ABSTRACT
The splicing of pre-mRNAs into mature transcripts is remarkable for its precision, but the mechanisms by which the cellular machinery achieves such specificity are incompletely understood. Here, we describe a deep neural network that accurately predicts splice junctions from an arbitrary pre-mRNA transcript sequence, enabling precise prediction of noncoding genetic variants that cause cryptic splicing. Synonymous and intronic mutations with predicted splice-altering consequence validate at a high rate on RNA-seq and are strongly deleterious in the human population. De novo mutations with predicted splice-altering consequence are significantly enriched in patients with autism and intellectual disability compared to healthy controls and validate against RNA-seq in 21 out of 28 of these patients. We estimate that 9%-11% of pathogenic mutations in patients with rare genetic disorders are caused by this previously underappreciated class of disease variation.
Subject(s)
Forecasting/methods , RNA Precursors/genetics , RNA Splicing/genetics , Algorithms , Alternative Splicing/genetics , Autistic Disorder/genetics , Deep Learning , Exons/genetics , Humans , Intellectual Disability/genetics , Introns/genetics , Neural Networks, Computer , RNA Precursors/metabolism , RNA Splice Sites/genetics , RNA Splice Sites/physiologyABSTRACT
Exome sequencing studies have identified multiple genes harboring de novo loss-of-function (LoF) variants in individuals with autism spectrum disorders (ASD), including TBR1, a master regulator of cortical development. We performed ChIP-seq for TBR1 during mouse cortical neurogenesis and show that TBR1-bound regions are enriched adjacent to ASD genes. ASD genes were also enriched among genes that are differentially expressed in Tbr1 knockouts, which together with the ChIP-seq data, suggests direct transcriptional regulation. Of the nine ASD genes examined, seven were misexpressed in the cortices of Tbr1 knockout mice, including six with increased expression in the deep cortical layers. ASD genes with adjacent cortical TBR1 ChIP-seq peaks also showed unusually low levels of LoF mutations in a reference human population and among Icelanders. We then leveraged TBR1 binding to identify an appealing subset of candidate ASD genes. Our findings highlight a TBR1-regulated network of ASD genes in the developing neocortex that are relatively intolerant to LoF mutations, indicating that these genes may play critical roles in normal cortical development.
