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AJMB-Avicenna Journal of Medical Biotechnology. 2016; 8 (2): 84-90
in English | IMEMR | ID: emr-178492

ABSTRACT

Background: DNA isolation procedure can significantly influence the quantification of DNA by real time PCR specially when cell free DNA [cfDNA] is the subject. To assess the extraction efficiency, linearity of the extraction yield, presence of co-purified inhibitors and to avoid problems with fragment size relevant to cfDNA, development of appropriate External DNA Control [EDC] is challenging. Using non-human chimeric nucleotide sequences, an EDC was developed for standardization of qPCR for monitoring stability of cfDNA concentration in blood samples over time


Methods: A DNA fragment of 167 bp chimeric sequence of parvovirus B19 and pBHA designated as EDC fragment was designed. To determine the impact of different factors during DNA extraction processing on quantification of cfDNA, blood samples were collected from normal subjects and divided into aliquots with and without specific treatment. In time intervals, the plasma samples were isolated. The amplicon of 167 bp EDC fragment in final concentration of 1.1 pg/ 500 microl was added to each plasma sample and total DNA was extracted by an in house method. Relative and absolute quantification real time PCR was performed to quantify both EDC fragment and cfDNA in extracted samples


Results: Comparison of real time PCR threshold cycle [Ct] for cfDNA fragment in tubes with and without specific treatment indicated a decrease in untreated tubes. In contrast, the threshold cycle was constant for EDC fragment in treated and untreated tubes, indicating the difference in Ct values of the cfDNA is because of specific treatments that were made on them


Conclusions: Spiking of DNA fragment size relevant to cfDNA into the plasma sample can be useful to minimize the bias due to sample preparation and extraction processing. Therefore, it is highly recommended that standard external DNA control be employed for the extraction and quantification of cfDNA for accurate data analysis

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