Jennifer E. Posey

Rare disease research and diagnosis rely on the integration of genomic and phenotypic data generated across diverse clinical sites; however, the absence of widely adopted standards for representing genomic data and associated metadata has limited data interoperability, reuse, and cross-study analysis. The Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) Consortium was established to investigate challenging rare disease cases and evaluate emerging multi-omic technologies for clinical translation. To support coordinated data integration across distributed research sites, we developed a common Consortium Data Model in partnership with domain experts to standardize the capture of participant-, family-, phenotype- and assay-level metadata, with a particular emphasis on using a modular architecture to support linking of multiple data versions from multiple omic technologies to a single individual and attribution of a genetic finding to the specific technology used for its initial discovery. Adoption of the GREGoR Data Model has enabled continued generation and public release of a harmonized, analysis-ready Consortium Dataset. The most recent release includes phenotypic, family and multi-omic data from 12,292 participants in 5,029 families. Other rare disease data sharing efforts are beginning to adopt this data model which will facilitate cross consortium analyses and empower rare disease research. This work demonstrates that a collaborative, flexible, and scalable data model can enable large-scale rare disease research, facilitate cross-center data harmonization, and enable data interoperability.

Genetic variants in RNU4-2 , which is transcribed into the U4 small nuclear RNA component of the major spliceosome, were recently shown to cause ReNU syndrome, a prevalent dominant neurodevelopmental disorder (NDD). These variants almost exclusively arise de novo and cluster within 18 nucleotides of RNU4-2 . Here we describe a new recessive NDD associated with homozygous and compound heterozygous variants in RNU4-2 . We identify 38 individuals with biallelic variants outside the 18-nucleotide ReNU syndrome region that cluster within other functionally important elements of U4: Stem II, the k-turn and the Sm protein binding site. We characterize the clinical phenotype in 31 individuals, demonstrating that the recessive disorder is clinically distinct from ReNU syndrome and is associated with distinctive white matter abnormalities, including enlarged perivascular spaces. Finally, we find reduced RNU4-2 transcript levels in individuals with the recessive disorder, suggesting a loss-of-function disease mechanism that is distinct from the mechanism underlying ReNU syndrome. Together, these findings expand the genotypic and phenotypic spectrum of RNU4-2 -associated NDDs.

Poly(rC)-binding protein 1 (PCBP1), a splicing factor and key member of the hnRNP E family, was initially characterized for its tumor suppressive properties. More recently, its role in regulating gene expression in the brain and nervous system has attracted growing interest. Through an international multicenter collaboration, we identified 13 de novo pathogenic variants in PCBP1 across 13 unrelated families. All affected individuals exhibited intellectual disability (ID), with autism spectrum disorder (ASD) as a prominent feature. Functional analysis in primary hippocampal mouse neuron cultures demonstrated that PCBP1 variants impair dendritic arborization, underscoring their deleterious effects. Transcriptomic profiling by RNA sequencing of subjects-derived T cells showed a distinctive signature characterized by significantly increased exon skipping. These results highlight the essential role of PCBP1 in neurogenesis and neuritogenesis, revealing the impact of loss-of-function variants in cells harboring PCBP1 pathogenic variants, thereby confirming the link between splicing defects and neurodevelopmental disorders. Collectively, our findings demonstrate the critical role of PCBP1 in neurodevelopment, reaffirming the importance of splicing regulation in mammalian neurodevelopment.

We present Trio-barcoded ONT Adaptive Sampling (TBAS), a cost-efficient long-read sequencing strategy combining sample barcoding and adaptive enrichment to sequence rare-disease trios on a single PromethION flow cell. TBAS achieved near-complete variant phasing and detection of small variants, structural variants, and tandem repeats with high accuracy and 77% potential solve rate. This scalable approach retains methylation data and enables clinically relevant, phenotype-guided long-read diagnostics at a fraction of current costs.

Despite significant advances in genomic sequencing, the resolution of many rare disease cases is still hindered by variant detection limitations. Short reads struggle in homologous regions, and long reads remain costly and difficult to scale. Here, we present the first systematic evaluation of Illumina’s Constellation sequencing technology for rare disease research. By fragmenting long DNA molecules directly on the flow cell surface, Constellation unlocks proximity information that enables long-range phasing and structural variant detection. Across 21 families, Constellation independently identified all known causative variants and resolved previously unsolved trios. It reliably resolved complex structural and copy number variants (e.g. impacting MECP2 ) and recovered haplotype phasing information across key disease impacting variants, all from low DNA input using existing Illumina infrastructure. These findings establish Constellation as a scalable, cost-efficient advance, closing critical diagnostic gaps and broadening access to long-range variant analysis in rare disease genomics.