Ataxia gene identification by integrated genomic analysis

University Of Michigan At Ann Arbor, Ann Arbor MI

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Abstract

DESCRIPTION (provided by applicant): Ataxias are a heterogeneous group of neurological disorders caused by environmental as well as genetic factors. While mutations in more than 40 genes have been implicated in hereditary ataxia, and genetic testing has become an increasingly routine clinical practice, most sporadic and many inherited cases are still of unknown origin. Individual families with unexplained ataxia are often too small to allow gene identification by traditional positional cloning approaches; and the lack of understanding of ataxia etiology in these cases continues to hamper accurate diagnosis and identification of novel targets for effective and personalized therapy. Recently, massively parallel sequencing allows efficient discovery of nearly all variants in a genome, or at least its coding portion. However, as each person carries thousands of novel variants, sequencing alone does not permit immediate identification of causative mutations. Here, we hypothesize that genetic linkage, sequencing-based variant discovery, and gene expression analysis, while not sufficiently informative separately, provide complementary information and allow identification of novel ataxia genes in families with a minimum of two recessive or three dominantly affected members. We already have recruited and started to analyze 12 such pedigrees, and have developed expertise to collect and analyze the relevant genomic data. We propose to study 22 pedigrees using an integrated pipeline that combines linkage analysis, gene expression profiling, next-generation sequencing, and gene network analysis. Since different ataxia families likely carry distinct variants, none of these techniques alone will be sufficient, but their combination will be highly informative to pinpoint candidates. Candidate mutations will be tested for absence in control samples, and candidate genes will be screened for additional mutations in unrelated cases. By using such an integrated approach we have recently identified an auditory neuropathy gene and have found a credible novel candidate gene for dominant central nuclear myopathy. We also have promising preliminary data for several ataxia pedigrees. In addition to global analyses of complementary genomic datasets, we are committed to rapid functional follow-up using appropriate neuronal cells. This is achieved by reprogramming fibroblasts from biopsy cultures from selected families into neurons, and testing the effect of potential mutations on splicing and amount of mRNA, on other genes within the relevant cell type, and on cellular phenotypes. We predict that this pipeline will lead to the identification of new rare ataxia gene mutations that were not previously possible using purely genetic positional cloning strategies. The discoveries will enable better diagnosis and prognosis which will immediately help the affected families. It may lead to personalized treatment & generate new hypotheses to study the more common sporadic forms of ataxia. The identification of validated & functionally characterized molecular lesions is expected to facilitat informed drug development. Our experience with this approach will also establish a useful paradigm for other rare Mendelian disorders.