课题基金 / 基金详情

Genetic and alcohol regulation of brain RNA levels

Genetic and alcohol regulation of brain RNA levels
大脑 RNA 水平的遗传和酒精调节
批准号:
6865676
负责人:
SUSAN E. BERGESON
金额:
$13.88万
依托单位国家:
美国
项目类别:
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-03-01 至 2007-02-28

项目摘要

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中文摘要
翻译
描述(由申请人提供): 这项提案的目标是为苏珊·伯格森博士提供职业发展 机会包括Adron Harris博士的指导、微阵列培训 与Vishy Layer博士合作,并减少教学工作量,这将允许时间 发展一项独立的研究计划。优秀的研究 德克萨斯大学的环境、师资和设施将允许 将她在分子生物学方面的专业知识扩展到一个新的和创新的 分析基因表达在酒精耐受和依赖中的作用。 该提案研究部分的目的是:1)确定变化 急性酒精暴露所产生的脑内信使核糖核酸水平 小鼠行为遗传学将表达的协调变化与 分子神经回路的适应性导致耐受、依赖和 敏化。这将通过mRNA差异显示(DD)来实现 再加上DNA微阵列分析。已知数量性状中的基因 将优先考虑基因座(QTL)并对构建的同源基因小鼠进行分析 对于急性戒断,QTL将提供一个概念验证。QTL分析是 目前,一种用于定位包含基因的染色体区域的常用方法 在复杂的(多基因)哺乳动物特征中很重要,包括对 酒精,但这只是了解其潜在机制的第一步 酒精的影响。几项表达研究,NAVE确定了其基因 MRNA水平会因酒精的作用而改变,但尚不清楚 分子方面,酒精作用的后果已经出现。组合遗传 工具和分子技术提供了一种合理的策略来检测和 对影响酒精相关的重要遗传差异的验证 特征。修改后的DD分析,它具有筛选大多数 表达的转录本以及识别插入和缺失 多态,将在C57BL/6J(B6)和DBA/2J(D2)小鼠和两个 急性酒精QTL分析产生的同源菌株 戒烟。首先,对B6、D2和同源菌株进行DD分析 提供酒精反应和品系特异性表达差异。下一首, 微阵列将用于验证、剂量效应、时间进程和 脑区域特异性将通过添加DD分离基因如下定义 DNA微阵列分析的额外靶点提供了足够的能力 通过聚类分析阐明具有收敛调节的分子途径 用乙醇。此外,B6、D2之间的表达和序列多态 这些同源基因菌株将对许多具有或 将使用BXD战略。所有遗传和特征数据将免费共享 通过存放在MGI数据库(http://www.informaticsjax.org)和一个网站 在UT创建的站点,详细说明了协议和结果;例如 参见:V.Iyer,(http://genome-www.stanford.edu/serum).
英文摘要
DESCRIPTION (provided by applicant): The goal of this proposal is to provide Dr. Susan Bergeson career development opportunities including mentoring by Dr. Adron Harris, microarray training with Dr. Vishy Iayer, and a reduction in teaching effort that will allow time to develop an independent research program. The excellent research environment, faculty and facilities of the University of Texas will allow expansion of her expertise in molecular biology toward a new and innovative analysis of the role of gene expression in alcohol tolerance and dependence. The aims of the research component of the proposal are to 1) Identify changes in brain MRNA levels produced by acute alcohol exposure and to 2) Utilize mouse behavioral genetics to link I coordinated changes in expression to adaptations in molecular neurocircuitry that cause tolerance, dependence and sensitization. This will be accomplished by MRNA differential display (DD) coupled with DNA microarray analysis. Genes within known Quantitative Trait Loci (QTL) will be given priority and analysis of congenic mice constructed for acute withdrawal QTLs will provide a proof-of-concept. QTL analysis is currently a common method for mapping chromosomal regions that contain genes important in complex (polygenic) mammalian traits, including responses to alcohol but is only a first step in understanding mechanisms underlying alcohol's effects. Several expression studies, nave identified genes whose mRNA levels are changed by alcohol's actions yet no clear picture of the molecular, consequences of alcohol action have emerged. Combining genetic tools and molecular techniques offers a logical strategy for the detection and validation of important genetic differences that influence alcohol-related traits. A modified DD analysis, which has the capacity to screen most expressed transcripts as well as identify insertion and deletion polymorphisms, will be completed on C57Bl/6J (B6) and DBA/2J (D2) mice and two congenic strains created as a result of QTL analysis for acute alcohol withdrawal. First, DD analysis of B6, D2, and the congenic strains will provide alcohol-responsive and strain specific expression differences. Next, microarrays will be used for validation, and dose-effect, time-course, and brain region specificity will be defined by adding the DD isolated genes as additional targets for DNA microarrays analysis providing sufficient power to elucidate, by cluster analyses, molecular pathways with convergent regulation by ethanol. In addition, expression and sequence polymorphisms between B6, D2 and these congenic strains will be of value to numerous studies that have or will use a BXD strategy. All genetic and profiling data will be freely shared by deposition in the MGI data base (http:/www.informaticsjax.org) and a web site created at UT that details both the protocol and results; for an example see: V.Iyer,(http://genome-www.stanford.edu/serum).
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