Rapid advances in genomics have ushered in new opportunities for Mendelian disease discovery and diagnosis. In the last decade, exome and genome sequencing have moved from the research domain to clinical practice. These approaches have identified new disease genes and causative variants for ~30% of individuals suffering from a rare genetic disease. We believe that the systematic application of promising new genomics assays coupled with innovative computational approaches will foster discovery benefitting the 70% of symptomatic individuals without a genetic diagnosis. To this end we will apply long-read whole genome sequencing, RNA-sequencing, epigenomics assays, metabolomics and targeted in vitro and in vivo assays to evaluate a cohort of undiagnosed individuals suspected to have a Mendelian disorder. Our approach will be augmented through the development and application of computational strategies enabling improved gene and phenotype matching, integrative multi-omics analysis, and variant interpretation. This work is expected to establish a new frontier in Mendelian disease discovery. Our Mendelian Genomics Research Center (MRGC) team has developed key prior expertise and leadership in the use of diverse state-of-the-art experimental and computational methods for the diagnosis and discovery of Mendelian disorders. We hypothesize that the next phase of Mendelian genomics research will be defined by assessing and deploying the most effective ‘omics’ strategies. We propose that ongoing and iterative integration of functional genomics data into the translational genomics toolkit will significantly increase discovery of new gene and variant disease associations beyond the capabilities of DNA-sequencing assays alone. To facilitate this, we will comprehensively study 400 individuals and their immediate family members (N= 900 total) with Mendelian disease where exome sequencing has not yielded a genetic diagnosis. These represent a select cohort of hard to solve cases intractable to DNA sequencing to date. In Aim 1, individuals recruited into the study will undergo short-read and long-read whole genome sequencing, RNA-seq, ATAC-seq and MethylC-seq across multiple commonly used cell/tissue types as well as metabolomics and lipidomics assays. This dataset will define a holistic view of emerging genomics approaches for Mendelian disease diagnosis and facilitate evaluation of the relative merits of each approach. In Aim 2, we focus on computational innovations that will improve integration of these multi-omics data in gene and variant interpretation by integrating functional genomics outliers and advanced statistical learning approaches. These methods will be applicable broadly across the MGRC and the world. In Aim 3, we apply state-of-the-art targeted approaches including massively-parallel reporter assays, induced-pluripotent stem cell functional genomics, CRISPR screens for modifier genes and engineered mouse models to detect and validate novel causal va...