Application of High-resolution Melting to Large-scale, High-throughput SNP Genotyping: a Comparison with the TaqMan Method
Overview
Affiliations
Because of the wide use of single-nucleotide polymorphisms (SNPs) as markers of genetic variation, several high-throughput genotyping methods have been developed and applied during the past decades. High-resolution melting (HRM) is a very attractive, advanced, fast, and cost-effective SNP genotyping technology based on the analysis of the melting profile of PCR products, using intercalating fluorescent dyes to monitor the transition from unmelted to melted DNA. The authors used HRM for genotyping 215 human DNA samples for SNPs in the ABCB1, NQO1, and SLC19A1 genes and 96 samples for SNPs in the IL1A and IL12B genes with the aim of assessing HRM sensitivity and accuracy in comparisons with the TaqMan((R)) assay in view of large-scale, high-throughput SNP-typing applications. The potential effect of PCR product size, T(M), GC content, and SNP position on HRM performances was explored with amplicons that were heterogeneous for these factors. Discrimination power ranged from 91.4% to 98.4%, being significantly lower only when the number of rare homozygotes dropped to 1 or few units. The availability of specific and validated assays, in addition to a better standardization of HRM experimental conditions, can considerably reduce time and costs of large-scale genotyping studies with a negligible risk of failure or misclassification.
Statistical methods for discrimination of STR genotypes using high resolution melt curve data.
Cloudy D, Boone E, Kuehnert K, Smith C, Cox J, J Seashols-Williams S Int J Legal Med. 2024; 138(6):2281-2288.
PMID: 38997516 PMC: 11490427. DOI: 10.1007/s00414-024-03289-x.
Universal probe-based intermediate primer-triggered qPCR (UPIP-qPCR) for SNP genotyping.
Li B, Liu Y, Hao X, Dong J, Chen L, Li H BMC Genomics. 2021; 22(1):850.
PMID: 34819030 PMC: 8611915. DOI: 10.1186/s12864-021-08148-2.
Robinson C, Garcia de Leaniz C, Consuegra S Sci Rep. 2019; 9(1):7230.
PMID: 31076591 PMC: 6510734. DOI: 10.1038/s41598-019-43570-3.
You Q, Yang X, Peng Z, Xu L, Wang J Front Plant Sci. 2018; 9:104.
PMID: 29467780 PMC: 5808122. DOI: 10.3389/fpls.2018.00104.
Slomka M, Sobalska-Kwapis M, Wachulec M, Bartosz G, Strapagiel D Int J Mol Sci. 2017; 18(11).
PMID: 29099791 PMC: 5713285. DOI: 10.3390/ijms18112316.