The last decade has seen remarkable progress in gene discovery for autism spectrum disorder (ASD), 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). These findings are mainly driven by highly deleterious de novo mutations in the genes most intolerant to such variation.

The next great challenge is to perform whole-genome sequencing (WGS) in order 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. WGS analysis is complicated by the sheer quantity of de novo and inherited variants across the genome and limited tools to reliably predict functional consequences of variants in noncoding regions of the genome. 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 SFARI cohorts (i.e., SSC and SPARK). In a series of four linked projects, the consortium expands these efforts to aggregate, analyze and interpret WGS data from multiple ASD cohorts and to evaluate the effects of associated variants on gene function.

Stephan Sanders’ laboratory, in project one of these four linked projects, will reprocess existing WGS data from thousands of ASD families using a common standardized pipeline in collaboration with investigators working on MSSNG, iHART (Hartwell Foundation’s Autism Research and Technology Initiative) and REACH (Research and Education for Autism in Children) studies. De novo and inherited variants will be predicted across the entire data set and shared with other projects and consortia.

By applying the Category-Wide Association Study (CWAS) framework, developed by the SSC-ASC WGS Consortium¹, along with novel tools that will be developed in project two, this study aims to identify categories of noncoding variation and specific noncoding variants associated with ASD.