Julia K. Goodrich

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 estimates mutation rates and variant effects using 700k exomes to identify genes with mutational hotspots and improve variant prioritization for genetic diagnostics.

The paper performs large-scale GWAS and RVAS on 392,030 whole genomes from All of Us, identifying 49,863 associations and 193 novel pLoF gene-phenotype links through meta-analysis with UK Biobank.

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.

The paper analyzes over 800,000 human genomes to assess penetrance of clinically relevant variants, finding that 95% of pLoF variants in severe diseases have explanations for lack of disease manifestation.

The paper harmonizes diverse human genomes from multiple datasets to create a new reference panel with improved variant coverage and population structure analysis.

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 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.

Rare-variant depletion in 1kb windows of 76,156 gnomAD genomes, versus feature-adjusted mutation expectations, marks regulatory elements and outperforms seven alternative scores at flagging functional non-coding variants.

The paper develops a method to infer compound heterozygosity from exome sequencing data, achieving high accuracy in phasing rare variants for recessive disease diagnosis.

CHARR estimates DNA contamination from variant-level sequencing data, offering accurate results with reduced computational costs compared to existing methods.

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 performs single-variant and gene-based association analyses of 4,529 phenotypes using exome data from 426,370 UK Biobank individuals, finding associations linked to variant frequency and deleteriousness.

The paper describes the role of the Centers for Mendelian Genomics in advancing gene discovery through data sharing, collaboration, and resource development over the past decade.

The paper evaluates penetrance and variable expressivity of monogenic metabolic conditions using exome data from 77,184 individuals, finding that monogenic variants have larger effect sizes than polygenic scores but low penetrance.

This study uses 16S rRNA gene sequencing in Diversity Outbred mice to identify genetic variants affecting gut microbiome composition, finding significant heritability and novel QTLs related to immune and metabolic pathways.

The paper analyzes loss-of-function variants in LRRK2 across large genomic datasets to assess the safety of partial LRRK2 inhibition as a Parkinson's disease therapy.

The paper shows that human AMY1 gene copy number affects oral and gut microbiome composition and function, with low-AMY1 associated with enhanced complex carbohydrate breakdown and high-AMY1 linked to resistant starch fermentation and higher adiposity.

This study examines the relationship between microbiome diversity and virome diversity in adult monozygotic twins, finding that microbiome discordance correlates with virome dissimilarity.