Sporadic point mutations and large copy number variants (CNVs) contribute significantly to the etiology of autism and currently account for approximately 10–30% of cases. One approach to identifying the remaining genetic causes is to sequence larger numbers of individuals. SPARK will accordingly add to this effort by sequencing approximately 50,000 trios.
The goal of Evan Eichler’s current project is to significantly increase the yield of high-impact autism mutations by focusing on the discovery of both CNVs and single nucleotide variants (SNVs) for the approximately 15,000 exomes that are currently available from 4,500 families with autism enrolled in SPARK. Unlike SNVs, CNVs are more difficult to discover and validate, especially from whole-exome sequencing data sets. CNV detection and validation is an area where the Eichler laboratory has focused considerable effort. Using established and novel computational pipelines, they propose to work with the SPARK consortium to generate a high-confidence set of potential pathogenic variants and then integrate these data into larger de novo SNV (e.g., denovo-db) and CNV (e.g., morbidity map) databases to pinpoint pathogenic variants and novel genes associated with autism.