Identification and functional analysis of noncoding mutations in autism

  • Awarded: 2019
  • Award Type: Bridge to Independence
  • Award #: 551150

The phenotypic and genetic heterogeneity of autism spectrum disorder (ASD) has posed immense clinical and research challenges to understanding the underlying genetic determinants of ASD risk. In the past several years, advancements of sequencing technologies and the availability of large cohorts have led to the discovery of many novel genes contributing to ASD risk, but the vast majority of individuals with ASD still lack a genetic diagnosis.

In this project, Ryan Doan and colleagues will screen for noncoding mutations with the greatest likelihood of impacting gene regulation (i.e., gene promoters, splicing regulators, cis-regulatory elements). Doan’s team will systematically assess underlying mechanisms by which mutations that disrupt transcriptional splicing, gene promoters and enhancers impact ASD risk using both computational predictions and large-scale functional screening.  The functional screening approach that will be taken involves measuring gene expression in neuronal cultures using a novel high-throughput massively parallel reporter assay as well as luciferase assays. Interesting candidates arising from these assays will be further investigated through a combination of knock-in cell line and transient transgenic mouse models. This screening approach allows for simultaneous assessment of thousands of promoter mutations. The further incorporation of transcription factor screening and chromatin immunoprecipitation methodologies with this screening approach will allow Doan’s group to elucidate the mechanisms underlying these ASD risk loci.

Together, these data will create the first large-scale genome-wide promoter database of functionally validated mutations with broad importance for both the research and clinical community. Even more, since the coding regions of the impacted genes remain fully intact, this class of mutations represents ideal targets for putative therapeutic attempts. This database of functionally tested mutations will therefore provide an important step toward developing strategies to correct abnormal gene splicing or expression in ASD; such approaches have already shown success in treating other disorders, including spinal muscular atrophy and Duchenne muscular dystrophy.

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