Next Generation gene discovery in neurogenetics

描述(申请人提供)：这项提案的目标是在华盛顿大学神经遗传学诊所和阿尔茨海默病研究中心进行了30多年的确定、表型和采样的家系中，确定导致孟德尔神经遗传学疾病的基因。这种广泛的收集对于发现导致神经退行性变的新基因是一个宝贵的资源。我们小组在发现神经性疾病的基因方面发挥了重要作用。致病基因仍有待发现的疾病提出了新的挑战，因为许多家族太小，无法进行位置克隆。以前，即使在有广泛病史的家庭中，当只有几个受影响的人的DNA可用时，也没有基因识别的方法。在这项提案中，我们将利用新的可用方法来检测稀有序列和拷贝数变体的全基因组，作为一种强大的创新方法来识别与神经遗传疾病有关的基因。这些新技术包括基于阵列的高分辨率比较基因组杂交，以检测基因内的缺失和复制，以及大规模并行测序，以检测基因组蛋白质编码部分(“外显子组”)的序列变化。我们的研究小组在将这些新技术应用于基因鉴定方面已经有了丰富的经验。我们准备最大限度地利用基础设施的融合、我们团队在分子遗传学方面的专业知识、现有的特征良好的样本以及阵列和测序技术的进步，这些进步现在使得在整个基因组规模上应用这种方法是可行的。只对两个受影响的亲属进行研究，就可以将候选基因的数量从2万个减少到几十个，然后根据功能进行排序，并在其他家庭成员、无关病例和对照中进行评估。例如，我们最近发表了一项研究，在该研究中，我们使用这种方法将感觉和运动神经病伴共济失调(SMNA)的候选基因数量从包含在大连锁区域中的300个减少到1个。虽然这里要研究的特定疾病并不常见，但所涉及的基因和途径可能是常见疾病的表型差异和易感性的基础，这些疾病具有共同的临床特征，并导致相当大的发病率。这些疾病包括阿尔茨海默氏症、帕金森氏症、小脑性共济失调、肌肉疾病和周围神经病，这些疾病经常困扰我们老龄化的人口。我们的创新方法可能会成为基因发现的新标准，这将使我们能够在理解神经遗传疾病的生物学和确定治疗干预的目标方面取得进一步进展。) 公共卫生相关性：这项提案的目标是确定导致孟德尔神经遗传性疾病的新基因，包括共济失调、神经疾病、肌病、运动障碍和高渗透性家族性痴呆。我们将使用新获得的强大的比较基因组阵列杂交、有针对性的捕获和对人类基因组中所有蛋白质编码区的大规模并行测序，以及生物信息学技术来检测可用患者数量太少而无法进行连锁分析的家庭中的致病突变。这一新方法可以快速确定人类许多罕见遗传病的原因。)

DESCRIPTION (provided by applicant): The goal of this proposal is to identify genes responsible for mendelian neurogenetic disorders in a collection of families that were ascertained, phenotyped and sampled over 30 years at the University of Washington Neurogenetics Clinics and Alzheimer's Disease Research Center. This extensive collection is a valuable resource for the discovery of new genes responsible for neurodegeneration. Our group has had a major role in discovery of genes for neurologic disorders. The disorders for which the causal genes remain to be found present a new challenge, as many of the families are too small to enable positional cloning. Previously there were no methods for gene identification even in families with an extensive history of disease when DNA from only a few affected persons is available. In this proposal we will exploit newly available methods for whole genome detection of rare sequence and copy number variants as a powerful and innovative approach to identify genes involved in neurogenetic disorders. These new techniques include array-based high-resolution comparative genomic hybridization to detect intragenic deletions and duplications, and massively parallel sequencing to detect sequence changes in the protein-coding portion of the genome (the "exome"). Our group of investigators already has substantial experience in applying these novel techniques toward gene identification. We are poised to take maximal advantage of the confluence of infrastructure, our group's expertise in molecular genetics, existing well characterized samples, and advances in array and sequencing techniques that now make it feasible to apply this approach on the whole genome scale. Study of only two affected relatives can reduce the number of candidate genes from 20,000 to several dozen that will then be ranked by function and evaluated in other family members, unrelated cases and controls. For example, we recently published a study in which we used this approach to reduce the number of candidate genes for sensory and motor neuropathy with ataxia (SMNA) from the 300 contained in the large linkage region to one. Although the specific diseases to be investigated herein are not common, the genes and pathways involved may underlie phenotypic differences in and susceptibility to common disorders with which they share clinical features and that are responsible for considerable morbidity. These conditions include Alzheimer's disease, Parkinson's disease, cerebellar ataxia, muscle disease, and peripheral neuropathy, diseases that frequently afflict our aging population. Our innovative approach will likely become the new standard for gene discovery that will enable further advances in the understanding the biology of neurogenetic disorders and identifying targets for therapeutic interventions. ) PUBLIC HEALTH RELEVANCE: The goal of this proposal is to identify novel genes that are responsible for mendelian neurogenetic disorders, including ataxias, neuropathies, myopathies, movement disorders, and highly penetrant familial dementia. We will employ newly available powerful comparative genomic array hybridization, targeted capture and massively parallel sequencing of all protein coding regions in the human genome, and bioinformatics techniques to detect causative mutations in families where the number of available affected persons is too few for linkage analyses. This new approach can rapidly identify the causes of many rare genetic diseases in humans.) )