Whole-genome shotgun sequencing strategy and assembly

全基因组鸟枪测序策略和组装

• 批准号: 8530260
• 负责人: David B Jaffe
• 金额: $ 72.58万
• 依托单位: BROAD INSTITUTE, INC.
• 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 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8530260
• 关键词: Achievement; Address; Algorithms; Base Sequence; Biology; Biomedical Research; Blood capillaries; Collaborations; Communities; Complex; Computing Methodologies; DNA Resequencing; DNA Sequence; Data; Defect; Diagnosis; Disease; Drops; Evolution; Foundations; Generations; Genes; Genetic; Genome; Goals; Grant; Health; Hereditary Disease; Human; Human Genetics; Human Genome; Individual; Industry; Institutes; Investigation; Island; Knowledge; Laboratories; Letters; Methods; Metric; Organism; Patients; Production; Reading; Repetitive Sequence; Reporting; Research; Research Personnel; Sampling; Technology; Time; Uncertainty; Variant; Whole-Genome Shotgun Sequencing; Work; base; cancer genetics; cancer genomics; capillary; comparative genomics; cost; falls; genome sequencing; human disease; improved; mammalian genome; meetings; new technology; next generation sequencing; pathogen; programs; standard of care; tool

DESCRIPTION (provided by applicant): The ability to read the DNA sequence of an organism's genome has revolutionized biology and biomedical research. Accurate assemblies of sequence data are critical because they provide the foundation for all subsequent work. Using capillary-based sequencing technology, high quality drafts were generated for many genomes. Over the past several years, massively parallel sequencing technologies have lowered sequencing cost by 1000-fold, but the reads from these technologies are shorter and less accurate than the capillary reads, hence harder to assemble, particularly for large genomes. We have recently demonstrated assemblies of massively parallel data that begin to approach the quality of those from capillary data. These assemblies were of genomes for which exceptionally high-quality ('finished') assemblies were already available, and we were thus able not only to rigorously assess the quality of our assemblies, but also to systematically diagnose their defects. Moreover we observe that in almost all cases, defective loci have enough coverage that they could in principle be assembled correctly, provided that the right algorithms were available. On this basis we have proposed a research program to develop computational methods for the creation of assemblies of unprecedented quality: In our first aim we propose to develop methods to achieve high quality draft assemblies of new genomes. Here our objective is to reach and exceed the level of quality that had been achieved using capillary sequencing. In our second aim we will develop methods to achieve ultra high quality assemblies of human genomes. To do this we will leverage the existing human reference sequence and reference sequences of other individuals, including those that we would create. In this way we aim to achieve near-finished quality for regions represented in the reference sequences (essentially via 'resequencing' methods), and at the same time (by de novo methods) capture those regions that are not present in the reference sequences. Our aim is thus to produce the best possible representation of each individual's genome. We note that as costs drop, this is likely to become 'standard of care' for patients. In our third aim, we look beyond existing data, to the next generation of sequencing technologies, to assemble very hard regions using very long and 'strobe' reads. These hard regions include segmental duplications, which are evolutionary hotspots, associated with many diseases, and inaccessible to current methods, except those using very expensive clone-by-clone sequencing. Finally our fourth aim is to make assembly methods accessible to the community. Here our goal is to make it as easy as possible for a range of users (including individual investigators) to match the results achievable by genome assembly experts. In short, through our four aims, we will enable the community to achieve the highest possible assembly quality using the lowest cost data. We thus anticipate that our work will advance a broad range of investigations of importance to biology and human disease.

描述(申请人提供)：读取生物体基因组的DNA序列的能力使生物学和生物医学研究发生了革命性的变化。序列数据的准确组装至关重要，因为它们为所有后续工作提供了基础。使用基于毛细管的测序技术，为许多基因组生成了高质量的草稿。在过去的几年里，大规模并行测序技术已经将测序成本降低了1000倍，但这些技术的读数比毛细管读数更短、更不准确，因此更难组装，特别是对于大基因组来说。我们最近展示了大量并行数据的集合，它们开始接近那些来自毛细血管数据的数据的质量。这些组装的基因组已经有了非常高质量的(‘成品’)组装，因此我们不仅能够严格评估我们组装的质量，而且还能够系统地诊断它们的缺陷。此外，我们观察到，在几乎所有的情况下，有缺陷的基因座有足够的覆盖率，原则上它们可以被正确组装，只要有正确的算法可用。在此基础上，我们提出了一个研究计划，以开发计算方法来创建前所未有的质量的组装：在我们的第一个目标，我们建议开发方法，以实现高质量的新基因组草稿组装。在这里，我们的目标是达到并超过使用毛细管测序所达到的质量水平。在我们的第二个目标中，我们将开发方法来实现人类基因组的超高质量组装。为了做到这一点，我们将利用现有的人类参考序列和其他个人的参考序列，包括我们将创建的那些。通过这种方式，我们的目标是获得参考序列中所代表的区域的接近完成的质量(主要通过‘重测序’方法)，同时(通过从头测序方法)捕获参考序列中不存在的那些区域。因此，我们的目标是尽可能地表现每个个体的基因组。我们注意到，随着成本的下降，这很可能成为患者的“标准护理”。在我们的第三个目标中，我们着眼于现有数据之外，着眼于下一代测序技术，使用非常长的“选通”读数来组装非常坚硬的区域。这些硬区包括节段性复制，这是进化的热点，与许多疾病相关，目前的方法无法获得，除非使用非常昂贵的逐个克隆测序。最后，我们的第四个目标是让社区能够访问组装方法。在这里，我们的目标是使一系列用户(包括个体研究人员)尽可能容易地匹配基因组组装专家所能实现的结果。简而言之，通过我们的四个目标，我们将使社区能够使用最低成本的数据实现尽可能高的组装质量。因此，我们预计，我们的工作将推动对生物学和人类疾病具有重要意义的广泛研究。

项目成果

Sensitive, specific polymorphism discovery in bacteria using massively parallel sequencing.

使用大量平行测序在细菌中发现敏感的特异性多态性。

• DOI: 10.1038/nmeth.1286
• 发表时间: 2009-01
• 期刊: NATURE METHODS
• 影响因子: 48
• 作者: Nusbaum, Chad;Ohsumi, Toshiro K.;Gomez, James;Aquadro, John;Victor, Thomas C.;Warren, Robert M.;Hung, Deborah T.;Birren, Bruce W.;Lander, Eric S.;Jaffe, David B.
• 通讯作者: Jaffe, David B.