- •A novel panel of six miRNAs was developed to classify seven body fluids.
- •QDA analysis of over 500 samples resulted in an overall prediction accuracy of 93%.
- •The QDA model is publicly available for testing at https://tinyurl.com/y9e5c9ca.
- •Using the current QDA model, mixtures were difficult to predict.
- •Alternate detection or analysis methods may be necessary to deconvolute mixtures.
Body fluid identification is an important step in the forensic DNA workflow, and more advanced methods, such as microRNA (miRNA) analysis, have been research topics within the community over the last few decades. We previously reported a reverse transcription-quantitative PCR (RT-qPCR) panel of eight miRNAs that could classify blood, menstrual secretions, feces, urine, saliva, semen, and vaginal secretions through analysis of differential gene expression. The purpose of this project was to evaluate this panel in a larger population size, develop a more statistically robust analysis method and perform a series of developmental validation studies. Each of the eight miRNA markers was analyzed in > 40 donors each of blood, menstrual secretions, feces, urine, saliva, semen, and vaginal secretions. A 10-fold cross-validated quadratic discriminant analysis (QDA) model yielded the highest classification accuracy of 93% after eliminating miR-26b and miR-1246 from the panel. Accuracy of body fluid predictions was between 84% and 100% when various population demographics and samples from the same donor over multiple time periods were evaluated, but the assay demonstrated limited scope and reduced accuracy when mixed body fluid samples were tested. Limit of detection was found to be less than 104 copies/µL across multiple commercially available RT-qPCR analysis methods. These data suggest that miR-200b, miR-320c, miR-10b, and miR-891a, when normalized to let-7 g and let-7i, can consistently and robustly classify blood, feces and urine, but additional work is important to improve classification of saliva, semen, and female intimate secretions before implementation in forensic casework.
To read this article in full you will need to make a payment
Purchase one-time access:Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
One-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:Subscribe to Forensic Science International: Genetics
Already a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
- Normalization of microRNA expression levels in quantitative RT-PCR assays: Identification of suitable reference RNA targets in normal and cancerous human solid tissues.RNA. 2008; https://doi.org/10.1261/rna.939908
- mRNA profiling using a minimum of five mRNA markers per body fluid and a novel scoring method for body fluid identification.Int J. Leg. Med. 2013; 127: 707-721https://doi.org/10.1007/s00414-012-0794-3
- Regulation of microRNA biogenesis.Nat. Rev. Mol. Cell Biol. 2014; 15: 509-524https://doi.org/10.1038/nrm3838
- Messenger RNA biomarker signatures for forensic body fluid identification revealed by targeted RNA sequencing.Forensic Sci. Int. Genet. 2018; 34: 206-221https://doi.org/10.1016/j.fsigen.2018.02.020
- Quantification of RNA degradation by semi-quantitative duplex and competitive RT-PCR: A possible indicator of the age of bloodstains?.Forensic Sci. Int. 2003; 138: 94-103https://doi.org/10.1016/j.forsciint.2003.09.008
- Altered profile of seminal plasma microRNAs in the molecular diagnosis of male.Infertility. 2011; https://doi.org/10.1373/clinchem.2011.169714
- Transcriptomic analysis of degraded forensic body fluids.Forensic Sci. Int. Genet. 2015; 17: 35-42https://doi.org/10.1016/J.FSIGEN.2015.03.005
- microRNA detection in blood, urine, semen, and saliva stains after compromising treatments.J. Forensic Sci. 2019; 64https://doi.org/10.1111/1556-4029.14113
- Identification of forensically relevant body fluids using a panel of differentially expressed microRNAs.Anal. Biochem. 2009; 387: 303-314https://doi.org/10.1016/j.ab.2009.01.037
- Database for mRNA half-life of 19 977 genes obtained by DNA microarray analysis of pluripotent and differentiating mouse embryonic stem cells.DNA Res.: Int. J. Rapid Publ. Rep. Genes Genomes. 2009; 16: 45-58https://doi.org/10.1093/dnares/dsn030
- Micro-RNA - a potential for forensic science?.Forensic Sci. Int. 2010; 203: 106-111https://doi.org/10.1016/j.forsciint.2010.07.002
- An evidence based strategy for normalization of quantitative PCR data from miRNA expression analysis in forensic organ tissue identification.Forensic Sci. Int. Genet. 2014; 13: 217-223https://doi.org/10.1016/j.fsigen.2014.08.005
- Degradation dynamics of microRNAs revealed by a novel pulse-chase approach.Genome Res. 2016; 26: 554-565https://doi.org/10.1101/gr.198788.115
- mRNA and microRNA stability validation of blood samples under different environmental conditions, Forensic Science.Forensic Sci. Int. Genet. 2021; 55https://doi.org/10.1016/j.fsigen.2021.102567
- MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation.Int. J. Leg. Med. 2010; 124: 217-226https://doi.org/10.1007/s00414-009-0402-3; 10.1007/s00414-009-0402-3
- Screening and confirmation of microRNA markers for forensic body fluid identification.Forensic Sci. Int. Genet. 2013; 7: 116-123https://doi.org/10.1016/j.fsigen.2012.07.006; 10.1016/j.fsigen.2012.07.006
- High-throughputmiRNA sequencing and identification of biomarkers for forensically relevantbiological fluids.Electrophoresis. 2016; 37: 2780-2788https://doi.org/10.1002/elps.201600258
- Detection of microRNAs in DNA extractions for forensic biological source identification.J. Forensic Sci. 2019; 64https://doi.org/10.1111/1556-4029.14070
- The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments.Clin. Chem. 2009; 55: 611-622https://doi.org/10.1373/clinchem.2008.112797
- The elements of statistical learning.Data Mining, Inference and Prediction. second ed. Springer, 2016
- Modern Applied Statistics with S.fourth ed. Springer, 2002
- Characterising the fluctuation of microRNA expression throughout a full menstrual cycle.Forensic Sci. Int. Genet. 2015; 5: e264-e266https://doi.org/10.1016/j.fsigss.2015.09.105
- Evolution of microRNA diversity and regulation in animals.Nat. Rev. Genet. 2011; 12: 846-860https://doi.org/10.1038/nrg3079
- MiR16 as a microRNA marker applied in species identification.Forensic Sci. Int.: Genet. 2011; 3: e313-e314https://doi.org/10.1016/j.fsigss.2011.09.019
- Microarray screening and qRT-PCR evaluation of microRNA markers for forensic body fluid identification.Electrophoresis. 2014; 35: 3062-3068https://doi.org/10.1002/elps.201400075
- Massively parallel sequencing of microRNA in bloodstains and evaluation of environmental influences on miRNA candidates using realtime polymerase chain reaction.Forensic Sci. Int. Genet. 2019; 38: 32-38https://doi.org/10.1016/J.FSIGEN.2018.10.001
J. Hayes, Forensic Testing Turn around Times in 50 States, (2010).
- Comparison of nine different real-time PCR chemistries for qualitative and quantitative applications in GMO detection.Anal. Bioanal. Chem. 2010; 396: 2023-2029https://doi.org/10.1007/s00216-009-3418-0
- Comparison of TaqMan and SYBR green qPCR methods for quantitative gene expression in tung tree tissues.J. Agric. Food Chem. 2012; 60: 12296-12303https://doi.org/10.1021/jf304690e
Published online: March 24, 2022
Accepted: March 21, 2022
Received in revised form: March 9, 2022
Received: December 2, 2021
☆This work was supportedby the National Institute of Justice [Award 2016-DN-BX-0163].
© 2022 Elsevier B.V. All rights reserved.