High Throughput Sequencing and Copy Number Variation in Schizophrenia

Univ Of North Carolina Chapel Hill, Chapel Hill NC

Investigators

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Abstract

DESCRIPTION (provided by applicant): Candidate: Dr. Jin P. Szatkiewicz, a postdoctoral trainee at the University of North Carolina at Chapel Hill, has a very strong background in both biology and statistics and a track record of biomedical research throughout her training. Inspired by family members who suffer from severe mental illness, she wishes to devote her life to genetic research that benefits the mentally ill. Long-term career goal: To become an independent academic researcher focused on the impact of copy number variation (CNV) on risk for schizophrenia and other psychiatric disorders. Training objectives: The candidate plans to further develop the technical and professional skills necessary to establish an independent program of future research in CNV and schizophrenia, and to lead future multidisciplinary studies. The candidate plans to produce a critical mass of preliminary data and publications to support an R01 grant application. The career development activities, proposed research plan, mentorship team, and institutional environment are all uniquely suited to assist the applicant in achieving these goals. Career development: A key element of the proposed career development is simultaneous training in computational biology, statistical genetics, psychiatric genetics, and computer science. Research Study: The objectives of the proposed research are to develop optimal protocols and software tools for detecting and analyzing CNVs from high-throughput sequencing (HTS) data. These tools will be made publicly available in user-friendly implementations. The optimal protocols will be fully implemented in multiple datasets to understand the role of CNVs in the etiology of schizophrenia. Mentorship team: The dedicated mentorship team includes internationally recognized, independently funded investigators with expertise in psychiatric genetics (Sullivan), statistical genetics (Lin), computational biology (Sun), and computer science (Wang). The supportive consultant/advisor team includes leading experts Drs. Purcell, Sebat, and Li, with expertise appropriate for the proposed research and career development. Environment: The University of North Carolina provides a productive, collegial, and collaborative atmosphere in which to pursue the above research and training goals. Impact: Completion of the proposed research will significantly impact the field by providing optimal protocols and user-friendly tools for CNV analysis using HTS and by identifying CNVs associated with schizophrenia. Upon completing the training and research plans in this application, the PI will be well positioned as an independent investigator with a deep understanding of schizophrenia and the capability to lead multidisciplinary future studies.