Functional characterization of 3’UTR variants identified from WGS data of an ASD cohort
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Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder which currently affects roughly 1% of the world population. Although the genetic components of the disorder have been extensively studied, the underlying genetic risk factors and mechanisms of ASD remain poorly understood. In this study, we highlight the importance of investigating the potential effects of noncoding variation and their role in the ASD phenotype. Herein, we functionally characterize de novo single nucleotide variants (SNVs) identified from whole genome sequencing (WGS) data of an ASD cohort. Our focus lies on microRNA binding sites in the 3 prime untranslated region (3'UTR), due to their interaction with microRNAs, which perform important regulatory functions that can affect brain development. By applying a bioinformatic pipeline to WGS data from 53 families affected by ASD, we were able to identify 12 regulatory variants predicted to fall into a microRNA binding site (MBS). Out of these 12 variants, we validated one as functional, in the 3'UTR of TAF7L. Our study further shows that many predicted MBSs were not functional in our luciferase assays, revealing a need for refined MBS prediction algorithms. In the future, the use of larger WGS data sets will enable sufficiently-powered studies that can follow-up on the role of MBS variants for ASD and lead to a better integration of coding and noncoding risk factors for the disorder.
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