Recent advances in genome-wide approaches for gene discovery in autism spectrum disorders (ASDs) have identified a large list of strongly associated ASD risk genes, as well as an even larger list of potential ASD risk genes. In total, these comprise approximately 250 genes. In order to further distinguish the true ASD risk genes from false-positive associations, additional sequencing data is required. Molecular inversion probe (MIP) sequencing is an efficient approach because of the low cost, potential for parallelization and high-throughput capacity.
Matthew State at the University of California, San Francisco (UCSF), in collaboration with Joseph Buxbaum at the Icahn School of Medicine at Mount Sinai School, Eric Morrow at Brown University, Young Shin Kim at UCSF, Bernie Devlin at the University of Pittsburgh, Kathryn Roeder at Carnegie Mellon University and John Overton at Regeneron, proposes to use MIP sequencing to investigate the number and spectrum of mutations in these putative ASD risk genes in 15,250 individuals, including 6,250 individuals with ASD. Based on current mutation rates and the size of the cohort, State and his colleagues anticipate identifying enough mutations to reclassify 20 probable genes as having high confidence for ASD association. Additionally, the team expects to greatly expand our knowledge of the allelic spectrum of mutations in the list of truly associated ASD genes. Together, these two advances will improve our ability to dissect the underlying biology of ASD using systems biological analyses and model systems approaches.