Reconstructing the complete mutational spectrum of DNA structural variation (SV) in healthy and diseasepopulations is a central challenge of computational biology in this new era of translational genomics. High-resolution genomics technologies have catalyzed the ongoing shift away from microarray-based methods todetect copy number variants (CNV) and toward whole-genome sequencing (WGS) in disease studies.However, there are major methodological barriers that have precluded a comprehensive benchmarking of thesensitivity and specificity of WGS-based algorithms for the detection of CNVs, as well as delineation ofbalanced and complex SVs such as the recently discovered dupINVdup and chromothripsis that have beencryptic to array technology. Given the high translational potential of defining genome structural changes, and tocharacterizing its functional consequences, there is at present a unique opportunity in genomics to developcutting-edge computational methods to enable detection of the full mutational spectrum of SV by integratinginformation from new and emerging technologies. Here, I propose to develop an SV detection tool to replacethe current mainstays of genetic research studies, with a focus on autism spectrum disorder (ASD) andneuropsychiatric disorders more broadly (NPDs). I will also seek to train in three primary areas to augment myexisting expertise in molecular cytogenetic methods: (1) computational genomics and analysis of WGStechnologies, (2) defining multi-allelic CNVs and complex SVs in ASD, (3) functional genomics to characterizethe transcriptional impact of complex SVs and chromothripsis. Each goal is incorporated into specific aims. InAim 1, I will develop and optimize algorithms for SV detection by integrating data from multiple technologies inthree trios, including long-read single-molecule sequencing, PCR-free Illumina WGS, jumping library WGS,10X Genomics synthetic long reads and haplotype phasing, BioNano genomics optical mapping, and Hi-C. InAim 2, I will apply these methods to evaluate the contribution of all classes of SV to ASD from analysis of4,000 genomes from ASD families. I will particularly focus on balanced, complex SVs multi-allelic CNVs, anatural extension from my PhD work creating the PennCNV and ParseCNV algorithms for CNV detection frommicroarray data. Finally, in Aim 3 I will learn a new area of expertise in functional genomics to investigate thelocal and global transcriptional impact of complex SVs and chromothripsis in patient-specific iPS-derivedneural precursors and neurons. At its conclusion, these studies will develop a sensitive and specific SVdetection tool from WGS data, having broad utility in gene discovery efforts in ASD, NPDs, and humandisease, while providing targeted career development.
Interagency Autism Coordinating Committee (IACC)
Autism Research Database (AFD)
