Jeffrey R. MacDonald

The paper develops FunBurd to analyze gene dosage effects on 43 traits in UK-Biobank, finding pleiotropy and non-monotonic responses linked to genetic constraint and brain-specific mechanisms.

The paper revises a human diploid genome assembly using a scalable workflow with Oxford Nanopore reads, achieving high accuracy and contiguity without ultra-long reads or other technologies.

The paper examines how gene dosage, polygenic background, and environment influence complex traits like height and BMI using large-scale data from multiple cohorts.

The paper identifies novel CNV loci and dose-dependent gene effects across six psychiatric disorders using genome-wide analysis.

The paper identifies shared and divergent genetic mechanisms across psychiatric disorders using gene-set burden analysis of copy number variants.

The paper develops a method to analyze genomic deletions and duplications across the cerebral cortex and finds opposing effects on cognitive ability depending on gene expression patterns in different cortical regions.

The paper identifies DDX53 genetic variants in individuals with ASD, showing a link between DDX53 and ASD, and highlights implications for genetic testing and mouse modeling.

The paper develops a genome-wide rare variant score linked to morphological subtypes of ASD and finds higher scores in dysmorphic ASD cases.

The paper investigates the association between gene copy number variation and mental health traits in children, finding links to ADHD, OCD, and cognitive biomarkers.

This study identifies 135 ASD-associated protein-coding genes using whole-genome sequencing data from 11,312 individuals and exome sequencing from over 18,000 trios, with a false discovery rate of 80%.