Cellular and developmental genetic regulation of 3' isoform diversity in the human brain and its contribution to neuropsychiatric disorders

PROJECT SUMMARY/ABSTRACT As large-scale genome-wide association studies (GWAS) continue to yield now thousands of genomic loci robustly associated with neurodevelopmental and psychiatric disorders, including autism spectrum disorder (ASD) and schizophrenia (SCZ), the major defining challenge of the post-GWAS era is to characterize the

concrete biological mechanisms through which this polygenic variation confers disease risk, at scale. To this end, we and others have recently developed methods and resources for systematic integration of GWAS results with population-level functional genomic reference panels -- identifying isoform-regulation during the second

trimester of human brain development as mediating the greatest proportion of heritability across multiple neuropsychiatric GWAS studies compared with earlier or postnatal timepoints. Yet, no studies have characterized genetic regulation of alternative polyadenylation (APA) in the developing brain, a critical yet

understudied tissue-specific gene-regulatory mechanism with established roles in neuronal mRNA metabolism, subcellular trafficking, and cellular differentiation. Our preliminary data indicates widespread dysregulation of APA in stem-cell-based models and postmortem brain tissues from subjects with ASD and SCZ, as well an

outsized enrichment of psychiatric GWAS signal with APA quantitative trait loci (QTL) in the developing human brain. This proposal seeks to integrate large-scale functional genomics, single-cell and long-read sequencing, deep learning, and genome-editing in human neuronal stem-cell models to develop a detailed, mechanistic

understanding of APA regulation during human brain development and its contribution to neuropsychiatric disorder pathophysiology. Specifically, we will generate a comprehensive atlas of APA regulation across neurodevelopment, leveraging data from >3650 bulk tissue samples as well as single-nucleus RNAseq data

across >700 unique donors, including 170 with SCZ/ASD. We will train and validate a deep learning model predicting APA changes from primary sequence. Through integration with psychiatric GWAS, we hypothesize that APA regulation will provide substantially greater resolution to detect candidate biological mechanisms

underlying psychiatric GWAS loci. Finally, predicted SNP-UTR-disease mechanisms will be experimentally tested via high-throughput screens and genome-engineering in iPSC-derived neurons. Together, these studies will systematically characterize a critical, yet underexplored area of genomic regulation in the human brain across

development, thereby providing novel insights into psychiatric disease mechanisms and identifying potential neurobiological targets for therapeutic development and intervention.