HIGH THROUGHPUT ANNOTATION OF GENOMIC DNA SEQUENCE

基因组 DNA 序列的高通量注释

• 批准号: 2655188
• 负责人: G. OVERTON
• 金额: $ 19.18万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-02-12 至 2000-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2655188
• 关键词: DNA; biotechnology; computer assisted sequence analysis; computer human interaction; computer program /software; computer system design /evaluation; data management; genes; genetic library; genetic techniques; genome; northern blottings; polymerase chain reaction; western blottings

DESCRIPTION (Adapted from the Investigator's Abstract): High-throughput genomic sequencing efforts must be accompanied by high throughput, cost-effective sequence annotation to fully realize the value of the data. Annotation encompasses the identification and archiving of putative biological signals, sequence characteristics, and features, including genes, and, wherever cost-effective, the further characterization of those features experimentally. While one might hope that annotation could be entirely computational and thus inexpensive and rapid, computational predictions, especially of gene models, must ultimately be confirmed experimentally as an additional and independent validation of the genomic sequence data, and as a means to establish the firm foundation necessary to simplify and accelerate future biological research. The proposed work integrates computational and experimental approaches, creating a test-bed and ultimately a production system for high-throughput, high-information-gain annotation. It is designed as an open system where new computational and experimental components, and new scientific visualization tools, can be easily installed and maintained in the data management and analysis framework. Experimental annotation will be streamlined, targeted versions of standard techniques, including single pass sequencing of cDNAs selected from EST hits of genomic DNA, RT-PCR across inter- and intra-regions of putative, and dot-blots of plasmid DNA used in genomic sequencing against labeled mRNA. The three basic goals of experimental annotation are to 1) establish laboratory protocols, management structures and automation techniques for high-throughput experimental annotation; 2) validate and refine computational annotation, especially for gene model finders such as GRAIL; and 3) extract high-information-gain data, for example, by concentrating single pass cDNA sequencing efforts on ESTs from unknown gene classes, to extend the sequence similarly databases and computational gene finders. In its initial phase, development of the system infrastructure will be tightly coupled to ongoing high-throughput sequencing at the University of Oklahoma with the goal of transitioning the technology for deployment to the genomics research community at large.

描述（改编自调查员的摘要）：高通量 基因组测序工作必须伴随着高吞吐量， 具有成本效益的序列注释，以充分实现数据的价值。 注释涵盖了推定的标识和归档 生物信号，序列特征和特征，包括基因， 而且，无论这些功能的成本效益，这些功能的进一步表征 实验。 虽然可能希望注释可以完全 计算，因此便宜，快速，计算预测， 特别是基因模型的，最终必须在实验中作为一个 基因组序列数据的其他独立验证，作为一个 建立简化和加速所必需的牢固基础的方法 未来的生物学研究。 拟议的工作集成了计算和 实验方法，创建测试床并最终生产 高通量，高信息增益注释的系统。 这是 设计为开放系统，新的计算和实验性 组件和新的科学可视化工具可以轻松安装 并保留在数据管理和分析框架中。 实验 注释将精简，针对性的标准技术的目标版本， 包括从基因组HITS选择的cDNA的单个通过测序 DNA，RT-PCR横跨推定的区域和内部区域以及 用于标记的mRNA的基因组测序中使用的质粒DNA。 实验注释的三个基本目标是1）建立 实验室协议，管理结构和自动化技术 高通量实验注释； 2）验证和完善 计算注释，特别是对于基因模型查找器，例如Grail； 3）例如，通过集中提取高信息增强数据 从未知基因类别到EST上的单个通过cDNA测序工作， 扩展序列类似的数据库和计算基因查找器。 在 它的初始阶段，系统基础架构的开发将紧密 结合俄克拉荷马大学正在进行的高通量测序 以将技术的技术转换为基因组学 整个研究社区。