Pinto Dalila, Marshall Christian, Feuk Lars, Scherer Stephen W
The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada.
Hum Mol Genet. 2007 Oct 15;16 Spec No. 2:R168-73. doi: 10.1093/hmg/ddm241.
Copy-number variation (CNV) is the most prevalent type of structural variation in the human genome, and contributes significantly to genetic heterogeneity. It has already been recognized that some CNVs can contribute to human phenotype, including rare genomic disorders and Mendelian diseases. Other CNVs are now amenable to genome-wide association studies so that their influence on human phenotypic diversity and disease susceptibility may soon be more readily determined. Population studies and reference databases for control and disease-associated samples are required to provide an information resource about CNV frequencies and their relative contribution to phenotypic outcomes. The relatively high cost of screening individual samples has tended to limit the number of controls assayed, and use of the data has often been hampered by the variety of technology platforms and analysis techniques. As a result, there is still a paucity of data on population frequency and distribution of CNVs, particularly for those that are rare. Here, we provide an example of how to discover new CNVs from existing genotype data from large-scale genetic epidemiological studies. We also discuss the need to expand surveys of CNV in different population-based cohorts and to apply the information to studies of human variation and disease.
拷贝数变异(CNV)是人类基因组中最普遍的结构变异类型,对遗传异质性有显著贡献。人们已经认识到,一些CNV可导致人类表型,包括罕见的基因组疾病和孟德尔疾病。现在,其他CNV也适用于全基因组关联研究,因此它们对人类表型多样性和疾病易感性的影响可能很快就能更轻易地确定。需要进行人群研究以及建立对照和疾病相关样本的参考数据库,以提供有关CNV频率及其对表型结果相对贡献的信息资源。筛查个体样本的成本相对较高,这往往限制了所检测对照的数量,而且数据的使用常常因技术平台和分析技术的多样性而受到阻碍。因此,关于CNV在人群中的频率和分布的数据仍然很少,尤其是那些罕见的CNV。在此,我们提供一个示例,说明如何从大规模遗传流行病学研究的现有基因型数据中发现新的CNV。我们还讨论了在不同的基于人群的队列中扩大CNV调查以及将这些信息应用于人类变异和疾病研究的必要性。