Single molecule DNA mapping for genome and CNV analysis

用于基因组和 CNV 分析的单分子 DNA 作图

• 批准号: 8786581
• 负责人: Pui-Yan KWOK
• 金额: $ 74.32万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-27 至 2016-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8786581
• 关键词: Algorithms; Communities; DNA; DNA mapping; Data; Detection; Development; Diploidy; Disease; Equilibrium; Genome; Genome Mappings; Genome Scan; Genomic DNA; Genomics; Haplotypes; Health; Housing; Human; Human Genome; Image Analysis; Individual; Label; Laboratories; Libraries; Location; Maps; Medical; Methods; Optical Methods; Principal Investigator; Reading; Resolution; Scanning; Scheme; Shotgun Sequencing; Solutions; Technology; Variant; base; comparative genomic hybridization; design; flexibility; fluorophore; genome analysis; genome sequencing; genome-wide; human genome sequencing; improved; instrument; nanochannel; novel; scaffold; screening; single molecule; tool

DESCRIPTION (provided by applicant): Two of the major challenges in genome analysis are de novo genome sequence assembly based on "short read" shotgun sequencing and genome-wide structural variation analysis. At present, most medical sequencing projects and whole genome sequencing projects map the sequencing data onto the reference human genome sequence without performing whole genome assemblies. When whole genome assembly is attempted, it is done by generating paired-end sequencing reads from a number of sequencing libraries with different insert sizes. The paired-end sequences provide the "scaffold" that helps with sequence assembly. However, it increases the complexity of the sequencing project and provides limited information on the haplotypes of the diploid human genome. Similarly, current structural variation scanning based on array-based comparative genomic hybridization is unable to determine the genomic locations of duplicated regions or identify genomic inversions or balanced translocations. We propose to optimize a new, highly flexible, automated method for optical mapping for general use. Our genome mapping strategy starts with sequence-specific labeling double-stranded genomic DNA fragments with fluorophores. The fluorescently labeled, large (100 kbp to 1 Mbp) DNA fragments are then linearized in nanochannel arrays for high-throughput, automated imaging and analysis on a commercially available instrument. As more and more groups are performing large-scale genomic sequencing and searching for structural variation, a method that average labs can use in-house will facilitate medical genomics studies. By intelligent probe design, one can therefore create genome maps tailored to the questions being asked, be it local structural variation screening, global structural variation detection, or scaffolding for de novo genome sequence assembly. In this proposal, we aim to improve and scale the method to generate, with ease, >300 individuals from the 1000 Genomes Project to provide both genome-wide structural variation data and fully assembled sequencing data on these whole-genome sequenced subjects.

描述（由申请人提供）：基因组分析的两个主要挑战是基于“短读”鸟枪测序的从头基因组序列组装和全基因组结构变异分析。目前，大多数医学测序项目和全基因组测序项目将测序数据映射到参考人类基因组序列上，而不进行全基因组组装。当尝试进行全基因组组装时，是通过从具有不同插入片段大小的多个测序文库生成双端测序读数来完成的。双末端序列提供了有助于序列组装的“支架”。然而，它增加了测序项目的复杂性，并提供了有关二倍体人类基因组单倍型的有限信息。类似地，当前基于阵列的比较基因组杂交的结构变异扫描无法确定重复区域的基因组位置或识别基因组倒位或平衡易位。我们建议优化一种新的、高度灵活的、自动化的通用光学测绘方法。我们的基因组作图策略从用荧光团对双链基因组 DNA 片段进行序列特异性标记开始。然后，荧光标记的大（100 kbp 至 1 Mbp）DNA 片段在纳米通道阵列中线性化，以便在市售仪器上进行高通量、自动成像和分析。随着越来越多的团体正在进行大规模基因组测序并寻找结构变异，普通实验室可以内部使用的方法将促进医学基因组学研究。通过智能探针设计，人们可以根据所提出的问题创建基因组图谱，无论是局部结构变异筛选、全局结构变异检测还是从头基因组序列组装的支架。在本提案中，我们的目标是改进和扩展该方法，以轻松生成来自千个基因组计划的超过 300 个个体，以提供全基因组结构变异数据和这些全基因组测序受试者的完全组装的测序数据。