Genome analysis to elucidate molecular mechanisms for peripheral neuropathies

描述(由申请人提供)：本建议书描述了一个指导临床和实验室培训的5年计划，旨在为候选人作为一名医生-科学家的独立学术生涯做好准备。申请人是医学博士，最近在贝勒医学院完成了为期4年的医学遗传学实习计划。职业发展计划包括有指导的研究培训，这将包括：i)与导师的定期会议，ii)与科学咨询委员会的半年会议，iii)授课课程，iv)研讨会，v)实验室会议，vi)国家会议，以及vii)国际会议。培训将在贝勒医学院进行，提供良好的培训环境，可使用最新的基因组研究工具。该项目的主要目的是通过鉴定与Charcot-Marie-Tooth(CMT)病有关的新基因，阐明人类周围神经在健康和疾病中的生物学意义。肌萎缩侧索硬化症是一种进行性神经系统疾病，由周围神经恶化并继发性肌肉萎缩和无力引起。这种疾病在临床和分子上都是非常不同的。我们将研究一组描述良好的遗传性周围神经病变患者，32个已知CMT基因中的任何一个都没有明显的致病序列变异。将应用最先进的分子技术(下一代测序和基因组微阵列)确定索引患者的基因组图谱，包括拷贝数变异和单核苷酸变异。基因组数据经过生物信息学处理和筛选后，将被挖掘以识别候选基因。传统遗传学、分子生物学和生物信息学的方法将被用来进一步验证新的候选对象的致病潜力。

DESCRIPTION (provided by applicant): This proposal describes a 5 year plan for mentored clinical and laboratory training designed to prepare the candidate to an independent academic career as a physician-scientist. The applicant is an MD, PhD, who recently completed the 4 year residency program in Medical Genetics at Baylor College of Medicine. The career development plan includes mentored research training which will include: i) regular meetings with the mentor, ii) biannual meetings with a Scientific Advisory Committee iii) didactic courses, iv) seminars, v) lab meetings, vi) national meetings, and vii) international meetings. The training will take place at Baylor College of Medicine providing an excellent training environment with access to the latest tools of genome study. The project main aim is to elucidate the biology of the human peripheral nerve in health and disease through the identification of novel genes implicated in Charcot-Marie-Tooth (CMT) disease. CMT is a progressive neurological disease caused by deterioration of the peripheral nerves with secondary muscle wasting and weakness. The disease is extremely heterogeneous both clinically and molecularly. We will study a cohort of well described patients with hereditary peripheral neuropathy and no obvious disease-causing sequence variants in any of the 32 known CMT genes. The genomic profile, including copy number variations and single nucleotide variations will be determined for index patients with the application of state of the art molecular techniques (next generation sequencing and genomic microarrays). Genomic data, after bioinformatics processing and filtering, will be mined to identify candidate genes. The methods of conventional genetics, molecular biology, and bioinformatics will be implemented to further validate the disease-causing potential of novel candidates