Transcriptional Genomics

努力了解信号转导通路调节机制的一个主要目标 基因表达程序是确定其直接靶基因和确定特定成分的程序 被招募到这些基因以响应调控信号的转录机制。至 为了支持这些目标，转录基因组核心将为PPG提供三项补充服务 研究人员；传统的基因表达(芯片)微阵列分析，最近发展的基因组(ChlP- 芯片)微阵列分析和相关生物信息学支持实验设计监督和数据 分析。传统的表达分析将利用市场上可买到的微阵列(例如，Affymetrix， 安捷伦和Illumina微阵列)。染色质免疫沉淀联合应用的研究进展 使用DNA微阵列的(芯片)分析使转录因子定位的全基因组分析能够 活细胞中的特定启动子序列。PPG转录基因组核心将构建小鼠 用于传统ChlP-Chipand ChlP-DSL方法的基因间/启动子微阵列 PPAR、NCoR、SMRT和其他与此相关的转录因子的广泛定位分析 申请。有效地利用全基因组方法需要了解其优点和 这些技术的局限性，特别是在误差来源和数量方面 以确定的和可接受的假阳性和可接受的假阳性建立基因列表所需的实验复制 假阴性率。PPG转录基因组学核心内的人员将与科学家互动 在每个项目内提供以这些问题为重点的实验设计监督。一次 进行了微阵列实验并收集了原始数据，转录基因组核心将 利用标准工具以特定的置信度编制基因列表并进行二次分析 (例如，基因本体论分析、映射到KEGG途径等)。转录基因组学核心将 提供用于数据存储和检索的数据库基础架构，以集成跨 PPG和更复杂的生物信息学方法的应用在每一个 项目。

A major goal in efforts to understand the mechanisms by which signal transduction pathways regulate programs ofgene expression is to identify their direct target genes and to determine the specificcomponents of the transcriptional machinery that are recruited to these genes in response to regulatory signals. To support these goals, the Transcriptional GenomicsCorewill provide three complementary services toPPG investigators; conventional gene expression (Chip)microarray analysis, recently developed genomic(ChlP- Chip) microarrayanalysis, and associated Bioinformaticssupport for experimental design oversight and data analysis. Conventional expression analysis will utilize commercially available microarrays (e.g., Affymetrix, Agilent and Illumina microarrays). Recent progress in combining the use of chromatin immunoprecipitation (ChIP) assays with DNAmicroarrays has allowed genome-wideanalysis oftranscription factor localization to specific promoter sequences in living cells. The PPGTranscriptional GenomicsCorewill fabricate murine intergenic/promoter microarrays for conventional ChlP-Chipand ChlP-DSL approaches to allowgenome- wide location analysis of PPARs,NCoR, SMRT, and other transcription factors of relevanceto this application. Effective utilization of genome-wide approaches requires an understanding ofthe strengths and limitations ofthese technologies, particularly with respect to sources of error and the number of experimental replicates that are required to develop gene lists at defined and acceptable false positive and false negative rates. Personnel within the PPGTranscriptional Genomics Corewill interact with scientists within each ofthe Projects to provide experimental design oversight focused on these issues. Once microarray experiments are performed and raw data is collected, the Transcriptional Genomics Core will utilize standard tools to develop gene lists at specifiedlevels of confidence and perform secondary analysis (e.g., Gene Ontology analysis, mapping to KEGG pathways, etc.). The Transcriptional Genomics Core will provide a database infrastructure for data storage and retrieval to allow integration of data collected across the PPGand the application of more sophisticated bioinformatics approaches outlined in each of the Projects.