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Updated: Jun 5, 2025

A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
Published on: June 15, 2011
Genetic architecture of RNA editing, splicing and gene expression in schizophrenia
Mudra Choudhury1, Ryo Yamamoto1, Xinshu Xiao1,2,3
1Bioinformatics Interdepartmental Program, University of California, Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA 90095-1570, United States.
Abstract:
Genome wide association studies (GWAS) have been conducted over the past decades to investigate the underlying genetic origin of neuropsychiatric diseases, such as schizophrenia (SCZ). While these studies demonstrated the significance of disease-phenotype associations, there is a pressing need to fully characterize the functional relevance of disease-associated genetic variants. Functional genetic loci can affect transcriptional and post-transcriptional phenotypes that may contribute to disease pathology. Here, we investigate the associations between genetic variation and RNA editing, splicing, and overall gene expression through identification of quantitative trait loci (QTL) in the CommonMind Consortium SCZ cohort. We find that editing QTL (edQTL), splicing QTL (sQTL) and expression QTL (eQTL) possess both unique and common gene targets, which are involved in many disease-relevant pathways, including brain function and immune response. We identified two QTL that fall into all three QTL categories (seedQTL), one of which, rs146498205, targets the lincRNA gene, RP11-156P1.3. In addition, we observe that the RNA binding protein AKAP1, with known roles in neuronal regulation and mitochondrial function, had enriched binding sites among edQTL, including the seedQTL, rs146498205. We conduct colocalization with various brain disorders and find that all QTL have top colocalizations with SCZ and related neuropsychiatric diseases. Furthermore, we identify QTL within biologically relevant GWAS loci, such as in ELA2, an important tRNA processing gene associated with SCZ risk. This work presents the investigation of multiple QTL types in parallel and demonstrates how they target both distinct and overlapping SCZ-relevant genes and pathways.
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