Genome-wide detection of human copy number variations using high-density DNA oligonucleotide arrays
Genome-wide detection of human copy number variations using high-density DNA oligonucleotide arrays
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DOI：
10.1101/gr.5629106
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发表时间：
2006-12-01
期刊：
影响因子：
7
通讯作者：
Aburatani, Hiroyuki
中科院分区：
文献类型：
--
作者：
Komura, Daisuke;Shen, Fan;Aburatani, Hiroyuki
最近的报道表明，人类基因组中的拷贝数变异(CNV)比单核苷酸多态(SNPs)对核苷酸多样性的贡献更大。此外，CNV对人类疾病易感性的贡献可能比先前预期的更大，尽管对CNV的表型后果的完全理解是不完整的。我们最近报道了使用高密度SNP基因分型阵列和BAC阵列CGH对270例HapMap样本中CNV的全面观察。在这份报告中，我们描述了一种使用Affymetrix基因芯片人类定位500K早期访问(500K EA)阵列的新算法，该算法识别了1203个CNV，大小从960bp到3.4Mb不等。该算法包括三个步骤：(1)强度预处理，通过直接估计等位基因特异性亲和力来提高成对比较的分辨率，并通过改进的基因组不平衡图(GIM)算法结合探针和靶序列特征来降低信号噪声；(2)利用改进的软件阵列程序自动且稳健地检测候选CNV区域来提取CNV；(3)拷贝数推断，其中总结所有成对比较以更准确地定义CNV边界和准确估计CNV拷贝数。用定量聚合酶链式反应和质谱仪对CNV的一个子集进行独立检测，显示出90%的确认率。与其他方法相比，使用高分辨率寡核苷酸阵列可以提取更精确的边界信息，从而能够更准确地分析CNV和其他基因组特征之间的关系。
Recent reports indicate that copy number variations (CNVs) within the human genome contribute to nucleotide diversity to a larger extent than single nucleotide polymorphisms (SNPs). In addition, the contribution of CNVs to human disease susceptibility may be greater than previously expected, although a complete understanding of the phenotypic consequences of CNVs is incomplete. We have recently reported a comprehensive view of CNVs among 270 HapMap samples using high-density SNP genotyping arrays and BAC array CGH. In this report, we describe a novel algorithm using Affymetrix GeneChip Human Mapping 500K Early Access (500K EA) arrays that identified 1203 CNVs ranging in size from 960 bp to 3.4 Mb. The algorithm consists of three steps: (1) Intensity pre-processing to improve the resolution between pairwise comparisons by directly estimating the allele-specific affinity as well as to reduce signal noise by incorporating probe and target sequence characteristics via an improved version of the Genomic Imbalance Map (GIM) algorithm; (2) CNV extraction using an adapted SW-ARRAY procedure to automatically and robustly detect candidate CNV regions; and (3) copy number inference in which all pairwise comparisons are summarized to more precisely define CNV boundaries and accurately estimate CNV copy number. Independent testing of a subset of CNVs by quantitative PCR and mass spectrometry demonstrated a < 90% verification rate. The use of high-resolution oligonucleotide arrays relative to other methods may allow more precise boundary information to be extracted, thereby enabling a more accurate analysis of the relationship between CNVs and other genomic features.