Large Scale Genome Sequencing

描述（由申请人提供）：随着参考人类基因组序列的完成，下一波大规模测序将瞄准能够进一步告知人类序列或以其他方式为生物发现提供重要价值的基因组。 这些序列必须是高质量的，但必须有效地产生，并以相当低的成本。 在该提案中，我们描述了技术发展，这些技术发展将使我们能够产生更长的序列读取长度，降低测序成本，改善物理图谱构建，简化基因组组装和自动化序列整理。 为了支持这些进步，我们将开发增强的信息化工具和基础设施，以有效地整合和改善我们实验室流程的整个范围的管理。 在这些技术发展的基础上，我们将在第一年以每月330万次读取的速度产生基因组序列数据，在第三年适度扩展到每月380万次读取。 在同一时期，我们的目标是将平均读取长度增加至少300 bp，并将每次读取的成本从1.35美元降至0.75美元或更低。改进方法和工具，以更有效地完成基因组序列，达到高质量和连续性标准，以及检测和注释基因和这些基因组中编码的其他元件的方法和工具，将进一步增强我们中心的输出数据。 再加上战略上的进步，这些改进将大大提高基因组测序的效率和经济性，使考虑分析更多的人类和动物基因组变得更加可行。

DESCRIPTION (provided by applicant): With the reference human genome sequence now completed, the next wave of large-scale sequencing will be aimed at genomes that can further inform the human sequence or otherwise provide significant value for biological discovery. These sequences must be of high quality, yet must be generated efficiently and at a substantially lower cost. In this proposal, we describe technical developments that will allow us to produce longer sequence read lengths, decrease sequencing costs, improve physical map construction, streamline genome assembly, and automate sequence finishing. To support these advances, we will develop enhanced informatics tools and infrastructure to effectively integrate and improve management of the entire range of our laboratory processes. On the basis of these technical developments, we will produce genome sequence data at a rate of 3.3M reads/month in Year 1, scaling moderately to 3.8M reads/month in Year 3. Over the same time period, we aim to increase average read length by at least 300 bp, and to cut our per-read cost from $1.35 to $0.75 or less. Refined methods and tools to more efficiently finish genome sequences to high quality and continuity standards, as well as methods and tools for detection and annotation of genes and other elements encoded within those genomes, will further enhance the output data from our Center. Coupled with advances in strategy, these improvements will substantially improve the efficiency and the economics of genome sequencing, making it much more feasible to consider the analysis of additional human and animal genomes.