生物
RNA结合蛋白
全基因组关联研究
RNA剪接
表达数量性状基因座
遗传学
数量性状位点
基因
计算生物学
核糖核酸
单核苷酸多态性
基因型
作者
Christopher Y. Park,Jian Zhou,Aaron K. Wong,Kathleen Chen,Chandra L. Theesfeld,Robert B. Darnell,Olga G. Troyanskaya
出处
期刊:Nature Genetics
[Nature Portfolio]
日期:2021-01-18
卷期号:53 (2): 166-173
被引量:67
标识
DOI:10.1038/s41588-020-00761-3
摘要
Despite the strong genetic basis of psychiatric disorders, the underlying molecular mechanisms are largely unmapped. RNA-binding proteins (RBPs) are responsible for most post-transcriptional regulation, from splicing to translation to localization. RBPs thus act as key gatekeepers of cellular homeostasis, especially in the brain. However, quantifying the pathogenic contribution of noncoding variants impacting RBP target sites is challenging. Here, we leverage a deep learning approach that can accurately predict the RBP target site dysregulation effects of mutations and discover that RBP dysregulation is a principal contributor to psychiatric disorder risk. RBP dysregulation explains a substantial amount of heritability not captured by large-scale molecular quantitative trait loci studies and has a stronger impact than common coding region variants. We share the genome-wide profiles of RBP dysregulation, which we use to identify DDHD2 as a candidate schizophrenia risk gene. This resource provides a new analytical framework to connect the full range of RNA regulation to complex disease.
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