John F. Fullard

The paper maps gene expression, chromatin accessibility, and DNA methylation in developing human brain cells to understand regulatory interactions and their role in disease.

This study uses single-cell RNA sequencing to track the maturation of human choroid plexus organoids and identifies a stage-dependent window of developmental plasticity.

This study compares transcriptome and proteome profiles of three microglia sources, identifying shared surface markers and HERV expression patterns, suggesting MDMi as a practical model for functional studies.

The paper introduces dreamlet, an R package for efficient differential expression analysis of large-scale single-cell transcriptomics data, showing improved speed and memory usage compared to existing methods.

This study performs a single-nucleus transcriptome-wide association study to identify gene-trait associations in brain disorders, revealing cell-type-specific genetic regulation and ancestry-specific patterns.

The paper constructs a single-nucleus atlas of genetic regulation in the human brain, identifying cell-type-specific regulatory effects and disease-associated genes.

The paper profiles human myeloid cells across aging and Alzheimer's disease, identifies AD-associated changes, and links GPNMB to neuroprotection via TREM2.

The paper identifies three gene regulatory states associated with cognitive resilience and pathogenesis in Alzheimer's disease using single-cell data from the dorsolateral prefrontal cortex.

The paper introduces ME-seq, a technology that profiles DNA methylation, gene expression, and chromatin accessibility in single nuclei, revealing early microglial priming in Alzheimer's disease.

The paper constructs a single-cell transcriptomic atlas of the human dorsolateral prefrontal cortex across neurodegenerative and neuropsychiatric diseases, revealing shared and distinct molecular mechanisms.

The paper develops an integrative sequencing strategy to catalog NRXN1 isoforms across human brain tissues and hiPSC organoids, revealing cell-type-specific splicing patterns and therapeutic potential of ASO targeting.

This study creates a single-nucleus transcriptomic atlas of Parkinson's disease progression, identifying cell-type-specific gene expression changes and linking them to genetic risk factors and disease stages.

The paper identifies ZBTB7A as a key regulator of MDD-specific chromatin signatures and astrocyte-mediated stress vulnerability in the orbitofrontal cortex.

This study identifies D1 and D2 dopamine receptor-expressing neurons in the mouse ventral hippocampus and shows they mediate opposing approach/avoidance behaviors during anxiety-related tasks.

The paper presents a long-read RNA-seq atlas of microglia isoforms, identifying novel isoforms and their associations with genetic risk loci in Alzheimer's and Parkinson's disease.

This study develops a human brain tissue model (miBrain) to show that APOE4 astrocytes with cholesterol dysregulation promote α-synuclein pathology through endolysosomal dysfunction.

This paper presents a computational drug repurposing framework that identifies FDA-approved drugs for COVID-19 by integrating genetic expression data and EMR data, finding four compounds with protective effects in validation.

This study profiles small RNAs in schizophrenia and bipolar disorder, finding altered sncRNA abundance and links to accelerated aging and key biological processes.

The paper maps transcriptomic and chromatin accessibility profiles across 25 human brain regions and identifies genes linked to neuropsychiatric disorder risk.

This study creates a single-nucleus transcriptomic atlas of the human DLPFC across the lifespan, revealing three transcriptomic phases and ten age-related trajectories linked to neurodevelopmental and neurodegenerative disease risk.

The paper analyzes longitudinal blood transcriptomics in cocaine use disorder to identify gene co-expression networks and transcript associations linked to abstinence and relapse behaviors.

This study compares A-to-I RNA editing in postmortem and living human brain tissues, revealing significant differences in editing levels and their association with cellular processes and neurological conditions.

The paper identifies 46,802 enhancers and 164 psychiatric disorder variants with regulatory effects in the developing cortex and organoids using massively parallel reporter assays and deep learning.

The paper processes single-nuclei multi-omics data from 388 human brains to identify regulatory elements and build cell-type networks, revealing changes in aging and neuropsychiatric disorders.

The paper identifies cell-type specific chromatin accessibility QTLs and their functional impact on brain disease risk.

The paper evaluates deconvolution methods on human brain data, finding dtangle and bMIND perform best, and identifies decon-eQTLs that explain more schizophrenia heritability than bulk or single-cell eQTLs.

The paper generates a molecular neuroanatomical map of the human prefrontal cortex using spatial transcriptomics and single nucleus RNA-sequencing, revealing novel spatial domains and cell-cell interactions linked to psychiatric disorders.

The paper identifies distinct transcriptional profiles in striatal ensembles activated during initial vs. repeated cocaine exposure, revealing differences in neuronal recruitment and memory retrieval mechanisms.

DeepGAMI improves phenotype prediction from multimodal data by integrating biological knowledge and imputing missing modalities, outperforming existing methods and providing interpretable insights.

The paper profiles gene expression and chromatin accessibility in 45,549 cortical nuclei across 6 developmental timepoints to study cell fate determination and neuropsychiatric disease mechanisms.