Searching for mutations : familial adenomatous polyposis as a case study.
1Colorectal Cancer Unit, Imperial Cancer Research Fund, St. Mark's Hospital, Middlesex, UK.
Methods in Molecular Medicine
|March 5, 2011
Summary
Choosing the right genetic mutation detection method involves balancing efficiency, cost, and disease-specific factors. Single-stranded conformational polymorphism (SSCP) is a common technique, but the optimal choice depends on various laboratory and clinical considerations.
Area of Science:
- Genetics
- Molecular Biology
- Medical Diagnostics
Background:
- Molecular diagnosis of genetic diseases traditionally relies on marker linkage.
- Identifying the specific mutation is generally preferred over linkage analysis.
- Numerous mutation detection techniques exist, each with varying efficiencies and applications.
Purpose of the Study:
- To review the diverse methods available for detecting gene mutations.
- To discuss the factors influencing the selection of mutation detection techniques.
- To illustrate these considerations using the molecular diagnosis of familial adenomatous polyposis (FAP).
Main Methods:
- Overview of mutation detection techniques, including single-stranded conformational polymorphism (SSCP).
- Analysis of factors influencing method choice: efficiency, reproducibility, ease, speed, cost, and available resources.
- Consideration of disease- and gene-specific factors: gene size, mutation hotspots, population frequency, mutation type, and new mutation rates.
- Evaluation of sample material types (DNA, cell lines, tissue) and their impact on diagnosis.
Main Results:
- No single mutation detection method is universally predominant; SSCP is widely used.
- Method selection is a complex decision based on a combination of technical, economic, and logistical factors.
- Disease-specific characteristics and sample availability significantly influence diagnostic strategy.
Conclusions:
- The choice of mutation detection method requires a comprehensive assessment of multiple variables.
- Cost-benefit analysis is crucial, especially for clinical service laboratories.
- Understanding these factors is essential for accurate and efficient molecular diagnosis of genetic disorders like FAP.
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