TY - JOUR
T1 - Genome-wide landscape of RNA-binding protein target site dysregulation reveals a major impact on psychiatric disorder risk
AU - Park, Christopher Y.
AU - Zhou, Jian
AU - Wong, Aaron K.
AU - Chen, Kathleen M.
AU - Theesfeld, Chandra L.
AU - Darnell, Robert B.
AU - Troyanskaya, Olga G.
N1 - Funding Information:
HHSN272201000054C and Simons Foundation grant no. 395506. O.G.T. is a senior fellow of the Genetic Networks program of the Canadian Institute for Advanced Research. We thank the Simons Foundation Autism Research Initiative, Simons Foundation and Flatiron Institute. A substantial portion of the work in this paper was performed at the Terascale Infrastructure for Groundbreaking Research in Science and Engineering high-performance computer center at Princeton University, which is jointly supported by the Princeton Institute for Computational Science and Engineering and the Princeton University Office of Information Technology’s Research Computing department.
Funding Information:
We thank Z. Zhang, A. Andersen and S. Lall for their help with the manuscript. We also thank all members of the Troyanskaya and Darnell laboratory for helpful discussions. This work is supported by National Institutes of Health grant nos. R01HG005998, U54HL117798 and R01GM071966, U.S. Department of Health and Human Services grant no.
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.
PY - 2021/2
Y1 - 2021/2
N2 - 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.
AB - 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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U2 - 10.1038/s41588-020-00761-3
DO - 10.1038/s41588-020-00761-3
M3 - Article
C2 - 33462483
AN - SCOPUS:85100120599
SN - 1061-4036
VL - 53
SP - 166
EP - 173
JO - Nature Genetics
JF - Nature Genetics
IS - 2
ER -