Cell Atlas of 3D Genome Organization and DNA Methylation

Higher-order chromatin structure and DNA methylation are critical for gene regulation, but how these vary across the human body remains unclear. We performed multi-omic profiling of 3D genome structure and DNA methylation for 86,689 single nuclei across 16 human tissues, identifying 35 major and 206 cell subtypes. We revealed extensive changes in CG and non-CG methylation across almost all cell types and characterized 3D chromatin structure at an unprecedented cellular resolution. Intriguingly, extensive discrepancies exist between cell types delineated by DNA methylation and genome structure, indicating that the role of distinct epigenomic features in maintaining cell identity may vary by lineage. This study expands our understanding of the diversity of DNA methylation and chromatin structure and offers an extensive reference for exploring gene regulation in human health and disease.

Enhancing Single-Cell and Bulk Hi-C Data Using a Generative Transformer Model

The 3D organization of chromatin in the nucleus plays a critical role in regulating gene expression and maintaining cellular functions in eukaryotic cells. High-throughput chromosome conformation capture (Hi-C) and its derivative technologies have been developed to map genome-wide chromatin interactions at the population and single-cell levels. However, insufficient sequencing depth and high noise levels in bulk Hi-C data, particularly in single-cell Hi-C (scHi-C) data, result in low-resolution contact matrices, thereby limiting diverse downstream computational analyses in identifying complex chromosomal organizations. To address these challenges, we developed a transformer-based deep learning model, HiCENT, to impute and enhance both scHi-C and Hi-C contact matrices. Validation experiments on large-scale bulk Hi-C and scHi-C datasets demonstrated that HiCENT achieves superior enhancement effects compared to five popular methods. When applied to real Hi-C data from the GM12878 cell line, HiCENT effectively enhanced 3D structural features at the scales of topologically associated domains and chromosomal loops. Furthermore, when applied to scHi-C data from five human cell lines, it significantly improved clustering performance, outperforming five widely used methods. The adaptability of HiCENT across different datasets and its capacity to improve the quality of chromatin interaction data will facilitate diverse downstream computational analyses in 3D genome research, single-cell studies and other large-scale omics investigations.

Single-cell technology grows up: Leveraging high-resolution omics approaches to understand neurodevelopmental disorders

The identification of hundreds of neurodevelopmental disorder (NDD) genes in the last decade led to numerous genetic models for understanding NDD gene mutation consequences and delineating putative neurobiological mediators of disease. In parallel, single-cell and single-nucleus genomic technologies have been developed and implemented to create high-resolution atlases of cell composition, gene expression, and circuit connectivity in the brain. Here, we discuss the opportunities to leverage mutant models (or human tissue, where available) and genomics approaches to systematically define NDD etiology at cellular resolution. We review progress in applying single-cell and spatial transcriptomics to interrogate developmental trajectories, cellular composition, circuit activity, and connectivity across human tissue and NDD models. We discuss considerations for implementing these approaches at scale to maximize insights and facilitate reproducibility. Finally, we highlight how standardized application of these technologies promises to not only define etiologies of individual disorders but also identify molecular, cellular, and circuit level convergence across NDDs.

Epigenetic Impacts of Non-Coding Mutations Deciphered Through Pre-Trained DNA Language Model at Single-Cell Resolution

DNA methylation plays a critical role in gene regulation, affecting cellular differentiation and disease progression, particularly in non-coding regions. However, predicting the epigenetic consequences of non-coding mutations at single-cell resolution remains a challenge. Existing tools have limited prediction capacity and struggle to capture dynamic, cell-type-specific regulatory changes that are crucial for understanding disease mechanisms. Here, Methven, a deep learning framework designed is presented to predict the effects of non-coding mutations on DNA methylation at single-cell resolution. Methven integrates DNA sequence with single-cell ATAC-seq data and models SNP-CpG interactions over 100 kbp genomic distances. By using a divide-and-conquer approach, Methven accurately predicts both short- and long-range regulatory interactions and leverages the pre-trained DNA language model for enhanced precision in classification and regression tasks. Methven outperforms existing methods and demonstrates robust generalizability to monocyte datasets. Importantly, it identifies CpG sites associated with rheumatoid arthritis, revealing key pathways involved in immune regulation and disease progression. Methven's ability to detect progressive epigenetic changes provides crucial insights into gene regulation in complex diseases. These findings demonstrate Methven's potential as a powerful tool for basic research and clinical applications, advancing this understanding of non-coding mutations and their role in disease, while offering new opportunities for personalized medicine.

DNA methylation patterns are influenced by Pax3::Foxo1 expression and developmental lineage in rhabdomyosarcoma tumours forming in genetically engineered mouse models

Rhabdomyosarcoma (RMS) is a family of phenotypically myogenic paediatric cancers consisting of two major subtypes: fusion-positive (FP) RMS, most commonly involving the PAX3::FOXO1 fusion gene, formed by the fusion of paired box 3 (PAX3) and forkhead box O1 (FOXO1) genes, and fusion-negative (FN) RMS, lacking these gene fusions. In humans, DNA methylation patterns distinguish these two subtypes as well as mutation-associated subsets within these subtypes. To investigate the biological factors responsible for these methylation differences, we profiled DNA methylation in RMS tumours derived from genetically engineered mouse models (GEMMs) in which various driver mutations were introduced into different myogenic lineages. Our unsupervised analyses of DNA methylation patterns in these GEMM tumours yielded two major clusters, corresponding to high and no/low expression of Pax3::Foxo1, which mirrored the results for human FP and FN RMS tumours. Two distinct methylation-defined subsets were found for GEMM RMS tumours with no/low Pax3::Foxo1 expression: one subset enriched in Pax7 lineage tumours and a second subset enriched in myogenic factor 5 (Myf5) lineage tumours. Integrative analysis of DNA methylation and transcriptomic data in mouse and human RMS revealed a common group of differentially methylated and differentially expressed genes, highlighting a conserved set of genes functioning in both human RMS models and GEMMs of RMS. In conclusion, these studies provide insight into the roles of oncogenic fusion proteins and developmental lineages in establishing DNA methylation patterns in FP and FN RMS respectively. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Are we there yet? Exploring astrocyte heterogeneity one cell at a time

Astrocytes are a highly abundant cell type in the brain and spinal cord. Like neurons, astrocytes can be molecularly and functionally distinct to fulfill specialized roles. Recent technical advances in sequencing-based single cell assays have driven an explosion of omics data characterizing astrocytes in the healthy, aged, injured, and diseased central nervous system. In this review, we will discuss recent studies which have furthered our understanding of astrocyte biology and heterogeneity, as well as discuss the limitations and challenges of sequencing-based single cell and spatial genomics methods and their potential future utility.

Cell type-specific 3D-genome organization and transcription regulation in the brain

3D organization of the genome plays a critical role in regulating gene expression. How 3D-genome organization differs among different cell types and relates to cell type-dependent transcriptional regulation remains unclear. Here, we used genome-scale DNA and RNA imaging to investigate 3D-genome organization in transcriptionally distinct cell types in the mouse cerebral cortex. We uncovered a wide spectrum of differences in the nuclear architecture and 3D-genome organization among different cell types, ranging from the size of the cell nucleus to higher-order chromosome structures and radial positioning of chromatin loci within the nucleus. These cell type-dependent variations in nuclear architecture and chromatin organization exhibit strong correlations with both the total transcriptional activity of the cell and transcriptional regulation of cell type-specific marker genes. Moreover, we found that the methylated DNA binding protein MeCP2 promotes active-inactive chromatin segregation and regulates transcription in a nuclear radial position-dependent manner that is highly correlated with its function in modulating active-inactive chromatin compartmentalization.

Scalable Screening of Ternary-Code DNA Methylation Dynamics Associated with Human Traits

Epigenome-wide association studies (EWAS) are transforming our understanding of the interplay between epigenetics and complex human traits and phenotypes. We introduce the Methylation Screening Array (MSA), a new iteration of the Infinium technology for scalable and quantitative screening of trait associations of nuanced ternary-code cytosine modifications in larger, more inclusive, and stratified human populations. MSA integrates EWAS, single-cell, and cell-type-resolved methylome profiles, covering diverse human traits and diseases. Our first MSA applications yield multiple biological insights: we revealed a previously unappreciated role of 5-hydroxymethylcytosine (5hmC) in trait associations and epigenetic clocks. We demonstrated that 5hmCs complement 5-methylcytosines (5mCs) in defining tissues and cells' epigenetic identities. In-depth analyses highlighted the cell type context of EWAS and GWAS hits. Using this platform, we conducted a comprehensive human 5hmC aging EWAS, discovering tissue-invariant and tissue-specific aging dynamics, including distinct tissue-specific rates of mitotic hyper- and hypomethylation rates. These findings chart a landscape of the complex interplay of the two forms of cytosine modifications in diverse human tissues and their roles in health and disease.

Visualization of chromosomal reorganization induced by heterologous fusions in the mammalian nucleus

Chromosomes are spatially organized and functionally folded into a specific macro-structure in the nucleus. Recently, we and others created haploid cells with chromosome fusions. However, there is still lack of an effective strategy for precisely investigating how the genome copes with fusions. Here, we developed a down-sampling method to convert the populational Hi-C dataset into single cell-like Khimaira Matrix (K-matrix). K-matrix preserves not only the most prominent functional genomic features but also cell-to-cell variations. K-matrix-originated genome 3D models display spatial approach of fused chromosomes and minor global structure alterations. Combined with a layered positional decomposition analysis, our models indicate slight re-adjustment of chromosome distributions accordingly with an increasing tendency following more fusions involved. Nevertheless, the radial distribution of the A/B compartment is not affected dramatically. By contrast, natural populations harboring Rb fusions display significant alterations of chromosome radial location. Overall, K-matrix-originated models enable visualization of chromosomal reorganization with high resolution.

Comparative Genomics and Epigenomics of Transcriptional Regulation

Transcriptional regulation in response to diverse physiological cues involves complicated biological processes. Recent initiatives that leverage whole genome sequencing and annotation of regulatory elements significantly contribute to our understanding of transcriptional gene regulation. Advances in the data sets available for comparative genomics and epigenomics can identify evolutionarily constrained regulatory variants and shed light on noncoding elements that influence transcription in different tissues and developmental stages across species. Most epigenomic data, however, are generated from healthy subjects at specific developmental stages. To bridge the genotype-phenotype gap, future research should focus on generating multidimensional epigenomic data under diverse physiological conditions. Farm animal species offer advantages in terms of feasibility, cost, and experimental design for such integrative analyses in comparison to humans. Deep learning modeling and cutting-edge technologies in sequencing and functional screening and validation also provide great promise for better understanding transcriptional regulation in this dynamic field.

Droplet-based high-throughput 3D genome structure mapping of single cells with simultaneous transcriptomics

Single-cell three-dimensional (3D) genome techniques have advanced our understanding of cell-type-specific chromatin structures in complex tissues, yet current methodologies are limited in cell throughput. Here we introduce a high-throughput single-cell Hi-C (dscHi-C) approach and its transcriptome co-assay (dscHi-C-multiome) using droplet microfluidics. Using dscHi-C, we investigate chromatin structural changes during mouse brain aging by profiling 32,777 single cells across three developmental stages (3 months, 12 months, and 23 months), yielding a median of 78,220 unique contacts. Our results show that genes with significant structural changes are enriched in pathways related to metabolic process and morphology change in neurons, and innate immune response in glial cells, highlighting the role of 3D genome organization in physiological brain aging. Furthermore, our multi-omics joint assay, dscHi-C-multiome, enables precise cell type identification in the adult mouse brain and uncovers the intricate relationship between genome architecture and gene expression. Collectively, we developed the sensitive, high-throughput dscHi-C and its multi-omics derivative, dscHi-C-multiome, demonstrating their potential for large-scale cell atlas studies in development and disease.

Atlas-scale single-cell DNA methylation profiling with sciMETv3

Single-cell methods to assess DNA methylation have not achieved the same level of cell throughput per experiment compared to other modalities, with large-scale datasets requiring extensive automation, time, and other resources. Here, we describe sciMETv3, a combinatorial indexing-based technique that enables atlas-scale libraries to be produced in a single experiment. To reduce the sequencing burden, we demonstrate the compatibility of sciMETv3 with capture techniques to enrich regulatory regions, as well as the ability to leverage enzymatic conversion, which can yield higher library diversity. We showcase the throughput of sciMETv3 by producing a >140,000 cell library from human middle frontal gyrus split across four multiplexed individuals using both Illumina and Ultima sequencing instrumentation. Finally, we introduce sciMET+ATAC to enable high-throughput exploration of the interplay between chromatin accessibility and DNA methylation within the same cell.

The Fetal Environment and the Development of Hypertension-The Epigenetic Modification by Glucocorticoids

Intrauterine growth restriction (IUGR) is a risk factor for postnatal cardiovascular, metabolic, and psychiatric disorders. In most IUGR models, placental dysfunction that causes reduced 11β-hydroxysteroid dehydrogenase 2 (11βHSD2) activity, which degrades glucocorticoids (GCs) in the placenta, resulting in fetal GC overexposure. This overexposure to GCs continues to affect not only intrauterine fetal development itself, but also the metabolic status and neural activity in adulthood through epigenetic changes such as microRNA change, histone modification, and DNA methylation. We have shown that the IUGR model induced DNA hypomethylation in the paraventricular nucleus (PVN) in the brain, which in turn activates sympathetic activities, the renin-angiotensin system (RAS), contributing to the development of salt-sensitive hypertension. Even in adulthood, strong stress and/or exogenous steroids have been shown to induce epigenetic changes in the brain. Furthermore, DNA hypomethylation in the PVN is also observed in other hypertensive rat models, which suggests that it contributes significantly to the origins of elevated blood pressure. These findings suggest that if we can alter epigenetic changes in the brain, we can treat or prevent hypertension.

Cancer neuroscience and glioma: clinical implications

In recent years, it has been increasingly recognized that tumor growth relies not only on support from the surrounding microenvironment but also on the tumors capacity to adapt to - and actively manipulate - its niche. While targeting angiogenesis and modulating the local immune environment have been explored as therapeutic approaches, these strategies have yet to yield effective treatments for brain tumors and remain under refinement. More recently, the nervous system itself has been explored as a critical environmental support for cancer, with extensive neuro-tumoral interactions observed both intracranially and in extracranial sites containing neural components. In the brain, interactions between glioma cells as well as metastatic lesions with neural components have clinical implications for diagnostics, risk assessments, neurological sequelae, and the development of innovative therapeutics. Here, we review these neuro-tumoral dynamics, emphasizing aspects relevant to neurosurgical practice.

DNA Methylation in Alzheimer's Disease

To date, DNA methylation is the best characterized epigenetic modification in Alzheimer's disease. Involving the addition of a methyl group to the fifth carbon of the cytosine pyrimidine base, DNA methylation is generally thought to be associated with the silencing of gene expression. It has been hypothesized that epigenetics may mediate the interaction between genes and the environment in the manifestation of Alzheimer's disease, and therefore studies investigating DNA methylation could elucidate novel disease mechanisms. This chapter comprehensively reviews epigenomic studies, undertaken in human brain tissue and purified brain cell types, focusing on global methylation levels, candidate genes, epigenome wide approaches, and recent meta-analyses. We discuss key differentially methylated genes and pathways that have been highlighted to date, with a discussion on how new technologies and the integration of multiomic data may further advance the field.

Human-unique brain cell clusters are associated with learning disorders and human episodic memory activity

The advanced evolution of the human cerebral cortex forms the basis for our high-level cognitive functions. Through a comparative analysis of single-nucleus transcriptome data from the human neocortex and that of chimpanzees, macaques, and marmosets, we discovered 20 subgroups of cell types unique to the human brain, which include 11 types of excitatory neurons. Many of these human-unique cell clusters exhibit significant overexpression of genes regulated by human-specific enhancers. Notably, these specific cell clusters also express genes associated with disease risk, particularly those related to brain dysfunctions like learning disorders. Furthermore, genes linked to cortical thickness and human episodic memory encoding activities show heightened expression within these cell subgroups. These findings underscore the critical role of human brain-unique cell clusters in the evolution of human brain functions.

Basic Epigenetic Mechanisms

The human genome consists of 23 chromosome pairs (22 autosomes and one pair of sex chromosomes), with 46 chromosomes in a normal cell. In the interphase nucleus, the 2 m long nuclear DNA is assembled with proteins forming chromatin. The typical mammalian cell nucleus has a diameter between 5 and 15 μm in which the DNA is packaged into an assortment of chromatin assemblies. The human brain has over 3000 cell types, including neurons, glial cells, oligodendrocytes, microglial, and many others. Epigenetic processes are involved in directing the organization and function of the genome of each one of the 3000 brain cell types. We refer to epigenetics as the study of changes in gene function that do not involve changes in DNA sequence. These epigenetic processes include histone modifications, DNA modifications, nuclear RNA, and transcription factors. In the interphase nucleus, the nuclear DNA is organized into different structures that are permissive or a hindrance to gene expression. In this chapter, we will review the epigenetic mechanisms that give rise to cell type-specific gene expression patterns.

Accurate sample deconvolution of pooled snRNA-seq using sex-dependent gene expression patterns

Single nucleus RNA sequencing (snRNA-seq) technology offers unprecedented resolution for studying cell type-specific gene expression patterns. However, snRNA-seq poses high costs and technical limitations, often requiring the pooling of independent biological samples and loss of individual sample-level data. Deconvolution of sample identity using inherent features would enable the incorporation of pooled barcoding and sequencing protocols, thereby increasing data throughput and analytical sample size without requiring increases in experimental sample size and sequencing costs. In this study, we demonstrate a proof of concept that sex-dependent gene expression patterns can be leveraged for the deconvolution of pooled snRNA-seq data. Using previously published snRNA-seq data from the rat ventral tegmental area, we trained a range of machine learning models to classify cell sex using genes differentially expressed in cells from male and female rats. Models that used sex-dependent gene expression predicted cell sex with high accuracy (90-92%) and outperformed simple classification models using only sex chromosome gene expression (69-89%). The generalizability of these models to other brain regions was assessed using an additional published data set from the rat nucleus accumbens. Within this data set, model performance remained highly accurate in cell sex classification (89-90% accuracy) with no additional re-training. This work provides a model for future snRNA-seq studies to perform sample deconvolution using a two-sex pooled sample sequencing design and benchmarks the performance of various machine learning approaches to deconvolve sample identification from inherent sample features.

Isolation and Molecular Profiling of Nuclei of Specific Neuronal Types from Human Cerebral Cortex and Striatum

Most pathological conditions of the central nervous system do not affect all cell types to the same extent. Delineation of molecular events underlying disease symptoms, including genetic, epigenetic, and transcriptional changes, thus relies on the ability to characterize a specific cell type separately from others. We have developed a methodology for the collection of nuclear RNA and genomic DNA of specific cell types from frozen post-mortem striatum and cerebral cortex. This allows deep transcriptomic profiling of specific cell populations and characterization of their genomes and epigenetic properties. The method is based on the purification of cell nuclei, followed by fluorescence-activated sorting of nuclei (FANS) labeled with nucleic acid probes or antibodies binding to targets present in specific cell types. The protocol describes in detail the procedure for isolating and labeling neuronal and glial nuclei from human brain tissue, the steps that can be taken to extract RNA and genomic DNA, a way to combine the procedure with ATAC-seq to yield information about chromatin accessibility, as well as computational measures for assessing the quality of cell type-specific RNA-seq and ATAC-seq datasets. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Tissue homogenization, isolation of cell nuclei by ultracentrifugation and formaldehyde-fixation Basic Protocol 2: Antibody-based labeling and isolation of nuclei of specific neocortical neuron types Support Protocol 1: Generation of ATAC-seq libraries from the nuclei of specific neuron types of the cerebral cortex Basic Protocol 3: Nucleic acid hybridization-based labeling and isolation of nuclei of specific striatal projection neuron types Alternate Protocol 1: Labeling and isolation of nuclei of specific striatal interneuron types Support Protocol 2: Generation of ATAC-seq libraries from the nuclei of specific striatal neuron types Basic Protocol 4: Extraction of genomic DNA and nuclear RNA and preparation of sequencing libraries Basic Protocol 5: Processing and quality control of FANS-seq and ATAC-seq data.

Integrated multimodal cell atlas of Alzheimer's disease

Alzheimer's disease (AD) is the leading cause of dementia in older adults. Although AD progression is characterized by stereotyped accumulation of proteinopathies, the affected cellular populations remain understudied. Here we use multiomics, spatial genomics and reference atlases from the BRAIN Initiative to study middle temporal gyrus cell types in 84 donors with varying AD pathologies. This cohort includes 33 male donors and 51 female donors, with an average age at time of death of 88 years. We used quantitative neuropathology to place donors along a disease pseudoprogression score. Pseudoprogression analysis revealed two disease phases: an early phase with a slow increase in pathology, presence of inflammatory microglia, reactive astrocytes, loss of somatostatin+ inhibitory neurons, and a remyelination response by oligodendrocyte precursor cells; and a later phase with exponential increase in pathology, loss of excitatory neurons and Pvalb+ and Vip+ inhibitory neuron subtypes. These findings were replicated in other major AD studies.

Epigenetics and the timing of neuronal differentiation

Epigenetic regulation of the genome is required for cell-type differentiation during organismal development and is especially important to generate the panoply of specialized cell types that comprise the brain. Here, we review how progressive changes in the chromatin landscape, both in neural progenitors and in postmitotic neurons, orchestrate the timing of gene expression programs that underlie first neurogenesis and then functional neuronal maturation. We discuss how disease-associated mutations in chromatin regulators can change brain composition by impairing the timing of neurogenesis. Further, we highlight studies that are beginning to show how chromatin modifications are integrated at the level of chromatin architecture to coordinate changing transcriptional programs across developmental including in postmitotic neurons.

Multifaceted Role of Specialized Neuropeptide-Intensive Neurons on the Selective Vulnerability to Alzheimer's Disease in the Human Brain

Regarding Alzheimer's disease (AD), specific neuronal populations and brain regions exhibit selective vulnerability. Understanding the basis of this selective neuronal and regional vulnerability is essential to elucidate the molecular mechanisms underlying AD pathology. However, progress in this area is currently hindered by the incomplete understanding of the intricate functional and spatial diversity of neuronal subtypes in the human brain. Previous studies have demonstrated that neuronal subpopulations with high neuropeptide (NP) co-expression are disproportionately absent in the entorhinal cortex of AD brains at the single-cell level, and there is a significant decline in hippocampal NP expression in naturally aging human brains. Given the role of NPs in neuroprotection and the maintenance of microenvironments, we hypothesize that neurons expressing higher levels of NPs (HNP neurons) possess unique functional characteristics that predispose them to cellular abnormalities, which can manifest as degeneration in AD with aging. To test this hypothesis, multiscale and spatiotemporal transcriptome data from ~1900 human brain samples were analyzed using publicly available datasets. The results indicate that HNP neurons experienced greater metabolic burden and were more prone to protein misfolding. The observed decrease in neuronal abundance during stages associated with a higher risk of AD, coupled with the age-related decline in the expression of AD-associated neuropeptides (ADNPs), provides temporal evidence supporting the role of NPs in the progression of AD. Additionally, the localization of ADNP-producing HNP neurons in AD-associated brain regions provides neuroanatomical support for the concept that cellular/neuronal composition is a key factor in regional AD vulnerability. This study offers novel insights into the molecular and cellular basis of selective neuronal and regional vulnerability to AD in human brains.

Human Brain Ancestral Barcodes

Dynamic CpG methylation "barcodes" were read from 15,000 to 21,000 single cells from three human male brains. To overcome sparse sequencing coverage, the barcode had ~31,000 rapidly fluctuating X-chromosome CpG sites (fCpGs), with at least 500 covered sites per cell and at least 30 common sites between cell pairs (average of ~48). Barcodes appear to start methylated and record mitotic ages because excitatory neurons and glial cells that emerge later in development were less methylated. Barcodes are different between most cells, with average pairwise differences (PWDs) of ~0.5 between cells. About 10 cell pairs per million were more closely related with PWDs < 0.05. Barcodes appear to record ancestry and reconstruct trees where more related cells had similar phenotypes, albeit some pairs had phenotypic differences. Inhibitory neurons showed more evidence of tangential migration than excitatory neurons, with related cells in different cortical regions. fCpG barcodes become polymorphic during development and can distinguish between thousands of human cells.

Single-cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue

Human subcutaneous adipose tissue (SAT) contains a diverse array of cell-types; however, the epigenomic landscape among the SAT cell-types has remained elusive. Our integrative analysis of single-cell resolution DNA methylation and chromatin conformation profiles (snm3C-seq), coupled with matching RNA expression (snRNA-seq), systematically cataloged the epigenomic, 3D topology, and transcriptomic dynamics across the SAT cell-types. We discovered that the SAT CG methylation (mCG) landscape is characterized by pronounced hyper-methylation in myeloid cells and hypo-methylation in adipocytes and adipose stem and progenitor cells (ASPCs), driving nearly half of the 705,063 detected differentially methylated regions (DMRs). In addition to the enriched cell-type-specific transcription factor binding motifs, we identified TET1 and DNMT3A as plausible candidates for regulating cell-type level mCG profiles. Furthermore, we observed that global mCG profiles closely correspond to SAT lineage, which is also reflected in cell-type-specific chromosome compartmentalization. Adipocytes, in particular, display significantly more short-range chromosomal interactions, facilitating the formation of complex local 3D genomic structures that regulate downstream transcriptomic activity, including those associated with adipogenesis. Finally, we discovered that variants in cell-type level DMRs and A compartments significantly predict and are enriched for variance explained in abdominal obesity. Together, our multimodal study characterizes human SAT epigenomic landscape at the cell-type resolution and links partitioned polygenic risk of abdominal obesity to SAT epigenome.

Temporally distinct 3D multi-omic dynamics in the developing human brain

The human hippocampus and prefrontal cortex play critical roles in learning and cognition1,2, yet the dynamic molecular characteristics of their development remain enigmatic. Here we investigated the epigenomic and three-dimensional chromatin conformational reorganization during the development of the hippocampus and prefrontal cortex, using more than 53,000 joint single-nucleus profiles of chromatin conformation and DNA methylation generated by single-nucleus methyl-3C sequencing (snm3C-seq3)3. The remodelling of DNA methylation is temporally separated from chromatin conformation dynamics. Using single-cell profiling and multimodal single-molecule imaging approaches, we have found that short-range chromatin interactions are enriched in neurons, whereas long-range interactions are enriched in glial cells and non-brain tissues. We reconstructed the regulatory programs of cell-type development and differentiation, finding putatively causal common variants for schizophrenia strongly overlapping with chromatin loop-connected, cell-type-specific regulatory regions. Our data provide multimodal resources for studying gene regulatory dynamics in brain development and demonstrate that single-cell three-dimensional multi-omics is a powerful approach for dissecting neuropsychiatric risk loci.

ImputeHiFI: An Imputation Method for Multiplexed DNA FISH Data by Utilizing Single-Cell Hi-C and RNA FISH Data

Although multiplexed DNA fluorescence in situ hybridization (FISH) enables tracking the spatial localization of thousands of genomic loci using probes within individual cells, the high rates of undetected probes impede the depiction of 3D chromosome structures. Current data imputation methods neither utilize single-cell Hi-C data, which elucidate 3D genome architectures using sequencing nor leverage multimodal RNA FISH data that reflect cell-type information, limiting the effectiveness of these methods in complex tissues such as the mouse brain. To this end, a novel multiplexed DNA FISH imputation method named ImputeHiFI is proposed, which fully utilizes the complementary structural information from single-cell Hi-C data and the cell type signature from RNA FISH data to obtain a high-fidelity and complete spatial location of chromatin loci. ImputeHiFI enhances cell clustering, compartment identification, and cell subtype detection at the single-cell level in the mouse brain. ImputeHiFI improves the recognition of cell-type-specific loops in three high-resolution datasets. In short, ImputeHiFI is a powerful tool capable of imputing multiplexed DNA FISH data from various resolutions and imaging protocols, facilitating studies of 3D genome structures and functions.

The 3D Genome in Brain Development: An Exploration of Molecular Mechanisms and Experimental Methods

The human brain contains multiple cell types that are spatially organized into functionally distinct regions. The proper development of the brain requires complex gene regulation mechanisms in both neurons and the non-neuronal cell types that support neuronal function. Studies across the last decade have discovered that the 3D nuclear organization of the genome is instrumental in the regulation of gene expression in the diverse cell types of the brain. In this review, we describe the fundamental biochemical mechanisms that regulate the 3D genome, and comprehensively describe in vitro and ex vivo studies on mouse and human brain development that have characterized the roles of the 3D genome in gene regulation. We highlight the significance of the 3D genome in linking distal enhancers to their target promoters, which provides insights on the etiology of psychiatric and neurological disorders, as the genetic variants associated with these disorders are primarily located in noncoding regulatory regions. We also describe the molecular mechanisms that regulate chromatin folding and gene expression in neurons. Furthermore, we describe studies with an evolutionary perspective, which have investigated features that are conserved from mice to human, as well as human gained 3D chromatin features. Although most of the insights on disease and molecular mechanisms have been obtained from bulk 3C based experiments, we also highlight other approaches that have been developed recently, such as single cell 3C approaches, as well as non-3C based approaches. In our future perspectives, we highlight the gaps in our current knowledge and emphasize the need for 3D genome engineering and live cell imaging approaches to elucidate mechanisms and temporal dynamics of chromatin interactions, respectively.

The neuroscience of mental illness: Building toward the future

Mental illnesses arise from dysfunction in the brain. Although numerous extraneural factors influence these illnesses, ultimately, it is the science of the brain that will lead to novel therapies. Meanwhile, our understanding of this complex organ is incomplete, leading to the oft-repeated trope that neuroscience has yet to make significant contributions to the care of individuals with mental illnesses. This review seeks to counter this narrative, using specific examples of how neuroscientific advances have contributed to progress in mental health care in the past and how current achievements set the stage for further progress in the future.

Epigenetic and 3D genome reprogramming during the aging of human hippocampus

Age-related cognitive decline is associated with altered physiology of the hippocampus. While changes in gene expression have been observed in aging brain, the regulatory mechanisms underlying these changes remain underexplored. We generated single-nucleus gene expression, chromatin accessibility, DNA methylation, and 3D genome data from 40 human hippocampal tissues spanning adult lifespan. We observed a striking loss of astrocytes, OPC, and endothelial cells during aging, including astrocytes that play a role in regulating synapses. Microglia undergo a dramatic switch from a homeostatic state to a primed inflammatory state through DNA methylome and 3D genome reprogramming. Aged cells experience erosion of their 3D genome architecture. Our study identifies age-associated changes in cell types/states and gene regulatory features that provide insight into cognitive decline during human aging.

Emerging methods and applications in 3D genomics

Since the advent of Hi-C in 2009, a plethora of high-throughput sequencing methods have emerged to profile the three-dimensional (3D) organization of eukaryotic genomes, igniting the era of 3D genomics. In recent years, the genomic resolution achievable by these approaches has dramatically increased and several single-cell versions of Hi-C have been developed. Moreover, a new repertoire of tools not based on proximity ligation of digested chromatin has emerged, enabling the investigation of the higher-order organization of chromatin in the nucleus. In this review, we summarize the expanding portfolio of 3D genomic technologies, highlighting recent developments and applications from the past three years. Lastly, we present an outlook of where this technology-driven field might be headed.

Schizophrenia genomics: genetic complexity and functional insights

Determining the causes of schizophrenia has been a notoriously intractable problem, resistant to a multitude of investigative approaches over centuries. In recent decades, genomic studies have delivered hundreds of robust findings that implicate nearly 300 common genetic variants (via genome-wide association studies) and more than 20 rare variants (via whole-exome sequencing and copy number variant studies) as risk factors for schizophrenia. In parallel, functional genomic and neurobiological studies have provided exceptionally detailed information about the cellular composition of the brain and its interconnections in neurotypical individuals and, increasingly, in those with schizophrenia. Taken together, these results suggest unexpected complexity in the mechanisms that drive schizophrenia, pointing to the involvement of ensembles of genes (polygenicity) rather than single-gene causation. In this Review, we describe what we now know about the genetics of schizophrenia and consider the neurobiological implications of this information.

Aberrant proximal tubule DNA methylation underlies phenotypic changes related to kidney dysfunction in patients with diabetes

Epigenetic mechanisms are considered to contribute to diabetic nephropathy by maintaining memory of poor glycemic control during the early stages of diabetes. However, DNA methylation changes in the human kidney are poorly characterized, because of the lack of cell type-specific analysis. We examined DNA methylation in proximal tubules (PTs) purified from patients with diabetic nephropathy and identified differentially methylated CpG sites, given the critical role of proximal tubules in the kidney injury. Hypermethylation was observed at CpG sites annotated to genes responsible for proximal tubule functions, including gluconeogenesis, nicotinamide adenine dinucleotide synthesis, transporters of glucose, water, phosphate, and drugs, in diabetic kidneys, whereas genes involved in oxidative stress and the cytoskeleton exhibited demethylation. Methylation levels of CpG sites annotated to ACTN1, BCAR1, MYH9, UBE4B, AFMID, TRAF2, TXNIP, FOXO3, and HNF4A were correlated with the estimated glomerular filtration rate, whereas methylation of the CpG site in RUNX1 was associated with interstitial fibrosis and tubular atrophy. Hypermethylation of G6PC and HNF4A was accompanied by decreased expression in diabetic kidneys. Proximal tubule-specific hypomethylation of metabolic genes related to HNF4A observed in control kidneys was compromised in diabetic kidneys, suggesting a role for aberrant DNA methylation in the dedifferentiation process. Multiple genes with aberrant DNA methylation in diabetes overlapped genes with altered expressions in maladaptive proximal tubule cells, including transcription factors PPARA and RREB1. In conclusion, DNA methylation derangement in the proximal tubules of patients with diabetes may drive phenotypic changes, characterized by inflammatory and fibrotic features, along with impaired function in metabolism and transport.NEW & NOTEWORTHY Cell type-specific DNA methylation patterns in the human kidney are not known. We examined DNA methylation in proximal tubules of patients with diabetic nephropathy and revealed that oxidative stress, cytoskeleton, and metabolism genes were aberrantly methylated. The results indicate that aberrant DNA methylation in proximal tubules underlies kidney dysfunction in diabetic nephropathy. Aberrant methylation could be a target for reversing memory of poor glycemic control.

Cell-type-specific effects of age and sex on human cortical neurons

Altered transcriptional and epigenetic regulation of brain cell types may contribute to cognitive changes with advanced age. Using single-nucleus multi-omic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex from young adult and aged donors, we found widespread age- and sex-related variation in specific neuron types. The proportion of inhibitory SST- and VIP-expressing neurons was reduced in aged donors. Excitatory neurons had more profound age-related changes in their gene expression and DNA methylation than inhibitory cells. Hundreds of genes involved in synaptic activity, including EGR1, were less expressed in aged adults. Genes located in subtelomeric regions increased their expression with age and correlated with reduced telomere length. We further mapped cell-type-specific sex differences in gene expression and X-inactivation escape genes. Multi-omic single-nucleus epigenomes and transcriptomes provide new insight into the effects of age and sex on human neurons.

Decoding the Epigenetic Landscape: Insights into 5mC and 5hmC Patterns in Mouse Cortical Cell Types

The DNA modifications, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), represent powerful epigenetic regulators of temporal and spatial gene expression. Yet, how the cooperation of these genome-wide, epigenetic marks determine unique transcriptional signatures across different brain cell populations is unclear. Here we applied Nanopore sequencing of native DNA to obtain a complete, genome-wide, single-base resolution atlas of 5mC and 5hmC modifications in neurons, astrocytes and microglia in the mouse cortex (99% genome coverage, 40 million CpG sites). In tandem with RNA sequencing, analysis of 5mC and 5hmC patterns across cell types reveals astrocytes drive uniquely high brain 5hmC levels and support two decades of research regarding methylation patterns, gene expression and alternative splicing, benchmarking this resource. As such, we provide the most comprehensive DNA methylation data in mouse brain as an interactive, online tool (NAM-Me, https://olsenlab.shinyapps.io/NAMME/) to serve as a resource dataset for those interested in the methylome landscape.

Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.

BAllC and BAllCools: efficient formatting and operating for single-cell DNA methylation data

MOTIVATION

With single-cell DNA methylation studies yielding vast datasets, existing data formats struggle with the unique challenges of storage and efficient operations, highlighting a need for improved solutions.

RESULTS

BAllC (Binary All Cytosines) emerges as a tailored format for methylation data, addressing these challenges. BAllCools, its complementary software toolkit, enhances parsing, indexing, and querying capabilities, promising superior operational speeds and reduced storage needs.

AVAILABILITY AND IMPLEMENTATION

https://github.com/jksr/ballcools.

Extensive long-range polycomb interactions and weak compartmentalization are hallmarks of human neuronal 3D genome

Chromatin architecture regulates gene expression and shapes cellular identity, particularly in neuronal cells. Specifically, polycomb group (PcG) proteins enable establishment and maintenance of neuronal cell type by reorganizing chromatin into repressive domains that limit the expression of fate-determining genes and sustain distinct gene expression patterns in neurons. Here, we map the 3D genome architecture in neuronal and non-neuronal cells isolated from the Wernicke's area of four human brains and comprehensively analyze neuron-specific aspects of chromatin organization. We find that genome segregation into active and inactive compartments is greatly reduced in neurons compared to other brain cells. Furthermore, neuronal Hi-C maps reveal strong long-range interactions, forming a specific network of PcG-mediated contacts in neurons that is nearly absent in other brain cells. These interacting loci contain developmental transcription factors with repressed expression in neurons and other mature brain cells. But only in neurons, they are rich in bivalent promoters occupied by H3K4me3 histone modification together with H3K27me3, which points to a possible functional role of PcG contacts in neurons. Importantly, other layers of chromatin organization also exhibit a distinct structure in neurons, characterized by an increase in short-range interactions and a decrease in long-range ones.

Basic Science in Movement Disorders: Fueling the Engine of Translation into Clinical Practice

Basic Science is crucial for the advancement of clinical care for Movement Disorders. Here, we provide brief updates on how basic science is important for understanding disease mechanisms, disease prevention, disease diagnosis, development of novel therapies and to establish the basis for personalized medicine. We conclude the viewpoint by a call to action to further improve interactions between clinician and basic scientists. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Single-cell mapping of cell-type specific chromatin architecture in the central nervous system

Determining how chromatin is structured in the nucleus is critical to studying its role in gene regulation. Recent advances in the analysis of single-cell chromatin architecture have considerably improved our understanding of cell-type-specific chromosome conformation and nuclear architecture. In this review, we discuss the methods used for analysis of 3D chromatin conformation, including sequencing-based methods, imaging-based techniques, and computational approaches. We further review the application of these methods in the study of the role of chromatin topology in neural development and disorders.