Jonathan K. Pritchard

The paper compares genetic architectures of brain-related traits and finds they have weaker associations and stronger selection pressures compared to other traits.

Genome-scale CRISPRi perturb-seq in 22 million primary human CD4+ T cells maps stimulation-specific regulators and links perturbation signatures to T cell states and autoimmune genetics.

The paper introduces coalescent-based time-stratified statistics to accurately infer population structure dynamics using Ancestral Recombination Graphs.

This paper develops a virus-like particle-based system for CRISPR gene editing and screening in primary human myeloid cells, identifying TNFAIP3 as a key regulator of inflammatory polarization.

This study finds that allele frequencies at recessive disease genes are mainly shaped by pleiotropic effects in heterozygotes, not purely recessive selection.

The paper introduces PerturbPair, a platform integrating transcriptomic and optical screens to map macrophage regulatory networks, revealing cross-modal relationships and disease-relevant gene programs.

The paper introduces a framework for multimodal chemical screens combining RNA, protein, and epigenomic readouts, revealing compound-specific mechanisms and off-target effects in T cells.

The paper identifies genetic variants associated with diurnal glucose levels and their role in type 2 diabetes risk.

The paper investigates how gene regulatory network topology influences the genetic architecture of gene expression, finding that local motifs and hub regulators shape heritability distribution.

The paper analyzes rDNA copy number variation in humans, finding distinct associations with metabolic diseases and growth traits.

This study estimates the false sign rate in transcriptome-wide association studies (TWAS) for plasma proteins and complex traits, finding high discordance between predicted and expected gene effects.

This study analyzes MHC gene evolution across primates using sequence data to show faster Class I evolution compared to Class II and highlights the role of pseudogenes in understanding evolutionary history.

The paper simulates gene regulatory networks and models perturbation effects to understand network structure and function.

The paper identifies rRNA sequence variants affecting human traits and diseases by analyzing UK Biobank data and developing the RiboVAn method.

This study uses haplotype analysis to identify disease associations in the HLA region across 412,181 Finnish individuals, revealing pleiotropic patterns and 7,649 associations across 647 traits.

The paper uses transfer learning to predict how TF dosage affects chromatin accessibility, finding that motif affinity and distribution determine sensitivity or buffering of TF concentration changes.

The paper integrates genetic associations with Perturb-seq data to build causal graphs linking genes to traits through regulatory programs.

This paper compares how GWAS and rare variant burden tests prioritize genes for 209 traits in the UK Biobank, showing they focus on different genes due to distinct prioritization criteria.

The paper analyzes gene dosage response curves for human complex traits and shows that they exhibit biased direction of effect, developing a theoretical model to explain this phenomenon.

This study uses CRISPR perturbations in CD4+ T cells to infer a gene regulatory network, revealing trans-regulatory mechanisms linking immune GWAS genes to signaling pathways.

This study identifies and characterizes rRNA variants in human tissues and cancer, revealing tissue-specific ribosome subtypes and cancer-specific ribosome variations.

This paper introduces a Bayesian framework combining population genetics and machine learning to estimate gene constraint, improving accuracy for short genes and providing a flexible tool for gene-level property estimation.

The paper develops a Bayesian model and software for analyzing CRISPR screens and validates its effectiveness in maintaining statistical power under low coverage conditions.

The paper introduces conditional frequency spectra to study selection on complex traits in biobanks, finding evidence for stabilizing or purifying selection on GWAS-associated variants.

This study analyzes ancient DNA from 204 individuals to show stable population structure in Europe despite high mobility during the historical period.

The paper identifies impactful rare variants by integrating multi-omic data from MESA, showing that combining expression and protein data increases the detection of rare stop and frameshift variants.

This study analyzes ancient genomes from the Iron Age central Mediterranean to explore population continuity and mobility, finding significant local contributions and diverse non-local ancestries.

The paper investigates the evolutionary retention of ribosomal protein paralogs eS27 and eS27L by showing their subfunctionalized expression patterns are necessary for maintaining total protein expression across cell types.

The paper identifies a quantitative trait locus on chromosome 13 associated with STR expansion propensity in mice, implicating Msh3 in genome-wide mutation patterns.

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.