Comparative genomic hybridization (CGH) is a method for detecting copy-number polymorphisms and chromosomal imbalances in the genome. It is estimated that as many as 5–6% of inherited disorders caused by gene mutations are due to changes in the copy number of the gene. Early CGH was carried out using a single test and a single reference probe competitively hybridized onto metaphase chromosomes. The relative fluorescence of the test and reference DNA were then plotted for each chromosome to determine copy number changes. This method had some drawbacks including spatial resolution limited to 5–15 megabases (Mb) and a technically difficult protocol.

Sequencing of the human genome allowed CGH to be updated by replacing metaphase chromosomes with arrayed DNA fragments. Array CGH led to increased resolutions and made it possible to detect micro-rearrangements of the chromosomes. In array CGH, instead of metaphase chromosomes, oligonucleotides are arrayed on a glass slide. The size of the oligonucleotide probes can range in size from a very short 25 base pair chain to large bacterial artificial chromosomes up to 200,000 base pairs. The resolution of the array is based on the size of the probes and the genomic distance between the probes. Resolutions of microarray CGH are about tenfold greater than CGH using metaphase chromosomes.1

Resolutions of microarray CGH are about tenfold greater than CGH using metaphase chromosomes.

Array CGH has become a standard method in human genetics for research and clinical diagnostic applications. The typical protocol for array CGH starts with extracting DNA from a sample and labeling it with a fluorescent dye. A control DNA sample is labeled with a different color fluorescent dye. The two samples are combined and applied to the microarray, and the fluorescence intensities of the hybridized samples are compared to give the copy number of genes in the test genome compared to a normal genome.2

Choosing CGH

CGH is an established technology with fully validated protocols, so implementing the technology in the lab is straightforward. CGH microarrays provide excellent copy number results for different throughput requirements depending on the experimental plan and number of samples, allowing researchers to maximize time to results and cost per sample. Unlike gene expression arrays, CGH array experiments can provide a result from a single sample.

According to Heidi Kijenski, director of clinical marketing for Agilent Technologies, and Valentina Maran, global product manager of Cytogenetics for Agilent, certain preliminary questions can drive the choice toward CGH microarray over other technologies. Those include:

1. What type of information is required from the experiment?

2. Is my primary interest copy number and absence of heterozygosity (AOH)?

3. What type of sample will be used? Fresh, frozen, FFPE or degraded DNA?

“If copy-number variation and AOH are the primary goal of the study, then a CGH microarray is the best choice of technology as it provides excellent genome-wide copy number analysis, with a fast protocol and excellent price per sample,” said Kijenski and Maran. As well, CGH microarray can interrogate known genomes at resolutions ranging from whole chromosome to single exons. The type and quality of the sample should be taken into consideration when designing the experiment.

CGH works with DNA, while other microarray applications are more focused on RNA (mRNA, lincRNA and miRNA) so it has been necessary to develop specific labeling protocols. Agilent has developed two different kits based on DNA quality: an enzymatic labeling kit called SureTag, for fresh/frozen tissues; and a non-enzymatic labeling, ULS lablling kit, developed specifically for FFPE or degraded DNA.

Enzo Life Sciences product manager Nadia Rana also emphasized the importance of labeling in a CGH workflow. ““Effective dye incorporation and high specific activity are key to achieving low DLR scores and obtaining unambiguous results. If the label-incorporation is not high, it can result in ambiguous results, false positives and more failed runs. This is problematic for both clinical and research labs, especially when samples are precious and of limited quantity, and because each extra run is an added expense,” Rana said.

According to Rana, FFPE samples are some of the most difficult samples to handle in a microarray CGH workflow. Being embedded in paraffin makes it more difficult to extract DNA in enough quantity for a microarray study. That challenge was a driver for the development of a CGH labeling kit by Enzo specifically designed for challenging samples (CYTAG CGH Labeling kit). A study by Memorial Sloan Kettering and Cancer Genetics reportedly showed that the CYTAG CGH labeling kit is capable of handling challenging samples with better DLR scores than competitors.

Preconception screening

Using microarrays, CGH can detect a range of abnormalities including deletions, duplications, aneuploidy, duplications or amplifications of genes. Subtelomeric and pericentromeric rearrangements cause a number of birth defects and inherited syndromes. Subtelomeric rearrangements are thought to cause a large proportion of cases of idiopathic mental retardation. Array CGH has proven to be a powerful method for investigating these types of abnormalities, with more accurate and detailed results than fluorescence in situ hybridization (FISH).

The potential for detecting and preventing birth defects has spurred interest in microarray technology for preconception screening. Thermo Fisher Scientific recently announced a new assay product called CarrierScan Assay designed to detect more than 6,000 genomic variants associated with inherited disease.

The potential for detecting and preventing birth defects has spurred interest in microarray technology for preconception screening.

Typical carrier screening for hereditary disease requires multiple assays and platforms, and usually only focuses on the most serious abnormalities. CarrierScan can detect more than 6,000 mutations, and is customizable for the set of mutations that is of interest to the user of the array.

Doron Behar, CSO of Gene by Gene, worked with Thermo Fisher to develop CarrierScan. According to Behar, expanded preconception screening is “one of the most immediate applications that can come out of looking at the genome.”

Behar said that compared to technologies like whole-genome sequencing, microarray screening is much more affordable and has potential to be applied routinely to entire populations. “Array technology is more cost-effective than other technologies when discussing the need to screen thousands of well-defined mutations,” Behar added.

Plant genome research

Understanding copy number variation in plant genomics has economic value for the agricultural industry. In one study of grape genomes, researchers used Agilent’s CGH customization capabilities to identify CNVs in grapevines, creating an inter-varietal atlas of four types of grapevines based on structural variations and single nucleotide variants (SNVs). The group found 4.8 million SNVs, and found that 8% of the grapevine genome was affected by genomic variations. There were 700 regions with copy number variations affecting more than 2,000 genes that were candidates for phenotypic variations between varieties.3

Cancer research

Copy number variations can be very significant in cancer. Genomic and proteomic tests are widely used to diagnose, choose therapies, and determine prognosis. Genome-wide analysis can provide enhanced information about tumor origins for clinical or research use.

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Christopher Krebs is the manager of the microarray group at the University of Michigan’s DNA Sequencing Core. His group uses the OncoScan CGH microarray assay by Affymetrix (a part of Thermo Fisher Scientific) for research screening of tumor tissues. The OncoScan FFPE Assay Kit is designed for genome-wide copy number and loss-of-heterozygosity (LOH) profiles for about 900 cancer genes, as well as status of frequently tested somatic mutations using as little as 80 ng of FFPE-derived DNA. “It’s designed to be very comprehensive,” he explained.

Microarray CGH is a mature technology widely used in life science research and advancing toward clinical diagnostic use in many areas of medicine, bringing us one step closer to personalized medicine. Advances in array CGH are centered on improving results with difficult and low concentration DNA samples, including FFPE samples or low input samples such as amniotic fluid.

References

1. Redon, R., & Carter, N. (2009). Comparative Genomic Hybridization: microarray design and data interpretation. Methods Mol. Bio.,529, 37-49. [PMID: 19381971] 

2. Theisen, A. (2008). Microarray-based Comparative Genomic Hybridization (aCGH). Nature Education,1(1), 45-45

3. Cardone, M. F., D'addabbo, P., Alkan, C., Bergamini, C., Catacchio, C. R., Anaclerio, F., . . . Antonacci, D. (2016). Inter-varietal structural variation in grapevine genomes. The Plant Journal,88(4), 648-661. [PMID: 27419916] 

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