Integrated Assembly Software for Sanger and Next Generation Sequence Technologies

描述(申请人提供)：下一代(下一代)测序技术的出现已经开始了全基因组测序和重新测序的浪潮，仅2008年一年就有四篇论文描述了五个完整的人类基因组，这是一个壮观的例子。一家名为Knome的公司现在甚至使用下一代测序技术向客户提供他们的整个基因组序列。这些进展，加上有针对性的基因组重测序，预示着1000美元人类基因组的到来。大规模的全人类基因组重测序将对个性化医学、人类进化和人类多样性等领域产生巨大的影响。然而，为了充分实现这一潜力，必须大幅增强软件能力，以应对这些项目中产生的大量数据、特定技术数据特征的多样性以及简单地分析60亿个碱基对二倍体人类基因组所带来的重大挑战。此外，我们看到有一天，技术的进步和成本的降低使WHGR像今天的细菌基因组测序一样司空见惯。要做到这一点，与目前破译信息的高度专业化的生物信息学团队相比，组装和分析软件必须能被更广泛、更不懂计算机的研究人员所使用。此外，即使是资金充足的研究实验室，计算机资源也比大型测序中心的资源有限得多。因此，这项提议的总体目标是开发下一代序列组装和分析流水线DESKAPP，它将在一台负担得起(5000美元)的高端台式计算机上运行，并在合理的时间框架内(几天，而不是几周)产生人类基因组序列。DESKAPP的WHGR将涉及一个参考引导的主组装以及一个从头组装分支，以表征相对于参考的新基因组的独特区域。这些组件的合并产生了一个完整的序列，可以通过基于网络的外部数据库搜索来识别已知的等位基因变异，也可以通过直接检查序列来识别新的多态，从而评估基因含量、单核苷酸多态(SNPs)和结构变异(SV；Indels、Indels、易位)。磁盘排序对齐算法允许对太大而无法在内存中处理的数据集进行评估和聚集，以便由我们的桌面汇编引擎SeqMan N-Gen(SM N-Gen)进行汇编。使用原型DSA-SM N-Gen管道，我们已经使用DSA在31小时内将James Watson基因组的全部7.4x454数据集处理到布局文件中，并使用SM N-Gen.组装了三条染色体：8；21；和X；21号染色体的组装时间从1小时到8号染色体等平均大小的染色体的10.6小时不等。这些结果证明了为WHGR构建DESKAPP管道的可行性。第二阶段的目标旨在建立在这一基础上，并在几天内为人类基因组的桌面组装和分析产生一条无缝管道。 与公共健康相关：下一代测序技术通过以不断降低的成本提供前所未有的数量的DNA序列数据，在整个生物学领域开始了一场新的革命。这些数据在个性化医疗的新兴时代和探索生命的巨大多样性方面将是无价的。该项目的目标是开发台式计算机软件，使任何规模的研究实验室和诊所能够实现这些新技术的承诺。

DESCRIPTION (provided by applicant): The advent of next-generation (Next-gen) sequencing technologies has begun a surge in whole genome sequencing and resequencing, exemplified spectacularly by four papers describing five complete human genomes in 2008 alone. One company, Knome, now even offers customers their entire genome sequence using Next-gen sequencing technology. These developments, together with targeted resequencing of genome, presage the day of the $1000 human genome. Broad-scale whole human genome resequencing (WHGR) will have enormous impact on the areas of personalized medicine, human evolution and human diversity. To fully realize that potential, however, software capabilities must be dramatically enhanced to meet the significant challenges posed by the sheer volume of data generated in these projects, the diversity of technology-specific data characteristics and simply analyzing the 6 billion base pair diploid human genome. Moreover, we see the day when technology improvements and cost reductions make WHGR as commonplace as bacterial genome sequencing has become today. For that to occur, assembly and analysis software must be accessible to a far broader and less computer savvy range of researchers than the highly specialized bioinformatics teams that decode the information now. Also, computer resources are far more limited even for a well funded research laboratory than available to a large sequencing center. Therefore, the overall goal of this proposal is to develop a Next-gen sequence assembly and analysis pipeline, DESKAPP, that will run on an affordable ($5000) high- end desktop computer and produce a human genome sequence in a reasonable timeframe (days, not weeks). WHGR by DESKAPP will involve a reference-guided main assembly as well as a de novo assembly branch to characterize unique regions of the new genome relative to the reference. Merging of the assemblies produces a complete sequence that can be evaluated for gene content, single nucleotide polymorphisms (SNPs) and structural variation (SV; indels, inversion, translocations) both by web-based searches of external databases to identify known allelic variation and by direct examination of the sequence to identify new polymorphisms. A Disk Sort Alignment algorithm allows the data sets which are far too large for in-memory processing to be evaluated and clustered for assembly by SeqMan N-Gen (SM N-Gen), our desktop assembly engine. Using a prototype DSA-SM N-Gen pipeline, we have processed the entire 7.4x 454 data set from the James Watson genome to a layout file in 31 hours using DSA and have assembled three chromosomes: 8; 21; and X; using SM N-Gen. Assembly times varied from 1 hour for Chromosome 21 to 10.6 hours for an average- sized chromosome, such as Chromosome 8. Together, these results demonstrate the feasibility of constructing a DESKAPP pipeline for WHGR. The Phase II Aims are designed to build upon this foundation and produce a seamless pipeline for the desktop assembly and analysis of a human genome in a matter of days. PUBLIC HEALTH RELEVANCE: Next-gen sequencing technologies have started a new revolution throughout biology by providing DNA sequence data in unprecedented quantities at continually decreasing costs. This data will be invaluable in the emerging era of personalized medicine and in exploring the immense diversity of life. The goal of this project is to develop desktop computer software that will enable research laboratories and clinics of any size to realize the promise of these new technologies.