Mapping Nonsyndromic Cleft Lip and Palate Genetic Loci

描述（由申请人提供）：非综合征性唇裂伴或不伴腭裂（NSCLP）是一种常见的复杂口面出生缺陷，与显著的发病率和死亡率增加相关。手术矫正始终是必需的，多学科保健干预措施每年花费约5亿美元。候选基因研究和GWAS已经确定了一些推定的NSCLP基因和基因座，估计仅占遗传变异的约20%。虽然这是一个重要的起点，但大多数NSCLP的遗传风险仍未被发现，代表了一个有待探索的前沿。我们使用候选基因和GWAS方法来定义NSCLP中的遗传变异;发现一个先前未被怀疑的基因CRISPLD 2与NSCLP相关，当在斑马鱼中被敲除时，会导致腭和下颌异常。该项目的目标是继续识别和理解未发现的变异，有助于非小细胞肺癌的遗传结构。为了实现这一目标，我们将应用最新的技术，全外显子下一代测序（WES）和染色体微阵列分析（CMA）到我们的广泛的基于家族的NSCLP数据集。我们将使用检测编码和非编码变体的WES（Agilent 50 Mb v.4外显子含量+UTR），因为我们已经证明这两种类型的变异都有助于NSCLP。此外，CMA将检测WES可能遗漏的拷贝数变异（CNV）。这将提供最完整的覆盖范围，并且基于家族的设计将允许检测NSCLP的家族原因。候选基因将被优先排序，在斑马鱼中进行功能测试以确定生物学意义，并在我们的病例对照中进行光谱变异和风险建模分析。结果将提供有关风险变异的重要信息， 总的来说。在整个研究期间，我们将继续扩大我们的NSCLP数据集，用于这项和未来的遗传研究。将最新技术应用于我们广泛的基于家庭的数据集是揭示导致这种常见出生缺陷的遗传变异的有力方法。这种方法是向前迈出的重要一步;结果将为负责NSCLP的遗传变异的发展知识库增加重要的新信息，这将转化为对高危家庭的遗传咨询。

DESCRIPTION (provided by applicant): Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common complex orofacial birth defect associated with significant morbidity and increased mortality. Surgical correction is always required and the multidisciplinary health interventions cost approximately a half billion dollars each year. Candidate gene studies and GWAS have identified a number of putative NSCLP genes and loci that are estimated to account for only ~20% of the genetic variation. While this represents an important starting point, the majority of genetic risk for NSCLP remains undiscovered and represents a frontier to be explored. We have used both candidate gene and GWAS approaches to define genetic variation in NSCLP; a previously unsuspected gene, CRISPLD2, was found to be associated with NSCLP and, when knocked down in zebrafish, causes palatal and jaw abnormalities. The goal of this project is to continue identifying and understanding the undiscovered variation that contributes to the genetic architecture of NSCLP. To accomplish this goal, we will apply the newest technologies, whole exome next generation sequencing (WES) and chromosomal microarray analysis (CMA) to our well-characterized extensive family-based NSCLP dataset. We will use the WES that detects coding and noncoding variants (Agilent 50Mb v.4 exon content +UTR) because we have shown that both types of variation contribute to NSCLP. In addition, CMA will detect copy number variants (CNVs) that would be missed by WES. This will provide the most complete coverage and the family-based design will allow for detection familial causes of NSCLP. Candidate genes will be prioritized, functionally tested in zebrafish to determine biological significance and analyzed in our case controls for spectrum variation and risk modeling. The results will provide important information about risk variants, individually and in aggregate. During the entire study period, we will continue to expand our NSCLP dataset for this and future genetic studies. Application of the newest technology to our extensive family-based dataset is a powerful method for uncovering the genetic variation contributing to this common birth defect. This approach is a significant step forward; the results will add important new information to the developing knowledge base of genetic variation responsible for NSCLP, which will translate into genetic counseling for at-risk families.