High Throughput Detection of Copy Number Variation

Initial analysis of the human genome suggested that SNPs, estimated to occur on average in 1 of 300 nucleotides within the human genome, were the main source of genetic and phenotypic individual variation. However, with the completion of the primary sequence of the human genome, creation of new strategies and tools for assessing genomic composition such as genome scanning technologies and comparative DNA sequence analyses revealed the large extent of DNA variation involving DNA segments smaller than those recognizable microscopically, but larger that those detected by conventional sequence analysis. These submicro-scopic variants ranged from ~1 kilobase to 3 megabases, and comprised deletions, duplications, and large-scale copy number variants. These variants are now collectively referred to as copy number variants (CNVs) or copy number polymorphisms (CNPs). Such variants in some genomic regions have no apparent phenotypic consequences, whereas others influence gene dosage, which might cause disease either alone or in combination with other genetic or environmental factors.

In 2004, two reports using genome-scanning DNA microarray technologies highlighted the widespread nature of normal CNV.209,210 Other studies have amply confirmed and extended these observations.211-213 In the initial studies, the key to the identification of the extent of variation was the use of array-based comparative genomic hybridization (array CGH). The microarray that Iafrate et al. used was a commercial BAC array with one clone about every 1 megabase across the genome, while Sebat et al. used long nucleotide arrays with an effective resolution of >90 kb. Both were of limited resolution. While advances in array technology continued to improve resolution, the use of array-CGH was found to be noisy and necessitated averaging of multiple probes to call CNVs.

Recently, Redon, Fieger, and colleagues have described a new tool for high-throughput detection of CNVs in the human genome. These investigators constructed a large-insert clone tiling path resolution DNA array covering the entire human genome,213 and used it to identify CNVs in human populations.214 The array consisted of26,574 clones selected primarily from the "Golden Path'' used to generate the reference human sequence215 covering 93.7% of euchromatic regions. They also developed an algorithm, "CVNfinder," for calling copy number changes. On using CNVfinder to detect CNVs in human populations using DNAs from the 270 cell lines extensively genotyped in the HapMap project, they found that this tool provides accurate, reliable estimates of CNV in the human genome.

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