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PubMed2026

Spatial biology reveals altered macrophage states in immunosuppressed non-melanoma skin cancer.

Immunosuppressed patients with non-melanoma skin cancer experience worse clinical outcomes, yet the tumor immune microenvironment associated with systemic immunosuppression remains incompletely defined. Using integrated single-cell, spatial transcriptomic, multiplex immunofluorescence, and spatial epigenomic profiling across immunocompetent and immunosuppressed tumors, we found that overall immune-cell composition was largely preserved despite differences in immune-cell distribution, spatial organization, and T cell clonality. Immunosuppressed tumors demonstrated reduced intratumoral macrophage densities, decreased T cell clonal diversity, altered antigen-presenting cell and T cell spatial interactions, and distinct fibroblast- and macrophage-associated spatial niches. Multi-cohort validation across complementary spatial and single-cell platforms identified consistent alterations in innate-adaptive immune organization in immunosuppressed tumors. Together, these findings define spatial and functional remodeling of the tumor immune microenvironment under systemic immunosuppression and provide a framework for future therapeutic investigation in high-risk patients.

Humans↗
PubMed2026

Multi-omics approaches in idiopathic pulmonary fibrosis: from molecular mechanisms to therapeutic targets and precision medicine.

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with limited therapeutic options and marked molecular heterogeneity. Despite available antifibrotic therapies, disease progression remains poorly predictable, highlighting the need for improved mechanistic understanding and therapeutic targeting. This review summarizes recent advances in multi-omics research to elucidate the molecular mechanisms underlying IPF and to identify potential biomarkers and pharmacological targets. Multi-omics studies, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiome profiling, and single-cell sequencing, have revealed key pathogenic mechanisms in IPF. Genetic susceptibility factors such as MUC5B promoter variants and telomere-related genes contribute to disease risk. Epigenetic regulation, including DNA methylation, histone modifications, and non-coding RNAs, plays a central role in fibrotic remodeling. Transcriptomic and proteomic analyses have identified dysregulated signaling pathways, including TGF-β, mTOR, cellular senescence, and extracellular matrix remodeling. Metabolomic alterations indicate disrupted lipid and amino acid metabolism. Importantly, integration of multi-omics datasets enables the identification of molecular endotypes, candidate biomarkers, and potential therapeutic targets. However, challenges including data integration, tissue heterogeneity, limited cohort size, and the need for functional validation remain important barriers to clinical translation. Continued development of multi-omics approaches may facilitate more accurate disease classification and support the development of personalized therapeutic strategies for IPF.

biomarkers↗
PubMed2025

Using Callus as an Ex Vivo System for Chromatin Analysis.

Next-generation sequencing has revolutionized epigenetics research, enabling a comprehensive analysis of DNA methylation and histone modification profiles to explore complex biological systems at unprecedented depth. Deciphering the intricate epigenetic mechanisms that regulate gene activity presents significant challenges, including the issue of analyzing heterogeneous cell populations in bulk. Bulk analysis introduces bias and can obscure crucial information by averaging readouts from distinct cells. Various approaches have been developed to address this issue, such as cell-type-specific enrichment or single-cell sequencing techniques. However, the need for transgenic lines with fluorescent markers, along with technical challenges such as efficient protoplast isolation and low yield, limits their widespread adoption and use in multi-omic studies. This review discusses the pros and cons of these approaches, providing a valuable basis for selecting the most suitable strategy to minimize heterogeneity. We will also highlight the use of cotyledon-derived callus as an ex vivo system as a simple, accessible, and robust platform for enabling high-throughput multi-omic analyses.

Chromatin↗
PubMed2024

A time-resolved single-cell roadmap of the logic driving anterior neural crest diversification from neural border to migration stages.

Neural crest cells exemplify cellular diversification from a multipotent progenitor population. However, the full sequence of early molecular choices orchestrating the emergence of neural crest heterogeneity from the embryonic ectoderm remains elusive. Gene-regulatory-networks (GRN) govern early development and cell specification toward definitive neural crest. Here, we combine ultradense single-cell transcriptomes with machine-learning and large-scale transcriptomic and epigenomic experimental validation of selected trajectories, to provide the general principles and highlight specific features of the GRN underlying neural crest fate diversification from induction to early migration stages using Xenopus frog embryos as a model. During gastrulation, a transient neural border zone state precedes the choice between neural crest and placodes which includes multiple converging gene programs. During neurulation, transcription factor connectome, and bifurcation analyses demonstrate the early emergence of neural crest fates at the neural plate stage, alongside an unbiased multipotent-like lineage persisting until epithelial-mesenchymal transition stage. We also decipher circuits driving cranial and vagal neural crest formation and provide a broadly applicable high-throughput validation strategy for investigating single-cell transcriptomes in vertebrate GRNs in development, evolution, and disease.

Animals↗
PubMed2026

Multiomics approaches to cardiovascular disease: technological innovations and clinical translation.

Cardiovascular diseases (CVDs) remain the leading cause of global morbidity and mortality, reflecting a persistent gap between clinical phenotyping and the molecular mechanisms that govern disease initiation, progression, and interindividual variability. Recent advances in emerging technologies have fundamentally reshaped cardiovascular physiology by enabling high-resolution, cross-layer profiling of the heart and vasculature across genomic, epigenomic, transcriptomic, proteomic, metabolomic, lipidomic, glycomic, and fluxomic layers, increasingly at single-cell and spatial resolution. These approaches reveal CVD as a coordinated, multilayered process driven by dynamic interactions among cell types, regulatory programs, and metabolic states, rather than isolated gene-level defects. In this review, we synthesize how emerging multiomic, computational, and functional genomic technologies are redefining the study of cardiovascular disease across molecular, cellular, and tissue levels. We highlight recent innovations in single-cell and spatial atlases, long-read sequencing, proteomics and metabolomics, integrative data modeling, and functional omics approaches, including genome-scale perturbation screens and single-cell perturbation frameworks. These platforms enable mechanistic dissection of regulatory circuits, distinguish primary disease drivers from secondary adaptations, and directly assess therapeutic reversibility, advancing the field beyond associative biomarker discovery toward mechanism-guided target prioritization. We further discuss key methodological and translational challenges accompanying high-dimensional cardiovascular data, including preanalytical variability, control selection, temporal misalignment across molecular layers, population diversity, and reference bias. By integrating technological innovation with computational rigor and functional validation, this review frames emerging omics-enabled strategies as a unified, physiologically grounded framework for translating molecular insight into clinically meaningful cardiovascular phenotypes and advancing precision cardiovascular medicine.

Humans↗
PubMed2025

scPOEM: robust co-embedding of peaks and genes revealing peak-gene regulation.

MOTIVATION: Identifying regulatory elements in various chromosomal regions that influence gene expression is a fundamental challenge in epigenomics, with profound implications for understanding gene regulation and disease mechanisms. The advent of paired single-cell RNA sequencing and single-cell ATAC sequencing has created unprecedented opportunities to address this challenge by enabling simultaneous profiling of gene expression and chromatin accessibility at single-cell resolution. However, the inherent signals between them are weak due to the highly sparse and noisy nature of data. RESULTS: This article proposes single-cell meta-Path based Omics Embedding (scPOEM), a novel embedding method that jointly projects chromatin accessibility peaks and expressed genes into a shared low-dimensional space. By integrating the relationships among peak-peak, peak-gene, and gene-gene interactions, scPOEM assigns closer representations in the embedding space to related peak-gene pairs. Our experiments demonstrate that scPOEM generates stable representations of peaks and genes, outperforms existing methods in recovering biologically meaningful peak-gene regulatory relationships and enables new insights in subgroup and differential analysis of gene regulation. These results highlight its potential to uncover gene regulatory mechanisms and enhance the understanding of transcriptional regulation at single-cell resolution. AVAILABILITY AND IMPLEMENTATION: The source code of scPOEM is available at https://github.com/Houyt23/scPOEM. The datasets can be obtained from the 10× Genomics (https://www.10xgenomics.com/datasets/pbmc-from-a-healthy-donor-granulocytes-removed-through-cell-sorting-10-k-1-standard-1-0-0) and GEO database under access codes GSE194122 and GSE239916.

Gene Expression Regulation↗
PubMed2027

A Standardized Protocol for Generating iPSC-Derived Human Microglia for Functional Genomic Assays.

Human induced pluripotent stem cell (iPSC)-derived microglia (iMG) provide an in vitro experimental system for studying human microglial biology, neuroinflammation, and genetic risk mechanisms associated with neurological disease. This chapter describes a standardized, scalable, and reproducible protocol for the differentiation of human iPSCs into functional microglia-like cells, with particular emphasis on applications in transcriptional and epigenomic network analysis. The protocol supports high-viability floating iMG production, compatibility with pooled CRISPR perturbation approaches, and downstream multiomic profiling, including single-cell RNA sequencing, chromatin accessibility assays, and proteomics. Detailed procedures are provided for iPSC maintenance, hematopoietic progenitor cell generation, microglial maturation, functional genomics integration, and quality control.

Humans↗
PubMed2024

Kick-starting the zygotic genome: licensors, specifiers, and beyond.

Zygotic genome activation (ZGA), the first transcription event following fertilization, kickstarts the embryonic program that takes over the control of early development from the maternal products. How ZGA occurs, especially in mammals, is poorly understood due to the limited amount of research materials. With the rapid development of single-cell and low-input technologies, remarkable progress made in the past decade has unveiled dramatic transitions of the epigenomes, transcriptomes, proteomes, and metabolomes associated with ZGA. Moreover, functional investigations are yielding insights into the key regulators of ZGA, among which two major classes of players are emerging: licensors and specifiers. Licensors would control the permission of transcription and its timing during ZGA. Accumulating evidence suggests that such licensors of ZGA include regulators of the transcription apparatus and nuclear gatekeepers. Specifiers would instruct the activation of specific genes during ZGA. These specifiers include key transcription factors present at this stage, often facilitated by epigenetic regulators. Based on data primarily from mammals but also results from other species, we discuss in this review how recent research sheds light on the molecular regulation of ZGA and its executors, including the licensors and specifiers.

Animals↗
PubMed2026

CHCHD10 Mitigates Alzheimer's Disease-Related Phenotypes in Association With Epigenetic Remodeling in Directly Reprogrammed Neurons.

Mitochondrial dysfunction and chromatin dysregulation are interconnected contributors to neuronal vulnerability in Alzheimer's disease (AD), yet the molecular mechanisms linking these processes remain poorly understood. CHCHD10, a mitochondrial intermembrane space protein, has been implicated in neurodegenerative disorders, but its role in AD has not been defined. Here, we identify CHCHD10 as a previously unrecognized modulator of neuronal epigenomic stability in AD. Using direct fibroblast-to-neuron reprogramming, which preserves patient-specific epigenetic signatures, we show that AD neurons recapitulate genome-wide hypomethylation patterns observed in postmortem AD cortex. CHCHD10 expression is significantly reduced in AD neurons and across multiple human brain datasets, including single-cell and bulk RNA sequencing, proteomics, and human cortical tissue analyses. Restoration of CHCHD10 in AD neurons reduces amyloid-β and insoluble tau accumulation while reversing AD-associated differentially methylated regions across CpG islands, promoters, and regulatory elements. CHCHD10-responsive methylation changes overlap with those observed in human AD brain regions and colocalize with significant AD loci and cortex-specific eQTL loci, including MAPT and ABCA7. Finally, we identify KATNAL2 as a CHCHD10-responsive effector whose loss enhances tau phosphorylation and seeding, whereas its restoration mitigates tau pathology. Together, these findings support a CHCHD10-associated neuroprotective pathway linking mitochondrial dysfunction, epigenomic instability, and tau pathology in AD.

Humans↗
PubMed2021

Comparative cellular analysis of motor cortex in human, marmoset and mouse.

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch-seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

Animals↗
PubMed2026

Regulatory Evolution and the Genetic Basis of Human Brain Expansion.

The evolution of the human brain is characterized by profound changes in structure and function, despite relatively limited divergence in protein-coding genes compared to other primates. This paradox has led to increasing recognition of gene regulatory elements (GREs) as primary drivers of evolutionary innovation. In this review, we synthesize current knowledge on the role of conserved noncoding elements (CNEs), human accelerated regions (HARs), and transposable element (TE)-derived sequences in shaping gene regulatory networks (GRNs) underlying brain development. Comparative analyses across humans and closely related primates, including the chimpanzee, gorilla, and orangutan, reveal that while core regulatory architectures are highly conserved, subtle changes in regulatory elements drive species-specific gene expression patterns. We highlight how CNEs provide a stable regulatory framework, whereas HARs and TE-derived elements introduce lineage-specific modifications that fine-tune neurodevelopmental processes. Advances in functional genomics, including CRISPR-based perturbations, massively parallel reporter assays, and single-cell multi-omics, have enabled direct interrogation of regulatory function, linking sequence variation to cellular phenotypes. Furthermore, we discuss how regulatory evolution contributes to both cognitive innovation and susceptibility to neurological disorders. Despite significant progress, challenges remain in establishing causal relationships between regulatory variation and phenotypic outcomes. Future integration of multi-omics data and comparative models will be essential for resolving these complexities. Together, this review provides a comprehensive framework for understanding the molecular basis of primate brain evolution through the lens of gene regulation.

Brain evolution↗
PubMed2026

Integrated Genomic and Epigenomic Analysis Reveals Epigenetic Plasticity in Disease Progression and Multidrug Resistance in Multiple Myeloma.

UNLABELLED: Multiple myeloma is marked by recurrent cytogenetic abnormalities and mutations that accumulate as the disease progresses. In this study, we sought to elucidate the transitions driving tumorigenesis and therapy resistance in multiple myeloma using a unique cohort of nearly 900 patients spanning premalignant to late-stage refractory multiple myeloma, comprehensively characterized at molecular and clinical levels. Waves of epigenetic dysregulation drove these critical transitions. In this paradigm, genomic and cytogenetic events unlocked epigenetic plasticity, reshaping multiple myeloma cell biology to evade tumor microenvironment constraints and therapeutic pressures. Functional perturbation studies in an isogenic proteasome inhibitor-resistant cell line model demonstrated enhanced reliance on transcriptional cofactors, supporting a mechanistic link between chromatin plasticity and therapy adaptation. Collectively, these findings support a unifying framework in which genomic heterogeneity unlocks gene regulatory plasticity, enabling plasma cells (PC) to evade microenvironmental constraints and therapeutic pressure. These results provide a mechanistic explanation for sequential relapse without new genomic alterations and nominate epigenetic plasticity-mediated PC adaptation as a therapeutic vulnerability in the heterogeneous genetic background of multiple myeloma. SIGNIFICANCE: Assembly and analysis of a multiple myeloma cohort spanning the continuum from premalignant to late relapse that integrates bulk transcriptomics with single-cell multiomic data provides insights into disease progression and epigenetic plasticity.

Multiple Myeloma↗
PubMed2026

Livestock Multi-Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation.

Livestock multi-omics integration is key to unraveling complex trait regulation, yet systematic, livestock-specific strategies remain scarce. This review traces the progression from single-omics accumulation to multi-dimensional integration, highlighting how large-scale genomic, epigenomic, and transcriptomic projects lay the foundation for functional dissection. We identify core impediments: extreme species diversity, marked data heterogeneity, limited sample sizes, and a pervasive reduction of multi-omics data to simplistic differential screens, resulting in low translational efficiency. We critically appraise four common pitfalls-overinterpreting correlation as causation, relegating proteomics to corroborating transcriptomics, incomplete microbiome-host integration lacking environmental context, and systematic neglect of metabolic fluxomics-and show how exposomics and fluxomics add necessary causal and dynamic dimensions. To address these, we propose a livestock-adapted three-tier analytical framework: (1) statistical association of cross-omics covariation patterns; (2) machine learning-driven feature mining and integrative modeling; and (3) causal interpretation encompassing Mendelian randomization, prior-knowledge-guided network inference, and physical causal evidence via fluxomics and metabolic control analysis. We further discuss how multimodal sequencing (single-cell, spatial, temporal) and generative AI can fundamentally mitigate heterogeneity and strengthen causal evidence. Finally, we outline future priorities in database standardization, livestock-specific benchmarking, and translational pipelines, charting a path from correlation-centric reporting to mechanistic causality and precision breeding.

Animals↗
PubMed2026

Pan-genomics and multi-omics for deciphering genetic variation and accelerating genetic improvement in ruminant livestock.

Livestock reference genomes have transformed the discovery of variants associated with production, reproduction, health, and environmental adaptation. Nevertheless, a single linear reference represents only one mosaic haplotype and incompletely captures sequence diversity within a species, particularly structural variants, copy-number changes, repeat-rich regions, and breed-specific sequences. Pangenomes address this limitation by integrating multiple high-quality assemblies or population-scale variants into a unified sequence or graph representation. Concurrently, multi-omics approaches connect genomic variation with transcriptomic, epigenomic, manuscriptproteomic, metabolomic, and microbiome responses, thereby improving biological interpretation of genotype-phenotype relationships. This review synthesizes recent progress in livestock pangenomics and multi-omics, with emphasis on cattle, goats, sheep, water buffalo, and chickens. It describes advances in long-read and haplotype-resolved sequencing, graph construction, structural-variant discovery and genotyping, functional annotation, and integrative analysis. Recent pangenome studies have uncovered substantial non-reference sequence, reduced reference bias, identified breed- and population-specific structural variants, and resolved candidate variants underlying pigmentation, body size, tail morphology, cashmere production, altitude adaptation, and other economically relevant traits. However, translation into routine breeding remains constrained by uneven population representation, inconsistent structural-variant definitions, limited functional annotation, computational demands, and insufficient validation across environments. Future progress will depend on diverse near-complete assemblies, graph-aware imputation and genomic prediction, long-read transcriptomics, single-cell and spatial omics, rigorous causal validation, and open, interoperable resources. Together, these developments can support more accurate, resilient, and biologically informed livestock improvement. Importantly, current dairy-cattle evidence indicates that pangenome-derived structural variants can substantially improve variant discovery and functional interpretation while yielding only marginal average gains in routine genomic prediction, favoring targeted augmentation rather than wholesale replacement of established SNP-based evaluations.

Animals↗
PubMed2025

Self-organization of mouse embryonic stem cells into reproducible pre-gastrulation embryo models via CRISPRa programming.

Embryonic stem cells (ESCs) can self-organize into structures with spatial and molecular similarities to natural embryos. During development, embryonic and extraembryonic cells differentiate through activation of endogenous regulatory elements while co-developing via cell-cell interactions. However, engineering regulatory elements to self-organize ESCs into embryo models remains underexplored. Here, we demonstrate that CRISPR activation (CRISPRa) of two regulatory elements near Gata6 and Cdx2 generates embryonic patterns resembling pre-gastrulation mouse embryos. Live single-cell imaging revealed that self-patterning occurs through orchestrated collective movement driven by cell-intrinsic fate induction. In 3D, CRISPRa-programmed embryo models (CPEMs) exhibit morphological and transcriptomic similarity to pre-gastrulation mouse embryos. CPEMs allow versatile perturbations, including dual Cdx2-Elf5 activation to enhance trophoblast differentiation and lineage-specific activation of laminin and matrix metalloproteinases, uncovering their roles in basement membrane remodeling and embryo model morphology. Our findings demonstrate that minimal intrinsic epigenome editing can self-organize ESCs into programmable pre-gastrulation embryo models with robust lineage-specific perturbation capabilities.

Animals↗
PubMed2026

Mapping ovarian cellular and molecular landscape across the lifespan of women: a scoping review.

BACKGROUND: With growing interest in ART, fertility preservation, and postmenopausal health of women, reproductive medicine is increasingly focused on characterizing oocytes and ovarian tissue composition, as well as understanding the molecular mechanisms that guide ovarian function throughout its lifecycle. High-throughput omics technologies have enabled the characterization of different molecular layers, leading to substantial advances in our understanding of their complex dynamics. However, not all molecular aspects are studied equally, and studies examining the same modalities often show inconsistencies, underscoring the need for data standardization and highlighting the potential for using transformative artificial intelligence and machine-learning (AI/ML) methods for ovary studies. OBJECTIVE AND RATIONALE: This study aims to evaluate how multi-omic studies have advanced our understanding of the ovarian lifecycle from fetal development to postmenopause. We systematically reviewed published studies that have investigated molecular/omic layers, including the genome, methylome, transcriptome, and proteome throughout ovarian development and aging. Our analysis identified key molecular and cellular patterns, highlighted inconsistencies across studies and addressed gaps in data analysis, interpretation, and reproducibility to guide future research. SEARCH METHODS: We conducted a systematic literature search of Medline (PubMed), Embase (Ovid), and Web of Science Core Collection (Clarivate) using a combination of controlled and free text terms for human ovary, oogenesis, folliculogenesis, ovary development and (epi)genome, transcriptome, proteome, and multi-omic mechanisms to find relevant articles published before August 2025. To focus the scope of the current review, studies of domesticated and farm animals, rodents and other model organisms, non-human primates, as well as those examining various human ovarian pathologies were excluded. OUTCOMES: The search identified 23 546 studies for screening, of which 637 full-text studies were assessed for eligibility. Subsequently, we extracted data from 121 studies. Most studies analyzed the transcriptome of oocytes, granulosa cells, and ovarian tissue from reproductive-age individuals (n = 91), with fewer studies examining samples from individuals of advanced reproductive age (n = 45) and fetal (n = 16) samples. Transcriptome analyses were most common (n = 103, 85%), followed by proteome (n = 19, 16%) and epigenome (n = 14, 12%) studies. We found substantial variation in how studies defined and reported participants' groups as well as in their sequencing technologies and data analysis methods, with a lack of standardized reporting of background clinical information, data analysis methods, and pipeline details. The key findings underscore the prevailing consensus on genes defining major ovarian cell types and their roles throughout the ovarian lifespan, from prenatal development to postmenopausal transformation. This review highlighted the underrepresentation of certain patient groups, particularly prepubertal and peri-/postmenopausal individuals, among researched populations, due to obvious clinical and ethical reasons. WIDER IMPLICATIONS: This scoping review offers a comprehensive overview and benchmark of the current state of high-throughput omics-based research on ovarian cellular composition and molecular dynamics. To address these shortcomings, we propose general recommendations for multi-omics ovary studies and emphasize the necessity for more thorough multi-omic data integration by effectively applying novel AI/ML approaches. They can potentially improve the quality of multi-omics analyses at both single-cell and tissue levels despite limited sample sizes and enable integration of molecular profiling data with clinical and radiology datasets, enabling a more comprehensive understanding of ovarian biology. Such advancements can enhance reproducibility of research findings and guide future research to deepen our understanding of ovarian biology and ultimately support the development of medical technologies for better preserving fertility and alleviating infertility. REGISTRATION NUMBER: A protocol was published a priori on the Open Science Framework (https://osf.io/z38gb/).

Female↗
PubMed2026

BACH1 orchestrates macrophage state transitions to coordinate regenerative inflammation.

Efficient tissue regeneration requires the precise coordination of inflammatory and regenerative programs, principally mediated by monocyte-derived macrophages. However, the transcriptional wiring and epigenomic processes behind complex macrophage subtype specification and transition between the different states are not known. Here we have identified the transcriptional repressor BACH1 as a critical, cell-intrinsic regulator of monocyte-derived macrophage specification during skeletal muscle regeneration. Using a myeloid-specific BACH1 knockout mouse model, we demonstrate that BACH1 deficiency disrupts the temporal coordination of monocyte-to-macrophage differentiation, leading to aberrant macrophage subsets with concurrent opposing pro- and anti-inflammatory features. Single-cell RNA-sequencing profiling reveals that BACH1 controls a core transcriptional network, including Nfkb1, Cebpb, and interferon signaling, governing inflammatory resolution and functional macrophage specialization. Mechanistically, BACH1 loss accelerates macrophage differentiation but also affects its core cellular identity, resulting in sustained, rather than declining inflammatory programs including upregulation of Il1b and thus, defective tissue remodeling. These immune alterations compromise the paracrine landscape during regenerative inflammation and impair muscle stem cell differentiation. Our findings establish BACH1 as a molecular tuner or controller that integrates early innate immune signaling with regenerative output, positioning it as a central node linking transcriptional control, immune fate decisions, and tissue repair.

Animals↗
PubMed2026

Beyond Bulk: Cell-Type-Resolved Epigenomics as the Path Forward in Alzheimer's Disease Research.

Alzheimer's disease (AD) is a complex neurodegenerative disorder in which most risk variants are noncoding and are enriched at gene regulatory regions, implicating epigenetic mechanisms as central mediators of disease pathogenesis. For most of the history of AD epigenetics research, bulk tissue analysis has dominated, obscuring the fundamentally distinct epigenomic landscapes of individual brain cell types and masking cell-type-specific contributions to disease. Advances in single-cell and single-nucleus sequencing, fluorescence-activated nuclei sorting and multiplexed epigenomic platforms have transformed this landscape, enabling cell-type-resolved profiling of chromatin accessibility, DNA methylation, histone modifications and transcription across the major neuronal, glial and neurovascular populations of the human brain. Here, we review these advances, structured around the argument that cell-type resolution is not a methodological refinement but a conceptual necessity. We describe the distinct epigenomic programs disrupted in neurons, microglia, astrocytes, oligodendrocytes and neurovascular cells in AD, highlighting how each cell type responds to pathology. We discuss the discovery of epigenomic erosion, the progressive loss of cell-type-specific epigenomic identity across virtually all brain cell populations as AD advances, as a unifying disease mechanism linking chromatin dysregulation to cognitive decline. Finally, we identify critical gaps in current knowledge, including the near-complete absence of cell-type-resolved histone modification and DNA methylation data for most brain cell types, the underrepresentation of rare populations in standard preparations and the untapped potential of metabolic acylation marks as indicators of the epigenome-metabolism interface in neurodegeneration.

Humans↗