US EPA

3696357 

Journal Article 

Evaluating genomic DNA extraction methods from human whole blood using endpoint and real-time PCR assays 

Koshy, L; Anju, AL; Harikrishnan, S; Kutty, VR; Jissa, VT; Kurikesu, I; Jayachandran, P; Jayakumaran Nair, A; Gangaprasad, A; Nair, GM; Sudhakaran, PR 

2017 

1 

Molecular Biology Reports
ISSN: 0301-4851
EISSN: 1573-4978 

44 

1 

97-108 

English 

27686559 

10.1007/s11033-016-4085-9 

WOS:000394349600011 

The extraction of genomic DNA is the crucial first step in large-scale epidemiological studies. Though there are many popular DNA isolation methods from human whole blood, only a few reports have compared their efficiencies using both end-point and real-time PCR assays. Genomic DNA was extracted from coronary artery disease patients using solution-based conventional protocols such as the phenol-chloroform/proteinase-K method and a non-phenolic non-enzymatic Rapid-Method, which were evaluated and compared vis-a-vis a commercially available silica column-based Blood DNA isolation kit. The appropriate method for efficiently extracting relatively pure DNA was assessed based on the total DNA yield, concentration, purity ratios (A260/A280 and A260/A230), spectral profile and agarose gel electrophoresis analysis. The quality of the isolated DNA was further analysed for PCR inhibition using a murine specific ATP1A3 qPCR assay and mtDNA/Y-chromosome ratio determination assay. The suitability of the extracted DNA for downstream applications such as end-point SNP genotyping, was tested using PCR-RFLP analysis of the AGTR1-1166A>C variant, a mirSNP having pharmacogenetic relevance in cardiovascular diseases. Compared to the traditional phenol-chloroform/proteinase-K method, our results indicated the Rapid-Method to be a more suitable protocol for genomic DNA extraction from human whole blood in terms of DNA quantity, quality, safety, processing time and cost. The Rapid-Method, which is based on a simple salting-out procedure, is not only safe and cost-effective, but also has the added advantage of being scaled up to process variable sample volumes, thus enabling it to be applied in large-scale epidemiological studies.