Patterned Gene Expression in Drosophila Development

果蝇发育中的模式基因表达

• 批准号: 8529552
• 负责人: SUSAN E CELNIKER
• 金额: $ 44.31万
• 依托单位: UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2015-08-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8529552
• 关键词: Algorithms; Animal Model; Applications Grants; Atlases; Automation; Binding Sites; Biological Assay; Cataloging; Catalogs; Code; Collection; Communities; Complement; Complementary DNA; Complex; Computer Analysis; Computer Assisted; Controlled Vocabulary; DNA; Data; Data Analyses; Data Collection; Data Set; Databases; Development; Differentiation and Growth; Disease; Drosophila Proteins; Drosophila genome; Drosophila genus; Elements; Embryo; Embryonic Development; Enhancers; Eukaryota; Evolution; Gene Expression; Gene Expression Profile; Gene Expression Regulation; Generations; Genes; Genetic; Genome; Genomics; Goals; Grant; Homologous Gene; Human; Image; Image Analysis; Improve Access; In Situ; In Situ Hybridization; Informatics; Intergenic DNA; Internet; Label; Manuals; Manuscripts; Methods; Microscope; Nucleic Acid Regulatory Sequences; Online Systems; Ontology; Pattern; Preparation; Process; Production; Proteins; Protocols documentation; Publishing; RNA; RNA Probes; Regulator Genes; Reporter; Research; Research Personnel; Resolution; Resources; Reverse Transcriptase Polymerase Chain Reaction; Role; Staging; Testing; Time; Tissue Differentiation; Transcription factor genes; Transgenic Organisms; Vocabulary; base; computerized tools; data mining; data modeling; design; genome wide association study; genome-wide; human disease; improved; insight; novel; public health relevance; research study; tool; transcription factor; virtual

DESCRIPTION (provided by applicant): Our long-term objective is to understand the complex network of genetic interactions that control gene expression underlying the processes of normal development, disease and evolution. At the Berkeley Drosophila Genome Project (BDGP), we have established a gene expression resource for Drosophila development that contains spatial and temporal embryonic expression patterns, annotations of the patterns using a standardized, controlled vocabulary, based on an anatomical ontology and a standardized virtual representation of the patterns. We created tools to identify similar, partially overlapping or anti-correlated expression. Our database currently contains over 100,000 annotated images showing expression patterns generated using in-situ hybridization of staged whole-mounted embryos for approximately 60% (8500) of the protein-coding genes in the Drosophila genome. We propose to: (1) obtain expression patterns for as many of the remaining 40% of the protein-coding genes as possible, (2) develop fully automatic image acquisition with a motorized microscope and analysis pipeline to accelerate data collection and in preparation for high-throughput studies, (3) continue advancements and refinements to our virtual image representation and create web-tools and interfaces for the research community to conduct analysis with our dataset and uploaded images and (4) characterize and analyze expression patterns of conserved regulatory modules from transcription factors. The primary resource for generation of RNA probes is our Drosophila Gene Collection (DGC), which currently contains cDNA clones corresponding to 88% of the annotated genes. To capture expression patterns for genes that do not have a representative cDNA clone (12%), we used gene-specific PCR products to generate RNA probes in 96- well format. The gene expression data produced by our study will provide fundamental information for elaborating the function of the 13,831 protein-coding genes in Drosophila and will aid in elucidating the function of the homologous genes in other eukaryotes, including humans. Genome wide association studies have shown fundamental roles for regulatory regions and gene expression in human diseases. The functional analysis of regulatory regions will provide novel insights into the developmental roles of transcription factors. In addition, the integration of the gene expression data with regulatory and gene sequences will promote research to discover networks of regulatory interactions. PUBLIC HEALTH RELEVANCE: Elucidating the mechanisms responsible for genome-wide gene expression and regulation in Drosophila development will aid in understanding normal growth and differentiation of tissues in humans, prerequisites for understanding human disease.

描述（由申请人提供）：我们的长期目标是了解控制正常发育、疾病和进化过程中基因表达的复杂遗传相互作用网络。在伯克利果蝇基因组计划 (BDGP)，我们建立了果蝇发育的基因表达资源，其中包含空间和时间胚胎表达模式，以及基于解剖本体和标准化虚拟表示的标准化受控词汇对模式的注释的模式。我们创建了工具来识别相似、部分重叠或反相关的表达。我们的数据库目前包含超过 100,000 张带注释的图像，显​​示了果蝇基因组中约 60% (8500) 的蛋白质编码基因通过分阶段整体胚胎的原位杂交生成的表达模式。我们建议：(1) 获得尽可能多的剩余 40% 蛋白质编码基因的表达模式，(2) 使用电动显微镜和分析管道开发全自动图像采集，以加速数据收集并为高通量研究，(3) 继续改进和完善我们的虚拟图像表示，并为研究界创建网络工具和界面，以使用我们的数据集和上传的图像进行分析，以及 (4) 表征和分析保守调控模块的表达模式来自转录因子。生成 RNA 探针的主要资源是我们的果蝇基因库 (DGC)，其中目前包含与 88% 注释基因相对应的 cDNA 克隆。为了捕获没有代表性 cDNA 克隆 ​​(12%) 的基因的表达模式，我们使用基因特异性 PCR 产物生成 96 孔形式的 RNA 探针。我们的研究产生的基因表达数据将为阐述果蝇中 13,831 个蛋白质编码基因的功能提供基础信息，并将有助于阐明包括人类在内的其他真核生物中同源基因的功能。全基因组关联研究表明，调控区域和基因表达在人类疾病中发挥着重要作用。调节区域的功能分析将为转录因子的发育作用提供新的见解。此外，基因表达数据与调控和基因序列的整合将促进发现调控相互作用网络的研究。 公共卫生相关性：阐明果蝇发育中全基因组基因表达和调控的机制将有助于了解人类组织的正常生长和分化，这是了解人类疾病的先决条件。