Flatiron Institute, Simons Foundation, New York, NY, USA.
Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.
Nat Genet. 2021 Feb;53(2):166-173. doi: 10.1038/s41588-020-00761-3. Epub 2021 Jan 18.
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.
尽管精神疾病有很强的遗传基础，但其中的分子机制在很大程度上仍是未知的。RNA 结合蛋白（RBPs）负责大多数转录后调控，从剪接、翻译到定位。因此，RBPs 是细胞内稳态的关键调控因子，尤其是在大脑中。然而，量化影响 RBP 靶位点的非编码变异的致病贡献具有挑战性。在这里，我们利用一种深度学习方法，可以准确预测突变对 RBP 靶位点失调的影响，并发现 RBP 失调是导致精神疾病风险的主要因素。RBP 失调解释了大量大规模分子数量性状基因座研究未捕获的遗传率，其影响比常见的编码区变异更强。我们共享了 RBP 失调的全基因组图谱，我们利用这些图谱来识别 DDHD2 作为候选精神分裂症风险基因。这个资源提供了一个新的分析框架，将 RNA 调控的全部范围与复杂疾病联系起来。
