STRUCTURAL VARIATION IN NEUROLOGICAL DISEASE

摘要 在过去的二十年中，已经变得明显的是，基因组重排通常是基因重排的类型。 神经系统疾病的潜在突变这不仅适用于神经发育障碍， 智力残疾（ID）和人类畸形的不同可识别模式（例如Potocki-Lupski 综合征），但也用于晚发性成人神经系统疾病，如腓骨肌萎缩症。 此外，基因组重排往往是复杂性状和散发性疾病（如帕金森病）的基础， 阿尔茨海默病和其他神经变性过程。与先前的解释相反， 对疾病相关的基因组重排的评估经常证明，它们可以比 比预期的复杂。复杂性可以发生在单个位点，并给出复杂性的特定模式。 在全基因组阵列CGH上观察到的基因组重排（CGR）;如重复-正常- 重复（DUP-NML-DUP）或嵌入重复内的三重（DUP-TRP-DUP）。此外，委员会认为， 复杂性可能发生在基因组水平上，导致复杂的染色体重排（CCR）， 在癌症和神经发育障碍中观察到的染色体断裂现象，以及 一种不寻常的实验观察到的模式，多个从头拷贝数变异（CNVs）的传播显然 随机分布在整个基因组中。阐明产生这种复杂性的机制是一个 新兴领域。我们建议进一步描述已经发现与神经系统疾病相关的CGR， 疾病具体来说，我们将研究：1）CGR，包括：i）DUP-NML-DUP模式和ii）DUP-NML-DUP模式。 一个反向的三重片段嵌入基因组的一个重复片段中的模式 （DUP-TRP/INV-DUP）;这些是新观察到的CGR类型，其中一种提出的机制在 我们以前的申请; 2）复发性三联症的机制; 3）阐明潜在的分子 CGR的特征和断点连接，伴随着长的基因组缺失延伸 杂合性（AOH），并导致基因组（CGR）和遗传（AOH）改变; 4）β-Alu 重排及其在基因组不稳定性和疾病中的作用; 5）我们将尝试分离一个基因， 这对多个新生CNV似乎随机分布在整个基因组中的现象很重要。 用于实现这些具体目标的实验方法现在在我们的范围内。 到达。这些研究主要需要能够进行全基因组变异测定的基因组方法 例如阵列比较基因组杂交、全基因组SNP芯片、全外显子组测序（WES） 全基因组测序（WGS）和其他绘图和分子方法，用于描绘 特定断点连接。预计这些研究将表征这些新型的 重排，并提供进一步了解驱动基因和基因组的基本分子突变机制 这会导致无数的神经系统疾病

ABSTRACT During the previous two decades it has become apparent that genomic rearrangements are often the type of mutation that underlies neurological disease. This is so not only for neurodevelopmental disorders such as intellectual disability (ID) and different recognizable patterns of human malformation (e.g. Potocki-Lupski syndrome), but also for late-onset adult neurological disorders such as Charcot-Marie-Tooth disease. Moreover, genomic rearrangement can often underlie complex traits and sporadic diseases such as Parkinson, Alzheimer disease and other neurodegenerative processes. Contrary to prior interpretations, experimental evaluation of disease associated genomic rearrangements has often documented that they can be much more complex than anticipated. Complexities can occur at individual loci and give specific patterns for complex genomic rearrangements (CGR) as observed on genome-wide array CGH; such as duplication - normal - duplication (DUP-NML-DUP), or a triplication embedded within duplications (DUP-TRP-DUP). Furthermore, complexities can occur on a genomic level leading to complex chromosomal rearrangements (CCR) and the phenomena of chromothripsis observed both in cancer and neurodevelopmental disorders, as well as an unusual experimentally observed pattern of multiple de novo copy number variants (CNVs) spread apparently randomly throughout the genome. The elucidation of mechanisms that can generate such complexities is an emerging field. We propose to further characterize CGR that have been found in association with neurological disease. Specifically, we will investigate: 1) CGRs that consists of: i) a DUP-NML-DUP pattern and ii) a pattern of a triplicated segment in inverse orientation embedded within a duplicated segment of the genome (DUP-TRP/INV-DUP); these are newly observed types of CGR with one proposed mechanism elucidated in our previous application; 2) The mechanism for recurrent triplications; 3) Elucidate the underlying molecular characteristics and breakpoint junctions of CGR that are accompanied by long genomic stretches of absence of heterozygosity (AOH), and resulting in both genomic (CGR) and genetic (AOH) alterations; 4) Alu-Alu rearrangements and their role in genomic instability and disease and 5) We will attempt to isolate a gene important to the phenomena of multiple de novo CNV seemingly randomly distributed throughout the genome. The experimental approaches to be utilized to accomplish each one of these specific aims are now within our reach. These studies predominately require genomic approaches that enable genomewide assays of variation such as array comparative genomic hybridization, genomewide SNP chips, whole exome sequencing (WES), whole genome sequencing (WGS), and other mapping and molecular approaches for the delineation of specific breakpoint junctions. It is anticipated these studies will characterize these novel types of rearrangements and lend further insight into basic molecular mutational mechanisms driving gene and genome evolution and that can cause the myriad of neurological diseases.