Center for Systems Neurogenetics of Addiction

总体项目总结 系统神经遗传学成瘾中心(CSNA)利用行为方面的方法和专业知识 神经科学、计算科学、基因组生物学、小鼠和人类遗传学，以及基因工程 确定可卡因生物行为风险的共同和不同的生物机制，并对其进行情景分析和建模 自治。药物成瘾是一种受多种病因影响的破坏性复杂的疾病。 各种因素。广泛的证据表明，基因变异对一系列成瘾行为的作用，从 对强迫吸毒行为的实验和用药启动。然而，发现了易感因素 人类群体中的基因和变异受到高样本量要求、表型能力和 药物暴露和其他环境因素的变异性。先进的小鼠遗传群体展示 成瘾相关行为的变化，并为研究神经生物学提供了实验平台 易感特征预测自我给药可卡因倾向的机制。CSNA雇佣了 三个群体的协作性交叉遗传参考群体和多样性异交作图群体 综合研究项目侧重于成瘾易感性的三个相互关联的方面：冲动、可卡因 敏感化和自我管理。这些特征使用多维表型平台进行评估 在表现出极端遗传和表型变异的小鼠群体中，使可复制和可扩展 评估成瘾易损性的共同和不同的生物机制。这些相辅相成 群体来自相同的方正菌株，允许跨研究进行广泛的数据集成 在CSNA内部和外部。CSNA开发了数据集成方法，并产生了多功能 基因组学和表现学数据集，存放在广泛访问和功能强大的信息学资源中，用于 全球研究界。该中心还将其成果扩展到基础神经生物学和临床前 通过将研究结果与人类基因和基因组研究相结合进行治疗研究，产生新的、经过验证的 小鼠突变体和鉴定易受伤害和耐药的菌株，用于机理研究。三项研究支持 核心为CSNA研究项目和更大的研究社区提供最先进的方法， 包括一个复杂的、大容量的行为表型核心，一个集成的遗传学和基因组学 统计遗传学、分子图谱、生物库、数据整合和数据传播的核心，以及一个 鼠标资源和验证核心，用于为系统遗传学创建和交付新的鼠标资源， 验证和疾病建模。行政核心协调、整合和传播研究， 教育和外展活动。最后，试点核心支持协作工作，以促进创新和 成瘾科学的多样性。通过共同努力，CSNA将对研究产生持久影响 成瘾遗传学通过对生物行为风险的全面检查，生成社区数据 我们和其他人将在未来的研究中以及通过教育和培训扩大和利用的资源。

PROJECT SUMMARY OVERALL The Center for Systems Neurogenetics of Addiction (CSNA) leverages approaches and expertise in behavioral neuroscience, computational science, genome biology, mouse and human genetics, and genetic engineering to identify, contextualize and model shared and distinct biological mechanisms of biobehavioral risk for cocaine self-administration. Drug addiction is a devastating and complex disorder influenced by multiple etiological factors. Extensive evidence demonstrates the role of genetic variation on a range of addiction behaviors, from experimentation and initiation of drug use to compulsive drug-taking behavior. Yet discovery of predisposing genes and variants in human populations is limited by high sample size requirements, phenotyping capacity, and variability in drug exposure and other environmental factors. Advanced mouse genetic populations exhibit variation in addiction-relevant behaviors and offer an experimental platform to discover the neurobiological mechanisms by which predisposing traits predict the tendency to self-administer cocaine. The CSNA employs the Collaborative Cross genetic reference population and Diversity Outbred mapping population across three integrated research projects focused on three interrelated aspects of addiction susceptibility: impulsivity, cocaine sensitization and self-administration. These traits are evaluated using a multidimensional phenotyping platform in a mouse population exhibiting extreme genetic and phenotypic variation, enabling a replicable and extensible assessment of the shared and distinct biological mechanisms of addiction vulnerability. These complementary populations are derived from the same founder strains, allowing for extensive data integration across studies within and outside the CSNA. The CSNA develops data integration methods and produces multiple functional genomics and phenomics datasets, deposited in widely accessed and highly functional informatics resources for the global research community. The Center also extends its results into basic neurobiological and preclinical therapeutic research by integrating findings with human genetic and genomic studies, generating novel, validated mouse mutants and identifying vulnerable and resistant strains for mechanistic studies. Three research support cores provide state-of-the-art approaches to the CSNA research projects and the larger research community, including a sophisticated, large-capacity Behavioral Phenotyping Core, an Integrative Genetics and Genomics Core for statistical genetics, molecular profiling, biobanking, data integration and data dissemination, and a Mouse Resource and Validation Core for creating and delivering novel mouse resources for systems genetics, validation, and disease modeling. The Administrative Core coordinates, integrates, and disseminates research, education and outreach activities. Finally, a Pilot Core enables collaborative work to promote innovation and diversity in addiction science. Through its combined efforts, the CSNA will have a lasting impact on the study of addiction genetics through the holistic examination of biobehavioral risk, the generation of community data resources that we and others will expand and exploit in future studies, and through education and training.