Biology subjects

Bendl, J.

Publications and source records attributed to Bendl, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Human Choroid Plexus Organoids Progress to Postnatal-like Maturation and Reveal a Closing Window of Developmental Plasticity

The choroid plexus (ChP) produces cerebrospinal fluid (CSF) and forms the blood-CSF barrier, yet the developmental programme driving its maturation in humans remains poorly understood. Using a 15-timepoint single-cell RNA sequencing atlas of human ChP organoids benchmarked against human tissue, we resolve an ordered differentiation process comprising cell cycle exit, ciliogenesis and ion transporter expression. Maturation culminates in a transcriptional state with features of human adult ChP, establishing the first in vitro ChP model to reach postnatal-like milestones. Centrosome proteomics identified previously uncharacterised, stage-specific regulators of ciliogenesis. To probe developmental plasticity, we perturbed ChP organoids with valproic acid (VPA), a clinically used antiepileptic and established teratogen. Early VPA-mediated disruption of multiciliogenesis and secretion recovered upon drug withdrawal, whereas late treatment washout resulted in persistent impairment of mature transporters. Together, these findings resolve the developmental programme by which the ChP reaches functionally mature identity and identify a stage-dependent plasticity window during its maturation.

developmental biology↗

bioRxiv2025

Cell-type-resolved NRXN1 isoforms across human brain tissues and hiPSC organoids

NRXN1 undergoes extensive alternative splicing that generates a highly diverse repertoire of isoforms, diversifying protein-protein interactions, shaping synaptic specialization, and contributing to neuropsychiatric disease when disrupted. However, the splicing landscape of NRXN1 across distinct human brain cell types remains poorly defined. Because NRXN1 expression level is relatively low in adult brains and human induced pluripotent stem cell (hiPSC) derived neurons, single-cell long-read cDNA sequencing often provides insufficient coverage to capture its full isoform diversity, particularly across heterogeneous cell populations. To address this gap, we developed an integrative sequencing strategy that combines single-cell transcriptomics, targeted enrichment of NRXN1 transcripts, and long-read sequencing. This approach reveals a comprehensive catalog of cell-type resolved NRXN1 isoforms across adult and fetal human postmortem brains as well as hiPSC-derived cortical organoids. From the adult prefrontal cortex (PFC) region, our analyses reveal distinct splicing programs across interneuron subtypes, pyramidal neurons, and glial lineages. Comparisons between prenatal and adult brains indicate that NRXN1 isoform profiles are established during early development and remain stable throughout neuronal maturation. In hiPSC organoid models, splicing profiles partially mirror both developmental and mature brain patterns, with a subset of splice sites exhibiting cell type - and stage-specific divergence. In the cerebellum of an autism case and in organoids derived from schizophrenia patients, carrying non-recurrent heterozygous NRXN1 deletions, we identify disrupted isoform expression and mutant NRXN1 isoforms and characterize their distribution across diverse cell types. Using this integrated long-read sequencing framework in patient-derived organoids, we further show that antisense oligonucleotide (ASO) targeting of mutant splice junctions reduces gain-of-function NRXN1 isoforms and reshapes splicing patterns in a cell type-specific manner, providing a platform for evaluating ASO efficiency. Together, these findings help understand the cell type-specific splicing landscape of NRXN1 and establish a framework for decoding cell type-specific isoform diversity and assessing transcript-targeted therapies for genes with low expression levels.

neuroscience↗

bioRxiv2024

In vitro genotoxic and mutagenic potentials of combustion particles from marine fuels with different sulfur contents

Ship emissions cause serious environmental impacts and adverse effects toward human health. Therefore, the International Maritime Organization (IMO) restricted the fuel sulfur content (FSC) of marine fuels: FSC must be <0.5% m/m or <0.1% m/m in sulfur emission control areas, covering a range of fuels from distillate diesel-like fuels to low-sulfur heavy fuel oils (HFOs). As a result, ship emissions, e.g., sulfur oxides and particulate matter (PM) have been reduced. However, how FSC correlates with the toxicological potential of ship emissions is still uncertain. The objective of this study was to understand how the physical and chemical properties of particulate emissions from a marine engine operating on five marine fuels with different FSCs influence their toxicological outcome. For this scope, cytotoxic, genotoxic, mutagenic, and pro-inflammatory potentials of collected particles were evaluated in lung cell model systems. The involvement of intracellular reactive oxygen species and xenobiotic metabolism was also explored. While PM from different fuels combustion resulted in up to approximately 20% of reduction of cytotoxicity at the highest concentration, other toxicological outcomes, including clonogenic and genotoxic potentials, showed a stronger trend with the polycyclic aromatic hydrocarbon contents in PM compared with FSC. This trend was supported by evidence of a significant increase in gene mutation frequency and alterations in cellular mechanisms induced by an aromatic-rich HFO with an intermediate FSC. In conclusion, apart from reducing FSC in marine fuels, additional particle abatement systems should be considered to reduce the adverse effects of particulate emissions from shipping operations on human health.

pharmacology and toxicology↗

bioRxiv2024

Single-cell genomics and regulatory networks for 388 human brains

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized [~]250 disease-risk genes and drug targets with associated cell types. Summary Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/585576v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@70b24org.highwire.dtl.DTLVardef@6c9eddorg.highwire.dtl.DTLVardef@131fae2org.highwire.dtl.DTLVardef@4e0f1e_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2023

A public resource of single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of technologies that can support high-throughput profiling of single cell transcriptomes offers to revolutionize the study of brain tissue from persons with and without Alzheimers disease (AD). Integration of these data with additional complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link observed cell subpopulations and molecular network features within a broader disease-relevant context. We report here single nucleus RNA sequencing (snRNA-seq) profiles generated from superior frontal gyrus cortical tissue samples from 101 exceptionally well characterized, aged subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in peripheral hematological lab parameters, with these observations replicated in an independent, prospective cohort study of ageing and dementia. We also observed an AD-associated CD83(+) microglial subtype with unique molecular networks that encompass many known regulators of AD-relevant microglial biology, and which are associated with immunoglobulin IgG4 production in the transverse colon. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal novel disease biology. The transcriptomic, genetic, phenotypic, and network data resources described within this study are available for access and utilization by the scientific community.

genomics↗

bioRxiv2023

ZBTB7A regulates MDD-specific chromatin signatures and astrocyte-mediated stress vulnerability in orbitofrontal cortex

Hyperexcitability in the orbitofrontal cortex (OFC) is a key clinical feature of anhedonic domains of Major Depressive Disorder (MDD). However, the cellular and molecular substrates underlying this dysfunction remain unknown. Here, cell-population-specific chromatin accessibility profiling in human OFC unexpectedly mapped genetic risk for MDD exclusively to non-neuronal cells, and transcriptomic analyses revealed significant glial dysregulation in this region. Characterization of MDD-specific cis-regulatory elements identified ZBTB7A - a transcriptional regulator of astrocyte reactivity - as an important mediator of MDD-specific chromatin accessibility and gene expression. Genetic manipulations in mouse OFC demonstrated that astrocytic Zbtb7a is both necessary and sufficient to promote behavioral deficits, cell-type-specific transcriptional and chromatin profiles, and OFC neuronal hyperexcitability induced by chronic stress - a major risk factor for MDD. These data thus highlight a critical role for OFC astrocytes in stress vulnerability and pinpoint ZBTB7A as a key dysregulated factor in MDD that mediates maladaptive astrocytic functions driving OFC hyperexcitability.

neuroscience↗

bioRxiv2023

Efficient differential expression analysis of large-scale single cell transcriptomics data using dreamlet

Advances in single-cell and -nucleus transcriptomics have enabled generation of increasingly large-scale datasets from hundreds of subjects and millions of cells. These studies promise to give unprecedented insight into the cell type specific biology of human disease. Yet performing differential expression analyses across subjects remains difficult due to challenges in statistical modeling of these complex studies and scaling analyses to large datasets. Our open-source R package dreamlet (DiseaseNeurogenomics.github.io/dreamlet) uses a pseudobulk approach based on precision-weighted linear mixed models to identify genes differentially expressed with traits across subjects for each cell cluster. Designed for data from large cohorts, dreamlet is substantially faster and uses less memory than existing workflows, while supporting complex statistical models and controlling the false positive rate. We demonstrate computational and statistical performance on published datasets, and a novel dataset of 1.4M single nuclei from postmortem brains of 150 Alzheimers disease cases and 149 controls.

genomics↗

bioRxiv2023

Genetic regulation of cell-type specific chromatin accessibility shapes the etiology of brain diseases

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are major risk factors of human disease. We measured chromatin accessibility in sorted neurons and glia from 1,932 samples of human postmortem brain and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTL). Only 10.4% of caQTL are shared between neurons and glia, supporting the cell type specificity of genetic regulation of the brain regulome. Incorporating allele specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms underlying disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs, identifying the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides novel insights into brain disease etiology. One sentence summaryCell-type specific chromatin accessibility QTL reveals regulatory mechanisms underlying brain diseases.

genomics↗

bioRxiv2022

Multi-omic profiling of the developing human cerebral cortex at the single cell level

The cellular complexity of the human brain is established via dynamic changes in gene expression throughout development that is mediated, in part, by the spatiotemporal activity of cis-regulatory elements. We simultaneously profiled gene expression and chromatin accessibility in 45,549 cortical nuclei across 6 broad developmental time-points from fetus to adult. We identified cell-type specific domains in which chromatin accessibility is highly correlated with gene expression. Differentiation pseudotime trajectory analysis indicates that chromatin accessibility at cis-regulatory elements precedes transcription and that dynamic changes in chromatin structure play a critical role in neuronal lineage commitment. In addition, we mapped cell-type and temporally specific genetic loci implicated in neuropsychiatric traits, including schizophrenia and bipolar disorder. Together, our results describe the complex regulation of cell composition at critical stages in lineage determination, serve as a developmental blueprint of the human brain and shed light on the impact of spatiotemporal alterations in gene expression on neuropsychiatric disease. One-Sentence SummarySimultaneous profiling of gene expression and chromatin accessibility in single nuclei from 6 developmental time-points sheds light on cell fate determination in the human cerebral cortex and on the molecular basis of neuropsychiatric disease.

neuroscience↗

bioRxiv2022

Transcriptome and chromatin accessibility landscapes across 25 distinct human brain regions expand the susceptibility gene set for neuropsychiatric disorders

Brain region- and cell-specific transcriptomic and epigenomic molecular features are associated with heritability for neuropsychiatric traits, but a systematic view, considering cortical and subcortical regions, is lacking. Here, we provide an atlas of chromatin accessibility and gene expression in neuronal and non-neuronal nuclei across 25 distinct human cortical and subcortical brain regions from 6 neurotypical controls. We identified extensive gene expression and chromatin accessibility differences across brain regions, including variation in alternative promoter-isoform usage and enhancer-promoter interactions. Genes with distinct promoter-isoform usage across brain regions are strongly enriched for neuropsychiatric disease risk variants. Using an integrative approach, we characterized the function of the brain region-specific chromatin co-accessibility and gene-coexpression modules that are robustly associated with genetic risk for neuropsychiatric disorders. In addition, we identified a novel set of genes that is enriched for disease risk variants but is independent of cell-type specific gene expression and known susceptibility pathways. Our results provide a valuable resource for studying molecular regulation across multiple regions of the human brain and suggest a unique contribution of epigenetic modifications from subcortical areas to neuropsychiatric disorders.

neuroscience↗

bioRxiv2022

DeepGAMI: Deep biologically guided auxiliary learning for multimodal integration and imputation to improve phenotype prediction

Genotype-phenotype association is found in many biological systems, such as brain-related diseases and behavioral traits. Despite the recent improvement in the prediction of phenotypes from genotypes, they can be further improved and explainability of these predictions remains challenging, primarily due to complex underlying molecular and cellular mechanisms. Emerging multimodal data enables studying such mechanisms at different scales from genotype to phenotypes involving intermediate phenotypes like gene expression. However, due to the black-box nature of many machine learning techniques, it is challenging to integrate these multi-modalities and interpret the biological insights in prediction, especially when some modality is missing. Biological knowledge has recently been incorporated into machine learning modeling to help understand the reasoning behind the choices made by these models. To this end, we developed DeepGAMI, an interpretable deep learning model to improve genotype-phenotype prediction from multimodal data. DeepGAMI uses prior biological knowledge to define the neural network architecture. Notably, it embeds an auxiliary-learning layer for cross-modal imputation while training the model from multimodal data. Using this pre-trained layer, we can impute latent features of additional modalities and thus enable predicting phenotypes from a single modality only. Finally, the model uses integrated gradient to prioritize multimodal features and links for phenotypes. We applied DeepGAMI to multiple emerging multimodal datasets: (1) population-level genotype and bulk-tissue gene expression data for predicting schizophrenia, (2) population-level genotype and gene expression data for predicting clinical phenotypes in Alzheimers Disease, (3) gene expression and electrophysiological data of single neuronal cells in the mouse visual cortex, and (4) cell-type gene expression and genotype data for predicting schizophrenia. We found that DeepGAMI outperforms existing state-of-the-art methods and provides a profound understanding of gene regulatory mechanisms from genotype to phenotype, especially at cellular resolution. DeepGAMI is an open-source tool and is available at https://github.com/daifengwanglab/DeepGAMI.

bioinformatics↗

bioRxiv2021

From compartments to gene loops: Functions of the 3D genome in the human brain

The 3D genome plays a key role in the regulation of gene expression. However, little is known about the spatiotemporal organization of chromatin during human brain development. We investigated the 3D genome in human fetal cortical plate and in adult prefrontal cortical neurons and glia. We found that neurons have weaker compartments than glia that emerge during fetal development. Furthermore, neurons form loop domains whereas glia form compartment domains. We show through CRISPRi on CNTNAP2 that transcription is coupled to loop domain insulation. Gene regulation during neural development involves increased use of enhancer-promoter and repressor-promoter loops. Finally, transcription is associated with gene loops. Altogether, we provide novel insights into the relationship between gene expression and different scales of chromatin organization in the human brain.

genomics↗

bioRxiv2021

Acetylated Chromatin Domains Link Chromosomal Organization to Cell- and Circuit-level Dysfunction in Schizophrenia and Bipolar Disorder

To explore modular organization of chromosomes in schizophrenia (SCZ) and bipolar disorder (BD), we applied population-scale correlational structuring of 739 histone H3-lysine 27 acetylation and H3-lysine 4 trimethylation profiles, generated from the prefrontal cortex (PFC) of 568 cases and controls. Neuronal histone acetylomes and methylomes assembled as thousands of cis-regulatory domains (CRDs), revealing fine-grained, kilo-to megabase scale chromatin organization at higher resolution but firmly integrated into Hi-C chromosomal conformations. Large clusters of domains that were hyperacetylated in disease shared spatial positioning within the nucleus, predominantly regulating PFC projection neuron function and excitatory neurotransmission. Hypoacetylated domains were linked to inhibitory interneuron- and myelination-relevant genes. Chromosomal modular architecture is affected in SCZ and BD, with hyperacetylated domains showing unexpectedly strong convergences defined by cell type, nuclear topography, genetic risk, and active chromatin state across a wide developmental window.

genomics↗

bioRxiv2021

Transcribed enhancers in the human brain identify novel disease risk mechanisms

Identification of risk variants for neuropsychiatric diseases within enhancers underscores the importance of understanding the population-level variation of enhancers in the human brain. Besides regulating tissue- and cell-type-specific transcription of target genes, enhancers themselves can be transcribed. We expanded the catalog of known human brain transcribed enhancers by an order of magnitude by generating and jointly analyzing large-scale cell-type-specific transcriptome and regulome data. Examination of the transcriptome in 1,382 brain samples in two independent cohorts identified robust expression of transcribed enhancers. We explored gene-enhancer coordination and found that enhancer-linked genes are strongly implicated in neuropsychiatric disease. We identified significant expression quantitative trait loci (eQTL) for 25,958 enhancers which mediate 6.8% of schizophrenia heritability, mostly independent from standard gene eQTL. Inclusion of enhancer eQTL in transcriptome-wide association studies enhanced functional interpretation of disease loci. Overall, our study characterizes the enhancer-gene regulome and genetic mechanisms in the human cortex in both healthy and disease states.

neuroscience↗

bioRxiv2021

The three-dimensional landscape of chromatin accessibility in Alzheimer's disease

Much is still unknown about the neurobiology of Alzheimers disease (AD). To better understand AD, we generated 636 ATAC-seq libraries from cases and controls to construct detailed genomewide chromatin accessibility maps of neurons and non-neurons from two AD-affected brain regions, the entorhinal cortex and superior temporal gyrus. By analyzing a total of 19.6 billion read pairs, we expanded the known repertoire of regulatory sequences in the human brain. Multi-omic data integration associated global patterns of chromatin accessibility with gene expression and identified cell-specific enhancer-promoter interactions. Using inter-individual variation in chromatin accessibility, we define cis-regulatory domains capturing the 3D structure of the genome. Multifaceted analyses uncovered disease associated perturbations impacting chromatin accessibility, transcription factor regulatory networks and the 3D genome, and implicated transcriptional dysregulation in AD. Overall, we applied a systematic approach to understand the role of the 3D genome in AD and to illuminate novel disease biology that can advance diagnosis and therapy.

neuroscience↗

bioRxiv2020

Sex differences in the human brain transcriptome of cases with schizophrenia

While schizophrenia differs between males and females in age of onset, symptomatology and the course of the disease, the molecular mechanisms underlying these differences remain uncharacterized. In order to address questions about the sex-specific effects of schizophrenia, we performed a large-scale transcriptome analysis of RNA-seq data from 437 controls and 341 cases from two distinct cohorts from the CommonMind Consortium. Analysis across the cohorts identifies a reproducible gene expression signature of schizophrenia that is highly concordant with previous work. Differential expression across sex is reproducible across cohorts and identifies X- and Y-linked genes, as well as those involved in dosage compensation. Intriguingly, the sex expression signature is also enriched for genes involved in neurexin family protein binding and synaptic organization. Differential expression analysis testing a sex-by-diagnosis interaction effect did not identify any genome-wide signature after multiple testing corrections. Gene coexpression network analysis was performed to reduce dimensionality and elucidate interactions among genes. We found enrichment of co-expression modules for sex-by-diagnosis differential expression signatures, which were highly reproducible across the two cohorts and involve a number of diverse pathways, including neural nucleus development, neuron projection morphogenesis, and regulation of neural precursor cell proliferation. Overall, our results indicate that the effect size of sex differences in schizophrenia gene expression signatures is small and underscore the challenge of identifying robust sex-by-diagnosis signatures, which will require future analyses in larger cohorts.

genomics↗

bioRxiv2020

Common variants contribute to intrinsic functional architecture of human brain

The human brain remains active in the absence of explicit tasks and forms networks of correlated activity. Resting-state functional magnetic resonance imaging (rsfMRI) measures brain activity at rest, which has been linked with both cognitive and clinical outcomes. The genetic variants influencing human brain function are largely unknown. Here we utilized rsfMRI from 44,190 individuals of multiple ancestries (37,339 in the UK Biobank) to discover and validate the common genetic variants influencing intrinsic brain activity. We identified hundreds of novel genetic loci associated with intrinsic functional signatures (P < 2.8 x 10-11), including associations to the central executive, default mode, and salience networks involved in the triple network model of psychopathology. A number of intrinsic brain activity associated loci colocalized with brain disorder GWAS (e.g., Alzheimers disease, Parkinsons disease, schizophrenia) and cognition, such as 19q13.32, 17q21.31, and 2p16.1. Particularly, we detected a colocalization between one (rs429358) of the two variants in the APOE {varepsilon}4 locus and function of the default mode, central executive, attention, and visual networks. Genetic correlation analysis demonstrated shared genetic influences between brain function and brain structure in the same regions. We also detected significant genetic correlations with 26 other complex traits, such as ADHD, major depressive disorder, schizophrenia, intelligence, education, sleep, subjective well-being, and neuroticism. Common variants associated with intrinsic brain activity were enriched within regulatory element in brain tissues.

genetics↗

bioRxiv2020

Transcriptional and epigenetic characterization of early striosomes identifies Foxf2 and Olig2 as factors required for development of striatal compartmentation and neuronal phenotypic differentiation

The basal ganglia, best known for processing information required for multiple aspects of movement, is also part of a network which regulates reward and cognition. The major output nucleus of the basal ganglia is the striatum, and its functions are dependent on neuronal compartmentation, including striosomes and matrix, which are selectively affected in disease. Striatal projection neurons are GABAergic medium spiny neurons (MSNs), all of which share basic molecular signatures but are subtyped by selective expression of receptors, neuropeptides, and other gene families. Neurogenesis of the striosome and matrix occurs in separate waves, but the factors regulating terminal neuronal differentiation following migration are largely unidentified. We performed RNA- and ATAC-seq on sorted murine striosome and matrix cells at postnatal day 3. Focusing on the striosomal compartment, we validated the localization and role of transcription factors and their regulator(s), previously not known to be associated with striatal development, including Irx1, Foxf2, Olig2 and Stat1/2. In addition, we validated the enhancer function of a striosome-specific open chromatin region located 15Kb downstream of the Olig2 gene. These data and data bases provide novel tools to dissect and manipulate the networks regulating MSN compartmentation and differentiation and thus provide new approaches to establishing MSN subtypes from human iPSCs for disease modeling and drug discovery.

neuroscience↗