Augmenting GWAS with Retrotransposon Polymorphisms

利用逆转录转座子多态性增强 GWAS

• 批准号: 7943987
• 负责人: HAIG H. KAZAZIAN
• 金额: $ 50.7万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7943987
• 关键词: 3' Flanking Region; Address; Area; Biological Assay; Cancer Etiology; Cataloging; Catalogs; Copy Number Polymorphism; Custom; Data; Detection; Disease; Elements; Family; Gene Frequency; Genetic Determinism; Genetic Polymorphism; Genetic Variation; Genome; Genomics; Genotype; Haplotypes; Human; Human Genome; Individual; International; Location; Malignant Neoplasms; Malignant neoplasm of prostate; Methods; Population; Positioning Attribute; Repetitive Sequence; Retroposon; Retrotransposon; Risk; SNP genotyping; Sequence Analysis; Site; Source; Study Subject; System; Techniques; Variant; base; cancer risk; design; disease phenotype; disease-causing mutation; genome wide association study; genome-wide; insight; neoplastic; next generation; novel marker; research study

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (08) Genomics and specific Challenge Topic, 08-CA-101: Augmenting Genome-Wide Association Studies. Genome-wide association studies (GWAS) are typically carried out to uncover potential correlations between SNP genotypes and disease phenotypes. Often, cancer or neoplastic conditions have been the subject of these studies, and they have provided useful insights into the genetic determinants of cancer etiology. While SNPs are the most common form of genetic variation, there are other forms such as copy number variation (CNV) and retrotransposon insertion polymorphisms (RIPs). Recently, GWAS incorporating CNV data have been completed with positive results, but to date no GWAS experiments have used RIPs as the genotypic marker despite the fact that active human families of retrotransposon (LINE-1, Alu, and SVA) are collectively responsible for over 60 disease-causing mutations. The reason for this omission of an important source of genomic variation has been largely technical: no large-scale detection method has enabled the cataloguing of RIPs. Recently, we have developed a robust method for the detection of human-specific LINE-1 (L1) insertions on a genome- wide scale using a hemi-specific PCR method to amplify L1 3' flanking regions in a manner amenable to next-generation sequencing on Illumina's Genome Analyzer platform. Subsequent analysis of the sequencing results reproducibly provides the location of human-specific L1 insertion locations. This technique can be readily extended to other forms of retrotransposon-induced variation including the Alu and SVA families of retroposons simply by interchanging the hemi- specific primer sequences. Once a significant amount of RIP-induced variation has been catalogued across several distinct populations, we will use these sites to design a genotyping array using Illumina's iSelect custom Infinium assay system. Using this array of RIP markers, we will then carry out a GWAS for prostate cancer on ~1000 cases and ~1000 controls. We fully expect to identify 4,000 or more RIP markers for this assay that will serve as an augmentation to GWAS studies in which RIPs have not yet been considered. Genome Wide Association Studies (GWAS) have proven their utility in identifying genomic variants associated with risk for many diseases. To date, SNPs and CNVs have been used as the variant markers in these studies, omitting a major contributor to Human variation: retrotransposon insertion polymorphisms (RIPs). We propose to use a technique we have developed which identifies RIPs on a genome-wide scale to collect a large number of RIP markers for a genotyping array and then conduct a GWAS on prostate cancer in a proof-of-concept attempt to identify new markers associated with the disease.

描述（由申请人提供）： 这个应用程序解决了广泛的挑战领域（08）基因组学和特定的挑战主题，08-CA-101：增强全基因组关联研究。全基因组关联研究（GWAS）通常用于揭示SNP基因型与疾病表型之间的潜在相关性。通常，癌症或肿瘤状况一直是这些研究的主题，并且它们为癌症病因学的遗传决定因素提供了有用的见解。虽然SNP是遗传变异的最常见形式，但也有其他形式，如拷贝数变异（CNV）和反转录转座子插入多态性（RIP）。最近，GWAS纳入CNV数据已经完成了积极的结果，但迄今为止，没有GWAS实验使用RIP作为基因型标记，尽管事实上，活跃的人类逆转录转座子家族（LINE-1，Alu和SVA）共同负责超过60种致病突变。遗漏基因组变异的一个重要来源的原因主要是技术性的：没有大规模的检测方法能够对RIP进行编目。最近，我们已经开发了一种用于在全基因组规模上检测人特异性LINE-1（L1）插入的稳健方法，其使用半特异性PCR方法以适于在Illumina的基因组分析仪平台上进行下一代测序的方式扩增L1 3'侧翼区。测序结果的后续分析可重复地提供人特异性L1插入位置的位置。这种技术可以容易地扩展到其他形式的反转录转座子诱导的变异，包括Alu和SVA家族的反转录转座子，只需互换半特异性引物序列。一旦在几个不同的人群中编目了大量RIP诱导的变异，我们将使用这些位点来设计使用Illumina的iSelect定制Infinium检测系统的基因分型阵列。使用RIP标记物阵列，我们将对约1000例病例和约1000例对照进行前列腺癌的GWAS。我们完全期望为该检测鉴定4，000个或更多RIP标记物，这将作为GWAS研究的补充，其中尚未考虑RIP。全基因组关联研究（GWAS）已经证明了它们在鉴定与许多疾病风险相关的基因组变异方面的实用性。到目前为止，SNPs和CNV已被用作这些研究中的变异标记，忽略了人类变异的主要贡献者：反转录转座子插入多态性（RIP）。我们建议使用我们开发的一种技术，该技术在全基因组范围内识别RIP，以收集大量RIP标记物用于基因分型阵列，然后在前列腺癌上进行GWAS，以验证概念，尝试识别与疾病相关的新标记物。