The last decade has seen remarkable progress in gene discovery for autism spectrum disorder (ASD). This has been catalyzed by exome sequencing of the 1.5 percent of the genome that encodes proteins and microarray analysis to find very large copy number variations (CNVs). The findings are mainly driven by highly deleterious de novo mutations in the genes most intolerant to such variation. The next great challenge is whole-genome sequencing (WGS) to assess how regulatory variants in the rest of the genome contribute to ASD and what insights these may give into when and where in the brain gene disruptions can cause symptoms.

Genome-wide sequence analysis is complicated by the sheer quantity of de novo and inherited variants across the genome and the limited tools to reliably predict functional consequences. The scale and complexity of WGS-based studies thus require expertise in human genetics, genome biology, computer science, bioinformatics, statistical genetics and functional modeling. Based on this need for complementarity, the Simons Simplex Collection (SSC)-Autism Sequencing Consortium (ASC) Whole-Genome Sequencing Consortium was established to analyze WGS data from the SSC and ASC cohorts. In a series of four linked projects, this consortium will expand on its initial efforts to aggregate, analyze and interpret WGS studies in ASD¹, as well as evaluating the effects of associated variants on gene function.

In Project 3 of this consortium, Michael Talkowski will define the mutational spectrum of structural variation associated with ASD risk. Talkowski’s team will evaluate structural variants that disrupt individual ASD loci, putative noncoding functional elements and three-dimensional regulatory architecture in the genome. They will then incorporate single nucleotide and indel variants for joint analyses of all genomic variation and prioritize ASD-associated loci for in vitro and in vivo modeling. Findings arising from these studies will provide a comprehensive overview of the relative risk and functional impact associated with structural reorganization of the coding and noncoding genome from aggregated ASD data sets.