Joseph E. Powell

Impact of Rare and Common Genetic Variation on Cell Type-Specific Gene Expression

Single-cell eQTL mapping in 5.4 million PBMCs from 1,925 individuals with matched WGS finds common-variant eQTLs for 83% and rare-variant signals for 47% of 21,404 genes.

Tandem repeat variation shapes immune cell type-specific gene expression

The paper identifies immune cell type-specific gene expression regulated by tandem repeats using multi-omics data from large cohorts.

A Community-Driven Single-Cell PBMC Reference Integrating Landmark Datasets Spanning Health and Disease

HARP integrates PBMC data from multiple studies to create a reference atlas with consensus annotations and identifies age, sex, and disease-related cellular modules.

Scalable context-dependent single-cell eQTL mapping reveals disease-relevant regulatory variation beyond static models

The paper introduces CASTIE, a method for context-dependent eQTL mapping in single-cell data, identifying regulatory variants missed by static models and linking them to disease traits.

HLiCA: An integrated cell atlas of the healthy human liver

The paper integrates multiple datasets to create a comprehensive human liver cell atlas, identifying new cell types and associations with demographic factors.

A human developmental and adult brain atlas benchmarks dopaminergic stem cell models and cell therapy candidates

The paper benchmarks dopaminergic stem cell models and cell therapy candidates using a human brain atlas to identify off-target populations and lineage plasticity.

Patient induced pluripotent stem cells identify specificities of a reticular pseudodrusen phenotype in age-related macular degeneration

The paper uses iPSC-derived RPE cells to compare molecular differences between AMD with and without reticular pseudodrusen, identifying distinct pathways and genetic influences.

The impact of sex on the immune system explored at the single-cell level

The paper examines sex differences in the immune system at the single-cell level, identifying sex-biased genes and eQTLs linked to autoimmune diseases.

Classification of indeterminate and off-target cell types within human kidney organoid differentiation

This study classifies off-target and indeterminate cell types in human kidney organoid differentiation using single-cell transcriptomics.

Federated single-cell QTL meta-analysis reveals novel disease mechanisms

The paper performs a federated cis-eQTL meta-analysis across single-cell datasets to identify cell-type-specific genetic effects and link them to disease mechanisms.

The diploid reference genome of a human embryonic stem cell line

The paper presents the first telomere-to-telomere diploid reference genome of the human embryonic stem cell line H9, revealing genomic features and ancestry.

Protein Translation Dysregulation and Immune Cell Evasion Define Metastatic Clones in HPV-related Cancer of the Oropharynx

This study identifies mechanisms of immune evasion and metastasis in HPV-related oropharyngeal cancer using single-cell and spatial genomic data, showing dysregulated protein translation and immune pathway suppression in metastatic clones.

Mitochondrial Dysfunction in Endothelial Cells Drives Greater Vascular Impairment in Females with Diabetes-Associated Peripheral Artery Disease

This study identifies sex-specific mitochondrial dysfunction in endothelial cells of diabetic PAD patients, showing that MitoQ improves vascular function in females.

Single-cell genetics identifies cell-type-specific effector genes across complex traits and diseases

The paper uses single-cell eQTL data to identify cell-type-specific effector genes associated with 69 diseases and 31 biomarker traits, revealing distinct immune cell contributions to disease.

Genetic regulation of cell type-specific chromatin accessibility shapes immune function and disease risk

The paper maps chromatin accessibility and genetic variation in immune cells, showing how integrating cell-type-specific data improves disease risk understanding.

Endothelial Colony-Forming Cell Transcriptomic Profiling in CT-defined Coronary Artery Disease from the BioHEART-CT Study Implicate CCBE1 in Mitochondrial Dysfunction-associated Atherosclerosis

This study identifies CCBE1 as a gene associated with mitochondrial dysfunction in atherosclerosis using transcriptomic analysis of endothelial cells from CAD patients.

scPrediXcan integrates advances in deep learning and single-cell data into a powerful cell-type-specific transcriptome-wide association study framework

scPrediXcan improves transcriptome-wide association studies by integrating deep learning for cell-type-specific gene expression prediction, identifying more causal genes and explaining more GWAS loci in type 2 diabetes and systemic lupus erythematosus.

Single-cell atlas of the human immune system reveals sex-specific dynamics of immunosenescence

This study uses single-cell RNA sequencing to analyze immune aging in 982 donors, revealing sex-specific changes in immune cell composition and function during aging.

Identifying genetic variants that influence the abundance of cell states in single-cell data

The paper introduces GeNA, a tool to identify genetic variants influencing cell state abundance in single-cell data, finding five loci associated with immune cell state shifts.

Adult-type diffuse gliomas share recurring cell states driven by a common astrocyte-like glioma stem cell population

This study identifies recurring cell states across adult-type diffuse gliomas and reveals a shared astrocyte-like glioma stem cell population driving intratumoural heterogeneity.

Efficient and accurate mixed model association tool for single-cell eQTL analysis

SAIGE-QTL is a tool for single-cell eQTL analysis that directly maps eQTLs without pseudobulk aggregation and improves power for detecting rare variants.

Genetic variants associated with cell-type-specific intra-individual gene expression variability reveal new mechanisms of genome regulation

The paper introduces MEOTIVE, a statistical framework to identify genetic effects on gene expression variability, revealing new mechanisms of genome regulation and associations with autoimmune disease risk.

Demuxafy: Improvement in droplet assignment by integrating multiple single-cell demultiplexing and doublet detection methods

Demuxafy improves droplet assignment and doublet removal in scRNA-seq by combining multiple demultiplexing and doublet detection methods.

Deep Learning-based Identification of Intraocular Pressure-Associated Genes Influencing Trabecular Meshwork Cell and Organelle Morphology

The paper uses AI to identify genes associated with intraocular pressure by analyzing morphological changes in trabecular meshwork cells after gene knockouts.

Deep sequencing of proteotoxicity modifier genes uncovers a Presenilin-2/beta-amyloid-actin genetic risk module shared among alpha-synucleinopathies

The paper identifies a shared genetic risk module involving PSEN2 and actin regulation across alpha-synucleinopathies, linking them to Alzheimer's disease mechanisms.

High throughput functional profiling of genes at intraocular pressure loci reveals distinct networks for glaucoma

This study uses gene knockouts and single-cell RNA sequencing to identify genetic networks contributing to elevated intraocular pressure in glaucoma.

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution

The paper maps cell-type-specific eQTLs for HLA genes across multiple tissues and identifies dynamic regulation of HLA-DQ genes in immune cells.

Village in a dish: a model system for population-scale hiPSC studies

The paper demonstrates that village cultures of hiPSCs maintain consistent transcriptional profiles across uni- and village-cultured samples, enabling population-scale studies.

Single cell analysis of lymphatic endothelial cell fate specification and differentiation during zebrafish development

This study uses single-cell transcriptomics to investigate Prox1's role in lymphatic endothelial cell fate specification and differentiation in zebrafish, identifying new transcriptional targets and regulatory mechanisms.

OTTERS: A powerful TWAS framework leveraging summary-level reference data

OTTERS is a TWAS framework that uses summary-level eQTL reference data to estimate eQTL weights and perform omnibus TWAS, showing improved power and applicability.