Deep Sequencing of CNR1 Gene Network in Substance Dependence

说明（申请人提供）：D物质依赖CNR 1基因网络的深度测序：摘要本导师研究职业发展奖（K 01）旨在培养耶鲁大学精神病学系的初级教员左玲君博士成为物质依赖（SD）遗传学研究领域的独立研究者。培训包括三个主要领域：（1）先进的人类分子遗传学，特别是“Solexa”测序和大麻素受体1（CNR 1）基因网络;（2）神经科学，特别是SD、脑神经网络和大麻素受体与其他SD候选基因的蛋白质产物之间的功能关系;以及（3）用于高通量序列数据、基因网络数据以及基因x环境相互作用分析的生物信息学和统计学分析方法。为了获得这些培训，左博士的时间将被分配（1）课程和研讨会，（2）与导师和共同导师的会议，（3）与其他专家的互动，以及主要（4）拟议的研究项目本身。该研究计划将重点关注CNR 1基因网络的深度测序，该网络由CNR 1和其他五个生物相关基因组成。Zuo博士建议通过以下方式识别该基因网络中潜在的SD功能变体：（1）使用下一代测序方法在相对较大的样本中对靶基因区域进行测序，以及（2）使用多基因模型研究多个功能变体的联合效应，这些功能变体可能产生太弱的个体效应，无法使用单基因模型检测。这项研究有望阐明SD患者CNR 1基因网络中的遗传变异，为SD的病因学研究提供重要的进展，也有助于开发新的有效的治疗和预防策略。 公共卫生相关性：与公共卫生的相关性这个拟议项目将使用下一代深度测序技术仔细研究大麻素受体1基因（CNR 1）网络对物质依赖（SD）风险的影响，这将有助于我们更好地了解SD发展的机制。预期的调查结果将大大有助于改善公共卫生。

DESCRIPTION (provided by applicant): D Deep sequencing of CNR1 gene network in substance dependence: Abstract This Mentored Research Career Development Award (K01) is to train Dr. Lingjun Zuo, a junior faculty member of Department of Psychiatry at Yale University, to become an independent investigator in the research field on genetics of substance dependence (SD). The trainings include three main areas: (1) advanced human molecular genetics, in particularly in "Solexa" sequencing and cannabinoid receptor 1 (CNR1) gene network; (2) neuroscience, in particularly in SD, brain neural networks and functional relationship between cannabinoid receptor and protein product of other SD candidate genes; and (3) bioinformatic and statistical analytical methods for high-throughput sequence data, gene network data as well as gene x environment interaction analysis. To acquire these trainings, Dr. Zuo's time will be allocated (1) to courses and seminars, (2) to meetings with the mentor and co-mentors, (3) to interactions with other experts, and mainly (4) to the proposed research project per se. The research plan will focus on deep sequencing of CNR1 gene network that consists of CNR1 and five other biologically related genes. Dr. Zuo proposes to identify the potential functional variants underlying SD in this gene network by (1) sequencing the targeted gene regions in a relatively big size of sample using next generation sequencing approach, and by (2) using multiple-gene model to investigate the joint effects of multiple functional variants, which might exert too weak individual effects to be detectable using single-gene model. This proposed study would be promising to elucidate the genetic variants in the CNR1 gene network underlying SD, which would make a major progress in the etiology of SD, and may also be helpful to develop novel and effective treatment and prevention strategies for SD. PUBLIC HEALTH RELEVANCE: Relevance to public health This proposed project will carefully study the effects of cannabinoid receptor 1 gene (CNR1) network on risk for substance dependence (SD) using the next generation deep sequencing technology, which will help us better understand the mechanism for the development of SD. The expected findings would significantly contribute to the improvement of public health.