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PubMed2025

CUT&TIME captures the history of open chromatin in developing neurons.

Chromatin structure plays a central role in defining cell identity by regulating gene expression. During development, shifts in chromatin structure facilitate changes in gene expression needed to specify distinct cell types. To understand how changes in chromatin structure influence the developmental trajectory of neural progenitor cells, we developed CUT&TIME, a technique that uses a hyperactive 6-methyl adenosine (6mA) methyltransferase pulsed in living cells to map historical chromatin accessibility genome-wide in single cells. We show that CUT&TIME produces a record of the chromatin landscape during neurogenesis in the developing retina, specifically as neural progenitors produce the major projection neuron type, retinal ganglion cells (RGCs). We further show that this method is compatible with single cell profiling technologies, which allows us to visualize and capture the diversity of chromatin states that produce RGCs. Additionally, we identify changes in promoter accessibility associated with the transition from progenitor to RGC. Together, these data demonstrate that CUT&TIME captures a historical record of chromatin structure, which can be used to identify early changes in accessibility associated with cell-fate commitment.

Journal Article↗
PubMed2025

Recent Non-LTR Retrotransposon Activity Predicts Cancer Prevalence in Mammals.

Non-long terminal repeat retrotransposons (nLTRs), including long and short interspersed nuclear elements (L1 and SINEs), are the most abundant and active mobile elements in mammals. NLTRs play critical mutagenic and regulatory roles during oncogenesis in humans and model species. However, it is not known whether recent nLTR activity in the genome is related to the lifetime cancer risk of a species beyond humans and conventional model organisms. We examined whether recent nLTR activity predicts cancer prevalence across mammals using comparative analyses of de novo whole-genome repeat annotations from 55 species, each with over 20 published zoo pathology records. We quantified nLTR activity as the number of potentially active elements, their proximity to protein-coding genes and cancer gene orthologs (CGOs), and insertions within these genes. Across all three metrics, neoplasia prevalence was associated with both L1 and combined L1-SINE activity, while malignancy was linked exclusively to the L1-SINE predictors. This pattern suggests a complementary and escalating trajectory, where L1s contribute to early tumorigenic events, while SINE activity, driven by L1s, amplifies their impact and fuels the transition to malignancy. Moreover, genomes harboring more CGOs tended to exhibit higher neoplasia prevalence, and the number of fusion cancer genes was strongly correlated with the number of potentially active L1s across species. Our results further revealed a pattern wherein species with minimal cancer prevalence exhibit restricted activity of at least one major nLTR superfamily, suggesting that preserving genome stability through limited retrotransposition may serve as a protective mechanism against cancer.

Cancer Genes↗
PubMed2025

Learning neural dynamics through instructive signals.

Rapid learning is essential for flexible behavior, but its basis in the brain remains unknown. Here we introduce the PRISM plasticity rule, a unifying mechanistic model of three well-established, fast-acting synaptic plasticity rules-in hippocampus, cerebellum and mushroom body-which relies exclusively on pre-synaptic activity and an "instructive signal" from another brain area. Using a multi-region network model we show that guiding PRISM plasticity with instructive signals enables the network to quickly learn extremely flexible nonlinear dynamics underlying behaviorally relevant computations, as well as to emulate unknown external system dynamics from real-time error signals, which we demonstrate with comprehensive simulations supported by exact mathematical theory. Thus, PRISM plasticity guided by instructive signals is well-suited to rapidly learn general-purpose neural computations-in contrast to canonical Hebbian rules. Finally, we show how including this plasticity rule in artificial learning algorithms can solve long-range temporal credit assignment, a long-standing challenge in machine learning.

cerebellum↗
PubMed2025

Germline stem cell isolation, lineage tracing, and aging in a protochordate.

Germline stem cells (GSCs), the source of gametes, are the only stem cells capable of passing genes to future generations and are therefore considered units of natural selection. Yet, the factors that influence GSC fitness, and thus govern GSC competition, which exist in both protochordates and mammals, remain poorly understood. We studied how aging affects GSC fitness in the protochordate Botryllus schlosseri, an evolutionary crosspoint between invertebrates and vertebrates. GSCs were isolated and distinguished from developing and mature gametes using flow cytometry and scRNA-Seq, facilitated by a new PacBio genome assembly. Moreover, their function was validated through a novel lineage tracing approach that combines membrane-labeled GSC transplantation with scRNA-Seq. Leveraging our method to isolate them, single-cell transcriptomics showed significant age-related changes between young and old GSCs. Spermatids and sperm, however, showed minimal changes, suggesting that reproductive aging is governed by GSCs rather than by gametes. Reduced expressions of markers like DDX4 and PIWIL1 in aged GSCs mirrored trends in mammalian datasets, pointing to a conserved GSC-driven aging mechanism across chordate evolution. This study provides new techniques that lay the foundation to investigate further drivers of GSC fitness and highlights fertility-related genes as promising targets for therapies to preserve reproductive health.

Journal Article↗
PubMed2025

Discovery of additional ancient genome duplications in yeasts.

Whole genome duplication (WGD) has had profound macroevolutionary impacts on diverse lineages1,2, preceding adaptive radiations in vertebrates3-5, teleost fish6,7, and angiosperms8,9. In contrast to the many known ancient WGDs in animals10,11 and especially plants12-14, we are aware of evidence for only four in fungi15,16. The oldest of these occurred ~100 million years ago (mya) and is shared by ~60 extant Saccharomycetales species17,18, including the baker's yeast Saccharomyces cerevisiae (Fig. 1). Notably, this is the only known ancient WGD in the yeast subphylum Saccharomycotina. The dearth of ancient WGD events in fungi remains a mystery15. Some studies have suggested that fungal lineages that experience chromosome19 and genome15 duplication quickly go extinct, leaving no trace in the genomic record, while others contend that the lack of known WGD is due to an absence of data15,16. Under the second hypothesis, additional sampling and deeper sequencing of fungal genomes should lead to the discovery of more WGD events. Coupling hundreds of recently published genomes from nearly every described Saccharomycotina species with three additional long-read assemblies, we discovered three novel WGD events. While the functions of retained duplicate genes originating from these events are broad, they bear many similarities to the well-known WGD that occurred in the Saccharomycetales17. Our results suggest that WGD may be a more common evolutionary force in fungi than previously believed.

Convergent Evolution↗
PubMed2025

Translational reading frame determines the pathogenicity of C-terminal frameshift deletions in MeCP2: an alternative therapeutic approach.

Mutations in the MECP2 gene cause the severe neurological disorder Rett syndrome. A cluster of frameshift-causing C-terminal deletions (CTDs) lead to loss of ~100 amino acids at the C-terminus of the MeCP2 protein, and account for approximately 10% of RTT-causing mutations. The pathogenicity of C-terminal deletions (CTDs) is unexpected, as this C-terminal domain is non-essential in mice. Utilising databases of pathogenic and benign human MECP2 mutations, we find that some individuals with apparently typical CTDs do not exhibit Rett syndrome, confirming that C-terminal truncations are not intrinsically pathogenic. Using human DNA sequence data and mouse models, we demonstrate that pathogenicity results from a drastic reduction in MeCP2 levels and is determined by the presence of the short amino acid motif proline-proline-stop (-PPX) at the C-terminus, which results from a shift to the +2 reading frame. Individuals with CTDs that shift to the +1 frame avoid this motif and do not develop Rett syndrome. Mutating the stop codon of the PPX motif to tryptophan rescues MeCP2 expression and RTT-like phenotypes in a CTD mouse model. Finally, we demonstrate that an adenine base editor can efficiently introduce this tryptophan substitution in cultured cells. Overall, our findings uncover a simple and reliable prognostic distinction between benign and pathogenic CTDs and provide proof-of-concept for an editing strategy that potentially corrects all disease-causing CTD mutations.

Journal Article↗
PubMed2025

Integrative genomics elucidates the evolutionary, temporal, and developmental origins of a hydrocephalus risk gene.

INTRODUCTION: A prior integrative, multi-omics human genetics and functional genomics study identified maelstrom (MAEL), a gene involved in regulation of DNA transposon activity and genome structure, as a transcriptome-wide predictor of hydrocephalus (HC) in the brain cortex. Here we expand on this discovery and further characterize the evolutionary origin and expression of MAEL across developmental timescales and cell-lineages in the neonatal human brain towards a mechanistic understanding how variation in MAEL expression may cause HC. OBJECTIVE: To characterize the evolutionary, temporal, developmental, and lineages of MAEL expression in HC and the developing human brain. METHODS: Ensembl was used to delineate the evolution and taxonomy of MAEL across species. Analysis of single-cell RNA sequencing (scRNA-seq) of 49 brain regions across pre- and post-natal timescales from the Developing Human Brain Atlas (Allen Institute) identified temporal and spatial MAEL expression patterns. We quantified MAEL expression in primary cortical brain tissue obtained during the surgical treatment of HC. RESULTS: We performed taxonomic gene-mapping to define the evolutionary origin of MAEL to assess suitability for mechanistic characterization in vitro and in vivo across species. We find that MAEL is among the top 0.01% human-specific genes and < 50% sequence homology among commonly used model organisms with highly divergent functions, necessitating mechanistic validation in human tissue. scRNA-seq of the non-disease prenatal human brain identified MAEL expression enriched in cortical excitatory neurons, which was recapitulated in primary HC brain tissue obtained during surgery. Finally, using scRNA-seq of primary HC brain tissue, we functionally validated reduced MAEL expression, consistent with a prior human TWAS analysis. CONCLUSIONS: We identify the evolutionary, temporal, and developmental expression pattern of MAEL in the neonatal human brain. We also provide direct evidence for reduced MAEL expression in human HC brain tissue. These data, at least in part, implicate reduced MAEL expression underlying human HC across etiologies.

Journal Article↗
PubMed2025

Patterns of HIV-1 viral load suppression and drug resistance during the dolutegravir transition: a population-based longitudinal study.

BACKGROUND: Data on the population-scale impact of dolutegravir (DTG)-based HIV regimens in sub-Saharan Africa are extremely limited. We used data from a surveillance cohort in southern Uganda to assess viral suppression and antiretroviral (ART) resistance over 10-years alongside DTG scale-up. METHODS: Consenting participants in the population-based Rakai Community Cohort Study between August 2011 and March 2023 aged 15-59 completed questionnaires and provided samples for HIV testing, viral load quantification, and viral deep-sequencing. We collected data on DTG-utilization at HIV care clinics. We estimated the prevalence of HIV suppression (<1,000 copies/mL) and ART resistance using robust Poisson regression. Bayesian logistic regression quantified associations between resistance and individual-level suppression across surveys. FINDINGS: Among 20,383 people living with HIV (PLHIV), suppression increased from 57.1% (95% confidence interval [CI]: 55.4%-58.8%) to 90.3% (95%CI: 89.2%-91.4%) between 2014 and 2022. By 2020 84.4% (95%CI: 83.7%-85.2%) and 64.6% (95%CI: 63.9%-65.3%) of men and women were on DTG regimens. Among treatment-experienced viremic PLHIV, overall resistance decreased from 51.1% (95%CI: 40.7%-64.1%, 2014) to 27.9% (95%CI: 21.3%-36.5%, 2022). Only two participants harbored intermediate/high-level DTG resistance, attributable to inQ148R, inE138K, and inG140A. Low-level INSTI resistance (inS153Y) was observed in 23/207 (7.5%) of viremic individuals, with putative evidence of transmission. By 2022, suppression was unrelated to prior history of NNRTI/NRTI resistance (risk ratios: 1.14, 95%HPD: 0.96-1.32 and 1.12, 95%HPD: 0.88 - 1.35). INTERPRETATION: Viral suppression increased during the DTG-transition with minimal emerging intermediate/high-level resistance. Falling resistance among treatment-experienced PLHIV underscores the role of ART adherence in reducing viremia. The emergence of inS153Y justifies continued genomic surveillance of ART resistance. FUNDING: National Institutes of Health and the Gates Foundation.

Journal Article↗
PubMed2025

Estimating population structure using epigenome-wide methylation data.

INTRODUCTION: In epigenome-wide association analysis (EWAS), unaddressed population stratification often leads to inflation. We aimed to compute methylation population scores (MPSs) that predict genetic principal components (GPCs) using a feature selection and regression approach. METHODS: We used multi-ethnic methylation data (Illumina 450K/EPIC array) from unrelated MESA (n=929), CARDIA (n=1123), JHS (n=1365), ARIC (n=2338), and HCHS/SOL (n=1475) individuals, randomly assigning 85% of participants from each cohort to a training dataset and the remaining 15% to a test dataset. First, we estimated the associations of GPCs with each available CpG methylation site using linear regression within each cohort, adjusting for age, sex, smoking status, race/ethnic background (as a proxy for background information associated with lifestyle and other environmental exposures that may impact methylation), alcohol use status, body mass index, and cell type proportions. We meta-analyzed the associations across cohorts and selected CpG sites with association FDR-adjusted q-value <0.05. We next aggregated individuallevel data across the cohort-specific training datasets, and applied two-stage weighted least squares Lasso regression, with the GPCs as the outcomes and the selected CpG sites as penalized predictors, adjusting for the aforementioned covariates. The developed MPSs are the weighted sum of selected CpG sites from the Lasso. To evaluate the developed MPSs, we constructed them in the test dataset, and compared them with GPCs, and with MPSs constructed based on a previously-published paper. Comparison was based on correlation analysis and data visualization. We demonstrate the use of the MPSs in EWAS. RESULTS: In the test dataset, the MPSs were highly correlated with GPCs, with correlation decreasing, though not monotonically, for later components. Specifically, MPS1 and GPC1 had R2= 0.99, while MPS7 and GPC7 had R2=0.27 (the lowest observed correlation). In data visualization, MPSs had similar patterns as GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups, while outperforming MPC constructed using alternative published methods. MPSs showed comparable performance to GPCs in reducing some of the inflation in EWAS. CONCLUSIONS: Methylation-based population scores provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent. Unlike previous methods based on unsupervised methylation PCA, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations. The weights for each GPCs derived in our study can be applied to generate MPSs in other studies.

Journal Article↗
PubMed2025

Structural basis for the function of long noncoding RNA Pnky in neural stem cells.

LncRNA Pnky is a trans-acting regulator of neural stem cell (NSC) differentiation, but the molecular mechanisms by which Pnky regulates neurogenesis is unknown. A fundamental step towards mechanistic understanding is to determine whether a lncRNA has folded structure that underlies biological function. Using chemical probing and high-throughput analysis, we determined the secondary structure of Pnky folded in vitro and in cellulo. Pnky adopts a compact structure in vitro with distinct modules and evidence of tertiary interactions. In cellulo, Pnky structure is remarkably similar to the in vitro conformation. We used locked nucleic acid oligonucleotides to interrogate the entire Pnky transcript for function in NSCs and identified regions that when targeted increased neurogenesis - phenocopying Pnky knockdown - without decreasing transcript abundance. Our findings provide a structural basis for the role of Pnky in neurogenesis and, more broadly, illustrate how structural maps combined with phenotypic data can advance fundamental understanding of lncRNA mechanism.

LNA-ASOs↗
PubMed2025

An electrostatic repulsion model of centromere organisation.

During cell division, chromosomes reorganise into compact bodies in which centromeres localise precisely at the chromatin surface1-4 to enable kinetochore-microtubule interactions essential for genome segregation5-8. The physical principles guiding this centromere positioning remain unknown. Here, we reveal that human core centromeres are directed to the chromatin surface by repulsion of centromere-associated proteins - independent of condensin-mediated loop extrusion and microtubule engagement. Using cellular perturbations, biochemical reconstitution, and multiscale molecular dynamics simulations, we show that chromatin surface localisation emerges from repulsion between condensed chromatin and both the kinetochore and the highly negatively charged centromere protein, CENP-B. Together, these elements form a centromeric region composed of two domains with opposing affinities, one favouring integration within the mitotic chromosome and the other favouring exposure to the surrounding cytoplasm, thereby driving surface positioning. Tethering synthetic negatively charged proteins to chromatin was sufficient to recapitulate this surface localisation in cells and in vitro, indicating that electrostatic repulsion is a key determinant of surface localisation. These findings demonstrate that centromere layering is not hardwired by chromatin folding patterns but instead emerges from phase separation in chromatin. Our work uncovers electrostatic polarity as a general and programmable mechanism to spatially organise chromatin.

Journal Article↗
PubMed2025

Genome-scale multi-organ analysis of mutagenic effects of ethanol and acetaldehyde in Sprague Dawley rats.

Alcohol consumption is a major cancer risk factor, particularly for head and neck cancers, including the oral cavity. Acetaldehyde, the primary genotoxic metabolite of ethanol, may play key roles in oral carcinogenesis, though the mechanisms remain unclear. While mutational signatures SBS16, DBS4, and ID11 have been tentatively linked to alcohol use, they are not exclusive to alcohol-related cancers. In this study, we examined the genome-wide in vivo mutagenic effects of ethanol and acetaldehyde by analyzing tumors from the cheek, Zymbal gland, larynx, forestomach, and liver of rats chronically exposed to these compounds. Signature analysis revealed exposure-specific, early-onset formation of SBS17 in ~28% of head and neck tumors, suggesting inflammation and/or oxidative damage as potential mediators of carcinogenesis. Cancer driver gene analysis identified a relative enrichment of exposed tumors with mutations in the Tp53 and Mtor genes. No notable exposure-specific changes were observed in doublet-base substitutions, indel signatures, or copy number variants. Notably, SBS16, DBS4, and ID11 were absent. Our findings suggest direct mutagenicity may not be the main driver of alcohol-related cancer. Other harmful cellular effects, undetectable by whole genome sequencing, may be involved. Our findings suggest that SBS17 could function as a potential exposure-specific molecular marker of alcohol-related cancers in humans.

Journal Article↗
PubMed2025

Deciphering Cell Fate and Clonal Dynamics via Integrative Single-Cell Lineage Modeling.

Through natural or synthetic lineage barcodes, single-cell technologies now enable the joint measurement of molecular states and clonal identities, providing an unprecedented opportunity to study cell fate and dynamics. Yet, most computational methods for inferring cell development and differentiation rely exclusively on transcriptional similarity, overlooking the lineage information encoded by lineage barcodes. This limitation is exemplified by T cells, where subtle transcriptional differences mark divergent fates with distinct biological activity. Single-cell RNA and matched TCR sequencing is now ubiquitous in the analysis of clinical samples, where the TCR sequence provides an endogenous clonal barcode and could reveal clonal T cell responses. We present Clonotrace, a computational framework that jointly models gene expression and clonotype information to infer cell state transitions and fate biases with higher fidelity. While motivated by challenges in analyzing T cell populations, especially in the tumor microenvironment and immunotherapy settings, Clonotrace is broadly applicable to any lineage-barcoded single-cell dataset. Across diverse systems including T cells, hematopoietic differentiation, and cancer therapy resistance models, Clonotrace reveals differentiation hierarchies, distinguishes unipotent from multipotent states, and identifies candidate fate-determining genes driving lineage commitment.

Journal Article↗
PubMed2025

SimHumanity: Using SLiM 5.0 to run whole-genome simulations of human evolution.

The reconstruction of human evolutionary history has undergone repeated advances, each made possible by methodological innovations. In recent decades, genetic and genomic data played a central role in the reconstruction of major evolutionary events such as the out-of-Africa migration, and genetic simulations of human evolutionary history have come to play a major role in testing more specific hypotheses including proposed patterns of migration and admixture with archaic hominins. Increasing computational power has allowed human evolutionary history to be modeled at ever-larger scales, but simulations that encompass the complete human genome, including sex chromosomes and mitochondrial DNA, have been difficult due to the lack of support for whole-genome models in commonly used evolutionary simulation frameworks. With the recent introduction of SLiM 5 such simulations are now straightforward to construct, allowing the easy simulation of humans at whole-genome scale under different demographic models and evolutionary dynamics. We here present three versions of a reusable, customizable, open-source SLiM 5 model for simulating the molecular evolution of the full human genome. We also show some simple analyses of results from the model, to illustrate its utility. We hope this model, which we have nicknamed "SimHumanity" in jest, will facilitate further progress in the field of human evolutionary simulations.

SLiM↗
PubMed2025

Hormetic nutrient stress promotes longevity by orchestrating histone acetylation on key lipid catabolism and antioxidant defense genes.

Exposure to low levels of environmental challenges, known as hormetic stress, such as nutrient deprivation and heat shock, fosters subsequent stress resistance and promotes healthy aging in later life. However, specific mechanisms governing transcriptional reprogramming upon hormetic nutrient stress remain elusive. In this study, we identified histone H3 lysine 27 acetylation (H3K27ac) as a crucial driver of transcriptomic adaptation to hormetic fasting. Beyond its immediate function of enhancing lipid catabolism for alternative energy sources, stress-induced H3K27ac activates lifelong antioxidant defenses, thereby reducing reactive oxygen species (ROS) produced by stress-induced fatty acid oxidation and their accumulation during aging. The increase in H3K27ac, mediated by pioneer factor PHA-4/FOXA and cooperating transcription factor NHR-49/HNF4, is crucial for lifespan extension under hermetic nutrient stress in Caenorhabditis elegans. Our findings establish H3K27ac as a key transcriptional switch that bridges nutrient status with transcriptomic reprogramming, underpinning the pro-longevity effects of hormetic fasting through orchestrating lipid catabolism and antioxidative defenses.

Journal Article↗
PubMed2025

The impact of polygenic score and socioeconomic status in predicting risk for 19 complex diseases.

Both socioeconomic circumstances and genetic predisposition shape disease risk, yet their joint contribution across diseases has not been systematically examined. We studied 19 high-burden diseases in 743,194 participants (729,928 European; 13,266 non-European ancestry) from FinnGen, the UK Biobank, and Generation Scotland. Higher educational attainment was associated with lower risk of most conditions, but with higher risk of most common cancers. These associations were largely independent of disease-specific polygenic scores (PGSs). For seven out of 19 diseases, PGSs showed stronger effects among individuals with high education. Joint inclusion of education and PGSs modestly improved prediction for 14 and 10 out of 19 diseases in FinnGen and the UK Biobank, respectively. PGS associations were consistent across ancestries, whereas education effects were less stable; results using an alternative socioeconomic measure were directionally similar but smaller. Our findings highlight the distinct and partly interacting contributions of socioeconomic and genetic factors to disease risk.

Journal Article↗
PubMed2025

Systematic analysis of snRNA genes reveals frequent RNU2-2 variants in dominant and recessive developmental and epileptic encephalopathies.

Variants in spliceosomal small nuclear RNA (snRNA) genes RNU4-2 (ReNU syndrome), RNU5B-1, and RNU2-2 have recently been linked to dominant neurodevelopmental disorders (NDDs), revealing a major, previously overlooked role for noncoding snRNAs in human disease. Here, we systematically analysed 200 potentially functional snRNA genes in a French cohort comprising 26,911 individuals with rare disorders and through international collaborations. We identify de novo and biallelic variants in RNU2-2 associated with both dominant and recessive NDDs in 126 individuals from 108 unrelated families. Recessive RNU2-2 NDD is at least twice as frequent as the dominant NDD caused by n.4G>A and n.35A>G, and often arises from a de novo variant in trans with an inherited allele, reflecting the high mutability of snRNA genes. Dominant and recessive RNU2-2-NDDs share overlapping clinical features with frequent epilepsy. Blood transcriptomics and DNA methylation analyses revealed subtle, variant-specific effects on splicing and episignatures. Our findings support a gradient-of-impact model and a continuum between dominant and recessive inheritance, establishing RNU2-2 variants as a frequent cause of NDDs, nearly as prevalent as ReNU syndrome.

Journal Article↗
PubMed2025

Systematic identification of oscillatory gene expression in single cell types.

Many biological cycles are driven by oscillatory gene expression coordinated across cell types. For example, larval development in Caenorhabditis elegans involves coordinated cyclic changes in cell division, behavior, and growth, the latter requiring production of a structured extracellular matrix called the cuticle. Here, we combine single-cell RNA sequencing and novel computational approaches to identify oscillatory gene expression in individual cell types. We find that many cell types exhibit looping structures in PCA and UMAP space that correspond to transcriptional oscillations at each larval stage. Oscillatory gene expression is found in all cuticle-producing cell types, including glia, but not detected in neurons or muscle. We develop rigorous statistical approaches for de novo identification of oscillatory genes and cell types, yielding >5,000 genes. While many oscillatory genes relate to cuticle production, each cell type expresses largely distinct genes, suggesting that cuticle production is a patchwork of cell-type-specific programs. Finally, we derive a potential set of regulatory transcription factors that can explain coordinated oscillatory gene expression and find that shared upstream factors likely control gene timing across cell types. Together, our results suggest that shared regulators control cell-type-specific oscillatory gene expression, including in previously overlooked cell types such as glia.

Journal Article↗