Biology subjects

Levin, J. Z.

Publications and source records attributed to Levin, J. Z..

At least 19 recordsLinked to original sources

bioRxiv2026

Single cell eQTL mapping reveals convergent glial-neuronal risk architecture in Parkinson's disease

Synucleinopathies affect [~]15 million people and are classically divided into neuronal (Parkinsons disease (PD), dementia with Lewy bodies) and glial (multiple system atrophy) disorders. Here we challenge this dichotomy. We functionally fine-map 90 PD GWAS signals across nine cell types in cortex and substantia nigra using disease-context, population-scale single-nucleus eQTL meta-analysis (N = 1,197), bulk brain eQTL analysis (N = 1,182), and Mendelian randomization. A stringent causal framework integrates single-nucleus allelic imbalance (snASE) with orthogonal validation. We identify 125 functional risk genes for 50 loci--nearly doubling supported genes--and assign genes and cell types to over half of GWAS signals. Unexpectedly, 51% of risk genes are regulated in glia, particularly oligodendrocytes and their precursors. Across cell types, risk converges on a shared glial-neuronal vesiculopathy network. These findings uncover a convergent glial-neuronal risk architecture and establish a single-cell atlas for context-aware gene discovery and precision therapeutics for PD.

genetics↗

bioRxiv2026

Concordant transcriptional and morphological remodeling revealed by in vivo Perturb-CLEAR

The principle that form follows function has long guided thinking in biology and architecture alike. In the nervous system, however, form does more than reflect function: neuronal morphology actively constrains input patterns, synaptic integration, and circuit wiring. During postnatal neurodevelopment, dendritic architectures are assembled and remodeled through genetically encoded programs and activities, transforming molecular programs into circuit architecture. However, dendritic morphogenesis has been difficult to quantify at scale while systematically testing how genetic variants, including neurodevelopmental disorder (NDD) risk genes, alter these structures in vivo. We developed Perturb-CLEAR, which integrates pooled CRISPR screening and whole-mount imaging to quantify brain-wide cytoarchitecture, and paired it with Perturb-seq to link structural phenotypes to transcriptomic changes. Applying Perturb-CLEAR to the developing mouse cortex revealed morphogenesis trajectories accompanied by transcriptomic dynamics. Moreover, systematic perturbation of NDD risk genes uncovered gene-specific multimodal phenotypes. Adnp perturbation remodels basal dendrites in L4/5 IT (intratelencephalic) neurons but not other dendritic compartments or cell types, alongside consistent transcriptional shifts. Combined morphology and transcriptome analyses link NDD risk genes to concordant multimodal cellular phenotypes in the developing brain, highlighting diverse paths of perturbation effect propagation across modalities.

neuroscience↗

bioRxiv2026

Integrating Long-Read Structural Variant Analysis with single-nucleus RNA-seq to Elucidate Gene Expression Effects in Disease

Structural variants (SVs) are a major source of genetic diversity, yet how they impact cell types in complex brain diseases remains largely unexplored, partially due to limitations of short-read sequencing. Here, we addressed this fundamental question in Parkinsons disease (PD). generating long-read whole-genome sequencing (WGS) data for 100 post-mortem brain samples from a PD cohort, constructing a high-confidence catalog of 74,552 SVs. To resolve their functional impact, we integrated single-nucleus RNA-sequencing data from two brain regions from the same samples and focused functional analyses on SVs proximal to genes previously nominated as cis-regulated, potential causal targets of PD-associated GWAS loci. Using expression quantitative trait locus and allele-specific expression analyses, we uncovered SVs significantly associated with expression in specific cell types as well as effects shared across cell types. This study demonstrates the power of uniting long-read WGS with transcriptomics to uncover SVs underlying complex disease architecture with cell type resolution.

genomics↗

bioRxiv2026

In vivo multiomic Perturb-seq with enhanced nuclear gRNA capture

In vivo CRISPR screening with joint transcriptomic and chromatin readouts has been limited by inefficient recovery of gRNAs from nuclei. Here, we developed in vivo multiomic Perturb-seq, an effective platform combining nuclear transcript anchoring with gRNA-specific capture and amplification to enable high-fidelity, high-recovery gRNA assignment and scalable perturbation-resolved single-nucleus multiomics. Applying this platform to interrogate neurodevelopmental disorder risk genes in the developing cortex reveals cell-type-specific transcriptomic and epigenomic perturbation phenotypes.

genomics↗

bioRxiv2026

Disrupted Sleep-Dependent Neural Oscillations and Transcriptomic Changes in the Cacna1g Loss-of-Function Mouse Model Implicated in Schizophrenia

Sleep is an essential biological process for maintaining brain function, and impaired sleep microarchitecture is a well-established feature of schizophrenia (SCZ). Rare loss-of-function variants in CACNA1G, encoding the T-type calcium channel CaV3.1, confer substantial risk for SCZ, implicating sleep-regulatory circuits in disease pathophysiology. Here, we first show that among individuals with SCZ, carriers of rare CACNA1G missense variants exhibit more pronounced alterations in sleep neurophysiology than non-carriers, identifying a human phenotype suggestive of altered channel function. Motivated by this observation, we examined the consequences of Cacna1g loss of function in mice. Cacna1g deficiency produced profound disruptions in sleep microarchitecture, including reduced sleep spindles, altered slow oscillations, impaired spindle-slow oscillation coupling, and reduced cortical synchrony--closely recapitulating neurophysiological signatures observed in individuals with schizophrenia. Beyond sleep structure, Cacna1g loss disrupted the normal coordination of brain rhythms across the 24-hour cycle, most notably abolishing diurnal modulation of theta oscillations. At the molecular level, Cacna1g loss uncoupled sleep-wake state from gene and protein regulation, producing widespread, sleep-phase-biased transcriptional and synaptic alterations across brain regions and cell types, particularly in cortical excitatory neurons. These network and molecular disruptions were accompanied by behavioral hyperactivity during the active phase. Together, these findings establish CACNA1G/CaV3.1 as a key regulator linking sleep-dependent brain dynamics to molecular homeostasis and behavior, and provide a mechanistic framework through which genetic risk for SCZ may drive disease-relevant sleep and circuit dysfunction. One Sentence SummaryLoss of CACNA1G disrupts sleep rhythms and gene regulation, creating a mismatch between brain state and behavior linked to schizophrenia.

neuroscience↗

bioRxiv2025

GPR34 regulation of disease-associated microglial states and responses to physiological stimuli

Expression of the G protein coupled receptor GPR34 is highly enriched in microglia and has been reported to be downregulated in several brain disease contexts, including Alzheimers disease (AD) and multiple sclerosis (MS). GPR34 function is poorly understood, as is its role in regulation of microglial states. Using RNA-sequencing, we find that microglia from Gpr34 knockout (KO) mouse brains exhibited a transcriptomic shift toward disease-associated microglia (DAM) and inflammatory profiles, partially resembling the microglial phenotype seen in 5xFAD AD model mice. Moreover, when Gpr34 KO mice were crossed with 5xFAD mice, the DAM transcriptional profile of microglia and glial pathology were further enhanced beyond the already robust DAM signature driven by 5xFAD alone. This occurred without affecting amyloid plaque burden. Human stem cell-derived microglia (iMGLs) lacking GPR34 showed reduced calcium (Ca{superscript 2}) and phosphorylated ERK (pERK) signaling in response to stimulation with known GPR34 agonists (lyso-phosphatidylserine (lysoPS) and myelin), as well as transcriptomic changes in immune regulation and cell proliferation related pathways. Interestingly, GPR34 KO iMGLs were selectively impaired in phagocytosis of myelin but not amyloid-{beta} (A{beta}) or E. coli, and showed a diminished transcriptional response elicited by myelin. Together, these findings suggest that GPR34 is important for maintaining microglia in a homeostatic state, promotes phagocytosis of and transcriptional response to myelin, and limits microglial activation in neurodegenerative disease conditions.

neuroscience↗

bioRxiv2025

Human brain organoids record the passage of time over multiple years in culture

The human brain develops and matures over an exceptionally prolonged period of time that spans nearly two decades of life. Processes that govern species-specific aspects of human postnatal brain development are difficult to study in animal models. While human brain organoids offer a promising in vitro model, they have thus far been shown to largely mimic early stages of brain development. Here, we developed human brain organoids for an unprecedented 5 years in culture, optimizing growth conditions able to extend excitatory neuron viability beyond previously-known limits. Using module scores of maturation-associated genes derived from a time course of endogenous human brain maturation, we show that brain organoids transcriptionally age with cell type-specificity through these many years in culture. Whole-genome methylation profiling reveals that the predicted epigenomic age of organoids sampled between 3 months and 5 years correlates precisely with time spent in vitro, and parallels epigenomic aging in vivo. Notably, we show that in chimeric organoids generated by mixing neural progenitors derived from "old" organoids with progenitors from "young" organoids, old progenitors rapidly produce late neuronal fates, skipping the production of earlier neuronal progeny that are instead produced by their young counterparts in the same co-cultures. The data indicate that human brain organoids can mature and record the passage of time over many years in culture. Progenitors that age in organoids retain a memory of the time spent in culture reflected in their ability to execute age-appropriate, late developmental programs.

neuroscience↗

bioRxiv2025

Abnormal Lipid Metabolism and Altered Neuronal Support by Astrocytes Lacking Akap11, a Risk Gene for Schizophrenia and Bipolar Disorder

A-Kinase Anchoring Protein 11 (AKAP11) is a shared genetic risk factor for schizophrenia and bipolar disorder, yet its role in the brain remains poorly understood. Through multi-omic analysis of Akap11 mutant mouse brains and cultured astrocytes, we identified significant transcriptomic, proteomic, and metabolomic alterations. Key findings include the upregulation of cholesterol and fatty acid metabolic pathways, accumulation of lipid species such as cholesteryl esters, triacylglycerols, ceramides, and glycerophospholipids, and elevated levels of 3,5-cyclic AMP and protein kinase A (PKA) signaling. These metabolic perturbations manifested as increased lipid droplet accumulation in Akap11 mutant astrocytes, highlighting AKAP11s critical role in regulating intracellular lipid homeostasis. Mechanistically, AKAP11 functions as an autophagy receptor mediating PKA degradation and interacts with endoplasmic reticulum-resident proteins VAP-A and VAP-B through its FFAT motif, providing possible molecular insight into AKAP11s regulation of lipid metabolism. Co-culture experiments with mouse astrocytes and human induced pluripotent stem cell-derived neurons demonstrated that loss of Akap11 in astrocytes, relative to wild-type, increases excitatory neurotransmission and neuronal activity. Collectively, these findings link AKAP11-mediated lipid and synaptic dysregulation to psychiatric disease risk and highlight the potential role of astrocytes in these disorders.

cell biology↗

bioRxiv2025

Meta-analysis of the brain transcriptomes of multiple genetic mouse models of schizophrenia highlights dysregulation in striatum and thalamus

Schizophrenia is a severe mental illness with high heritability, but its underlying mechanisms are poorly understood. We meta-analyzed large-scale brain transcriptomic data from mice harboring individual loss-of-function mutations in seven schizophrenia risk genes (Akap11, Dagla, Gria3, Grin2a, Sp4, Srrm2, Zmym2). While all studied brain regions were affected, the striatum and the thalamus emerged as key brain regions of convergence. Striatum showed downregulation of synapse-and oxidative phosphorylation-related gene sets in all models. In the thalamus, mutants separated into two groups based on transcriptomic phenotype: synapse-related gene sets were upregulated in mutants with only schizophrenia and bipolar association, and were downregulated in mutants that are associated with developmental delay/intellectual disability in addition to schizophrenia. Overall, our meta-analysis reveals convergence and divergence in brain transcriptomic phenotype in these schizophrenia genetic models, supports the involvement of striatal disturbance and synapse dysfunction in schizophrenia, and points to a key role of the thalamus.

neuroscience↗

bioRxiv2025

Systematic evaluation of single-cell multimodal data integration for comprehensive human reference atlas.

The integration of multimodal single-cell data enables comprehensive organ reference atlases, yet its impact remains largely unexplored, particularly in complex tissues. We generated a benchmarking dataset for the renal cortex by integrating 3 and 5 scRNA-seq with joint snRNA-seq and snATAC-seq, profiling 119,744 high-quality nuclei/cells from 19 donors. To align cell identities and enable consistent comparisons, we developed the interpretable machine learning tool scOMM (single-cell Omics Multimodal Mapping) and systematically assessed integration strategies. "Horizontal" integration of scRNA and snRNA-seq improved cell-type identification, while "vertical" integration of snRNA-seq and snATAC-seq had an additive effect, enhancing resolution in homogeneous populations and difficult-to-identify states. Global integration was especially effective in identifying adaptive states and rare cell types, including WFDC2-expressing Thick Ascending Limb and Norn cells, previously undetected in kidney atlases. Our work establishes a robust framework for multimodal reference atlas generation, advancing single-cell analysis and extending its applicability to diverse tissues.

genomics↗

bioRxiv2024

Elevated synaptic PKA activity and abnormal striatal dopamine signaling in Akap11 mutant mice, a genetic model of schizophrenia and bipolar disorder

AbstractLoss-of-function mutations in AKAP11 (a protein kinase A (PKA)-binding protein) greatly increase the risk of bipolar disorder and schizophrenia. To determine the neurobiological functions of AKAP11, we conduct multi-omic and neurobiological analyses of Akap11 mutant mouse brains. We find that AKAP11 is a key regulator of PKA proteostasis in the brain whose loss leads to dramatically increased levels of PKA subunits and phosphorylated PKA substrates, especially in synapses. Akap11 mutant mice show extensive transcriptomic changes throughout the brain, including prominent decreases in synapse-related genes sets. Gene expression is highly impacted in spiny projection neurons of the striatum, a brain region implicated in motivation, cognition and psychotic disorders. Real-time measurements of PKA activity reveal elevated basal PKA activity in the striatum of Akap11-/- mice, with exaggerated additional response to dopamine receptor antagonists. Behaviorally, Akap11 mutant mice show abnormally prolonged locomotor response to amphetamine, deficits in associative learning and contextual discrimination, as well as depression-like behaviors. Our study connects molecular changes to circuit dysfunction and behavioral disturbance in a genetically valid animal model of psychotic disorder.

neuroscience↗

bioRxiv2024

Experimental and Computational Methods for Allelic Imbalance Analysis from Single-Nucleus RNA-seq Data

Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq), and introns are under lower purifying selection and thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. To further investigate ASE in the context of human disease, we applied our methods to a Parkinsons disease cohort of 94 individuals and show that ASE analysis had more power than eQTL analysis to identify significant SNP/gene pairs in our direct comparison of the two methods. Overall, we provide an end-to-end experimental and computational approach for future studies.

genomics↗

bioRxiv2024

Fetal brain response to maternal inflammation requires microglia

In utero infection and maternal inflammation can adversely impact fetal brain development. Maternal systemic illness, even in the absence of direct fetal central nervous system infection, is associated with an increased risk of autism and schizophrenia in affected offspring. The cell types mediating the response of the fetal brain to maternal inflammation are largely unknown, hindering the development of therapies to prevent and treat adverse neuropsychiatric outcomes. Here, we show that microglia, the resident phagocytes of the brain, are enriched for expression of receptors for relevant pathogens and cytokines, throughout embryonic development. Using a rodent maternal immune activation (MIA) model in which polyinosinic:polycytidylic acid is injected into pregnant dams, we demonstrate long-lasting transcriptional changes in fetal microglia that persist into postnatal life. We find that MIA induces widespread gene expression changes in neuronal and non-neuronal cells; importantly, these responses are abolished by selective genetic deletion of microglia, indicating that microglia are required for the transcriptional response of other cortical cell types to MIA. These findings demonstrate that microglia play a critical, durable role in fetal response to maternal inflammation, pointing at microglia as a potential therapeutic cell target.

neuroscience↗

bioRxiv2024

Neuronal-class specific molecular cues drive differential myelination in the neocortex

In the neocortex, oligodendrocytes produce distinct amounts of myelin in each cortical layer and along the axons of individual neuron types. Here we present a comprehensive single-cell molecular map of mouse cortical oligodendrocytes across different cortical layers and stages of myelination, spanning the initiation of cortical myelination into adulthood. We apply this dataset to show that neuron-class specific signals drive oligodendrocyte maturation and differential myelination across cortical layers. We find that each layer contains a similar compendium of oligodendrocyte classes, indicating that oligodendrocyte heterogeneity cannot explain layer-specific myelination. To evaluate whether neuronal diversity drives differential myelination across cortical layers, we generated a predicted ligand-receptor interactome between projection neuron types and oligodendrocyte states, across cortical layers and time. In vivo functional testing identified Fgf18, Ncam1, and Rspo3 as novel, neuron-derived pro-myelinating signals. Our results highlight neuron-class-dependent control of myelin distribution in the neocortex.

neuroscience↗

bioRxiv2023

Multi-donor human cortical Chimeroids reveal individual susceptibility to neurotoxic triggers

Inter-individual genetic variation affects the susceptibility to and progression of many diseases. Efforts to study the molecular mechanisms mediating the impact of human genetic variation on normal development and disease phenotypes are limited, however, by the paucity of faithful cellular human models, and the difficulty of scaling current systems to represent multiple individuals. Here, we present human brain "Chimeroids", a highly reproducible, multi-donor human brain cortical organoid model generated by the co-development of cells from a panel of individual donors in a single organoid, while maintaining fidelity to endogenous tissue. By reaggregating cells from multiple single-donor organoids at the neural stem or committed progenitor cell stage, we generate Chimeroids in which each donor produces all cell lineages of the cerebral cortex, even when using pluripotent stem cell lines with notable growth biases. We leveraged Chimeroids to investigate inter-individual variation in susceptibility to neurotoxic stressors that exhibit high clinical phenotypic variability: ethanol and the anti-epileptic drug valproic acid. Individual donors varied in both the penetrance of the effect on target cell types, and the molecular phenotype within each affected cell type. Our results show that human genetic background may be an important mediator of neurotoxin susceptibility and introduce Chimeroids as a scalable system for high-throughput investigation of the contribution of human genetic variation to brain development and disease.

neuroscience↗

bioRxiv2023

Massively parallel in vivo Perturb-seq reveals cell type-specific transcriptional networks in cortical development

Systematic analysis of gene function across diverse cell types in vivo is hindered by two challenges: obtaining sufficient cells from live tissues and accurately identifying each cells perturbation in high-throughput single-cell assays. Leveraging AAVs versatile cell type tropism and high labeling capacity, we expanded the resolution and scale of in vivo CRISPR screens: allowing phenotypic analysis at single-cell resolution across a multitude of cell types in the embryonic brain, adult brain, and peripheral nervous system. We undertook extensive tests of 86 AAV serotypes, combined with a transposon system, to substantially amplify labeling and accelerate in vivo gene delivery from weeks to days. Using this platform, we performed an in utero genetic screen as proof-of-principle and identified pleiotropic regulatory networks of Foxg1 in cortical development, including Layer 6 corticothalamic neurons where it tightly controls distinct networks essential for cell fate specification. Notably, our platform can label >6% of cerebral cells, surpassing the current state-of-the-art efficacy at <0.1% (mediated by lentivirus), and achieve analysis of over 30,000 cells in one experiment, thus enabling massively parallel in vivo Perturb-seq. Compatible with various perturbation techniques (CRISPRa/i) and phenotypic measurements (single-cell or spatial multi-omics), our platform presents a flexible, modular approach to interrogate gene function across diverse cell types in vivo, connecting gene variants to their causal functions.

neuroscience↗

bioRxiv2023

Lupus autoantibodies initiate a maladaptive equilibrium sustained by HMGB1:RAGE signaling and reversed by LAIR-1:C1q signaling

Cognitive impairment is a frequent manifestation of neuropsychiatric systemic lupus erythematosus (NPSLE), present in up to 80% of patients and leading to a diminished quality of life. We have developed a model of lupus-like cognitive impairment which is initiated when anti-DNA, anti-N-methyl D-aspartate receptor (NMDAR) cross-reactive antibodies, which are present in 30% of SLE patients, penetrate the hippocampus. This leads to immediate, self-limited excitotoxic death of CA1 pyramidal neurons followed by a significant loss of dendritic arborization in the remaining CA1 neurons and impaired spatial memory. Both microglia and C1q are required for dendritic loss. Here we show that this pattern of hippocampal injury creates a maladaptive equilibrium that is sustained for at least one year. It requires HMGB1 secretion by neurons to bind RAGE, a receptor for HMGB1 expressed on microglia, and leads to decreased expression of microglial LAIR-1, an inhibitory receptor for C1q. The angiotensin converting enzyme (ACE) inhibitor captopril, which can restore a healthy equilibrium, microglial quiescence, and intact spatial memory, leads to upregulation of LAIR-1. This paradigm highlights HMGB1:RAGE and C1q:LAIR-1 interactions as pivotal pathways in the microglial-neuronal interplay that defines a physiologic versus a maladaptive equilibrium.

immunology↗

bioRxiv2022

The effect of background noise and its removal on the analysis of single-cell expression data

BACKGROUNDIn droplet-based single-cell and single-nucleus RNA-seq experiments, not all reads associated with one cell barcode originate from the encapsulated cell. Such background noise is attributed to spillage from cell-free ambient RNA or barcode swapping events. Here, we characterize this background noise exemplified by three single-cell RNA-seq (scRNA-seq) and two single-nucleus RNA-seq (snRNA-seq) replicates of mouse kidney cells. For each experiment, kidney cells from two mouse subspecies were pooled, allowing to identify cross-genotype contaminating molecules and estimate the levels of background noise. RESULTSWe find that background noise is highly variable across replicates and individual cells, making up on average 3-35% of the total counts (UMIs) per cell and show that this has a considerable impact on the specificity and detectability of marker genes. In search of the source of background noise, we find that expression profiles of cell-free droplets are very similar to expression profiles of cross-genotype contamination and hence that the majority of background molecules originates from ambient RNA. Finally, we use our genotype-based estimates to evaluate the performance of three methods (CellBender, DecontX, SoupX) that are designed to quantify and remove background noise. We find that CellBender provides the most precise estimates of background noise levels and also yields the highest improvement for marker gene detection. By contrast, clustering and classification of cells are fairly robust towards background noise and only small improvements can be achieved by background removal that may come at the cost of distortions in fine structure. CONCLUSIONOur findings help to better understand the extent, sources and impact of background noise in single-cell experiments and provide guidance on how to deal with it.

bioinformatics↗