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Copy Number Variation (CNV) Analysis:
New Approach for Population Genetics and Disease Association Study
Traditionally, large-scale genomic variants visible in conventional karyotyping have been thought to be associated with early-onset, highly penetrant genetic disorders while incompatible with normal, disease-free phenotypes. This traditional concept has been recently challenged by the discovery that large structural variations are more prevalent than previously presumed. Using high-resolution whole genome scanning technologies such as array-based comparative genomic hybridization (array-CGH), two pioneering groups of scientists (Iafrate et al Nat Genet 2004; Sebat et al Science 2004) have identified widespread copy number variation (CNV) in apparently healthy, normal individuals proposing that our genome is more diverse than ever recognized. More than 11 thousand CNVs have been cataloged so far and investigated for their contribution to biological phenomenon such as individual heterogeneity, disease susceptibility etc.
The large-scale structural variants in addition to SNP have served as powerful sources for the understanding of human genetic variation and association studies for disease phenotypes. The current coverage of CNVs in the human genome already exceeded that of SNPs (approximately 600 Mb comprising ~12% of human genome) and is still increasing. Although it is unlikely that all CNVs in the human genome are associated with diseases, evidence of the association of CNVs and a wide spectrum of human diseases has rapidly accumulated. CNVs can affect disease susceptibility or individual differences in responses to drugs through alteration of gene expression. To get valid results from disease-association studies, knowledge about prevalence of normal CNVs in representative population is absolutely crucial. We are constructing normal CNV database derived from Asian population using Agilent Technologies Human Whole genome CNV microarray. Totally 120 phenotypically normal asian individuals have been collected and analyzed. Data processing and detection of CNVs will be performed using Agilent copy number analysis software. The identified CNVRs will be compared with the Database of Genomic Variants.
This Asian normal CNV database can facilitate CNV-disease association studies and pharmacogenomics studies in Asian population. In addition, this project provides an important opportunity to build more efficient CNV research network among Asian scientists and to arouse important stakeholders to take an action. | 
