Overall NIDA Core "Center of Excellence" in Transcriptomics, Systems Genetics and the Addictome

总体而言，NIDA 转录组学、系统遗传学和成瘾组核心“卓越中心”

• 批准号: 10177978
• 负责人: Laura Maren Saba
• 金额: $ 74.5万
• 依托单位: UNIVERSITY OF TENNESSEE HEALTH SCI CTR
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10177978
• 关键词: Archives; Bayesian Modeling; Behavior; Behavioral; Bioinformatics; Biology; Biometry; Cellular Assay; Chromosome Mapping; Collaborations; Communities; Complex; Computer software; Computing Methodologies; Consult; DNA; DNA Sequence; Data; Data Set; Databases; Development; Disease; Drug Interactions; Drug abuse; Educational workshop; Ensure; Environment; Environmental Risk Factor; Epigenetic Process; Foundations; Funding; Future; Genes; Genetic; Genetic Variation; Genome; Genomics; Genotype; Goals; Human; Hybrids; Image; Informatics; Institution; Joints; Leadership; Machine Learning; Metadata; Methods; Modeling; Molecular; National Institute of Drug Abuse; National Institute on Alcohol Abuse and Alcoholism; Neurosciences Research; Pharmaceutical Preparations; Pharmacotherapy; Population; Prevention; Proteome; Publications; Publishing; Quantitative Genetics; Quantitative Trait Loci; RNA; Rattus; Relapse; Reproducibility; Research; Research Personnel; Resources; Risk; Risk Factors; Rodent; Role; Scientist; Site; Standardization; Statistical Models; Stress; Sum; System; Systems Analysis; Testing; Training; Translations; United States National Institutes of Health; Update; Variant; Visualization; Work; addiction; archive data; archived data; base; behavior influence; brain cell; career; cohort; computerized tools; computing resources; data handling; data integration; data modeling; data repository; data tools; deep learning; digital imaging; drug relapse; epigenome; experience; genetic analysis; genetic variant; genomic variation; graphical user interface; health record; high dimensionality; image archival system; improved; innovation; insight; metagenome; mouse model; multiple omics; neurogenomics; neuronal circuitry; novel; precision medicine; prevent; programs; ranpirnase; rat genome; sex; single cell analysis; software systems; tool; transcriptome; transcriptomics; web portal

Addiction is a highly complex disease with risk factors that include genetic variants and differences in development, sex, and environment. The long term potential of precision medicine to improve drug treatment and prevention depends on gaining a much better understanding how genetics, drugs, brain cells, and neuronal circuitry interact to influence behavior. There are serious technical barriers that prevent researchers and clinicians from incorporating more powerful computational and predictive methods in addiction research. The purpose of the NIDA P30 Core Center of Excellence in Omics, Systems Genetics, and the Addictome is to empower and train researchers supported by NIH, NIDA, NIAAA, and other federal and state institutions to use more quantitative and testable ways to analyze genetic, epigenetic, and the environmental factors that influence drug abuse risk and treatment. In the Transcriptome Informatics and Mechanisms research core we assemble and upgrade hundreds of large genome (DNA) and transcriptome (RNA) datasets for experimental rodent (rat) models of addiction. In the Systems Analytics and Modeling research core, we are using innovative systems genetics methods (gene mapping) to understand the linkage between DNA differences, environmental risks such as stress, and the differential risk of drug abuse and relapse. Our Pilot core is catalyzing new collaborations among young investigator in the field of addiction research. In sum the Center is a national resource for more reproducible research in addiction. We are centralizing, archiving, distributing, analyzing and integrating high quality data, metadata, using open software systems in collaboration with many other teams of researchers. Our goal is to help build toward an NIDA Addictome Portal that will include all genomic research relevant to addiction research.

成瘾是一种高度复杂的疾病，其危险因素包括遗传变异和基因差异。 发展、性别和环境。精准医学改善药物治疗的长期潜力 预防取决于更好地了解遗传学、药物、脑细胞和 神经元回路相互作用以影响行为。存在严重的技术障碍阻碍研究人员 以及临床医生在成瘾研究中采用更强大的计算和预测方法。 NIDA P30 组学、系统遗传学和成瘾组核心卓越中心的目的 旨在授权和培训由 NIH、NIDA、NIAAA 以及其他联邦和州机构支持的研究人员 使用更加定量和可测试的方法来分析遗传、表观遗传和环境因素 影响药物滥用风险和治疗。在转录组信息学和机制研究核心中，我们 组装和升级数百个大型基因组 (DNA) 和转录组 (RNA) 数据集以进行实验 成瘾的啮齿动物（大鼠）模型。在系统分析和建模研究核心中，我们正在使用创新的 系统遗传学方法（基因作图）以了解 DNA 差异、环境差异之间的联系 压力等风险，以及药物滥用和复发的不同风险。我们的 Pilot 核心正在催生新的 成瘾研究领域年轻研究者之间的合作。总之，该中心是一个全国性的 更多可重复的成瘾研究资源。我们正在集中、归档、分发、分析和 与许多其他团队合作，使用开放软件系统集成高质量数据、元数据 研究人员。我们的目标是帮助建立一个涵盖所有基因组研究的 NIDA Addictome Portal 与成瘾研究相关。

项目成果

Genetic Modulation of Initial Sensitivity to Δ9-Tetrahydrocannabinol (THC) Among the BXD Family of Mice.

• DOI: 10.3389/fgene.2021.659012
• 发表时间: 2021
• 期刊: Frontiers in genetics
• 影响因子: 3.7
• 作者: Parks C;Rogers CM;Prins P;Williams RW;Chen H;Jones BC;Moore BM 2nd;Mulligan MK
• 通讯作者: Mulligan MK

Paraquat Toxicogenetics: Strain-Related Reduction of Tyrosine Hydroxylase Staining in Substantia Nigra in Mice.

• DOI: 10.3389/ftox.2021.722518
• 发表时间: 2021
• 期刊: Frontiers in toxicology
• 作者: Torres-Rojas C;Zhao W;Zhuang D;O'Callaghan JP;Lu L;Mulligan MK;Williams RW;Jones BC
• 通讯作者: Jones BC

Systems Genetics for Evolutionary Studies.

• DOI: 10.1007/978-1-4939-9074-0_21
• 发表时间: 2019
• 期刊: Methods in molecular biology
• 作者: P. Prins;G. Smant;D. Arends;Megan K. Mulligan;Rob Williams;R. Jansen