Investigation of the Application of miR10b and miR135b in the Identification of Semen Stains

PLoS One. 2015 Sep 10;10(9):e0137067. doi: 10.1371/journal.pone.0137067. eCollection 2015.

Abstract

To evaluate the identification method using the microRNA markers miR10b and miR135b to distinguish semen stains from menstrual blood, peripheral blood, vaginal fluid and so on body fluid stains. The expression levels of miR10b and miR35b in semen stains and menstrual blood and so on were detected utilizing a real-time quantitative PCR technique with a specific fluorescence-labeled TaqMan probe. RNU6b was used as the internal reference gene; the difference in their expression was analyzed, and the specificity, sensitivity, and detection capability of the techniques were evaluated. The expression of miR10b and miR135b in semen stains was significantly higher than that of other body fluid stains, with a mean value of ΔCт from-6 to-7. However, it ranged from-2 to-4 for other body fluid stains. The initial criteria for judging which semen stains can be identified were determined by analyzing the research results. When the threshold value was set to 0.04, the CT value could be detected in the target genes miR10b, miR135b and in the internal reference gene RNU6b, and CT values are<40, ΔCT[10b-U6]<-5.5, and ΔCT[135b-U6]<-6, respectively, and the semen stain could be identified. The expression levels of miR10b and miR135b are higher in semen with strong tissue specificity; thus, they can be used to differentiate semen stains from other body fluid stains in forensic science.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Biomarkers / metabolism
  • Gene Expression Regulation
  • Humans
  • Male
  • MicroRNAs / genetics
  • MicroRNAs / metabolism*
  • Real-Time Polymerase Chain Reaction
  • Reproducibility of Results
  • Semen / metabolism*
  • Sensitivity and Specificity
  • Staining and Labeling*

Substances

  • Biomarkers
  • MIRN10 microRNA, human
  • MIRN135 microRNA, human
  • MicroRNAs

Grants and funding

This research is supported by the National Natural Science Foundation (30400519), the Scientific Research Foundation of Ministry of Education (2008-890), and the application innovation program of the Ministry of Public Security (2007YYCXGDST079).