Whole-genome shotgun sequencing strategy and assembly

全基因组鸟枪测序策略和组装

• 批准号: 6973493
• 负责人: David B Jaffe
• 金额: $ 72.63万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-26 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6973493
• 关键词: bioinformatics; computer data analysis; computer program /software; computer system design /evaluation; data quality /integrity; genome; nucleic acid sequence; technology /technique development

DESCRIPTION (provided by applicant): Genome sequence, basic to biomedical research, is efficaciously produced by whole-genome shotgun (WGS) sequencing. Although WGS sequencing is a major NIH activity, we lack answers to fundamental questions about sequencing strategy and assembly of WGS data. Our work and the community's have focused on assembly of particular data sets and development of assembly algorithms. This grant focuses on mathematical underpinnings and rigorous analysis of genome sequencing and assembly, to improve our assembly tools and approaches. We will develop general methodology for optimally choosing specific sequencing strategies for new and varied organisms, fully exploiting data from emerging technologies. So that assembly is also optimal, we will develop algorithms that exploit the data's exact information content, retaining intrinsic ambiguity, and allowing assembly of genomes beyond current capabilities. We will develop strict internal consistency tests, guaranteeing accuracy and completeness of assembly units. A new assembly quality markup tool will label assembly regions from finished to inconsistent, by their inferred accuracy. This will guide finishing work (improving efficiency) and clearly describe reliability of particular assembly regions to end-users. In short, the work will produce better quality genome sequence at lower cost, marked to show reliability, thereby increasing utility for downstream analysis and laboratory experimentation.

描述（由申请人提供）：基因组序列是生物医学研究的基础，通过全基因组鸟枪法（WGS）测序有效产生。尽管 WGS 测序是 NIH 的一项主要活动，但我们缺乏有关测序策略和 WGS 数据组装的基本问题的答案。我们和社区的工作重点是特定数据集的组装和组装算法的开发。这笔赠款重点关注基因组测序和组装的数学基础和严格分析，以改进我们的组装工具和方法。我们将开发通用方法，为新的和多样化的生物体优化选择特定的测序策略，充分利用新兴技术的数据。因此，组装也是最佳的，我们将开发算法，利用数据的确切信息内容，保留内在的模糊性，并允许超出当前能力的基因组组装。我们将开展严格的内部一致性测试，保证装配单元的准确性和完整性。新的装配质量标记工具将根据装配区域的推断精度，将装配区域从完成标记到不一致标记。这将指导完成工作（提高效率）并向最终用户清楚地描述特定装配区域的可靠性。简而言之，这项工作将以更低的成本产生更高质量的基因组序列，并标记为显示可靠性，从而提高下游分析和实验室实验的实用性。