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MicroRNAs (miRNAs, 18-25 bases in length) are small, non-coding RNAs that regulate gene expression at the post-transcriptional level. MiRNA expression patterns, including presence and relative abundance of particular miRNA species, provide cell- and tissue-specific information that can be used for body fluid identification. Recently, two published studies reported that a number of body fluid-specific miRNAs had been identified. However, the results were inconsistent when different technology platforms and statistical methods were applied. To further study the role of miRNAs in identification of body fluids, this study sets out to develop an accurate and reliable model for data analysis of miRNA expression. To that end, the relative expression levels of three miRNAs were studied using the mirVana™ miRNA Isolation Kit, high-specificity stem-loop reverse transcription (RT) and high-sensitivity hydrolysis probes (TaqMan) quantitative real-time polymerase chain reaction (qPCR) in forensically relevant biological fluids, including venous blood, vaginal secretions, menstrual blood, semen and saliva. Accurate quantification of miRNAs requires not only a highly sensitive and specific detection platform for experiment operation, but also a reproducible methodology with an adequate model for data analysis. In our study, the efficiency-calibrated model that incorporated the impact of the quantification cycle (Cq) values and PCR efficiencies of target and reference genes was developed to calculate the relative expression ratio of miRNAs in forensically relevant body fluids. Our results showed that venous blood was distinguished from other body fluids according to the relative expression ratio of miR16 using as little as 50pg of total RNA, while the expression level of miR658 was unstable and that of miR205 was nonspecific among different body fluids. Collectively, the findings may constitute a basis for future miRNA-based research on body fluid identification and show miRNAs as a promising biomarker in forensic identification of body fluids. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Citation

Zheng Wang, Haibo Luo, Xiongfei Pan, Miao Liao, Yiping Hou. A model for data analysis of microRNA expression in forensic body fluid identification. Forensic science international. Genetics. 2012 May;6(3):419-23

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PMID: 21903498

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