Gene discovery in autism spectrum disorders (ASDs) has accelerated in the past several years. However, current efforts have mainly focused on the coding portion of the genome, which reflects approximately 1 percent of the total genome. This focus is partly due to the expense of characterizing the entire genome, as well as difficulties in interpreting the significance of variations in noncoding DNA information.

Whole-genome sequencing (WGS) is now entering an era of technical feasibility and affordability, which makes it an attractive method for pursuing variation in the noncoding regions of DNA. Nonetheless, there are still problems with interpretation of variations in noncoding DNA, mainly due to a lack of understanding of the composition and function of the noncoding genome.

To help overcome this challenge, Matthew State, Stephan Sanders, Jeremy Willsey, Nenad Sestan and David Goldstein aim to leverage a wealth of multidimensional data in order to begin to clarify the role(s) of noncoding regions and the impact of mutations within them. This team of researchers will comprehensively identify and analyze de novo variation from WGS data derived from the 500 Simons Simplex Collection (SSC) quartets and an additional 250 SSC quartets currently being sequenced by this group. To address the inherent difficulties in interpreting noncoding variation, the team will comprehensively annotate variants, using the group’s wealth of human and primate neurogenomic data. They will also assess conservation and mutational tolerance using tools previously developed in their laboratories.

Based on these annotations, the researchers will also address the question of mutation burden in the noncoding genome in individuals with ASD versus sibling controls and attempt to leverage recurrent de novo mutations to identify specific risk loci. The teams will also investigate whether the distribution of mutations in ASD individuals versus controls points to specific cell types or developmental periods that are enriched for risk, and conduct analyses using sex-specific annotations to characterize noncoding mutations in ASD boys versus girls.

This group of researchers is uniquely positioned to deploy the necessary resources to assess the importance of variations in noncoding DNA and the impact of these variations on ASD risk. The findings from this research will help to further explain some of the currently unidentified genetic risk for ASD.