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Development of High-resolution Melting Assays for the Detection of Single Nucleotide Polymorphisms in Iron-related Genes: The Food and Nutrition Research Institute’s Nutritional Genomics Laboratory Experience

Vanessa Joy A. Timoteo1,3*, Jacus S. Nacis1, Rod Erick L. Agarrado1,
Marietta P. Rodriguez1*, Leslie Michelle M. Dalmacio2, and Mario V. Capanzana1

1Food and Nutrition Research Institute, Department of Science and Technology,
DOST Complex, Bicutan, Taguig City 1631 Philippines
2Department of Biochemistry and Molecular Biology, College of Medicine,
University of the Philippines, 547 Pedro Gil St., Ermita, Manila 1000 Philippines
3Taiwan International Graduate Program in Molecular Medicine,
National Yang-Ming University and Institute of Biomedical Sciences, Academia Sinica,
No. 128, Sec. 2, Academia Rd., Nangang District, Taipei City 115 Taiwan (R.O.C.)

 

*Corresponding Author: This email address is being protected from spambots. You need JavaScript enabled to view it.
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ABSTRACT

Cost-effective and high-throughput genotyping assays will enable the routine detection of single nucleotide polymorphisms (SNPs) in iron-related genes in the Philippines, where anemia due to iron deficiency remains a public health concern throughout the years. This paper presents the development of high-resolution melting (HRM) assays that were able to identify SNPs in HFE or homeostatic iron regulator gene (rs1800562, rs1799945); TF or transferrin gene (rs3811647, rs1799852); and TMPRSS6 or transmembrane serine protease 6 gene (rs4820268) in the Nutritional Genomics Laboratory of the Department of Science and Technology – Food and Nutrition Research Institute (DOST-FNRI NuGen Lab). Genomic DNA was extracted from 112 peripheral blood samples and SNP-genotyped using the Precision Melt Analysis™ Software of Bio-Rad CFX96™ Real-Time PCR (polymerase chain reaction) Detection System. Real-time amplification reactions were evaluated in terms of varying conditions in annealing temperature (Ta) and number of amplification cycles. HRM assays were then compared against that of the gold-standard sequencing technique using the validation parameters: sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The ideal parameters of HRM assays that can genotype the target SNPs were determined. Genotype discrimination resulted in three genotypes of TF rs3811647, TF rs1799852, and TMPRSS6 rs4820268 with varying frequencies among samples used. Two genotypes were detected for HFE rs1799945, while only one genotype was obtained for HFE rs1800562. The confidence of genotype clusterings were at least 95%. All assays had 100% concordance with the sequencing results except for the TMPRSS6 rs4820268 assay, which achieved a sensitivity of 97%. Therefore, in line with the establishment of the DOST-FNRI NuGen Lab, HRM assays can be considered a reliable and affordable alternative to sequencing. Identifying genetically high-risk Filipinos in the diagnosis of anemia due to iron deficiency may be facilitated in the future.

 

 

INTRODUCTION

HRM is a post-amplification technique that allows for the genotyping and screening of genetic variants based on the characteristic melting points and profiles of DNA amplicons (Reed et al. 2007). Such melting profiles depend mainly on amplicon length, sequence covering the target loci and its guanine-cytosine (GC) content, and heterozygosity of a particular genetic marker locus. In essence, HRM analysis works by monitoring in real-time the fluorescence levels of a saturating DNA-binding dye (i.e., SYBR® Green Dye) during amplification followed by the generation of melting curves of fluorescence data against time (Erali et al. 2008). Compared to other polymerase chain reaction-based genotyping techniques such as restriction fragment length polymorphism, HRM is considered advantageous because it is simple, rapid, cost-effective, efficient, and can be high-throughput depending on the number of samples to be analyzed (Wittwer 2009). Current applications of HRM analysis among others include the genotyping of SNPs (i.e., variations in single base pairs that are being linked to disease phenotypes, personalized drug responses, etc.); assessment of DNA methylation (i.e., attachment of methyl groups to DNA bases that turns genes on or off and alters gene expression); and analysis of copy number variants or CNVs (i.e., varying number of copies of a particular gene among individuals) (Reed and Wittwer 2004, Wojdacz and Dobrovic 2007, Bruder et al. 2008). . . . read more

 


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