HIGH THROUGHPUT ANNOTATION OF GENOMIC DNA SEQUENCE

描述(改编自《调查者摘要》)：高吞吐量 基因组测序工作必须伴随着高通量， 性价比高的序列标注，充分实现数据的价值。 注释包括推定的识别和归档 生物信号、序列特征和特征，包括基因， 以及，只要具有成本效益，这些功能的进一步表征 试验性的。虽然人们可能希望注释可以完全 计算性的，因此廉价和快速的计算性预测， 尤其是基因模型，最终必须在实验上确认为 基因组序列数据的附加和独立验证，并作为 为简化和加速奠定必要的坚实基础的手段 未来的生物学研究。拟议的工作将计算和 试验性方法，创建试验台并最终生产 用于高吞吐量、高信息增益注释的系统。它是 设计为开放系统，提供全新的计算和实验功能 组件和新的科学可视化工具可以轻松安装 并在数据管理和分析框架内维护。实验 注释将是标准技术的精简、目标版本， 包括从基因组的EST序列中选择的cDNA的单程测序 DNA，RT-PCR跨推测的区域间和区域内，以及斑点杂交 用于针对标记的mrna进行基因组测序的质粒DNA。 实验注释的三个基本目标是：1)建立 实验室规程、管理结构和自动化技术 高通量实验标注；2)验证和提炼 计算注释，特别是对于GRAIL等基因模型搜索者； 以及3)提取高信息增益数据，例如通过集中 对未知基因类别的EST进行单次通过的cDNA测序工作，以 以类似的方式扩展序列数据库和计算基因搜索器。在……里面 在其初始阶段，系统基础设施的开发将紧锣密鼓 加上俄克拉荷马大学正在进行的高通量测序 目标是将部署技术过渡到基因组学 整个研究界。

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.