Document Type : Original Article
Department of Molecular Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran;Department of Biology, Faculty of Sciences, Shahid Bahonar University of Kerman, Kerman, Iran
National Institute of Genetic Engineering and Biotechnology, Tehran, Iran
4Janbazan Medical and Engineering Research Center (JMERC), Tehran, Iran
5Departmen of Biotechnology, Faculty of Biological Sciences, Alzahra University, Tehran, Iran
6Genetic Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran
7Chemical Injury Research Center (CIRC), Baqiyatallah University of Medical Sciences, Tehran, Iran
In spite of accumulating information about pathological aspects of sulfur mustard (SM), the precise mechanism responsible for its effects is not well understood. Circulating microRNAs (miRNAs) are promising biomarkers for disease diagnosis and prognosis. Accurate normalization using appropriate reference genes, is a critical step in miRNA expression studies. In this study, we aimed to identify appropriate reference gene for microRNA quantification in serum samples of SM victims.
Materials and Methods
In this case and control experimental study, using quantitative real-time polymerase chain reaction (qRT-PCR), we evaluated the suitability of a panel of small RNAs including SNORD38B, SNORD49A, U6, 5S rRNA, miR-423-3p, miR-191, miR-16 and miR-103 in sera of 28 SM-exposed veterans of Iran-Iraq war (1980-1988) and 15 matched control volunteers. Different statistical algorithms including geNorm, Normfinder, best-keeper and comparative delta-quantification cycle (Cq) method were employed to find the least variable reference gene.
miR-423-3p was identified as the most stably expressed reference gene, and miR- 103 and miR-16 ranked after that.
We demonstrate that non-miRNA reference genes have the least stabil- ity in serum samples and that some house-keeping miRNAs may be used as more reliable reference genes for miRNAs in serum. In addition, using the geometric mean of two reference genes could increase the reliability of the normalizers.