Copy number variation (CNV) is defined as a modification in the genome where the number of copies of a genomic DNA sequence differs from a reference or standard. Genomic alterations such as insertions, deletions, inversions, or translocation can lead to biallelic or multiallelic CNVs. CNVs are linked to susceptibility or resistance to disease, and thus are a critical area for detailed study. Many methods of CNV detection exist today, including fluorescent in situ hybridization (FISH), comparative genomic hybridization (CGH), array comparative genomic hybridization (aCGH), real-time PCR (qPCR), and next-generation sequencing (NGS).
Despite advances in some of these technologies, in many cases, measurements are not sufficiently precise for determining copy number differences where the ratios between the target and reference are very small. The advent of digital PCR (dPCR) now enables high-resolution determination of CNV through the accurate detection and quantification of low percent copy number differences.
By compartmentalizing PCR reactions into over 20,000 microchambers, digital PCR can easily detect small fold changes in CNV, for example from five to six copies, through counting the number of positive and negative reactions. This allows absolute quantification without the need for standard curves, even for small-fold changes.
This is especially critical for oncology research, where current data show that an increase in the copy number of oncogenes or high levels of somatic mosaicism can lead to aggressive cancers. It has also been suggested that CNV plays a role in different neurological diseases, with research happening to better understand their role in autism spectrum disorders, schizophrenia, attention deficit disorder, and spinal muscular atrophy. CNV may even be linked to how plants respond to stress and determine flowering time among other plant physiological responses.
1. How does dPCR compare to other methods for copy number variation (CNV) analysis, such as qPCR or microarray?
Answer: dPCR can provide highly accurate and precise CNV analysis, with lower variability and higher resolution than for small fold changes compared to qPCR or microarray methods.
2. What are the advantages of using dPCR for CNV analysis?
Answer: dPCR can provide absolute quantification of target DNA, enabling accurate and precise CNV analysis for multiple targets in a single reaction. dPCR has extremely high sensitivity requiring very little DNA input making it suitable CNVs for low concentration, rare or otherwise precious DNA samples.
3. How can dPCR be used for CNV analysis in cancer research?
Answer: dPCR can provide high sensitivity and accuracy for detecting low-level CNVs and can be used to monitor CNV changes over time while studying cancer progression or exploring treatment. However, the complex genetic heterogeneity of tumors can make CNV analysis challenging, and careful assay design and analytical evaluation is important to help ensure accurate and reliable results.