The mechanisms regulating transcriptional changes during brain aging remain poorly understood. Here, we use single-cell epigenomics to profile chromatin accessibility and gene expression across eight mouse brain regions at 2, 9, and 18 months of age. In addition to a marked decline in progenitor populations involved in neurogenesis and myelination, we observe widespread and concordant age-associated changes in transcription and chromatin accessibility across both neuronal and glial cell types. These alterations are accompanied by dysregulation of master transcription factors and a shift toward stress-response programs driven by activator protein 1 (AP-1), indicating progressive drift in cellular identity with aging. We further identify region- and cell-type-specific heterochromatin loss, characterized by increased accessibility at H3K9me3-marked domains, activation of transposable elements, and upregulation of long noncoding RNAs, particularly in glutamatergic neurons. Together, these findings reveal age-related disruption of heterochromatin maintenance and transcriptional regulation, highlighting vulnerable brain regions, cell types, and molecular pathways in brain aging.

Abscisic acid (ABA) is a plant hormone that mediates abiotic stress tolerance and regulates growth and development. ABA binds to members of the PYL/RCAR ABA receptor family that initiate signal transduction inhibiting type 2C protein phosphatases. Although crosstalk between ABA and the hormone Jasmonic Acid (JA) has been shown, the molecular entities that mediate this interaction have yet to be fully elucidated. We report a link between ABA and JA signaling through a direct interaction of the ABA receptor PYL6 (RCAR9) with the basic helix-loop-helix transcription factor MYC2. PYL6 and MYC2 interact in yeast two hybrid assays and the interaction is enhanced in the presence of ABA. PYL6 and MYC2 interact in planta based on bimolecular fluorescence complementation and co-immunoprecipitation of the proteins. Furthermore, PYL6 was able to modify transcription driven by MYC2 using JAZ6 and JAZ8 DNA promoter elements in yeast one hybrid assays. Finally, pyl6 T-DNA mutant plants show an increased sensitivity to the addition of JA along with ABA in cotyledon expansion experiments. Overall, the present study identifies a direct mechanism for transcriptional modulation mediated by an ABA receptor different from the core ABA signaling pathway, and a putative mechanistic link connecting ABA and JA signaling pathways.

Most genetic risk variants linked to ocular diseases are nonprotein coding and presumably contribute to disease through dysregulation of gene expression; however, understanding their mechanisms has been impeded by incomplete annotation of transcriptional regulatory elements across retinal cell types. To address this, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome, and three-dimensional (3D) chromatin architecture in human retina, macula, and retinal pigment epithelium/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 retinal cell types. Comparative analysis of chromatin landscapes between human and mouse retina cells further revealed both evolutionarily conserved and divergent retinal gene-regulatory programs. Leveraging the advancements in deep-learning techniques, we developed sequence-based predictors to interpret noncoding risk variants of retinal 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 ocular diseases.

Elevated levels of maternal pro-inflammatory cytokines following severe infection during gestation can disrupt offspring neural development and increase the risk of neurodevelopmental disorders. The viral mimetic Poly(I:C) reproduces the effects of gestational influenza exposure, leading to behavioral outcomes that recapitulate neurodevelopmental disorder phenotypes. Although Poly(I:C)-induced maternal immune activation (PIC-MIA) alters the epigenome, behavior and cognition of offspring in adulthood, it remains unclear when these changes occur and how MIA influences the epigenomic regulatory programming across the transition from embryonic development to the mature brain. Here, we examined the effects of PIC-MIA on the epigenomic maturation of the frontal cortex, focusing on excitatory neuron-specific DNA methylation and transcriptomic dynamics throughout perinatal development. Mid-gestation PIC-MIA disrupted development of the excitatory neuron transcriptome, with the largest alterations observed at birth. PIC-MIA altered the development of the mature DNA methylation program of excitatory neurons at thousands of genomic regulatory regions that normally gain or lose methylation during development. Transcription factor binding site analyses of these differentially methylated regions revealed a significant enrichment of Tbr1 motifs within hyper-methylated deep-layer neuron-specific regions at birth. Notably, transcriptional targets of Tbr1 were down-regulated at birth despite up-regulation of Tbr1 transcription, suggesting PIC-MIA uncouples Tbr1 expression from its regulatory function in deep-layer neurons. Electrophysiological recordings of intrinsic and firing properties further confirmed a lasting disruption in deep-layer neuronal activity. Our results suggest that mid-gestation MIA may alter the development of deep-layer neurons through an epigenomic blockade of Tbr1 function, thereby perturbing normal cortical circuit formation.

Arabidopsis has been pivotal in uncovering fundamental principles of plant biology, yet a comprehensive, high-resolution understanding of its cellular identities throughout the entire life cycle remains incomplete. Here we present a single-nucleus and spatial transcriptomic atlas spanning ten developmental stages, encompassing over 400,000 nuclei from all organ systems and tissues-from seeds to developing siliques. Leveraging paired single-nucleus and spatial transcriptomic datasets, we annotate 75% of identified cell clusters, revealing striking molecular diversity in cell types and states across development. Our integrated approach identified conserved transcriptional signatures among recurrent cell types, organ-specific heterogeneity and previously uncharacterized cell-type-specific markers validated spatially. Moreover, we uncover dynamic transcriptional programs governing secondary metabolite production and differential growth patterns, exemplified by detailed spatial profiling of the compact yet complex apical hook structure; this profiling revealed transient cellular states linked to developmental progression and hormonal regulation, highlighting the hidden complexity underlying plant morphogenesis. Functional validation of genes uniquely expressed within specific cell contexts confirmed their essential developmental roles, underscoring the predictive power of our atlas. Collectively, this comprehensive resource provides an invaluable foundation for exploring cellular differentiation, environmental responses and genetic perturbations at high resolution, advancing our understanding of plant biology.

Leaf development is dynamic, adapting to environmental stress to optimize resource use. For example, in response to drought, Arabidopsis restricts leaf growth to enhance water use efficiency. While this plastic response is well described at the physiological level, the underlying transcriptional changes that facilitate adjustments in leaf development in response to stress remain poorly described. By constructing a ~1 million single-nuclei transcriptome atlas, we demonstrate that drought stress limits leaf growth by advancing transcriptional responses related to maturation and aging. Notably, we find that these transcriptional changes scale with environmental stress, and help explain how shoot size can decline proportionally with stress intensity. Leveraging these insights, we increased leaf growth under stress by cell-type targeted upregulation of FERRIC REDUCTION OXIDASE 6 in the mesophyll. ### Competing Interest Statement J.S. is a co-founder of Crop Diagnostix, a company that provides sequencing services. The remaining authors declare no competing interests.

Astrocytes shape synapses and circuits, yet human basal ganglia astrocyte diversity is incompletely defined. We built a multimodal atlas by integrating single-nucleus RNA-sequencing and chromatin accessibility with DNA methylation, 3D chromatin conformation, and spatial transcriptomics, then mapped basal ganglia programs onto a whole-brain reference. Astrocytes segregated into three anatomical subgroups spanning striatal gray matter, extra-striatal gray matter, and white matter, with subgroup-biased neurotransmitter transporters and synapse-associated programs consistent with differences in dominant afferent input. Within striatum, dorsal and ventral astrocyte populations aligned with distinct microcircuits and were conserved in nonhuman primates. A deep learning sequence model identified subgroup-associated enhancer code and, when benchmarked against published enhancer-AAV datasets, supported the design of candidate viral tools to target basal ganglia astrocyte programs in vivo. Together, these data define major axes of human astrocyte specialization and provide a framework for cell type-specific dissection of basal ganglia function. ### Competing Interest Statement The authors have declared no competing interest. National Institutes of Health, https://ror.org/01cwqze88, UM1MH130981 Research Foundation Flanders (FWO) PhD fellowship, 1SH6J24N & V428025N

Pathogen and chemical exposures lead to profound remodeling of the gene-regulatory landscape across human immune cell populations. Here, we present a single-nucleus chromatin accessibility atlas of human immune cells of individuals exposed to HIV-1, COVID-19, Influenza virus, organophosphates as well as healthy controls that provides insights into gene regulation driven by these cell-extrinsic stimuli. This atlas comprises 271,299 cells and 319,420 candidate regulatory elements that exhibit dynamic accessibility associated with gene expression across immune cell states. Our longitudinal HIV cohort reveals epigenetic signatures of T cell exhaustion, manifested in changes in the accessibility of binding sites for the FOXP family transcription factors. We further identified changes in the accessibility of candidate regulatory elements in CD14 monocytes upon SARS-CoV-2 exposure that are associated with a switch in NF-κB to AP-1-based regulation of cytokine networks. By integrating single-cell profiles of DNA methylation from matched samples we created a multimodal epigenome atlas of human immune cells across exposure states using the accessibility-derived candidate regulatory elements. Both modalities exhibit complementary epigenetic signatures at transcription factor binding sites associated with cell state, as exemplified in the process of memory formation in T-cells. Finally, by linking potentially regulatory DNA methylation signatures to changes in chromatin accessibility in monocytes, we identify AP1 motifs exhibiting epigenetic dynamics, indicating selective remodeling in TF networks in severe cases of COVID-19.

Exercise and diet are direct physical contributors to human health, wellness, resilience, and performance[1][1]–[5][2]. Endurance and resistance training are known to improve healthspan through various biological processes such as mitochondrial function[6][3]–[8][4], telomere maintenance[9][5], and inflammaging[10][6]. Although several training prescriptions have been defined with specific merits [1][1],[10][6]–[20][7], the long-term effects of these in terms of their molecular alterations have not yet been well explored. In this study, we focus on two combined endurance and resistance training programs: (1) traditional moderate-intensity continuous endurance and resistance exercise (TRAD) and (2) a variation of high-intensity interval training (HIIT) we refer to as high intensity tactical training (HITT), to assess the dynamics of DNA methylation (DNAm) in blood and muscle derived from males (N=23) and females (N=31), over a 12-week period of training followed by a 4-week period of detraining, sampled at pre-exercise and acute time points, totaling 528 samples. Due to its rapid responsiveness to stimuli and its stability, DNAm has been known to facilitate regulatory cascades that significantly affect various physiological processes and pathways. We find that several thousand differentially methylated regions (DMRs) associated with acute exercise in blood, many of which are shared across males and females. This trend is reversed when comparing the baseline (pre-exercise) time points or post-exercise timepoints at the untrained state with those at the post-conditioned state. Here, muscle shows majority of DNAm changes, with most of those being unique. We also find several hundred “memory” DMRs in muscle that maintain the gain or loss of methylation after four weeks of inactivity. Comparing phenotypic measurements, we find specific DMRs that correlate significantly with mitochondrial function and myofiber switching. Using machine learning, we select a subset of DMRs that are most characteristic of training modalities, sex and timepoint. Most of the DMRs are enriched in pathways associated with immune function, cell differentiation, and exercise adaptation. These findings reveal mechanisms by which exercise- and training-induced epigenetic changes alter immune surveillance, mitochondrial function, and inflammatory response, and underscore the relevance of epigenetic plasticity to health monitoring and wellness. ### Competing Interest Statement J.R.E. serves on the scientific advisory board of Zymo Research Inc. U. S. Department of Defense through the Office of Naval Research (ONR), , N000141613159 National Human Genome Research Institute (NHGRI) of National Institutes of Health (NIH), , HG010634 [1]: #ref-1 [2]: #ref-5 [3]: #ref-6 [4]: #ref-8 [5]: #ref-9 [6]: #ref-10 [7]: #ref-20

The periderm provides a protective barrier in many seed plant species. The development of the suberized phellem, which forms the outermost layer of this important tissue, has become a trait of interest for enhancing both plant resilience to stresses and plant-mediated CO2 sequestration in soils. Despite its importance, very few genes driving phellem development are known. Employing single-nuclei sequencing, we have generated an expression census capturing the complete developmental progression of Arabidopsis root phellem cells, from their progenitor cell type, the pericycle, through to their maturation. With this, we identify a whole suite of genes underlying this process, including MYB67, which we show has a role in phellem cell maturation. Our expression census and functional discoveries represent a resource, expanding our comprehension of secondary growth in plants. These data can be used to fuel discoveries and engineering efforts relevant to plant resilience and climate change.

Identifying cell-type-specific enhancers is critical for developing genetic tools to study the mammalian brain. We organized the "Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Species Multi-Omics" to evaluate machine learning and feature-based methods for nominating enhancer sequences targeting mouse cortical cell types. Methods were assessed using in vivo data from hundreds of adeno-associated virus (AAV)-packaged, retro-orbitally delivered enhancers. Open chromatin was the strongest predictor of functional enhancers, while sequence models improved prediction of non-functional enhancers and identified cell-type-specific transcription factor codes to inform in silico enhancer design. This challenge establishes a benchmark for enhancer prioritization and highlights computational and molecular features critical for identifying functional cortical enhancers, advancing efforts to map and manipulate gene regulation in the mammalian cortex.

Aging is a major risk factor for neurodegenerative diseases, yet underlying epigenetic mechanisms remain unclear. Here, we generated a comprehensive single-nucleus cell atlas of brain aging across multiple brain regions, comprising 132,551 single-cell methylomes and 72,666 joint chromatin conformation-methylome nuclei. Integration with companion transcriptomic and chromatin accessibility data yielded a cross-modality taxonomy of 36 major cell types. We observed that age-related methylation changes were more pronounced in non-neuronal cells. Transposable element methylation alone distinguished age groups, showing cell-type-specific genome-wide demethylation. Chromatin conformation analysis demonstrated age-related increases in TAD boundary strength with enhanced accessibility at CTCF binding sites. Spatial transcriptomics across 895,296 cells revealed regional heterogeneity during aging within identical cell types. Finally, we developed novel deep-learning models that accurately predict age-related gene expression changes using multi-modal epigenetic features, providing mechanistic insights into gene regulation. This dataset advances our understanding of brain aging and offers potential translational applications. Highlights ### Competing Interest Statement J.R.E. is a scientific adviser for Zymo Research Inc., Ionis Pharmaceuticals, and Guardant Health. B.R. is a cofounder and consultant for Arima Genomics Inc. and cofounder of Epigenome Technologies.

Polygenic risk scores (PRSs) predict an individual’s genetic risk for complex diseases, yet their utility in elucidating disease biology remains limited. We introduce scPRS, a graph neural network-based framework that computes single-cell-resolved PRSs by integrating reference single-cell chromatin accessibility profiles. scPRS outperforms traditional PRS approaches in genetic risk prediction, as demonstrated across multiple diseases including type 2 diabetes, hypertrophic cardiomyopathy, Alzheimer disease and severe COVID-19. Beyond risk prediction, scPRS prioritizes disease-critical cells and, when combined with a layered multiomic analysis, links risk variants to gene regulation in a cell-type-specific manner. Applied to these diseases, scPRS fine-maps causal cell types and cell-type-specific variants and genes, demonstrating its ability to bridge genetic risk with cell-specific biology. scPRS provides a unified framework for genetic risk prediction and mechanistic dissection of complex diseases, laying a methodological foundation for single-cell genetics.

Somatic mutations alter the genomes of a subset of an individual's brain cells, impacting gene regulation and contributing to disease processes. Mosaic single-nucleotide variants have been characterized with single-cell resolution in the brain, but we have limited information about large-scale structural variation such as whole-chromosome duplication or loss. We used a dataset of over 415,000 single-cell DNA methylation and chromatin conformation profiles from the adult mouse brain to comprehensively identify and characterize aneuploid cells. Somatic trisomy events were strongly enriched on chromosome 16, which is syntenic with human chromosome 21. We also observed a specific enrichment of chromosome gain and loss events in specific cell types, including Pons neurons and oligodendrocyte precursor cells. Chromosome 16 trisomy occurred in multiple cell types and across brain regions, suggesting that nondisjunction is a recurrent feature of somatic structural variation in the brain.

Plants lack specialized and mobile immune cells. Consequently, any cell type that encounters pathogens must mount immune responses and communicate with surrounding cells for successful defence. However, the diversity, spatial organization and function of cellular immune states in pathogen-infected plants are poorly understood1. Here we infect Arabidopsis thaliana leaves with bacterial pathogens that trigger or supress immune responses and integrate time-resolved single-cell transcriptomic, epigenomic and spatial transcriptomic data to identify cell states. We describe cell-state-specific gene-regulatory logic that involves transcription factors, putative cis-regulatory elements and target genes associated with disease and immunity. We show that a rare cell population emerges at the nexus of immune-active hotspots, which we designate as primary immune responder (PRIMER) cells. PRIMER cells have non-canonical immune signatures, exemplified by the expression and genome accessibility of a previously uncharacterized transcription factor, GT-3A, which contributes to plant immunity against bacterial pathogens. PRIMER cells are surrounded by another cell state (bystander) that activates genes for long-distance cell-to-cell immune signalling. Together, our findings suggest that interactions between these cell states propagate immune responses across the leaf. Our molecularly defined single-cell spatiotemporal atlas provides functional and regulatory insights into immune cell states in plants.

Variations in DNA methylation patterns in human tissues have been linked to various environmental exposures and infections. Here, we identified the DNA methylation signatures associated with multiple exposures in nine major immune cell types derived from peripheral blood mononuclear cells (PBMCs) at single-cell resolution. We performed methylome sequencing on 111,180 immune cells obtained from 112 individuals who were exposed to different viruses, bacteria, or chemicals. Our analysis revealed 790,662 differentially methylated regions (DMRs) associated with these exposures, which are mostly individual CpG sites. Additionally, we integrated methylation and ATAC-seq data from same samples and found strong correlations between the two modalities. However, the epigenomic remodeling in these two modalities are complementary. Finally, we identified the minimum set of DMRs that can predict exposures. Overall, our study provides the first comprehensive dataset of single immune cell methylation profiles, along with unique methylation biomarkers for various biological and chemical exposures.

All organisms experience stress as an inevitable part of life, from single-celled microorganisms to complex multicellular beings. The ability to recover from stress is a fundamental trait that determines the overall resilience of an organism, yet stress recovery is understudied. To investigate how plants recover from drought, we examine a fine-scale time series of RNA sequencing starting 15 min after rehydration following moderate drought. We reveal that drought recovery is a rapid process involving the activation of thousands of recovery-specific genes. To capture these rapid recovery responses in different Arabidopsis thaliana (A. thaliana) leaf cell types, we perform a single-nucleus transcriptome analysis at the onset of drought recovery, identifying a cell type-specific transcriptional state developing independently across cell types. To further validate the cell-type specific transcriptional changes observed during drought recovery, we employ spatial transcriptomics using multiplexed error-robust fluorescence in situ hybridization (MERFISH), revealing anatomical localization of recovery-induced gene expression programs across Arabidopsis leaf tissues. Furthermore, we reveal a recovery-induced activation of the immune system that occurs autonomously, and which enhances pathogen resistance in vivo in A. thaliana, wild tomato (Solanum pennellii) and domesticated tomato (Solanum lycopersicum cv. M82). Since rehydration promotes microbial proliferation and thereby increases the risk of infection, the activation of drought recovery-induced immunity may be crucial for plant survival in natural environments. These findings indicate that drought recovery coincides with a preventive defense response, unraveling the complex regulatory mechanisms that facilitate stress recovery in different plant cell types.

Single-cell genomics permits a new resolution in the examination of molecular and cellular dynamics, allowing global, parallel assessments of cell types and cellular behaviors through development and in response to environmental circumstances, such as interaction with water and the light-dark cycle of the Earth. Here, we leverage the smallest, and possibly most structurally reduced, plant, the semiaquatic Wolffia australiana, to understand dynamics of cell expression in these contexts at the whole-plant level. We examined single-cell-resolution RNA-sequencing data and found Wolffia cells divide into four principal clusters representing the above- and below-water-situated parenchyma and epidermis. Although these tissues share transcriptomic similarity with model plants, they display distinct adaptations that Wolffia has made for the aquatic environment. Within this broad classification, discrete subspecializations are evident, with select cells showing unique transcriptomic signatures associated with developmental maturation and specialized physiologies. Assessing this simplified biological system temporally at two key time-of-day (TOD) transitions, we identify additional TOD-responsive genes previously overlooked in whole-plant transcriptomic approaches and demonstrate that the core circadian clock machinery and its downstream responses can vary in cell-specific manners, even in this simplified system. Distinctions between cell types and their responses to submergence and/or TOD are driven by expression changes of unexpectedly few genes, characterizing Wolffia as a highly streamlined organism with the majority of genes dedicated to fundamental cellular processes. Wolffia provides a unique opportunity to apply reductionist biology to elucidate signaling functions at the organismal level, for which this work provides a powerful resource.

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. Using a single-nucleus multi-omics approach, a study jointly profiles the reorganization of the epigenome and the three-dimensional chromatin conformation during the development of the human hippocampus and prefrontal cortex.

DNA methylation (DNAm), a crucial epigenetic mark, plays a key role in gene regulation, mammalian development, and various human diseases. Single-cell technologies enable the profiling of DNAm states at cytosines within the DNA sequence of individual cells, but they often suffer from limited coverage of CpG sites. In this study, we introduce scMeFormer, a transformer-based deep learning model designed to impute DNAm states for each CpG site in single cells. Through comprehensive evaluations, we demonstrate the superior performance of scMeFormer compared to alternative models across four single-nucleus DNAm datasets generated by distinct technologies. Remarkably, scMeFormer exhibits high-fidelity imputation, even when dealing with significantly reduced coverage, as low as 10% of the original CpG sites. Furthermore, we applied scMeFormer to a single-nucleus DNAm dataset generated from the prefrontal cortex of four schizophrenia patients and four neurotypical controls. This enabled the identification of thousands of differentially methylated regions associated with schizophrenia that would have remained undetectable without imputation and added granularity to our understanding of epigenetic alterations in schizophrenia within specific cell types. Our study highlights the power of deep learning in imputing DNAm states in single cells, and we expect scMeFormer to be a valuable tool for single-cell DNAm studies.