Center for Modeling Non-Coding Disease Variants: Bioinformatics Core

University Of California-Irvine, Irvine CA

Investigators

Abstract

PROJECT SUMMARY/ABSTRACT: BIOINFORMATICS CORE The vast majority of disease-associated variants reside in the non-coding genome (estimated at 90%), yet their contributions to disease mechanisms remain underrepresented in current models. Despite growing evidence that non-coding variants influence gene regulation, cellular processes, and disease phenotypes, understanding their function from genomic sequence alone remains a significant challenge. This program seeks to address this gap by identifying and characterizing causal monogenic mutations within the non-coding genome, focusing on when and where these regions are active. Our approach builds on recent advancements in transcriptomic mapping, leveraging both long- and short-read sequencing in human and mouse models to uncover active regulatory elements and their associated unstable transcripts (e.g., enhancer RNAs, TSS-RNA, PROMPTs). By depleting factors involved in transcription-coupled ncRNA degradation, we provide unprecedented insight into the functional outputs of regulatory noncoding loci. These datasets enable integrative bioinformatic analyses, generating a summary score for each mutated Active Non-Coding Variant (ANCV) based on conservation, context-specific interactions, and cell-specific mechanisms. The program's central aims are to 1) Defining ANCV expression patterns, conservation, and gene-regulatory networks to prioritize disease-relevant variants. Using a stepwise pipeline, we will narrow down the hundreds of thousands of non-coding variants to a manageable list for further study. And 2) Functionally dissecting prioritized ANCVs using massively parallel reporter assays (MPRAs) to validate their regulatory roles and identify downstream targets in native cellular contexts. Our novel MPRA design simultaneously measures local and distal regulatory functions, bridging computational predictions and experimental validation. In collaboration with the Preclinical Core, the Disease Modeling Core, and external partners, the Bioinformatics Core will support the identification, prioritization, and validation of non-coding variants associated with rare and undiagnosed diseases. By integrating computational and molecular tools, the program will nominate actionable genomic regions for experimental modeling and characterization of disease mechanisms. Through an iterative and collaborative framework, we aim to elucidate the regulatory roles of noncoding variants, advancing the understanding of their contributions to disease and enabling the development of targeted therapeutic strategies. This effort will be bolstered by a user-friendly platform for data sharing, fostering accessibility and collaboration within the broader research community.