Array comparative genomic hybridization

Array comparative genomic hybridization

Array comparative genomic hybridization (also CMA, Chromosomal Microarray Analyisis, Microarray-based comparative genomic hybridization, array CGH, a-CGH, or aCGH) detects genomic copy number variations at a higher resolution level than chromosome-based comparative genomic hybridization (CGH).


DNA from a tumor sample and normal reference sample are labelled differentially, using different fluorophores, and hybridized to several thousand probes. The probes are derived from most of the known genes and non-coding regions of the genome, printed on a glass slide.

The ratio of the fluorescence intensity of the tumor to that of the reference DNA is then calculated, to measure the copy number changes for a particular location in the genome.


Using this method, copy number changes at a level of 5-10 kilobases of DNA sequences can be detected. This method allows one to identify new recurrent chromosome changes such as

in disease conditions such as cancer and birth defects due to chromosome microdeletions.

Technical considerations

There are several requirements that are dependent on the application of aCGH:

  • Complexity. Measurement becomes difficult in larger organisms because of decreasing partial concentrations of each portion of the sequence that is involved in the hybridization to the array element as the size of the genomes increase. This issue may be addressed by increasing the threshold in which one detects only larger increases in copy number of DNA extracted from cells, but this comes at the cost of increasing failure to detect low level gains and losses.
  • Samples. Tissue specimens may contain heterogeneous cell populations, which may further decrease the ability to detect copy number change in genes in the aberrant tumor cells because the population may contain normal cells. Furthermore, the use of tissue from clinical specimens severely limit the amount of DNA available for analysis.
  • Error tolerance. If the investigator is set to obtain a generalized description of aberrations that may occur in a set of samples, then errors in the detection may not be critical. However, the margin for error is drastically narrowed in a clinical setting, where an individual specimen is used to obtain specific information.

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