Sharp Andrew J
Department of Genetic Medicine and Development, University of Geneva Medical School, University Medical Center (CMU), Geneva, Switzerland.
Hum Mutat. 2009 Feb;30(2):135-44. doi: 10.1002/humu.20843.
The widespread use of array-comparative genomic hybridization (array-CGH) for the detection of copy number variants (CNVs) in both research and clinical laboratories has created a renaissance in the field of molecular cytogenetics, revealing that the human genome contains both a wealth of structural polymorphism and many novel genomic disorders. A new generation of experimental platforms enable structural variants to be identified with increasing resolution, and will require the development of more sophisticated methods to assess the pathogenic significance of novel structural variants if these technologies are to be of clinical utility. Indeed, we are now entering an era in which technologies to detect CNVs have advanced much faster than our understanding of the consequences of these variants on human phenotypes, and I argue that over the last few years the problem has now become one of interpretation rather than identification. This problem is made more complex by the realization that many genomic disorders show highly variable penetrance, blurring the boundary of how to define benign vs. pathogenic variants. I discuss insights from recent research which shed light on potential mechanisms that may underlie this phenomenon, and possible methods to determine the genetic elements that are responsible for the associated phenotype. Furthermore, there is now a growing appreciation that the underlying chromosomal architecture which catalyses many genomic disorders is polymorphic within the general population, and I discuss potential mechanisms by which inversion polymorphisms might create predispositions to genomic disorders.
在研究和临床实验室中,阵列比较基因组杂交技术(array-CGH)被广泛用于检测拷贝数变异(CNV),这在分子细胞遗传学领域引发了一场复兴,揭示出人类基因组既包含丰富的结构多态性,也存在许多新型基因组疾病。新一代实验平台能够以越来越高的分辨率识别结构变异,如果这些技术要具有临床实用性,就需要开发更复杂的方法来评估新型结构变异的致病意义。事实上,我们现在正进入一个时代,检测CNV的技术发展速度远远超过我们对这些变异对人类表型影响后果的理解,我认为在过去几年里,问题已变成一个解释问题而非识别问题。认识到许多基因组疾病具有高度可变的外显率,模糊了如何定义良性与致病变异的界限,这使得这个问题更加复杂。我讨论了近期研究的见解,这些见解揭示了可能是这一现象基础的潜在机制,以及确定负责相关表型的遗传元件的可能方法。此外,现在人们越来越认识到,催化许多基因组疾病的潜在染色体结构在普通人群中是多态性的,我讨论了倒位多态性可能导致基因组疾病易感性的潜在机制。