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Population Analysis of Large Copy Number Variants and Hotspots of Human Genetic Disease

机译:人类遗传疾病大拷贝数变异和热点的种群分析

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摘要

Copy number variants (CNVs) contribute to human genetic and phenotypic diversity. However, the distribution of larger CNVs in the general population remains largely unexplored. We identify large variants in ∼2500 individuals by using Illumina SNP data, with an emphasis on “hotspots” prone to recurrent mutations. We find variants larger than 500 kb in 5%–10% of individuals and variants greater than 1 Mb in 1%–2%. In contrast to previous studies, we find limited evidence for stratification of CNVs in geographically distinct human populations. Importantly, our sample size permits a robust distinction between truly rare and polymorphic but low-frequency copy number variation. We find that a significant fraction of individual CNVs larger than 100 kb are rare and that both gene density and size are strongly anticorrelated with allele frequency. Thus, although large CNVs commonly exist in normal individuals, which suggests that size alone can not be used as a predictor of pathogenicity, such variation is generally deleterious. Considering these observations, we combine our data with published CNVs from more than 12,000 individuals contrasting control and neurological disease collections. This analysis identifies known disease loci and highlights additional CNVs (e.g., 3q29, 16p12, and 15q25.2) for further investigation. This study provides one of the first analyses of large, rare (0.1%–1%) CNVs in the general population, with insights relevant to future analyses of genetic disease.
机译:拷贝数变异(CNV)有助于人类遗传和表型多样性。但是,较大的CNV在一般人群中的分布仍未得到充分开发。我们使用Illumina的SNP数据在大约2500个个体中识别出大的变异,重点是易于重复突变的“热点”。我们发现5%–10%的个体中的变异大于500 kb,而1%–2%的变异大于1 Mb。与以前的研究相比,我们发现在地理上不同的人群中CNV分层的证据有限。重要的是,我们的样本量允许在真正稀有和多态但低频拷贝数变异之间进行强有力的区分。我们发现单个CNV的很大一部分大于100 kb是罕见的,并且基因密度和大小都与等位基因频率高度抗相关。因此,尽管正常个体中通常存在大的CNV,这表明不能单独使用大小来预测致病性,但这种变异通常是有害的。考虑到这些观察结果,我们将我们的数据与来自12,000多个对照和神经系统疾病对照的个人发表的CNV相结合。该分析可识别已知的疾病位点,并突出显示其他CNV(例如3q29、16p12和15q25.2)以供进一步研究。这项研究提供了对普通人群中大型,罕见(0.1%–1%)CNV的首批分析之一,并提供了与未来遗传疾病分析相关的见解。

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