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Comprehensive genomic approach to rare hearing disorders and ataxia

Comprehensive genomic approach to rare hearing disorders and ataxia
罕见听力障碍和共济失调的综合基因组方法
批准号:
7857691
负责人:
Margit Burmeister
金额:
$11.55万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-07-17 至 2010-06-30

项目摘要

项目成果

Margit Burmeister的其他基金

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中文摘要
翻译
描述(申请人提供):位置克隆已经帮助确定了许多孟德尔疾病的分子原因。与更常见的耳聋和共济失调有关的基因已经被识别出来,并经常进行临床测试。然而,大多数基因罕见形式的原因仍不清楚,因为这些家系往往太小,本身无法提供足够的统计力量来明确识别连锁。此外,即使家系大到足以识别一个连锁的基因座,这些区域通常也如此之大,以至于涉及数百个基因。在某些情况下,连锁不平衡分析可以进一步缩小区域。最近,基因表达的全球分析已经成为现实。我们假设突变基因的一个子集直接或间接地导致异常表达水平,可以通过对淋巴母细胞系(LCLS)的基因表达分析和遗传分析相结合来识别。使用这种组合方法,最近只在三个受影响的受试者中发现了一种新的癫痫基因。我们最近发现了一个新的听神经病基因,并有令人鼓舞的数据来鉴定第二个新的耳聋基因和几个新的共济失调基因。在这项试验/可行性R21赠款中,我们将探索这种方法在几个原因不明的耳聋或共济失调家庭中的普及性。我们将进行遗传连锁、连锁不平衡和全球基因表达分析。候选基因将被确定为连锁区和那些表现出显著表达变化的基因之间的截取。将开发、实施和测试确定遗传和基因表达数据之间的交集的计算方法。虽然在某些情况下,结合遗传连锁和连锁不平衡与全局基因表达分析可以直接识别突变基因,但在另一些情况下,突变可能导致一条途径的功能差异,而不直接影响其自身基因的表达。在这种情况下,有必要对突变基因下游受影响的基因表达变化进行更复杂的分析,以确定缺陷途径和突变。为此目的,将使用表达分析、动物模型和文献以及公共生物信息学数据库中的途径。从这些方法中出现的候选基因将被测序,以识别变异,并在无关的对照中测试潜在的突变。 与公共卫生相关:许多形式的耳聋或共济失调的遗传原因尚不清楚。我们的研究将导致识别与这些疾病有关的新基因和代谢途径。这些发现可以提高准确的诊断、症状前检查、计划生育和个性化治疗。它也可能最终导致新的治疗方法。
英文摘要
DESCRIPTION (provided by applicant): Positional cloning has helped identify the molecular causes of many of Mendelian disorders. Genes involved in the more common forms of deafness and ataxia have been identified and are often clinically tested. However, the cause of most genetically rare forms is still unknown because such families are often too small to provide by themselves sufficient statistical power to unambiguously identify linkage. In addition, even if families are large enough to identify a linked locus, the regions are typically so large that hundreds of genes are implicated. In some situations, linkage disequilibrium analysis can further narrow a region. Recently, global analysis of gene expression has become a reality. We hypothesize that a subset of mutated genes directly or indirectly leads to abnormal expression levels, and can be identified by combining genetic analysis with gene expression analysis of mRNA from lymphoblastoid cell lines (LCLs). Using such a combined approach, a novel epilepsy gene was recently identified in only three affected subjects. We have recently identified a novel auditory neuropathy gene, and have encouraging data for identification of a second novel deafness gene and for several novel ataxia genes. In this pilot/feasibility R21 grant, we will explore the generalizability of this approach in several families with unidentified causes of deafness or ataxia. We will perform genetic linkage, linkage disequilibrium and global gene expression analysis. Candidates genes will be identified as the intercept between genes in linkage regions and those that show significant expression changes. Computational approaches to define the intersect between genetic and gene expression data will be developed, implemented and tested. While in some cases combining genetic linkage and linkage disequilibrium with global gene expression analysis may directly identify the mutant gene, in other cases the mutation may result in functional differences in a pathway without affecting the expression of its own gene directly. In that case, more complex analysis of affected gene expression changes downstream of a mutant gene will be necessary to identify the deficient pathway and the mutation. Pathways from expression analysis, animal models and the literature and public bioinformatic databases will be used for this purpose. Candidate genes emerging from these approaches will be sequenced to identify variants, and potential mutations tested in unrelated controls. PUBLIC HEALTH RELEVANCE: The genetic cause of many forms of deafness or ataxia is still unknown. Our research will result in the identification of new genes and metabolic pathways involved in these disorders. These findings can improve accurate diagnosis, presymptomatic testing, family planning and personalizing treatment. It may also ultimately lead to new treatments.
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Integrating context-specific networks to predict ataxia genes
Ataxia gene identification by integrated genomic analysis
Ataxia gene identification by integrated genomic analysis
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