Discovery of Addiction-Related Genes with Advanced Mouse Resources

项目摘要/摘要 我们的首要目标是发现行为倾向背后的遗传和基因组机制。 以及成瘾的发展。成瘾在世界范围内仍然是一个沉重的社会和经济负担，尽管 广泛努力遏制药物的可获得性和使用。可卡因成瘾的高遗传率表明 药物暴露后发生物质使用障碍(SUD)的倾向受到遗传因素的影响。两者都有 人类和动物的研究表明，诸如追求新奇的行为特征与 发生SUD的倾向，但这种关系的生物学基础尚不清楚。我们确定并 利用小鼠的研究进展来表征成瘾和易感行为的生物学机制 遗传资源，包括高精度的杂交系(DO)小鼠种群，验证 转基因小鼠，通过RNA序列分析进行基因表达定量，并进行计算 以及系统遗传学中的统计方法。在目标1中，我们将确定 利用QTL分析易感新奇相关性状与药物自我给药 一大群DO老鼠。其中最引人注目和最容易处理的将在基因靶向小鼠身上得到验证。 模特们。静脉给药(IVSA)范式，被认为是 在啮齿动物研究中对成瘾特征的评估，将使成瘾的核心特征得以量化 包括开始吸毒、消灭不良和加强恢复强化吸毒。在AIM 2 我们将量化两个与成瘾相关的组织，即前额叶的基因表达遗传差异 大脑皮层和纹状体，定位表达QTL，并利用RNA- 在药物天真的DO小鼠亚群中进行SEQ，并通过广泛使用的信息学传播这些结果 资源。药物幼稚小鼠的基因表达分析使其能够分离出 由于药物暴露的生物后遗症而容易上瘾。在目标3中，我们将解决 评估成瘾多个组成部分之间协调基因表达的基本问题 评估相对失调的回路，以识别全球与大脑区域特定的因子 上瘾的脆弱性。这将通过发展稳健的多变量统计来实现 用于识别跨多个高维数据集的关系的方法。这一战略将使 继续使用共同的表型集合，以将不同和不兼容的度量关联到 两组独立的小鼠，同时延伸到多个组织共表达网络。这方面的发展 成瘾研究方面的技术将把统一的数据集成框架扩展到 从人类到小鼠的所有疾病领域的多维遗传和基因组研究。企业间的协同效应 AIMS将揭示从多态到与成瘾相关的行为的网络。

PROJECT SUMMARY/ABSTRACT Our overarching goal is to discover the genetic and genomic mechanisms underlying behavioral predisposition and development of addiction. Addiction remains a substantial worldwide social and economic burden despite extensive efforts to curb drug availability and use. The high heritability of cocaine addiction, indicates that the propensity to develop a substance use disorder (SUD) after drug exposure is genetically influenced. Both human and animal studies indicate that behavioral traits such as novelty seeking are strongly correlated with the propensity to develop an SUD, but the biological basis of this relationship is unknown. We identify and characterize biological mechanisms of addiction and predisposing behavior by harnessing advances in mouse genetic resources, including the high-precision Diversity Outbred (DO) mouse population, validation in genetically modified mice, gene expression quantitation through RNA sequence analysis, and computational and statistical methods in systems genetics. In Aim 1 we will identify genetic mechanisms underlying predisposing novelty-related traits and drug self-administration through quantitative trait locus (QTL) analysis in a large set of DO mice. The most compelling and tractable of these will be validated in gene targeted mouse models. The intravenous drug-self administration (IVSA) paradigm, considered the gold standard for the assessment of addiction traits in rodent research, will enable quantification of the core features of addiction including initiation of drug use, poor extinction and enhanced reinstatement of reinforced drug taking. In Aim 2 we will quantify gene expression genetic variation in two connected addiction relevant tissues, the prefrontal cortex and striatum, map expression QTLs and identify genetic correlates of predisposing behavior using RNA- seq in a drug-naïve subset of DO mice, and disseminate these results through widely used informatics resources. Gene expression analysis in drug-naïve mice enables separation of the biological substrates of predisposition to addiction from the biological sequelae of drug exposure. In Aim 3, we will address the fundamental problem of evaluating coordinated gene expression across multiple components of the addiction circuitry to assess relative dysregulation toward the identification of global- vs brain region-specific factors in addiction vulnerability. This will be accomplished through the development of robust multivariate statistical methods for identification of relations across multiple high dimensional data sets. This strategy will make continued use of a common collection of phenotypes to relate disparate and incompatible measures across two independent sets of mice, while extending into multiple tissue co-expression networks. Development of this technique in the context of addiction research will extend a unifying data integration framework to multidimensional to human and mouse genetic and genomic studies for all disease areas. Synergy among the aims will reveal networks from polymorphism to addiction-related behavior.