Discovery of Addiction-Related Genes with Advanced Mouse Resources

项目总结/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 和成瘾的发展。尽管成瘾仍然是全球社会和经济的巨大负担， 广泛努力遏制毒品供应和使用。可卡因成瘾的高遗传性表明， 药物暴露后发生物质使用障碍（SUD）的倾向受遗传影响。两 人类和动物的研究表明，行为特征，如新奇寻求强烈相关， 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 通过利用小鼠的进展来描述成瘾和诱发行为的生物学机制 遗传资源，包括高精度的多样性远交（DO）小鼠种群， 转基因小鼠，通过RNA序列分析的基因表达定量，和计算 系统遗传学中的统计方法在目标1中，我们将确定潜在的遗传机制 通过数量性状基因座（QTL）分析， 一大群DO小鼠。其中最引人注目和最易处理的将在基因靶向小鼠中得到验证 模型静脉内药物自我给药（IVSA）模式，被认为是 在啮齿动物研究中评估成瘾特征，将使成瘾的核心特征量化 包括开始使用药物、不良消退和强化药物服用的增强恢复。在目标2中 我们将量化两个相连的成瘾相关组织中的基因表达遗传变异， 皮质和纹状体，绘制表达QTL，并使用RNA- seq在未用药的DO小鼠亚组中，并通过广泛使用的信息学传播这些结果 资源在未用药小鼠中的基因表达分析使得能够分离药物的生物底物。 药物暴露的生物后遗症导致的成瘾倾向。在目标3中，我们将解决 评估成瘾多个组成部分的协调基因表达的基本问题 电路，以评估相对失调，以确定全球与大脑区域特异性因素， 成瘾的脆弱性这将通过发展稳健的多元统计 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，将不同和不相容的指标与 两组独立的小鼠，同时扩展到多个组织共表达网络。发展这一 成瘾研究背景下的技术将扩展统一的数据集成框架， 对所有疾病领域的人类和小鼠遗传学和基因组研究进行多维化。之间的协同作用 目标将揭示网络从多态性到成瘾相关行为。

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.