Microarray CGH is a molecular cytogenetic method used to detect copy number variations (CNVs) in the DNA of a test sample relative to a reference sample. CNVs include deletions, duplications, and other changes in the number of copies of DNA segments. These variations can have significant implications for health and disease, influencing everything from cancer progression to developmental disorders.
The Basics of Microarray CGH
The technique involves the following key steps:
DNA Extraction: DNA is extracted from both the test sample (e.g., a patient’s tissue) and a reference sample (often normal DNA).
Labeling: The DNA from both samples is labeled with different fluorescent dyes, typically green for the test sample and red for the reference sample.
Hybridization: The labeled DNA samples are mixed and co-hybridized onto a microarray chip. The chip contains thousands of DNA probes that correspond to specific regions of the genome.
Scanning and Analysis: After hybridization, the microarray is scanned to measure the intensity of the fluorescent signals. The ratio of green to red fluorescence at each probe indicates the relative copy number of the DNA segments in the test sample compared to the reference.
Advantages of Microarray CGH
Microarray CGH offers several advantages over traditional karyotyping and fluorescence in situ hybridization (FISH):
Higher Resolution: Microarray CGH can detect small CNVs that are missed by karyotyping, which typically identifies changes larger than 5-10 Mb.
Genome-Wide Analysis: Unlike FISH, which targets specific regions, microarray CGH provides a comprehensive analysis of the entire genome.
Quantitative Data: The technique provides quantitative data on copy number changes, allowing for precise measurement of duplications and deletions.
Speed and Efficiency: The process is relatively quick and can be automated, making it suitable for high-throughput analysis.
Applications of Microarray CGH
The versatility of microarray CGH has led to its adoption in various areas of genetics and medicine. Here are some key applications:
1. Cancer Research and Diagnosis
Cancer is often driven by genetic alterations, including CNVs that lead to oncogene amplification or tumor suppressor gene deletion. Microarray CGH is widely used to identify these alterations, providing valuable insights into tumorigenesis and helping to tailor personalized treatment strategies.
2. Prenatal and Postnatal Diagnostics
Microarray CGH has become a standard tool in prenatal and postnatal diagnostics for detecting chromosomal abnormalities. It can identify CNVs associated with developmental disorders, intellectual disabilities, and congenital anomalies more accurately.
3. Rare Genetic Disorders
Many rare genetic disorders are caused by CNVs that affect specific genes or genomic regions. Microarray CGH is instrumental in diagnosing these conditions, facilitating early intervention and genetic counseling.
4. Research on Genetic Variation
Researchers use microarray CGH to study genetic variation in populations, shedding light on evolutionary processes and identifying genetic factors that contribute to disease susceptibility and other traits.
Case Study
A child presents with developmental delays and physical abnormalities, but standard genetic tests, including karyotyping, reveal no abnormalities. The clinician orders a microarray CGH test, which detects a small deletion in a region of chromosome 16 known to be associated with developmental delay and intellectual disability. This information not only provides a definitive diagnosis but also guides the management plan and informs the parents about the recurrence risk in future pregnancies.
Challenges and Limitations
Despite its many advantages, microarray CGH faces challenges in the interpretation of CNV variants, resolution limitations, and expertise to analyze the data.
The above challenges can be overcome by:
1. Integration with Next-Generation Sequencing (NGS)
Combining microarray CGH with NGS to enhance the resolution and accuracy of CNV detection.
2. Improved Databases and Algorithms
Efforts to improve databases of known CNVs and develop more sophisticated algorithms for data interpretation will help clinicians make more accurate and clinically relevant diagnoses.
3. Increased Accessibility
Technological advancements and cost reductions will likely make microarray CGH more accessible, extending its benefits to a broader range of patients and populations.
-Written by Sohni Tagore
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