Biology subjects

Fullard, J. F.

Publications and source records attributed to Fullard, J. F..

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↗

bioRxiv2026

Cross-source proteogenomic profiling of human microglia reveals a conserved core membrane protein and HERV signature

Microglia are essential immune cells of the brain parenchyma which are responsible for maintaining homeostasis and responding to brain injury. When activated, they induce immune signaling and become phagocytic. In the context of neurodegenerative diseases, they exhibit both pro- and anti-inflammatory properties. Human endogenous retroviruses (HERVs) are the remnants of ancient retroviral germline infections that integrated into the human genome, and their expression has been directly linked to microglial-mediated neurodegenerative diseases. Despite this, HERV expression is not consistently included in analyses characterizing microglia. Investigating the function of microglia across different diseases is critical for elucidating mechanisms of disease progression and for the development of effective therapeutic interventions. Approaches to studying microglia include isolation from post-mortem brain tissues, differentiation from peripheral blood monocytes or differentiation of induced pluripotent stem cells (iPSC). Ex vivo brain derived microglia (BdMG) are considered most physiologically relevant, but constraints including the unpredictable timing of availability, labor-intensive protocols, and low yields reduce their practicality. Existing alternatives are iPSC-derived microglia (iMG) and monocyte-derived microglia (MDMi) models that circumvent sample accessibility and scalability issues. Here, we explored the transcriptome and proteome of these three microglia sources and identified a common microglia surface marker expression profile, establishing that MDMi and iMG exhibit similar phenotypes relative to BdMG. We also identified a common HERV expression profile across BdMG, iMG and MDMi, indicating deeper similarities across different sources. Altogether, our findings indicate that given the phenotypic similarities of the 2 models, MDMi represent a practical and reliable model for investigating microglial function with iMG models serving for more molecular based approaches, such as CRISPRa/i.

neuroscience↗

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

Transcriptional correlates of cocaine-associated learning in striatal ARC ensembles.

Learned associations between the rewarding effects of drugs and the context in which they are experienced underlie context-induced relapse. Previous work demonstrates the importance of sparse neuronal populations - called neuronal ensembles - in associative learning and cocaine seeking, but it remains unknown whether the encoding vs. retrieval of cocaine-associated memories involves similar or distinct mechanisms of ensemble activation and reactivation in nucleus accumbens (NAc). We use ArcCreERT2 mice to establish that mostly distinct NAc ensembles are recruited by initial vs. repeated exposures to cocaine, which are then differentially reactivated and exert distinct effects during cocaine-related memory retrieval. Single-nuclei RNA-sequencing of these ensembles demonstrates predominant recruitment of D1 medium spiny neurons and identifies transcriptional properties that are selective to cocaine-recruited NAc neurons and could explain distinct excitability features. These findings fundamentally advance our understanding of how cocaine drives pathological memory formation during repeated exposures.

neuroscience↗

bioRxiv2023

Dopaminoceptive D1 and D2 neurons in ventral hippocampus arbitrate approach and avoidance in anxiety

The hippocampus 1-7, as well as dopamine circuits 8-11, coordinate decision-making in anxiety-eliciting situations. Yet, little is known about how dopamine modulates hippocampal representations of emotionally-salient stimuli to inform appropriate resolution of approach versus avoidance conflicts. We here study dopaminoceptive neurons in mouse ventral hippocampus (vHipp), molecularly distinguished by their expression of dopamine D1 or D2 receptors. We show that these neurons are transcriptionally distinct and topographically organized across vHipp subfields and cell types. In the ventral subiculum where they are enriched, both D1 and D2 neurons are recruited during anxiogenic exploration, yet with distinct profiles related to investigation and behavioral selection. In turn, they mediate opposite approach/avoidance responses, and are differentially modulated by dopaminergic transmission in that region. Together, these results suggest that vHipp dopamine dynamics gate exploratory behaviors under contextual uncertainty, implicating dopaminoception in the complex computation engaged in vHipp to govern emotional states.

neuroscience↗

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

Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data

Sample-wise deconvolution methods have been developed to estimate cell-type proportions and gene expressions in bulk-tissue samples. However, the performance of these methods and their biological applications has not been evaluated, particularly on human brain transcriptomic data. Here, nine deconvolution methods were evaluated with sample-matched data from bulk-tissue RNAseq, single-cell/nuclei (sc/sn) RNAseq, and immunohistochemistry. A total of 1,130,767 nuclei/cells from 149 adult postmortem brains and 72 organoid samples were used. The results showed the best performance of dtangle for estimating cell proportions and bMIND for estimating sample-wise cell-type gene expression. For eight brain cell types, 25,273 cell-type eQTLs were identified with deconvoluted expressions (decon-eQTLs). The results showed that decon-eQTLs explained more schizophrenia GWAS heritability than bulk-tissue or single-cell eQTLs alone. Differential gene expression associated with multiple phenotypes were also examined using the deconvoluted data. Our findings, which were replicated in bulk-tissue RNAseq and sc/snRNAseq data, provided new insights into the biological applications of deconvoluted data.

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↗

bioRxiv2022

Convergent impact of schizophrenia risk genes

Genetic studies of schizophrenia reveal a complex polygenic risk architecture comprised of hundreds of risk variants; most are common in the population at-large, non-coding, and act by genetically regulating the expression of one or more gene targets ("eGenes"). It remains unclear how genetic variants predicted to confer individually small effects combine to yield substantial clinical impacts in aggregate. Here, we demonstrate that eGenes have shared downstream transcriptomic effects ("convergence") that may underlie unexpected interactions ("non-additive effects") observed when eGenes are manipulated in combination. We apply a pooled CRISPR approach to perturb schizophrenia eGenes in human induced pluripotent stem cell-derived glutamatergic neurons. The strength and specificity of convergence increased between functionally similar eGenes. Predicting that convergence might impact additive relationships between risk loci when inherited together, we use an arrayed approach to explore bidirectional combinatorial perturbations of a partially overlapping set of fifteen schizophrenia eGenes. When specifically considering groups of synaptic or epigenetic eGenes, combinatorial eGene perturbations yield changes that are smaller than predicted by summing individual eGene effects ("sub-additive effects"). Moreover, convergent and non-additive downstream transcriptomic effects overlap, suggesting that functional redundancy of eGenes may be a major mechanism underlying non-additivity. Combinatorial perturbations result in outcomes that are not yet well-predicted by single eGene perturbations alone, indicating that the effects of polygenic risk cannot necessarily be extrapolated from experiments testing one risk gene at a time.

neuroscience↗

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

A comprehensive series of temporal transcription factors in the fly visual system

The brain consists of thousands of different neuronal types that are generated through multiple divisions of neuronal stem cells. These stem cells have the capacity to generate different neuronal types at different stages of their development. In Drosophila, this temporal patterning is driven by the successive expression of temporal transcription factors (tTFs). While a number of tTFs are known in different animals and across various parts of the nervous system, these have been mostly identified by informed guesses and antibody availability. We used single-cell mRNA sequencing to identify the complete series of tTFs that specify most Drosophila medulla neurons in the optic lobe. We tested the genetic interactions among these tTFs. While we verify the general principle that tTFs regulate the progression of the series by activating the next tTFs in the series and repressing the previous ones, we also identify more complex regulations. Two of the tTFs, Eyeless and Dichaete, act as hubs integrating the input of several upstream tTFs before allowing the series to progress and in turn regulating the expression of several downstream tTFs. Moreover, we show that tTFs not only specify neuronal identity by controlling the expression of cell type-specific genes. Finally, we describe the very first steps of neuronal differentiation and find that terminal differentiation genes, such as neurotransmitter-related genes, are present as transcripts, but not as proteins, in immature larval neurons days before they are being used in functioning neurons; we show that these mechanisms are conserved in humans. Our results offer a comprehensive description of a temporal series of tTFs in a neuronal system, offering mechanistic insights into the regulation of the progression of the series and the regulation of neuronal diversity. This represents a proof-of-principle for the use of single-cell mRNA sequencing for the comparison of temporal patterning across phyla that can lead to an understanding of how the human brain develops and how it has evolved.

developmental biology↗

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↗