PROJECT ABSTRACT The Center for Reproductive Medicine (CRM) represents a multi-disciplinary program to explore the genetic architecture of infertility. The CRM Genomics Core (GC) described herein envisages providing a centralized and catalytic resource for genomic variation, statistical association, and functional perturbations for all components of this overarching CRM program. This genomics hub will specifically catalyze discoveries by providing expertise in the data and methods that will be leveraged for deeper insights into rare and common forms of infertility in Projects 1 and 2, respectively. The GC will also serve as the focal point for cross-fertilization of data, analyses, and functional modeling across the program. Over the last several years, we have developed a compendium of computational tools, statistical approaches, and functional genomics methods to interrogate the mutational spectrum of variation in human diseases. Our methods incorporate joint analyses of short variants (SNVs, indels) and structural variants (SVs), including canonical balanced SVs and copy number variants (CNVs), as well as a diverse catalog of complex SVs that are surprisingly abundant and associated with an array of human disease. These studies have required methods to uniformly generate, process, and rigorously analyze genomics datasets for association studies. In the GC, we will discover and annotate variation, interpret association against population-scale datasets in excess of 1,000,000 genomes from our related studies, and perform scalable engineering to generate an allelic series of perturbations in genes associated with rare and common forms of infertility using human induced pluripotent stem cell (hiPSC) derived GnRH models. Overall, we will support the CRM by completing three objectives related to providing datasets, methods, and functional resources. Objective 1 will develop a comprehensive genomics resource from exome, genome and long-read sequencing, and uniform data processing of the CRM cohorts. Objective 2 will perform integrated rare variant association and interpretation of these datasets by jointly analyzing CRM cohorts with population-scale datasets generated in our genome aggregation database (gnomAD) project and complex disease consortia studies. Objective 3 will then perform scalable CRISPR perturbation of infertility genes in GnRH neuronal models by engineering loss-of-function mutations and an allelic series for select infertility genes. Transcriptional profiling in the genomics core will identify signatures associated with perturbation of these infertility genes, and will seek convergence of these signatures on a small number of infertility relevant pathways. All CRISPR-engineered models will be distributed relevant projects for further functional assays, and all data and models will be made openly available for distribution to the community. These objectives in the genomics hub of the CRM will thus provide datasets, gene discoveries, ...