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Generation of Ethanol Response Gene Resource by Large-Scale Data Integration

通过大规模数据集成生成乙醇反应基因资源

基本信息

批准号：
7655504
负责人：
Zhongming Zhao
金额：
$ 18.41万
依托单位：
VANDERBILT UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2008
资助国家：
美国
起止时间：
2008-07-10 至 2011-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7655504
关键词：
Alcoholism Algorithms Animal Model Behavior Behavioral Bioinformatics Candidate Disease Gene Communities Comparative Genomic Analysis DNA Microarray Chip Data Data Analyses Data Collection Data Set Databases Ethanol Future Gene Expression Generations Genes Genetic Genetic Risk Genomics Genotype Goals Human Individual Institutes Intervention Investigation Link Location Methods Molecular Mus National Institute on Alcohol Abuse and Alcoholism Online Systems Ontology Organism Pathway Analysis Pattern Quantitative Trait Loci Rattus Research Research Personnel Resources Sampling Scanning Schizophrenia Screening procedure Statistical Data Interpretation Subgroup Susceptibility Gene System Technology United States National Institutes of Health Update alcohol response comparative computer program data integration data management design fly gene function genome wide association study interest novel open source prototype public health relevance text searching tool trait trend user-friendly web interface

项目摘要

DESCRIPTION (provided by applicant): Over the last 10-15 years rapid progress has been made in the study of ethanol related traits including alcoholism and behavioral responses to ethanol in both humans and animal models. Refined genetic strategies and high-throughput molecular technologies such as large-scale genotyping and DNA microarrays have identified a relatively large number of chromosomal locations and candidate genes contributing to the genetic risk for alcoholism and ethanol response behaviors. At present, integrating and making the combined wealth of results easily accessible and interpretable presents significant challenges for researchers. In this application, we propose to construct such a unique and important ethanol response gene resource (ERGR). We will first collect and curate all the available data sets for ethanol response genes including those generated by the groups at VCU and publicly available. Examples of these internal and external data include human linkage scan and association studies, mouse ethanol QTL, microarray data, high throughput literature searches, and candidate genes in other organisms (e.g. rat, fly, worm). The collected data will be integrated via a data management system and updated routinely by computer programs. Many analyses will be performed for the identification of susceptibility genes and their features, including comparative genomics, gene network, Gene Ontology term, and gene expression analyses. We will also develop scoring algorithms for prioritizing candidate genes and implement tools for customization of gene prioritization. Finally, we will design and implement a user-friendly web-based platform. This platform will provide (1) simultaneous access to the data collected and annotated and to certain public genomic databases and (2) tools for statistical analysis and data presentation. The overall goal is to provide a comprehensive ethanol response gene resource to NIAAA research community and to facilitate understanding the mechanism(s) of action for individual genes in alcoholism and identify potential targets for novel new interventions in alcoholism. Public Health Relevance: The proposed project will collect, curate, and analyze all the available data sets for ethanol response genes and prioritize the candidate genes for future investigation. A user-friendly web-based ethanol response gene database system will be constructed for NIAAA research community.

描述（由申请人提供）：在过去的10-15年中，乙醇相关性状的研究取得了快速进展，包括人类和动物模型中的酒精中毒和对乙醇的行为反应。精细的遗传策略和高通量分子技术，如大规模基因分型和DNA微阵列已经确定了相对大量的染色体位置和候选基因，有助于酒精中毒和乙醇反应行为的遗传风险。目前，整合并使合并后的大量结果易于访问和解释，这对研究人员提出了重大挑战。在本申请中，我们建议构建这样一个独特的和重要的乙醇反应基因资源（ERGR）。我们将首先收集和整理乙醇反应基因的所有可用数据集，包括VCU小组产生的和公开的数据集。这些内部和外部数据的例子包括人类连锁扫描和关联研究，小鼠乙醇QTL，微阵列数据，高通量文献检索，以及其他生物体（如大鼠，苍蝇，蠕虫）中的候选基因。收集的数据将通过数据管理系统进行整合，并通过计算机程序进行定期更新。为了识别易感基因及其特征，将进行许多分析，包括比较基因组学、基因网络、基因本体论术语和基因表达分析。我们还将开发用于优先排序候选基因的评分算法，并实现用于定制基因优先级的工具。最后，我们将设计和实现一个用户友好的基于Web的平台。该平台将提供（1）同时访问收集和注释的数据以及某些公共基因组数据库，以及（2）统计分析和数据呈现工具。总体目标是为NIAAA研究社区提供全面的乙醇反应基因资源，并促进了解酒精中毒中单个基因的作用机制，并确定酒精中毒新干预措施的潜在目标。公共卫生相关性：该项目将收集、整理和分析乙醇反应基因的所有可用数据集，并对候选基因进行优先排序，以供未来研究。一个用户友好的基于Web的乙醇反应基因数据库系统将被构建为NIAAA研究社区。