Jennifer Ellen Posey

The paper develops a model to predict NMD outcomes for protein-truncating variants using RNA-seq data, achieving ~78% ROC-AUC and identifying non-canonical determinants.

The paper identifies domain-specific phenotypic effects of MACF1 variants outside the GAR domain, revealing broader neurodevelopmental and craniofacial anomalies.

The paper identifies de novo variants in PCBP1 causing neurodevelopmental disorders, showing impaired dendritic arborization and increased exon skipping in T cells.

The paper reports new TUBB2B variants in multiple families, expanding the clinical and molecular spectrum of tubulinopathies and highlighting phenotypic heterogeneity and dual molecular diagnoses.

The paper introduces a data model and dataset for rare disease research, enabling interoperable multi-omic data integration across clinical sites.

The paper presents CHANGER, a Chilean exome reference dataset of 902 unrelated individuals, to improve genetic research and variant interpretation in South American populations.

This study identifies NMD-escape variants as a distinct class of disease-causing mutations, showing that altered C-terminal regions drive pathogenicity through phase separation.

This study uses whole-genome sequencing to analyze 9p deletion and duplication syndromes, identifying key genes and structural variants, and introduces a machine learning model for syndrome prediction.

TBAS enables cost-effective long-read sequencing of rare-disease trios with high variant detection accuracy and a 77% potential solve rate.

This paper evaluates Illumina Constellation sequencing for rare disease research, showing it can detect structural variants and haplotype phasing with low DNA input and existing infrastructure.

RAG-HPO improves HPO term assignment using retrieval-augmented generation, achieving higher precision and recall than existing tools in phenotypic analysis of clinical text.

The paper identifies biallelic variants in RNU4-2 causing a recessive neurodevelopmental syndrome with distinct white matter changes, expanding the known genotypic and phenotypic spectrum of RNU4-2-related disorders.

The paper presents a scalable CNV analysis workflow applied to rare disease cohorts, identifying 39 candidate pathogenic SVs within 2 days using collaborative tools and databases.

This study identifies EPHA4 signaling dysregulation as a contributor to idiopathic scoliosis by linking it to locomotion defects and CPG network disruption in zebrafish.

The paper identifies trans-heterozygous digenic variants in laterality defect genes using exome/genome sequencing data from CHD cohorts, finding significant enrichment in laterality cases compared to controls.

The paper identifies SPOUT1/CENP-32 as a causative gene for SpADMiSS, linking its dysfunction to mitotic spindle defects and neurodevelopmental disorders.

The paper analyzes variant classification disparities between European-like and non-European-like genetic ancestries and shows that MAVE data can reduce these disparities in VUS reclassification.

VizCNV is a tool for analyzing CNVs and phased BAF from trio genome sequencing data, identifying de novo and inherited CNVs in immunodeficiency cases.

The paper identifies a hypomorphic SLC6A1 variant causing variable expressivity in neurodevelopmental disorders using clinical phenotyping and Drosophila models.

The paper identifies biallelic FLVCR1 variants causing a range of neurodevelopmental and neurodegenerative disorders, linking them to choline and ethanolamine transport dysfunction.

The paper analyzes the Turkish population's variome to understand its impact on rare disease traits, finding that long ROHs and inbreeding contribute to recessive diseases.

The paper identifies monoallelic DHX9 variants as a cause of neurodevelopmental disorders and Charcot-Marie-Tooth disease, showing genotype-phenotype correlations and cellular dysfunction.

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 describes the clinical, neuroimaging, and molecular features of TECPR2-associated hereditary sensory and autonomic neuropathy with intellectual disability, providing variant interpretation guidelines and carrier frequency estimates.

The paper identifies RFX3, RFX4, and RFX7 mutations as causes of neurodevelopmental disorders including autism, ADHD, and intellectual disability, and links these genes to ASD risk genes through bioinformatic analysis.

The paper investigates how different FBN1 truncating mutations cause distinct clinical phenotypes in Marfan syndrome and Marfanoid-progeroid-lipodystrophy syndrome through molecular and genetic analysis.

The paper combines exome sequencing and array-based comparative genomic hybridization to identify genetic risk factors in familial Parkinson’s disease, finding novel SNVs and CNVs.

The paper identifies additional DDX3X variants in individuals with intellectual disability and expands the known phenotypic spectrum of DDX3X disorders.