Uncovering the genomic and transcriptomic variation due to mobile elements in the population and in neurological disease

Abstract Mobile element insertions (MEIs) are a diverse and poorly understood source of genetic variation in humans. These insertions occur when retrotransposons integrate into the genome. Recent advancements in genomics technologies in large populations have revealed over 100,000 polymorphic MEIs, making them a very prevalent class of genetic variation. MEIs have been shown to significantly impact gene function and contribute to human diseases. In many cases, specific noncoding MEIs have been linked to neurologic disease. In particular, my training lab has discovered that the cause of the neurodegenerative disease X-linked Dystonia Parkinsonism is an intronic insertion of a SINE-VNTR-Alu (SVA) element, which causes a distinct expression and alternative splicing signature. However, our understanding of the broader effects of MEIs on gene regulation, particularly alternative splicing, remains limited. This fellowship aims to leverage large-scale genetic datasets and cutting- edge analytical methods to characterize MEIs, explore their functional implications for gene expression and splicing, and investigate their association with neurological diseases. I will also specifically dissect the role of SVA elements, which are hominid specific and display unique patterns of internal variation. I will assemble a dataset of over 2000 matched short-read whole genome sequencing and bulk RNA-seq data, including multi- tissue expression data from the Genotype-Tissue Expression Project and brain sequencing data from the CommonMind Consortium, which includes neuropsychiatric cases and controls. Using this data, I will look at broad patterns of transcriptomic effects from MEIs (Aim 1) and identify specific MEIs associated with splicing changes in the brain (Aim 2). Finally, I will perform MEI discovery in long-read whole genome sequencing data from 10,000 individuals from the NIH All of Us initiative. I will harness this large dataset to comprehensively characterize MEIs and identify SVA elements associated with neurological disease (Aim 3). In parallel with these research aims, an exceptional team of mentors and advisors across multiple disciplines, career stages, and institutions will provide didactic training, hands-on research support, regular opportunities for presentation in seminars and conferences, and a variety of soft skill development sessions that directly align with my career objectives during my PhD training. Collectively, the aims outlined in this proposal will take advantage of unique tools and resources to yield novel insights into mobile element insertions and their relationship to neurological disease and will serve as an outstanding training opportunity for me in computational, statistical, and functional disease genomics.