Gene Array Technology Center for Alcohol Research (The R-GAP)

描述（由申请人提供）：啮齿动物基因阵列计划（R-GAP）将专注于创建可用于开发小鼠和大鼠脑表达QTL （eQTL）图谱的数据库，并用于表达控制元件的广泛研究。本研究将建立75株ISSXILS小鼠（LXS小鼠，雌雄分别）Rl脑基因表达谱数据库，并整合该小鼠菌株的超高密度SNP基因分型。此外，与基因网络（Gene Network）合作，基因表达分析的网络资源，我们所有的LXS菌株的关键数据将被整理并提供给公众使用。这些有价值的新数据集将催化eQTL映射，以及目前在LXS集中获得的酒精相关行为的qtl映射。当与复杂性状的QTL分析相结合时，eqtl的产生有助于识别这些性状的候选基因，R-GAP将利用这一策略在LXS小鼠以及其他品系的小鼠和大鼠中识别导致焦虑和酒精相关行为的强候选基因。脑基因表达数据的可用性和脑转录组的eQTL定位将为酗酒研究人员提供一种新颖而独特的资源。我们将从大量近交系小鼠中获得的基因表达数据将补充从小鼠Rl菌株中获得的数据，并利用NIEHS小鼠重测序项目产生的全基因组测序数据进行结构设计。RGAP数据库还将具有集成的神经信息学组件，提供可用于搜索与位于eqtl和上位位点内的转录因子相互作用的5'转录控制模块的信息和方法。R-GAP不仅将生成对酗酒调查人员有价值的数据，而且还将提供对生成数据进行规范化、统计分析和eQTL搜索的方法。R-GAP实质上将充当与基因网络一起使用的数据生成和初始筛选组件的“后端”。GeneNetwork将生成“前端”功能，使所有数据可供整个研究界使用。

DESCRIPTION (provided by applicant): The Rodent Gene Array Program (R-GAP) will focus on the creation of databases that can be used for developing expression QTL (eQTL) maps for mouse and rat brain and for use in extensive studies of expression control elements. The proposed studies will generate a database of gene expression profiles from brains of 75 Rl strains of ISSXILS mice (LXS mice; males and females separately), and integrate ultrahigh density SNP genotyping of the mouse strains. Additionally, in collaboration with the Gene Network, a web-based resource for gene expression analysis, all of our key data for LXS strains will be curated and made available for public use. These valuable new datasets will catalyze eQTL mapping, as well as mapping of QTLs for alcohol-related behaviors currently being acquired in the LXS set. When combined with QTL analysis of complex traits, the generation of eQTLs facilitates the identification of candidate genes for these traits, and R-GAP will exploit this strategy to identify strong candidate genes that contribute to anxiety and alcohol related behaviors in LXS mice, as well as in other strains of mice and rats. The availability of brain gene expression data and eQTL mapping of brain transcriptome will produce a novel and unique resource for use by alcoholism investigators. The data on gene expression which we will derive from large panels of inbred mice will complement data generated from the Rl strains of mice, and is structured to take advantage of whole genome sequencing data being generated by the NIEHS Mouse Resequencing Project. The RGAP database will also feature an integrated neuroinformatics component that provides information and methods that can be used to search for 5' transcriptional control modules that interact with transcription factors located within the eQTLs and epistatic loci. The R-GAP will not only generate data valuable to alcoholism investigators, but it will also provide access to methodology for normalization, statistical analysis and eQTL searches of the generated data. R-GAP will, in essence, act as the "back end" of a data generating and initial screening component which will be used with the GeneNetwork. GeneNetwork will generate the "front end" features to make all data available to the research community at large.