High-Resolution ROMA Analysis of Genome Copy Number Variation in the HapMap

根据我们小组和其他人最近发表的研究，发现大规模DMA复制 在细胞遗传学水平上不可见的数量变异（CNVs）是人类遗传学的普遍特征。 基因组我们的研究结果表明，平均而言，两个人的CNV相差十几个，涉及3 Mb或 大约0.1%的基因组。这相当于0.1%的遗传差异是由于单一的 核苷酸多态性（SNP）。然而，与核苷酸序列变体如SNP相反， 基因组中的结构变异还没有得到很好的表征。还有很多东西需要了解， 这些结构变异的基因组位置、频率和稳定性及其在人类中的重要性 进化和遗传疾病。为了进一步研究，有必要扩大电流 通过表征大样本个体并构建一个 验证的CNV数据库。一个全面的CNVs目录将有助于大规模研究（1） CNVs与疾病风险的关联（2）CNVs对药物治疗反应的影响，以及（3）CNVs在药物治疗中的作用。 人类进化中的结构变异。我们建议收集基因组拷贝数的数据资源 使用强大的高分辨率CNV对来自国际HapMap项目的270个个体进行变异 发现方法，代表性寡核苷酸微阵列分析（ROMA）。我们要表演罗马舞 使用提供8kb分辨率的380，000探针阵列进行扫描。此外，我们将整合我们的数据 与使用其他CNV发现方法获得的CNV信息相比较。我们将选择一组600个常见的CNV （次要等位基因频率>= 1%）进行精细尺度表征，并且常见CNV的边界将是 使用平铺路径寡核苷酸阵列以更高的分辨率定义，分辨率为每5个探针 BP.对于缺失和重复的另一个子集，我们将表征CNV连接处， 序列级。最后，为了将CNV整合到基于SNP的HapMap中，我们将识别 与CNV连锁不平衡的SNP标记。所有关于拷贝数变异的信息将 可通过dbSNP获得，原始微阵列数据可从www.hapmap.org获得。

Based on recent studies published by our group and others, it was discovered that large-scale DMA copy number variants invisible at the cytogenetic level (CNVs), are a ubiquitous characteristic of the human genome. Our findings indicated that, on average, two individuals differ by a dozen CNVs involving 3 Mb or approximately 0.1 % of the genome. This is comparable to the 0.1 % of genetic difference that is due to single nucleotide polymorphisms (SNPs). However, in contrast to nucleotide sequence variants such as SNPs, structural variation in the genome has not been well characterized. Much remains to be learned about the genomic locations, frequency, and stability of these structural variants and their importance in human evolution and genetic disease. To enable further research in this are it is necessary to expand the current knowledge of copy number variation by characterizing a large sample of individuals and constructing a database of validated CNVs. A comprehensive catalog of CNVs will facilitate large-scale studies of (1) the association of CNVs with disease risk (2) the effects of CNVs on response to drug treatment, and (3) the role of structural variation in human evolution. We propose to collect a data resource on genome copy number variation on 270 individuals from the international HapMap project using a powerful high-resolution CNV discovery method, Representational Oligonucleotide Microarray Analysis (ROMA). We will perform ROMA scans using a 380,000 probe array that provides a resolution of 8 kb. In addtion, we will integrate our data with CNV information obtain using other CNV discovery methods. We will select a set of 600 common CNVs (minor allele frequency >= 1%) for fine-scale characterization, and the boundaries of common CNVs will be defined at higher resolution using a tiling path Oligonucleotide array with a resolution of one probe every 5 bp. For a further subset of deletions and duplications, we will characterize the CNV junctions at the sequence level. Lastly, in order to integrate CNVs into the context the SNP-based HapMap, we will identify SNP markers that are in linkage disequilibrium with CNVs. All information on copy number variation will be made available through dbSNP and raw microarray data will be made available from www.hapmap.org.