Rates and patterns of recurrent structural variation in the mouse genome

描述（由申请人提供）：全基因组序列和高分辨率工具揭示了哺乳动物基因组具有复杂和高度可变的物理结构。我们现在认识到，结构变异（SV），定义为大于Ikb的基因组片段的拷贝数、方向或位置的差异，在哺乳动物中普遍存在。至少有1000个SVs区分了两个人的基因组，这些影响了基因的丰度，并且越来越多地发现SVs是正常和疾病表型的基础。SV与我们对进化和疾病的理解特别相关，因为单个突变事件可以影响大的表型变化，因为结构突变率在“热点”和“冷点”之间差异很大。在了解基因组在结构上的可塑性究竟如何，以及它们为什么会这样方面，我们还处于非常早期的阶段。现在，高通量DNA测序方法使我们能够常规地获得数百万对末端序列，提供关于基因组结构的非常有意义的信息。我们已经开发出复杂的工具，通过对端测序来重建基因组结构。我们的方法的一个新颖之处在于，它们被设计用于识别整个基因组中的SV，包括结构复杂和/或重复的区域。为了研究SV的范围和起源，特别是热点地区，我们将对来自4种不同近交系小鼠的3个独立繁殖菌落的基因组进行配对端DNA测序。这12个品系代表了品系间遗传变异的全部广度，以及约2000代的自发品系内突变。我们将发现SVs，识别那些由热点地区反复发生的结构突变引起的SVs，并对热点地区进行特征描述，以寻找其起源和功能的线索。我们的研究结果将解决三个基本问题：1)近交系小鼠基因组中存在多少SV ？2)哺乳动物基因组在短时间尺度上的结构可塑性如何？3)周期性结构突变对自然变异的贡献是什么？为了解决上述问题，并为更广泛的基因组学社区提供我们的计算工具，我们将继续开发和完善现有的SV发现算法。我们的最终目标是创建一个软件包，可以快速处理大量的成对端序列DNA与最小的计算资源。与William Pearson合作，我们将编写一个单一的算法，将读取映射和SV发现结合到一个高效的过程中，从而克服当前的分析瓶颈。该软件将允许小型基因组学实验室利用强大的新测序技术。我们的研究结果将使我们对哺乳动物生殖系结构基因组变异的动力学有一个基本的了解，并将使研究新的突变的原因和机制成为可能。鉴于结构突变在遗传性和自发性人类疾病（包括自闭症和精神分裂症）的病因学中所起的新作用，这是一个对人类健康至关重要的主题。

DESCRIPTION (provided by applicant): Whole genome sequences and high-resolution tools have revealed that mammalian genomes have a complex and highly variable physical structure. We now recognize that structural variation (SV), defined as differences in the copy number, orientation or location of genomic segments larger than Ikb, are prevalent in mammals. At least ~1,000 SVs distinguish the genomes of two humans, these affect an abundance of genes, and SVs are increasingly found to underlie normal and disease phenotypes. SV is of special relevance to our understanding of evolution and disease because single mutational events can affect large phenotypic changes, and because structural mutation rates vary dramatically between "hotspots" and "coldspots". We are only in the very early stages of understanding how structurally plastic genomes truly are, and why they are this way. High-throughput DNA sequencing methods now allow us to routinely obtain millions of paired-end sequence reads, providing extraordinarily meaningful information about genome structure. We have developed sophisticated tools to reconstruct genome architecture by paired-end sequencing. A novel aspect of our methods is that they are designed to Identity SV throughout the entire genome, including structurally complex and/or repetitive regions. To investigate the extent and origin of SV in general, and of hotspots in particular, we will apply paired-end DNA sequencing to the genomes of 3 independently-bred colonies from 4 different inbred mouse strains. These 12 lines represent the full breadth of inter-strain genetic variation, as well as ~2,000 generations of spontaneous intra-strain mutation. We will discover SVs, identify those that result from recurrent structural mutation at hotspots, and characterize hotspots for clues as to their origin and function. Our results will address three fundamental questions: 1) How much SV exists among the genomes of inbred mouse strains? 2) How structurally plastic are mammalian genomes over short time scales? and 3) What is the contribution of recurrent structural mutation to natural variation? In order to address the above questions, as well as to provide our computational tools to the broader genomics community, we will continue to develop and refine our existing SV discovery algorithms. Our ultimate goal is to create a software package that can rapidly process large amounts of paired-end sequence DNA with minimal computational resources. In collaboration with William Pearson, we will write a single algorithm that combines read mapping and SV discovery into one highly efficient process, thus overcoming current analysis bottlenecks. This software will allow small genomics labs to take advantage of powerful new sequencing technologies. Our results will yield a basic understanding of the dynamics of structural genomic variation in the mammalian germline, and will enable investigation of the causes and mechanisms of new mutation. This is a subject of paramount significance to human health given the emerging role of structural mutation in the etiology of inherited and spontaneous human diseases, including autism and schizophrenia.