Assessing high-resolution melt curve analysis for accurate detection of gene variants in complex DNA fragments

Abstract

Mutation detection has, until recently, relied heavily on the use of gel-based methods that can be both time consuming and difficult to design. Nongel-based systems are therefore important to increase simplicity and improve turn around time without compromising assay sensitivity and accuracy, especially in the diagnostic/ clinical setting. In this study, we assessed the latest of the nongel-based methods, namely high-resolution melt (HRM) curve analysis. HRM is a closed-tube method that incorporates a saturating dye during DNA amplification followed by a monitoring of the change in fluorescence as the DNA duplex is denatured by an increasing temperature. We assessed 10 amplicons derived from eight genes, namely SERPINA1, CXCR7, MBL, VDR, NKX3A, NPY, TP53, and HRAS using two platforms, the LightScanner s System using LC Green s PLUS DNA binding dye (Idaho Technology, Salt Lake City, UT, USA) and the LightCycler s 480 using the HRM Master dye (Roche Diagnostics, Indianapolis, IN, USA). DNA variants (mutations or polymorphims) were previously identified using denaturing gradient gel electrophoresis (DGGE) a method, similarly to HRM, based upon the different melting properties of doublestranded DNA. Fragments were selected based on variant and fragment complexity. This included the presence of multiple sequence variants, variants in alternate orientations, and single or multiple variants (constitutional or somatic) in GC-rich fragments. We demonstrate current limitations of the HRM method for the analysis of complex DNA regions and call for caution when using HRM as the sole method to make a clinical diagnosis based on genetic analysis.

High resolution melting as an alternative method to genotype diacylglycerol O-acyltransferase 1 (DGAT1) K232A polymorphism in cattle

“…HRM allows melt profiles of 96 or 384 different PCR products to be achieved in minutes, compared to at least 12 h for most gelbased methods (Tindall et al, 2009). HRM analysis has primarily been used for the discovery and genotyping of single nucleotide polymorphisms (SNPs) (Graham et al, 2005), but it has also been used for precise amplicon verification (Erali et al, 2006), sequence matching applications such as HLA identity (Zhou et al, 2004) and generating STS markers in linkage mapping studies (Croxford et al, 2008).…”

Application and Utility of Pharmacogenetics in the Clinical Laboratory

“…Changes in the shape of the melting curve profile against that of a wildtype standard can delineate wild-type from non-wild type sequences. HRM is superior to previously utilized melting curve techniques, primarily because this platform can acquire a higher density of data points per degree Celsius [104]. A more robust collection of data points allows for the detection of very small differences in melting temperature, facilitating the discrimination of a wild type from a non-wild type sequence.…”

“…Another consideration is the performance of HRM in detecting mutations in tumor material. It is now well established that the sensitivity of HRM is not suitable for detection of somatic mutations in a heavily wild type background, just as in the case of DNA extracted from tumor material [104,107]. Lastly, confirmatory testing would be required for samples that produce a mutant melting curve profile, since the variant arising within the amplicon region may not be the SNP in question.…”

Correlation between thyroglobulin gene polymorphisms and autoimmune thyroid disease

“…These methods require separate samples, enzymatic reactions and chemical reactions; these methods are complex, comprise multiple steps, and are time-consuming and challenging to perform. However, the high-resolution melting curve analysis (HRMA) method is relatively simple, fast, accurate, economical and suitable for high-throughput analysis (11)(12)(13)(14). HRMA can effectively distinguish between different alleles and genotypes at single nucleotide polymorphism (SNP) loci (13,15,16).…”

“…However, the high-resolution melting curve analysis (HRMA) method is relatively simple, fast, accurate, economical and suitable for high-throughput analysis (11)(12)(13)(14). HRMA can effectively distinguish between different alleles and genotypes at single nucleotide polymorphism (SNP) loci (13,15,16). To date, three novel methods have been developed for HRMA: The small-fragment amplification method (17), the non-labeled probe method (18) and the snapback probe primer method (19).…”