Sean Simmons

The paper fine-maps PD GWAS signals across cell types, revealing convergent glial-neuronal risk genes and a shared vesiculopathy network.

This paper develops computational tools for allelic imbalance analysis using single-nucleus RNA-seq and demonstrates their application in a Parkinson's disease cohort.

The paper develops Perturb-CLEAR to study dendritic morphogenesis in the developing mouse cortex, revealing gene-specific multimodal phenotypes linked to NDD risk genes.

This study integrates long-read WGS and single-nucleus RNA-seq to identify structural variants affecting gene expression in Parkinson's disease with cell type resolution.

This paper develops an in vivo multiomic Perturb-seq platform to improve gRNA recovery and applies it to study neurodevelopmental disorder risk genes in the cortex.

Loss of CACNA1G disrupts sleep rhythms and gene regulation, creating a mismatch between brain state and behavior linked to schizophrenia.

This study investigates Akap11 mutant mice to explore the neurobiological effects of AKAP11 loss, finding increased PKA activity and transcriptomic changes linked to schizophrenia and bipolar disorder.

This study shows that GPR34 maintains microglial homeostasis and limits disease-associated microglial responses in Alzheimer's disease models.

This study performs a meta-analysis of brain transcriptomes from genetic mouse models of schizophrenia, identifying dysregulation in striatum and thalamus with distinct patterns in different models.

The paper identifies three neuron-specific schizophrenia protein networks enriched for genetic and transcriptional perturbations and validates their disruption in 22q11.2 deletion carriers.

This study identifies AKAP11's role in regulating lipid metabolism and neuronal support in astrocytes, linking its dysfunction to schizophrenia and bipolar disorder risk.

This paper benchmarks multimodal single-cell data integration methods to improve kidney reference atlas quality by identifying adaptive states and rare cell types.

This study develops a high-throughput in vivo Perturb-seq platform to analyze gene function across diverse cell types in the brain and peripheral nervous system, identifying cell type-specific transcriptional networks.

The paper identifies neuron-class specific signals that drive differential myelination across cortical layers using single-cell data from mouse neocortex.

The paper maps antisense oligonucleotide activity in the brain using single-cell transcriptomics in mice and macaques, showing widespread target suppression across cell types with varying durations.

This study uses single-cell transcriptomics to show that heterochronic parabiosis alters aging signatures in multiple brain cell types, with endothelial cells showing significant transcriptional changes.

This study evaluates background noise in single-cell RNA-seq data and assesses methods for its removal, finding that CellBender performs best for marker gene detection.

This study identifies brain region-specific changes and dopamine dysregulation in Grin2a mutant mice, supporting schizophrenia hypotheses and highlighting their utility as a genetic model.

The paper benchmarks a new low-cost sequencing by synthesis method for scRNA-seq, showing comparable results to existing technologies and enabling cost-effective large-scale applications.

The paper compares statistical methods for cell type composition analysis in single-cell RNA-Seq, finding that some methods perform better than others while highlighting the importance of accounting for sample variability.

The paper uses scRNA-seq to show increased transcriptional heterogeneity in neurodegenerative disease models, suggesting early regulatory imbalances.

This study uses in vivo Perturb-Seq to analyze the effects of 35 autism risk genes on neuronal and glial cells in the developing brain.

This study uses human brain organoids to show that ASD risk genes cause accelerated development of specific cortical neuron classes.

This paper introduces privacy-preserving query-answering mechanisms for biomedical databases that maximize utility while achieving formal privacy guarantees, extending optimality results to asymmetric utility functions.

This study uses single-cell transcriptomics to analyze aged mouse brains, identifying cell-type-specific aging signatures and highlighting molecular processes like ribosomal biogenesis.

Seven single-cell and single-nucleus protocols run side by side on the same cell lines, PBMCs and mouse cortex, analysed through one pipeline: 10x Chromium led the high-throughput methods.

The paper identifies genetic variants influencing isoform usage in the anti-viral response, revealing ERAP2's role in balancing selection and influenza-specific regulation.