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: 8632667
• 负责人: Pui-Yan KWOK
• 金额: $ 79.39万
• 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/8632667
• 关键词: Algorithms; Communities; DNA; DNA mapping; Data; Detection; Development; Diploidy; Disease; Equilibrium; Genome; Genome Mappings; Genomic DNA; Genomics; Haplotypes; 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 association study; genome-wide; improved; instrument; nanochannel; novel; public health relevance; scaffold; screening; single molecule; tool

Abstract 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.

摘要 基因组分析中的两个主要挑战是从头基因组序列组装 基于“短读”鸟枪测序和全基因组结构变异分析。在 目前，大多数医学测序项目和全基因组测序项目绘制了 将数据测序到参考人类基因组序列上，而不进行整个测序。 基因组组装当尝试进行全基因组组装时， 来自具有不同插入大小的许多测序文库的双端测序读段。 双端序列提供了帮助序列组装的“支架”。然而，在这方面， 它增加了测序项目的复杂性，并提供了有限的信息， 二倍体人类基因组的单倍型。类似地，基于当前结构变化扫描的 基于阵列的比较基因组杂交无法确定基因组位置 或鉴定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、自动化的光学测绘方法，以供一般使用。我们 基因组作图策略从序列特异性标记双链基因组DNA开始 带有荧光团的片段。荧光标记的大（100 kbp至1 Mbp）DNA 然后将片段在纳米通道阵列中线性化，用于高通量自动成像 并在市售仪器上进行分析。随着越来越多的团体 大规模基因组测序和寻找结构变异，一种平均 实验室内部可以使用的技术将促进医学基因组学研究。通过智能探头设计， 因此，可以创建针对所问问题的基因组图谱，无论是局部结构， 变异筛选、全局结构变异检测或从头基因组构建 序列组装。在这个提议中，我们的目标是改进和扩展生成方法， 轻松地，来自1000个基因组计划的>300个个体提供全基因组 这些全基因组的结构变异数据和完全组装的测序数据 有序的主题。