Transcriptional Genomics

一个主要目标是努力了解信号转导途径调节的机制， 基因表达程序的目的是鉴定其直接靶基因并确定其特异组分 这些转录机器在响应调节信号时被招募到这些基因中。到 为了支持这些目标，转录基因组学核心将为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，最近开发的基因组（ChIP- 芯片）微阵列分析和相关的生物信息学支持实验设计监督和数据 分析.常规的表达分析将利用市售的微阵列（例如，阿菲耶， Agilent和Illumina微阵列）。染色质免疫沉淀技术的研究进展 利用DNA微阵列进行的ChIP检测允许对转录因子定位进行全基因组分析， 活细胞中的特异性启动子序列。PPG转录基因组学核心将构建小鼠 用于常规ChIP-Chip和ChIP-DSL方法的基因间/启动子微阵列， PPARs、NCoR、SMRT和其他与此相关的转录因子的广泛定位分析 应用程序.有效利用全基因组方法需要了解基因组的优势， 这些技术的局限性，特别是在误差来源和 在定义的和可接受的假阳性下开发基因列表所需的实验重复， 假阴性率。PPG转录基因组学核心内的人员将与科学家互动 在每一个项目中，提供针对这些问题的实验设计监督。一旦 进行微阵列实验并收集原始数据后，转录基因组学核心将 利用标准工具在特定的置信水平上建立基因列表，并进行二次分析 (e.g.,基因本体分析，映射到KEGG途径等）。转录基因组学核心将 为数据存储和检索提供数据库基础设施，以允许跨 PPG和更复杂的生物信息学方法的应用， 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.