Despite the strong genetic basis of psychiatric disorders, the molecular origins of these diseases are still largely unmapped. RNA-binding proteins (RBPs) are responsible for most post- transcriptional regulation, from splicing to translational to localization. RBPs thus act as key gatekeepers of cellular homeostasis, especially in the brain. Here, we leverage a deep learning approach to interrogate variant effects genome-wide, and discover that the dysregulation of RBP target sites is a principal contributor to psychiatric disorder risk. We show that specific modes of RBP regulation are genetically linked to the heritability of psychiatric disorders, and demonstrate that diverse RBP regulatory functions are reflected in distinct genome-wide negative selection signatures. Notably, RBP dysregulation has a stronger impact on psychiatric disorders than common coding region variants and explains heritability not currently captured by large-scale molecular QTL studies (expression QTLs and splicing QTLs). We share genome-wide profiles of RBP target site dysregulation, which we used to identify DDHD2 as a candidate schizophrenia risk gene, in a public web server. This resource provides a novel analytical framework to connect the full range of RNA regulation to complex disease.

中文翻译：

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RNA结合蛋白失调的全基因组情况揭示了对精神疾病风险的重大影响

尽管精神疾病有很强的遗传基础，但这些疾病的分子起源仍未明确。RNA结合蛋白（RBP）负责大多数转录后调控，从剪接，翻译到定位。因此，RBP充当了细胞动态平衡（尤其是在大脑中）的关键守门员。在这里，我们利用深度学习方法来研究全基因组的变异效应，并发现RBP目标位点的失调是导致精神病风险的主要因素。我们表明，RBP调节的特定模式与精神疾病的遗传性遗传相关，并证明了不同的RBP调节功能反映在不同的全基因组负选择特征中。值得注意的是 与常见的编码区变体相比，RBP失调对精神疾病的影响更大，并解释了目前尚不为大规模分子QTL研究（表达QTL和剪接QTL）所捕获的遗传力。我们在公共Web服务器中共享RBP目标位点失调的全基因组概况，我们将其用于识别DDHD2作为候选的精神分裂症风险基因。该资源提供了新颖的分析框架，可将各种RNA调控与复杂疾病联系起来。