Jonathan K. Pritchard

The paper modulates SOX9 levels in human facial progenitors to study dosage sensitivity and identifies regulatory elements and genes that are sensitive to SOX9 changes.

The paper develops a probabilistic model to explain genetic architectures of complex traits using scaling laws, finding that traits share similar selection coefficients but differ in scaling parameters.

The paper performs metabolite GWAS on UK Biobank data to investigate pleiotropy and genetic correlation, finding pathway-relevant genes and contrasting variant effects.

The paper identifies upstream regulators of immune genes in human T cells and maps their regulatory network, revealing its enrichment for immune disease variants.

The paper tests for genetic interactions affecting causal variant effect sizes in gene expression and LDL-C across European and African American populations, finding significant evidence in gene expression but not LDL-C.

The paper identifies a natural mutator allele in mice that increases C>A germline mutations by 50% due to a variant of the Mutyh gene.

GWAS hits (44 UK Biobank traits) and GTEx v8 cis-eQTLs (38 tissues) differ systematically: eQTLs cluster near transcription start sites of weakly constrained genes; GWAS hits favour constrained, multifunctional genes.

The paper uses linked-read whole-genome sequencing to identify DNA variants in BXD mice and maps them to phenotypes, enabling systems genetics and precision medicine.

This paper introduces a framework for estimating variant effect sizes from GWAS summary statistics, improving polygenic score accuracy by jointly inferring individual variant effects and distributional properties.

The paper models resource competition for polymerases during transcription and finds it cannot explain most of the heritability in complex traits.

The paper uses blood eQTL meta-analysis to explore the polygenic architecture of complex traits, finding that trans-eQTLs are more informative for identifying causal genes than cis-eQTLs.

This study performs GWAS on three molecular traits, identifying core genes and pathways while highlighting a polygenic background contributing to trait variance.

This study identifies shared genetic loci influencing brain and facial shape, distinct from cognitive traits, suggesting a developmental link between brain and face formation.

The paper shows that polygenic scores have varying prediction accuracy within a single ancestry group based on factors like age, sex, and GWAS study design.

The paper shows that DNA methylation persists in Cryptococcus neoformans despite the loss of a de novo methyltransferase, with methylation patterns maintained through replication and natural selection.

The paper maps stimulation-responsive chromatin changes in immune cells and identifies variants linked to autoimmunity.

UK Biobank genetics of 38 blood and urine lab tests yields 1,857 independent loci; combining biomarker and disease polygenic scores improves FinnGen prediction of incident renal failure and alcoholic cirrhosis.

The paper proposes a model where trans-acting variation drives most genetic variance in complex traits through co-regulated networks of core genes.

The paper develops a PCA-based method to improve genetic interaction detection in CRISPR screens and identifies co-functional gene pairs that refine cancer cell network understanding.

This study identifies genetic risk loci for narcolepsy, showing enrichment in immune cells and suggesting autoimmune modulation via T cell receptor chains and influenza-A infection.

The paper measures selective constraint on human gene expression by analyzing copy number variants and allele-specific expression data, finding that singletons have larger effects but explain only 5% of cis-regulatory expression heritability.

This study identifies genetic variants influencing the transcriptomic response to doxorubicin in cardiomyocytes and links them to anthracycline-induced cardiotoxicity risk.

The paper examines regulatory variation in iPSCs and differentiated cells, finding lower individual variation in iPSCs and identifying shared chromatin regions for some cell type-specific QTLs.

LeafCutter quantifies RNA splicing variation from short-read RNA-seq data without transcript annotations, identifying more sQTLs and improving disease gene associations.

The paper identifies frequent non-allelic gene conversion in human gene duplicates and estimates its parameters, showing it has a small average effect on sequence divergence.

RolyPoly links GWAS summary statistics with single-cell RNA-seq to identify trait-relevant cell types and genes, finding associations between microglia and Alzheimer's disease, and oligodendrocytes and schizophrenia.