James Boocock

This study uses genome-scale CRISPR base editing in yeast to assess the functional effects of 308,461 variants, identifying 18,009 with significant growth impacts.

This paper introduces a 96-well liquid format for high-throughput QTL mapping in yeast, enabling efficient analysis of multiple crosses and environmental conditions.

This study identifies context-specific eQTLs and their dynamic effects on gene expression in yeast under acute environmental stress, linking genetic variation to physiological adaptation.

The paper maps eQTLs in yeast using single-cell RNA sequencing, revealing tradeoffs between growth and reproduction through allele-specific effects on gene expression and cell-cycle progression.

The paper identifies chromosome 1 in Schmidtea mediterranea as a sex-primed autosome through genomic analysis showing restricted recombination and sex-specific gene expression.

The paper maps eQTLs at cellular resolution in C. elegans using single-cell RNA sequencing, revealing cell-type-specific and single-cell-specific eQTL effects.

The paper introduces V-seq, a cost-effective method for viral genome sequencing that uses multiplexed RT primers to improve coverage and reduce costs.

This paper identifies 15 novel serum urate loci and links them to 44 genes, revealing new molecular mechanisms of urate control through genomic and eQTL analysis.

The paper examines common genetic variants' contribution to bipolar disorder risk in multiplex families and finds higher polygenic risk scores in affected individuals compared to controls and unaffected family members.

This study identifies 73 genome-wide significant loci for mood disorders, revealing shared and distinct genetic factors between major depressive disorder and bipolar disorder.

This study shows rare DNA variants have a larger impact on quantitative traits in yeast compared to common variants, due to their greater effect sizes and recent evolutionary origins.

This paper introduces ceX-QTL, a method for fast genetic mapping of complex traits in C. elegans using bulk selection on millions of individuals, and demonstrates its application in identifying drug resistance, gene expression, and fitness loci.

This study identifies 30 genome-wide significant loci associated with bipolar disorder, including novel genes involved in ion channels, neurotransmitters, and synaptic components.

This study identifies 114 genome-wide significant loci for schizophrenia and bipolar disorder, with specific subphenotype associations and four genes distinguishing the disorders.

This paper introduces a Bayesian framework to identify regulatory effects at GWAS risk loci by integrating GWAS summary data with molecular QTL data.

The paper uses transcriptomic imputation to identify schizophrenia risk genes across multiple brain regions, finding 71 associated genes and 36 enriched pathways.

The paper integrates GWAS and conditional eQTL data to identify schizophrenia risk loci with co-localization, finding 40 loci and six with conditional eQTL co-localization.