Genome-wide landscape of RNA-binding protein target site dysregulation reveals a major impact on psychiatric disorder risk
| Autor: | Robert B. Darnell, Olga G. Troyanskaya, Kathleen M. Chen, Christopher Y. Park, Jian Zhou, Aaron K. Wong, Chandra L. Theesfeld |
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| Rok vydání: | 2021 |
| Předmět: |
endocrine system
medicine.medical_specialty Quantitative Trait Loci Cellular homeostasis RNA-binding protein Quantitative trait locus Biology Polymorphism Single Nucleotide Genome Article 03 medical and health sciences Deep Learning 0302 clinical medicine Gene Frequency Genetics medicine Humans Coding region Genetic Predisposition to Disease RNA Processing Post-Transcriptional Nuclear Factor 90 Proteins Psychiatry 3' Untranslated Regions Ribonucleoprotein U5 Small Nuclear 030304 developmental biology 0303 health sciences Mental Disorders RNA-Binding Proteins Translation (biology) Peptide Elongation Factors medicine.disease Gene Expression Regulation Phospholipases Schizophrenia Mutation RNA splicing Trans-Activators RNA Helicases 030217 neurology & neurosurgery Genome-Wide Association Study |
| Zdroj: | Nature genetics |
| ISSN: | 1546-1718 1061-4036 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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