In this application we propose to identify the molecular etiologies of genetic movement disorders as an important step towards improving diagnoses, elucidating pathogeneses, and facilitating efforts to develop targeted therapies. The categories of disease studied in this project, including parkinsonian syndromes, ataxias, spastic paraplegias, and choreiform or dystonic disorders, are all genetically heterogeneous and many more subtypes remain to be discovered. We will accomplish our goals through three specific aims. We will: 1) continue to ascertain and characterize individuals and families with genetically unattributed movement disorders; 2) take advantage of advances in gene localization and molecular biology technologies and bioinformatics to discover and validate new genes for movement disorders; and 3) evaluate the effects of pathogenic variants on gene function and clinical manifestations. We build on established synergistic collaborations between the Investigators and their neurology and molecular genetics colleagues, and leverage the invaluable resources of two large collections of samples ascertained, extensively characterized, and extended over 30 years (Neurogenetics and Parkinson's disease repositories). The transition from positional cloning to mutational cloning was made possible by the development of massively parallel DNA sequencing and the success of the Human Genome Project that provided a template against which to compare the sequences obtained from any individual. Because the great majority of genetic diseases are caused by mutations that affect the protein sequence, this research focuses on the “exome”, the collective protein-coding regions of the genome. The challenge of mutational cloning is to identify a pathogenic mutation in the background of thousands of benign protein changing variations in individual exomes. Our proposed approach combines traditional linkage or identity-by-descent (IBD) analysis to identify genomic regions shared by all affected family members and exome sequencing of several affected relatives to identify the variants they share in the linkage/IBD region. Advances in statistical genetics make it possible to perform such studies in smaller families and more powerful bioinformatics offer a stepwise filtering approach to select the likely pathogenic variants for further study. Cosegregation of the variant with disease in single families and identification of mutations in the same gene in other families and panels of sporadic cases with the same disorder provide validation that the gene is responsible for the disease. Disease pathogenesis can then be investigated through mechanistic studies. This approach has led to our documented record of consistent productivity in parsing genetic neurologic disorders. For illustration, we describe multiple disorders whose causative genes we recently discovered, including RAB39B- and ATP6AP2-related parkinsonian syndromes. Beyond the implication of gene discovery for...