Abstract
BackgroundSingle nucleotide polymorphisms (SNP) have proven to be powerful genetic markers for genetic applications in medicine, life science and agriculture. A variety of methods exist for SNP detection but few can quantify SNP frequencies when the mutated DNA molecules correspond to a small fraction of the wild-type DNA. Furthermore, there is no generally accepted gold standard for SNP quantification, and, in general, currently applied methods give inconsistent results in selected cohorts. In the present study we sought to develop a novel method for accurate detection and quantification of SNP in DNA pooled samples.MethodsThe development and evaluation of a novel Ligase Chain Reaction (LCR) protocol that uses a DNA-specific fluorescent dye to allow quantitative real-time analysis is described. Different reaction components and thermocycling parameters affecting the efficiency and specificity of LCR were examined. Several protocols, including gap-LCR modifications, were evaluated using plasmid standard and genomic DNA pools. A protocol of choice was identified and applied for the quantification of a polymorphism at codon 136 of the ovine PRNP gene that is associated with susceptibility to a transmissible spongiform encephalopathy in sheep.ConclusionsThe real-time LCR protocol developed in the present study showed high sensitivity, accuracy, reproducibility and a wide dynamic range of SNP quantification in different DNA pools. The limits of detection and quantification of SNP frequencies were 0.085% and 0.35%, respectively.SignificanceThe proposed real-time LCR protocol is applicable when sensitive detection and accurate quantification of low copy number mutations in DNA pools is needed. Examples include oncogenes and tumour suppressor genes, infectious diseases, pathogenic bacteria, fungal species, viral mutants, drug resistance resulting from point mutations, and genetically modified organisms in food.
Highlights
IntroductionSingle Nucleotide Polymorphisms (SNP) are the most common type of genetic markers and refer to a position where two alternative bases occur at appreciable frequency (.1%) in a population [1]
Examples include oncogenes and tumour suppressor genes, infectious diseases, pathogenic bacteria, fungal species, viral mutants, drug resistance resulting from point mutations, and genetically modified organisms in food
Single Nucleotide Polymorphisms (SNP) are the most common type of genetic markers and refer to a position where two alternative bases occur at appreciable frequency (.1%) in a population [1]
Summary
Single Nucleotide Polymorphisms (SNP) are the most common type of genetic markers and refer to a position where two alternative bases occur at appreciable frequency (.1%) in a population [1]. SNP detection is of great importance to agriculture and animal science, addressing quantitative trait loci (QTL) identification, marker assisted selection, genome mapping, food traceability, parental tests, detection of genetically modified organisms in food and feed, diagnosis of animal genetic diseases, and disease susceptibility. In cases where mutated DNA molecules correspond to a small fraction of the wild-type DNA, for example oncogenes or tumour suppressor genes and microbial or viral mutations associated with drug resistance, the sensitivity of SNP detection becomes a critical factor [4]. Association studies of non-Mendelian complex diseases have emphasized cost benefits of allele frequency estimation in DNA pools [5] and raised the need for reliable, highly sensitive, fast throughput screening assays. In the present study we sought to develop a novel method for accurate detection and quantification of SNP in DNA pooled samples
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