Comparative Genomic Hybridization (CGH) is a powerful technique employed in modern genomics to detect chromosomal gains and losses across the whole genome.
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Introduction
CGH serves as a critical tool for uncovering various types of genomic variations, such as deletions and duplications. These variations can significantly impact gene function and are often associated with disease states, cancer development, and evolutionary divergence.
The significance of CGH lies in its ability to provide a genome-wide view of these variations. Unlike traditional methods focusing on specific genes, CHG allows researchers to scan the entire genome simultaneously, offering a comprehensive picture of such chromosomal imbalances.
What is Genomics?
Foundations of CGH
Comparative genomic hybridization (CGH) is a powerful tool for spotting changes in a sample's DNA amount.
It works by taking DNA from a test sample and healthy control, labelling them with different colored fluorescent dyes (often cyanine 3, green, and cyanine 5, red), and then letting them "stick" together (hybridize) to normal chromosomes.
By looking at the colors under a microscope, scientists can see if there's an imbalance in the DNA, revealing areas with missing or extra copies1,2.
CGH facilitates the detection of gross chromosomal aberrations in cells without requiring cell culture. In this regard, differentially labelled and reference DNA undergo co-hybridization to normal human metaphase chromosomes.
Each sample is marked with distinct fluorescent probes of contrasting colors. Deviations in the fluorescence intensity ratios serve as an indicator of DNA copy number variations along chromosome 3.
Applications of CGH
CGH offers multiple advantages in diverse biological and medical fields:
Clinical Diagnostics
In clinical settings, CGH is used to identify chromosomal abnormalities in patients with developmental issues, intellectual disabilities, and congenital disabilities.
By pinpointing deletions or duplications in specific chromosomal regions, CGH can aid in diagnosing genetic disorders and guiding patient management.
Cancer Research
Extensive chromosomal rearrangements often characterize cancer. CGH plays a crucial role in cancer research by identifying these rearrangements, which can lead to the activation of oncogenes or the inactivation of tumor suppressor genes.
Understanding these genomic alterations is essential for developing targeted cancer therapies.
Evolutionary Biology
In comparative genomics, CGH may potentially help to discover genes that are shared across different species (conserved) and those that contribute to each organism's distinctive features (unique characteristics).
This information may be valuable for understanding the processes of adaptation and speciation.
Learn more about Genetics and Genomics
Advantages of CGH
CGH has several key strengths that make it a valuable tool in modern genomics
Genome-wide Coverage
Unlike techniques like FISH (Fluorescence In Situ Hybridization) that target specific regions, CGH offers a genome-wide analysis. This allows researchers to identify copy number variations (CNVs) across the entire DNA landscape, potentially uncovering unexpected abnormalities.
High resolution (aCGH)
While conventional CGH has limitations in resolution, the advancement to array-based CGH (aCGH) significantly improves this aspect. aCGH offers a whole-genome view, making it a powerful tool for identifying large chromosomal imbalances.
This includes abnormalities like extra or missing chromosomes (aneuploidies), as well as insertions and deletions of genetic material4.
Moreover, this technique (CGH) exhibits some strengths compared to fluorescence in situ hybridization (FISH): while FISH offers excellent spatial resolution for pinpointing specific chromosomal regions, it requires prior knowledge of the suspected abnormality and is limited in its ability to scan the entire genome.
Limitations of CGH
CGH excels at identifying copy number variations (CNVs) but struggles to detect smaller mutations like single nucleotide polymorphisms (SNPs) or balanced chromosomal rearrangements (inversions, translocations) that don't involve copy number changes.
Moreover, CGH may not be sensitive enough to detect mosaicism, where only a portion of cells have the abnormality, although aCGH may be more likely to detect mosaicism for unbalanced chromosome abnormalities than traditional cytogenetic procedures5.
It is also important to highlight that regions with highly repetitive DNA sequences can be problematic for CGH analysis, as they can interfere with accurate hybridization.
Finally, it is also worth noting that CGH data analysis requires expertise to distinguish true variations from technical artifacts.
Recent Advances and Future Directions
The field of CGH is constantly evolving, focusing on enhancing resolution and expanding capabilities. High-resolution CGH techniques, like array-based CGH (aCGH) with ever-increasing probe densities, are allowing researchers to detect copy number variations (CNVs) at high resolution.
Technological innovations like single-cell CGH are pushing the boundaries further, enabling the analysis of CNVs within individual cells providing crucial insights into cellular heterogeneity and mosaicism.
Ongoing research and development are exploring exciting possibilities. Next-generation sequencing (NGS) data integration with CGH is being explored to provide a more comprehensive picture of genomic alterations6.
Additionally, the development of targeted CGH probes holds promise for focusing on specific regions of interest, increasing sensitivity and specificity for particular clinical applications or research questions.
Conclusion
CGH has become a cornerstone technology in modern genomics, offering a powerful tool to analyze copy number variations (CNVs) across the entire genome.
This genome-wide approach has revolutionized diagnostics, enabling the identification of chromosomal abnormalities in developmental disorders and guiding patient management.
In cancer research, CGH unveils the genomic landscape of tumors, pinpointing critical rearrangements that drive cancer development. Advancements like aCGH have significantly improved resolution, while ongoing research explores integration with next-generation sequencing and targeted probes.
Continued innovation in CGH holds immense potential for personalized medicine, deeper insights into cancer biology, and even unraveling evolutionary patterns.
References
- Ahmad, E., Ali, A., Sharma, A. K., Kumar, A., Dar, G. M., Sattar, R. S. A., ... & Saluja, S. S. (2022). Molecular markers in cancer. Clinica Chimica Acta, 532, 95-114. https://pubmed.ncbi.nlm.nih.gov/35667477/
- Ahmad, E., Ali, A., Sharma, A. K., Ahmed, F., Dar, G. M., Singh, A. M., ... & Saluja, S. S. (2022). Molecular approaches in cancer. Clinica Chimica Acta, 537, 60-73. https://pubmed.ncbi.nlm.nih.gov/36244434/
- Zhang, J., Chen, K., & Fan, Z. H. (2016). Circulating tumor cell isolation and analysis. Advances in clinical chemistry, 75, 1-31. https://pubmed.ncbi.nlm.nih.gov/27346614/
- Jennings, R. (2019). Development and application of mammalian molecular cytogenetic tools for genome reconstruction, evolution and reproductive screening. University of Kent (United Kingdom). https://kar.kent.ac.uk/82794/
- Ballif, B. C., Rorem, E. A., Sundin, K., Lincicum, M., Gaskin, S., Coppinger, J., ... & Bejjani, B. A. (2006). Detection of low‐level mosaicism by array CGH in routine diagnostic specimens. American journal of medical genetics Part A, 140(24), 2757-2767. https://onlinelibrary.wiley.com/doi/abs/10.1002/ajmg.a.31539
- Heitzer, E., Auer, M., Gasch, C., Pichler, M., Ulz, P., Hoffmann, E. M., ... & Speicher, M. R. (2013). Complex tumor genomes inferred from single circulating tumor cells by array-CGH and next-generation sequencing. Cancer research, 73(10), 2965-2975. https://aacrjournals.org/cancerres/article/73/10/2965/584240/Complex-Tumor-Genomes-Inferred-from-Single
Further Reading