Daniel G. MacArthur

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.

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

The Rare Genomes Project provides remote genomic sequencing to rare disease families, achieving a 23.3% diagnostic solve rate and highlighting the role of research in overcoming clinical diagnostic barriers.

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.

This study identifies a homozygous SECISBP2 variant causing lethal perinatal cardiomyopathy through loss of selenoprotein function, including GPX4, and suggests a ferroptosis mechanism.

This study uses proteomics to identify a cryptic JPH2 loss-of-function in a paediatric DCM patient, revealing a novel mechanism of recessive disease.

The Evidence Aggregator (EvAgg) uses generative AI to streamline rare disease diagnostics by extracting and summarizing genetic variant and clinical information from literature, improving efficiency and accuracy.

The paper performs whole exome sequencing on 44,028 British South Asians to identify gene-phenotype associations and knockout genes, finding novel links and implications for drug development.

The paper identifies two non-coding structural variants associated with Axenfeld-Rieger Syndrome, showing how enhancer disruption can cause disease without affecting the PITX2 gene itself.

gnomAD v4 (730,947 exomes) brings LOFTEE-2 loss-of-function annotation (0.90 precision, strict mode), missense-aware constraint, and LLM-mined literature evidence combined with constraint to rank disease genes.

This pilot study identifies British South Asians at high risk of cholestatic liver disease through genetic and phenotypic recall, finding 66.7% of participants had undetected liver disease.

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.

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

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

The paper identifies biallelic variants in RNU4-2 causing a recessive neurodevelopmental syndrome with distinct white matter changes, expanding the known genotypic and phenotypic spectrum of RNU4-2-related disorders.

The paper develops an automated tool for reanalyzing genomic data in rare disease cohorts, showing improved diagnostic yields through iterative reanalysis.

This study uses saturation genome editing to analyze RNU4-2 variants, identifying functional impacts and redefining the ReNU syndrome critical region.

This paper shows that genome-wide association studies on ratio traits can be misleading, as associations may be driven by the denominator rather than the numerator, and proposes a method to correct for collider bias.

This study estimates that ~6% of insulin-treated diabetic individuals with ambiguous features in British Pakistanis and Bangladeshis have T1D, highlighting the need for autoantibody and C-peptide testing.

The paper develops a cell type-aware framework to identify non-coding variants in Mendelian disorders by integrating single-cell multi-omic data and applying it to congenital cranial dysinnervation disorders.

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

The paper examines 5' untranslated regions (UTRs) to show their role in translational regulation of dosage-sensitive genes and introduces a web tool for analyzing 5UTR composition.

The paper quantifies regional missense mutational intolerance using 730,947 exomes to identify constrained gene regions and improve variant interpretation.

The paper detects and classifies copy number variants in exome data from 6,633 families, identifying causal CNVs in 173 families and improving classification standards.

The paper reports a rare splice-site variant in TNNT2 found in Oceanian ancestry individuals, highlighting the need for diverse genomic datasets to avoid misclassification of variants.

The paper identifies a novel neurodevelopmental disorder caused by de novo deletion of the lncRNA CHASERR, showing its role in regulating CHD2 expression and causing developmental and epileptic encephalopathy.

This paper estimates the penetrance of rare variants in cardiomyopathy genes using cross-sectional data from genetic testing, finding substantial penetrance for dominant cardiomyopathies and variant-specific differences.

This paper presents a framework to reduce false positives in predicted loss-of-function variants by analyzing LoF evasion mechanisms and adjusting ACMG/AMP guidelines.

This study evaluates genome sequencing's diagnostic yield in a cohort of undiagnosed rare disease patients, finding it solves 29.3% of cases with specific variant types not detectable by exome sequencing.

The paper presents phenotype and genetic analysis of 206 children with neurodevelopmental disorders from Kenya and South Africa, identifying pathogenic variants in 17% of South African and 38% of Kenyan cases.