HIGH THROUGHPUT ANNOTATION OF GENOMIC DNA SEQUENCE

描述（改编自研究者摘要）：高通量 基因组测序工作必须伴随高通量， 具有成本效益的序列注释，以充分实现数据的价值。 注释包括识别和存档推定的 生物信号、序列特征和特征，包括基因， 并且，只要成本有效，这些特征的进一步表征 实验性的 虽然人们可能希望注释可以完全 计算性的，因此便宜和快速的，计算性的预测， 特别是基因模型，最终必须通过实验证实， 对基因组序列数据进行额外和独立的验证， 这意味着建立必要的坚实基础，以简化和加速 未来的生物学研究 拟议的工作集成了计算和 实验方法，创建一个测试平台，并最终生产 用于高通量、高信息增益注释的系统。 是 设计成一个开放的系统，新的计算和实验 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中维护。 实验 注释将被简化，标准技术的目标版本， 包括从基因组的EST命中中选择的cDNA的单程测序， DNA，跨推定的区域间和区域内的RT-PCR，以及 用于对照标记的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 实验室协议、管理结构和自动化技术， 高通量实验注释; 2）验证和细化 计算注释，特别是对于基因模型查找器，如GRAIL; 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cDNA测序， 类似地扩展序列数据库和计算基因查找器。 在 在其初始阶段，系统基础设施的开发将严格 再加上俄克拉荷马州大学正在进行的高通量测序 其目标是将部署技术转移到基因组学， 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.