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Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis
Published on: August 26, 2020
Identifying functional genetic variants in DNA repair pathway using protein conservation analysis
Sevtap Savas1, David Y Kim, M Farhan Ahmad
1Fred A. Litwin Centre for Cancer Genetics, Mount Sinai Hospital, Samuel Lunenfeld Research Institute, 600 University Avenue Room 992A, Toronto, ON M5G 1X5, Canada.
Genetic variations in DNA repair genes, specifically non-synonymous single nucleotide polymorphisms (nsSNPs), can significantly impact cancer risk. Our study identified numerous nsSNPs likely to alter DNA repair protein function, aiding in cancer predisposition research.
Area of Science:
- Genetics
- Molecular Biology
- Cancer Research
Background:
- DNA repair mechanisms are crucial in preventing malignancy.
- Genetic variations, particularly single nucleotide polymorphisms (SNPs), in DNA repair genes are linked to altered cancer risk.
- Non-synonymous SNPs (nsSNPs) can change protein function and are potential determinants of genetic disease.
Purpose of the Study:
- To analyze non-synonymous single nucleotide polymorphisms (nsSNPs) in 88 DNA repair genes.
- To functionally evaluate these nsSNPs based on amino acid conservation within protein families.
- To identify functional nsSNPs associated with cancer predisposition.
Main Methods:
- Analysis of nsSNPs across 88 DNA repair genes.
- Functional evaluation of nsSNPs using amino acid conservation across protein families.
- Correlation of predicted functional nsSNPs with existing cancer risk data.
Main Results:
- >30% of analyzed DNA repair protein variants are predicted to significantly affect protein function.
- Three specific nsSNPs (XRCC1-R399Q, XRCC3-T241M, XRCC1-R280H) predicted to be functional were previously associated with cancer risk.
- The study provides a strategy for identifying functional nsSNPs in DNA repair pathways.
Conclusions:
- A significant proportion of nsSNPs in DNA repair genes likely impair protein function.
- Functional nsSNPs identified through this method show potential associations with cancer predisposition.
- This approach can help pinpoint specific genetic variants contributing to cancer risk.
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