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Activity Number: 4 - Utilizing Public Genomic Data for the Public Good: Improving Understanding of Disease Etiology and Treatment
Type: Invited
Date/Time: Monday, August 3, 2020 : 10:00 AM to 11:50 AM
Sponsor: WNAR
Abstract #309441
Title: Prioritizing Disease Candidate Genes Using Knockout Mouse Phenotype Data
Author(s): Donghyung Lee*
Companies: Miami University
Keywords: knockout mouse; IMPC; GWAS; gene prioritization; schizophrenia; sensorimotor gating
Abstract:

To characterize the relationship between protein-coding genes and phenotypes, the International Mouse Phenotyping Consortium (IMPC) is creating an extensive catalogue of mammalian gene function by i) producing knockout mouse lines for the approximately 20,000 protein-coding genes, ii) conducting systemic phenotyping on every knockout line and iii) studying the association between gene-knockout and phenotype. This unique and comprehensive open data set of genome and phenome-wide association opens an unprecedented opportunity to understand the etiology and underlying mechanism of diverse human diseases/traits. As a proof of concept of its utility in human disease studies, here we show that the IMPC gene-to-phenotype association data can be utilized to prioritize candidate genes in genome-wide association studies (GWAS) of psychiatric disorder (e.g., PGC Schizophrenia GWAS). In particular, we identify and prioritize genetic loci/genes associated with sensorimotor gating deficits in schizophrenia by using synthetic gene scores obtained from a meta-analysis combining association across multiple sensory gating phenotypes available in IMPC data (e.g., prepulse inhibition).


Authors who are presenting talks have a * after their name.

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