Whole-genome shotgun sequencing strategy and assembly

描述(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)测序有效地产生。尽管WGS测序是美国国立卫生研究院的一项主要活动，但我们对有关WGS数据的测序策略和组装的基本问题缺乏答案。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。这笔赠款侧重于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，充分利用新兴技术的数据，为新的和不同的生物体选择特定的测序策略。因此，组装也是最优的，我们将开发算法，利用数据的确切信息内容，保留固有的歧义，并允许超出当前能力的基因组组装。我们将制定严格的内部一致性测试，确保装配单元的准确性和完整性。一种新的装配质量标记工具将根据其推断的准确性为装配区域从已完成到不一致进行标记。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组装区域的可靠性。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，从而增加下游分析和实验室实验的实用性。

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.