Between missing chunks of chromosomes and single nucleotide polymorphisms (SNPs) lies a vast middle ground of genomic alterations. Among these are copynumber variations (CNVs) - the differences between individuals in the number of copies of a genomic region. "The total nucleotide content that is encompassed by CNVs most certainly exceeds that of SNPs," says Stephen Scherer of The Hospital for Sick Children in Toronto.

The recent surge of interest in CNVs has induced a proliferation of technologies designed to detect them in normal DNA, congenital diseases, and cancer cells, in which copynumber changes may induce their unruly divisions.

Scientists have largely turned to comparative genomic hybridization (CGH) arrays, which involve hybridizing two genomes - one as a reference and one to be tested...

<figcaption> Credit: Redrawn from WTCHG</figcaption>
Credit: Redrawn from WTCHG


User: Yao-Shan Fan, University of Miami

The project: Detecting pathogenic gene CNVs in patients with unexplained mental retardation.

The problem: Fan needs to detect CNVs associated with a disorder without overwhelming his detections with normal variations that occur in everyone.

The solution: Oligonucleotide arrays, which provide poorer signal-to-noise ratios than large-insert clones such as BACs but dense genome coverage, have just the right level of specificity and resolution for this type of project, Fan says. He uses the Agilent platform, which covers the whole human genome with 44,000 probes. Detecting normal CNVs in healthy individuals might work with an SNP array because of its superior resolution, Fan says, but that isn't desirable for his studies. "If you use the array with a very high resolution, then you see a lot of normal variations, and it's hard to pick up the pathogenic one," he says. Traditional BAC arrays, on the other hand, have resolutions that are too low for his purposes.

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