Identification of Genetic Variants that Contribute to Compulsive Cocaine Intakein Rats

摘要 NIDA动物遗传学计划的目的是识别遗传、基因组、表观遗传变异， 导致成瘾类行为的生理和大脑功能，相关的行为内表型， 以及药物使用障碍的行为共病。在过去的四年里，我们的多学科和 高度合作的联盟一直在识别与增加的基因变异相关的 对强迫性类可卡因使用的易感性通过使用慢性疾病的高级模型进行第一次GWA N/NIH异种血库(HS)静脉注射可卡因。我们还创建了第一个 临床前可卡因生物库，使没有资源的研究人员能够进行慢性 静脉给药或下一代基因组测序以执行高级遗传， 分子和细胞研究，以加深我们对类似成瘾的生物学变化的理解 行为。虽然这些努力在实现计划的里程碑方面非常成功，但它已经成为 很明显，我们的项目将受益于更大的样本量。特别是，增加样本量会导致 以指数式而非线性的方式增加已识别的基因座数目。此外，在过去的四年里， 在行为和基因分析方面取得了巨大的技术进步，可以利用这些技术来 提供前所未有的途径来确定单核苷酸和结构变异 与可卡因使用障碍高度相关的复杂行为内表型。这其中的第一个目标是 竞争性更新是将当前GWAs的样本量增加一倍，以增加基因变异的数量 确定并满足生物库的要求。第二个目标是使用高吞吐量行为 基于深度神经网络转移学习的无标记姿态估计表型识别 行为内表型可以帮助预测和识别患有抗性、轻度、中度或 严重的可卡因成瘾行为表型。第三个目标是使用 遗传分析，包括结构变异和串联重复序列的分析，以及增强的 与基因表达数据的整合。第四个目标是加强可卡因生物库基础设施。这 该项目可能会继续对外地产生持续和强大的影响，因为它将提供 与成瘾有关的遗传基因座、eQTL和Phewas分析的数量呈指数级增加- 类似行为；建立第一个高通量的类似成瘾行为的行为母题分析 并行视频记录和自动机器学习分析；识别新的行为内表型 对类似成瘾行为的脆弱性/抵抗力；以及扩大和改进可卡因生物库服务 和基础设施。

Abstract The purpose of the NIDA Animal Genetics Program is to identify genetic, genomic, epigenetic variants, physiology and brain functions that contribute to addiction-like behaviors, related behavioral endophenotypes, and behavioral comorbidities to substance use disorder. During the past four years, our multidisciplinary and highly collaborative consortium has been identifying gene variants that are associated with increased vulnerability to compulsive-like cocaine use by performing the first GWAS using an advanced model of chronic intravenous cocaine self-administration in N/NIH heterogeneous stock (HS). We have also created the first preclinical cocaine biobank which enables researchers who do not have the resources to perform chronic intravenous self-administration or next-generation genome sequencing to perform advanced genetic, molecular, and cellular studies to further our understanding of the biological changes underlying addiction-like behaviors. While these efforts have been very successful in achieving the planned milestones, it has become clear that our project would benefit from an even larger sample size. In particular, increasing sample sizes lead to exponential rather than linear increase in the number of loci identified. Moreover, in the past four years there has been tremendous technological advances in behavioral and genetic analysis that can be leveraged to provide unprecedented access to identify the single nucleotide and structural variants that contribute to complex behavioral endophenotypes of high relevance to cocaine use-disorders. The first goal of this competing renewal is to double the sample size of the current GWAS to increase the number of gene variants identified and meet the demands of the Biobank. The second goal is to use high-throughput behavioral phenotyping using markerless pose estimation based on transfer learning with deep neural network to identify behavioral endophenotypes that can help predict and identify individuals with a resistant, mild, moderate, or severe phenotype of cocaine addiction-like behaviors. The third goal is to use methodological improvements of the genetic analysis, including the analysis of structural variants and tandem repeats, as well as enhanced integration with gene expression data. The fourth goal is to strengthen the cocaine biobank infrastructure. This project is likely to continue having a sustained and powerful impact on the field because it will provide an exponential increase in the number of genetic loci identified, eQTLs and PheWAS analysis related to addiction- like behavior; establish the first high-throughput behavioral motifs analysis of addiction-like behaviors using parallel video-recording and automated machine learning analysis; identify novel behavioral endophenotypes of vulnerability/resistance to addiction-like behaviors; and expand and improve the Cocaine Biobank offering and infrastructure.