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，其风险因素包括遗传变异和 发展、性和环境。精准医疗改善药物治疗的长期潜力 预防依赖于更好地了解遗传学、药物、脑细胞和 神经回路相互作用影响行为。存在严重的技术障碍， 和临床医生将更强大的计算和预测方法纳入成瘾研究。 NIDA P30核心卓越中心在组学，系统遗传学和成瘾 是授权和培训由NIH、NIDA、NIAAA和其他联邦和州机构支持的研究人员 使用更多的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的核心中， 组装和升级数百个大型基因组（DNA）和转录组（RNA）数据集， 啮齿动物（大鼠）成瘾模型。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（基因定位），以了解DNA差异之间的联系，环境 风险，如压力，以及药物滥用和复吸的不同风险。我们的试点核心是催化新的 年轻研究人员在成瘾研究领域的合作。总之，该中心是一个国家 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 整合高质量的数据，元数据，使用开放的软件系统，与许多其他团队合作， 研究人员我们的目标是帮助建立一个NIDA Addicome Portal，其中包括所有基因组研究 与成瘾研究有关。

项目成果

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

BXD小鼠家族中对Δ9-四氢大麻酚（THC）的初始敏感性的遗传调节。

• 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

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

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