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Screening and confirmation of microRNA markers for forensic body fluid identification

  • Zheng Wang
    Affiliations
    Department of Forensic Genetics, West China School of Basic Science and Forensic Medicine, Sichuan University (West China University of Medical Sciences), Chengdu 610041, Sichuan, China
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  • Ji Zhang
    Affiliations
    Department of Forensic Genetics, West China School of Basic Science and Forensic Medicine, Sichuan University (West China University of Medical Sciences), Chengdu 610041, Sichuan, China
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  • Haibo Luo
    Affiliations
    Department of Forensic Genetics, West China School of Basic Science and Forensic Medicine, Sichuan University (West China University of Medical Sciences), Chengdu 610041, Sichuan, China
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  • Yi Ye
    Affiliations
    Department of Forensic Toxicological Analysis, West China School of Basic Science and Forensic Medicine, Sichuan University, Chengdu 610041, Sichuan, China
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  • Jing Yan
    Affiliations
    Department of Forensic Genetics, West China School of Basic Science and Forensic Medicine, Sichuan University (West China University of Medical Sciences), Chengdu 610041, Sichuan, China
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  • Yiping Hou
    Correspondence
    Corresponding author. Tel.: +86 28 85501550; fax: +86 28 85501549.
    Affiliations
    Department of Forensic Genetics, West China School of Basic Science and Forensic Medicine, Sichuan University (West China University of Medical Sciences), Chengdu 610041, Sichuan, China
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      Abstract

      MicroRNAs (miRNAs, ∼22 nucleotides) are small, non-protein coding RNAs that regulate gene expression at the post-transcriptional level. MiRNAs can express in a tissue-specific manner, and have been introduced to forensic body fluid identification. In this study, we employed the qPCR-array (TaqMan® Array Human MicroRNA Cards) to screen the body fluid-specific miRNAs. Seven candidate miRNAs were identified as potentially body fluid-specific and could be used as forensically relevant body fluid markers: miR16 and miR486 for venous blood, miR888 and miR891a for semen, miR214 for menstrual blood, miR124a for vaginal secretions, and miR138-2 for saliva. The candidate miRNA markers were then validated via hydrolysis probes quantitative real-time polymerase chain reaction (TaqMan-qPCR). In addition, BestKeeper software was used to validate the expression stability of four genes, RNU44, RNU48, U6 and U6b, regularly used as reference genes (RGs) for studies involving forensic body fluids. The current study suggests that U6 could be used as a proper RG of miRNAs in forensic body fluid identification. The relative expression ratios (R) of miR486, miR888, miR214, miR16 and miR891a can differentiate the target body fluid from other body fluids that were tested in this study. The detection limit of TaqMan-qPCR of the five confirmed miRNA markers was 10 pg of total RNA. The effect of time-wise degradation of blood stains and semen stains for 1 month under normal laboratory conditions was tested and did not significantly affect the detection results. Herein, this study proposes five body fluid-specific miRNAs for the forensic identification of venous blood, semen, and menstrual blood, of which miR486, miR888, and miR214 may be used as new markers for body fluid identification. Additional work remains necessary in search for suitable miRNA markers and stable RGs for forensic body fluid identification.

      Keywords

      1. Introduction

      Identifying the origin of body fluids left at a crime scene is important for crime scene reconstruction; however, conventional serology-based methods for body fluid identification are prone to various limitations such as sample consumption, intensive labor, time consumption, varying degrees of sensitivity and specificity [
      • Gaensslen R.E.
      Sourcebook in Forensic Serology, Immunology, and Biochemistry.
      ,
      • Ponce A.C.
      • Pascual F.A.V.
      Critical revision of presumptive tests for bloodstains.
      ,
      • Khaldi N.
      • Miras A.
      • Botti K.
      • Benali L.
      • Gromb S.
      Evaluation of three rapid detection methods for the forensic identification of seminal fluid in rape cases.
      ,
      • Tobe S.S.
      • Watson N.
      • Daéid N.N.
      Evaluation of six presumptive tests for blood, their specificity, sensitivity, and effect on high molecular-weight DNA.
      ,
      • Mayers J.R.
      • Adkins W.K.
      Comparison of modern techniques for saliva screening.
      ]. Several messenger RNA (mRNA) markers are expressed in a tissue-specific manner, and their expression patterns can confirm specific body fluids even after long periods of time under controlled conditions [
      • Juusola J.
      • Ballantyne J.
      Messenger RNA profiling: a prototype method to supplant conventional methods for body fluid identification.
      ,
      • Juusola J.
      • Ballantyne J.
      Multiplex mRNA profiling for the identification of body fluids.
      ,
      • Juusola J.
      • Ballantyne
      mRNA profiling for body fluid identification by multiplex quantitative RT-PCR.
      ,
      • Setzer M.
      • Juusola J.
      • Ballantyne J.
      Recovery and stability of RNA in vaginal swabs and blood, semen, and saliva stains.
      ]. However, humidity, heat, UV light, and ubiquitous ribonucleases are detrimental to mRNA stability as a specific and sensitive biomarker for forensic applications [
      • Setzer M.
      • Juusola J.
      • Ballantyne J.
      Recovery and stability of RNA in vaginal swabs and blood, semen, and saliva stains.
      ,
      • Zubakov D.
      • Kokshoorn M.
      • Kloosterman A.
      • Kayser M.
      New markers for old stains: stable mRNA markers for blood and saliva identification from up to 16-year-old stains.
      ].
      MiRNAs belong to a class of small, non-coding RNA molecules containing 18–25 nucleotides that regulate gene expression at the post-transcriptional level [
      • Bartel D.P.
      MicroRNAs: genomics, biogenesis, mechanism, and function.
      ,
      • Kim V.N.
      MicroRNA biogenesis: coordinated cropping and dicing.
      ,
      • Kim V.N.
      • Han J.
      • Siomi M.C.
      Biogenesis of small RNAs in animals.
      ]. By incorporating into the RNA-induced silencing complex (RISC) and hybridizing to the 3′UTR of specific mRNA targets, mature miRNA can cause translational repression and/or mRNA decay [
      • Gu S.
      • Jin L.
      • Zhang F.
      • Sarnow P.
      • Kay M.A.
      Biological basis for restriction of microRNA targets to the 3′ untranslated region in mammalian mRNAs.
      ,
      • Rana T.M.
      Illuminating the silence: understanding the structure and function of small RNAs.
      ,
      • Tavazoie S.F.
      • Alarcón C.
      • Oskarsson T.
      • Padua D.
      • Wang Q.
      • Bos P.D.
      • et al.
      Endogenous human microRNAs that suppress breast cancer metastasis.
      ]. Recent studies have demonstrated the important role of miRNAs in physiological functions and pathogenesis, revealing that they can express in a tissue-specific manner [
      • Rana T.M.
      Illuminating the silence: understanding the structure and function of small RNAs.
      ,
      • Tavazoie S.F.
      • Alarcón C.
      • Oskarsson T.
      • Padua D.
      • Wang Q.
      • Bos P.D.
      • et al.
      Endogenous human microRNAs that suppress breast cancer metastasis.
      ,
      • Hwang H.W.
      • Mendell J.T.
      MicroRNAs in cell proliferation, cell death, and tumorigenesis.
      ,
      • Sood P.
      • Krek A.
      • Zavolan M.
      • Macino G.
      • Rajewsky N.
      Cell-type-specific signatures of microRNAs on target mRNA expression.
      ,
      • Liang Y.
      • Ridzon D.
      • Wong L.
      • Chen C.
      Characterization of microRNA expression profiles in normal human tissues.
      ]. Theoretically, the shorter fragment and tissue-specific expression of miRNA make it less susceptible to degradation caused by chemical and/or physical environmental strain, thus rendering it a useful biomarker for body fluid identification. Interestingly, it was reported that miRNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue samples have obtained feasible and valid profiling results [
      • Leite K.R.
      • Canavez J.M.
      • Reis S.T.
      • Tomiyama A.H.
      • Piantino C.B.
      • Sañudo A.
      • et al.
      miRNA analysis of prostate cancer by quantitative real time PCR: comparison between formalin-fixed paraffin embedded and fresh-frozen tissue.
      ,
      • Hui A.B.
      • Shi W.
      • Boutros P.C.
      • Miller N.
      • Pintilie M.
      • Fyles T.
      • et al.
      Robust global micro-RNA profiling with formalin-fixed paraffin-embedded breast cancer tissues.
      ]. In several forensic laboratories, differentially expressed miRNAs have been investigated as a potential method for body fluid identification [
      • Hanson E.K.
      • Lubenow H.
      • Ballantyne J.
      Identification of forensically relevant body fluids using a panel of differentially expressed microRNAs.
      ,
      • Zubakov D.
      • Boersma A.W.
      • Choi Y.
      • Kuijk P.F.V.
      • Wiemer E.A.
      • Kayser M.
      MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation.
      ,
      • Courts C.
      • Madea B.
      Specific micro-RNA signatures for the detection of saliva and blood in forensic body-fluid identification.
      ,
      • Wang Z.
      • Luo H.B.
      • Pan X.F.
      • Liao M.
      • Hou Y.P.
      A model for data analysis of microRNA expression in forensic body fluid identification.
      ,
      • Li Y.
      • Wang Z.
      • Hou Y.P.
      MiR16 as a microRNA marker applied in species identification.
      ]. With an increasing number of miRNAs available on the chips, which are commonly used for screening, more specific miRNAs could be selected for the purpose of body fluid identification.
      Previously, we presented a simple procedure for miRNA-based body fluid identification and an accurate model for data analysis [
      • Wang Z.
      • Luo H.B.
      • Pan X.F.
      • Liao M.
      • Hou Y.P.
      A model for data analysis of microRNA expression in forensic body fluid identification.
      ]. In this study, we further searched potential body fluid-specific miRNAs through a qPCR-array (TaqMan® Array Human MicroRNA Cards) containing 754 known human miRNAs by using forensically relevant body fluid samples. We then confirmed five candidate miRNAs by the hydrolysis probes quantitative real-time polymerase chain reaction (TaqMan-qPCR). Additionally, to normalize qPCR data, four commonly used reference genes (RGs) were selected to validate the expression stability in forensically relevant body fluids. The relative expression ratios (R) of body fluid-specific miRNAs were calculated. We further tested body fluid-specific miRNA markers for degradation stability and assessed the sensitivity of marker-specific TaqMan assays.

      2. Materials and methods

      2.1 Collection of body fluid samples

      Five forensically relevant body fluids were used for initial miRNA TaqMan® Array screening. Body fluid samples were collected on sterile cotton swabs and dried at room temperature. Venous blood was collected by venipuncture without anticoagulation treatment, and 50 μl aliquots were spotted onto sterile cotton swabs. Freshly ejaculated semen was provided in sealed plastic cups and dried onto sterile cotton swabs. Semen-free vaginal secretions and menstrual blood were collected from the vagina with sterile cotton swabs and dried at room temperature. Saliva samples were provided in sealed plastic tubes and dried onto sterile cotton swabs. Written informed consent was obtained from all sample donors (18–47 years old) of the Chinese Han population living in the Sichuan Province. All samples were stored at −80 °C following collection. RNA isolation was performed on individual cotton swabs.
      Body fluid samples for TaqMan-qPCR validation (including those used for array screening) were collected from ten unrelated individuals. To observe the effect of natural environment on the miRNAs, cotton swabs were kept under normal laboratory conditions (approximately 15 °C and about 10-hour natural daylight exposure per day) for 1 month.

      2.2 RNA isolation and quantification

      Total RNA was extracted using the mirVana™ miRNA Isolation kit (Ambion, Austin, TX, USA) following the instructions of the manufacturer. Potential traces of genomic DNA were removed by DNase I digestion, performed with Turbo DNA-free™ kit (Ambion) according to manufacturer's protocol. Purity and quantity of RNA were assessed with the NanoDrop ND-1000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA). Equal quantities of total RNA from three donors were combined to produce pooled samples.

      2.3 TaqMan® Array analysis and candidate selection

      MiRNA profiling experiments using TaqMan® Array Human MicroRNA Cards (Cards A and B, Applied Biosystems, Foster City, CA, USA) for a total of 754 unique assays specific to human miRNAs (Comprehensive coverage of Sanger miRBase v14) were performed by Applied Biosystems. The sample of cDNA reverse-transcribed from saliva was pre-amplified according to the manufacturer's instructions. The Cq value is defined as the PCR cycle at which the fluorescent signal of the reporter dye crosses an arbitrarily placed threshold in the exponential phase. Since a quantification cycle (Cq) value of 35 represents single molecule template detection, Cq values > 35 were considered to be below the limit of detection [
      • Guthrie J.L.
      • Seah C.
      • Brown S.
      • Tang P.
      • Jamieson F.
      • Drews S.J.
      Use of Bordetella pertussis BP3385 to establish a cutoff value for an IS481-targeted real-time PCR assay.
      ]. Therefore, only the miRNAs with a Cq ≤ 35 were included in the analyses, carried out using DataAssist™ Software. Potential specific miRNA markers were selected primarily based on the absolute expression levels and large-magnitude fold-change of differential expression between body fluids. Preference was given to miRNA markers that were highly abundant (Cq ≤ 25) in the target body fluid and only minimally (Cq > 30) or not expressed in the non-target ones.

      2.4 TaqMan RT-qPCR

      cDNA was synthesized in a 15 μl reaction, containing 10 ng of total RNA, using TaqMan® MicroRNA Reverse Transcription Kit (Applied Biosystems). Reverse transcription (RT) reactions were performed on a GeneAmpPCR System 9600 (Applied Biosystems) under the following conditions: 16 °C for 30 min, 42 °C for 30 min, 85 °C for 5 min, and 4 °C on hold. Reactions without addition of reverse transcriptase (RT (−) controls) were used as controls for potential genomic DNA contamination. All TaqMan assays were run in triplicate on an ABI Prism 7500 using TaqMan® Universal PCR Master Mix II without UNG (Applied Biosystems). One μl of cDNA was used in the subsequent Real-time PCR reaction. Real-time PCR cycling conditions consisted of 95 °C for 10 min, followed by 40 cycles of 15 s at 95 °C and 1 min at 60 °C. Cq values were calculated using SDS software with an automatic baseline and a threshold of 0.2. Samples in which the fluorescent signal did not reach the threshold were considered invalid and were not used for further analysis.

      2.5 Reference genes validation

      RNU44, RNU48, U6 and U6b were chosen as RGs based on their high abundance (P/N: 044972, Applied Biosystems) and reported literatures about forensic body fluid identification [
      • Hanson E.K.
      • Lubenow H.
      • Ballantyne J.
      Identification of forensically relevant body fluids using a panel of differentially expressed microRNAs.
      ,
      • Zubakov D.
      • Boersma A.W.
      • Choi Y.
      • Kuijk P.F.V.
      • Wiemer E.A.
      • Kayser M.
      MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation.
      ,
      • Courts C.
      • Madea B.
      Specific micro-RNA signatures for the detection of saliva and blood in forensic body-fluid identification.
      ,
      • Wang Z.
      • Luo H.B.
      • Pan X.F.
      • Liao M.
      • Hou Y.P.
      A model for data analysis of microRNA expression in forensic body fluid identification.
      ,
      • Li Y.
      • Wang Z.
      • Hou Y.P.
      MiR16 as a microRNA marker applied in species identification.
      ]. We herein employed BestKeeper software to measure the expression stability of four putative RGs in different body fluids. The principle behind BestKeeper for identification of stably expressed RGs is that proper RGs should display a similar expression pattern [
      • Pfaffl M.W.
      • Tichopad A.
      • Prgomet C.
      • Neuvians T.P.
      Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper – Excel-based tool using pair-wise correlations.
      ].

      2.6 Data analysis

      Relative quantification of miRNA expression was performed by the relative expression ratio method [
      • Pfaffl M.W.
      A new mathematical model for relative quantification in real-time RT-PCR.
      ,
      • Soong R.
      • Ruschoff J.
      • Tabiti K.
      Detection of Colorectal Micrometastasis by Quantitative RT-PCR of Cytokeratin 20 mRNA.
      ]. The qPCR efficiency (E) was calculated according to the formula: E = 10[−1/slope] − 1, as previously described [
      • Wang Z.
      • Luo H.B.
      • Pan X.F.
      • Liao M.
      • Hou Y.P.
      A model for data analysis of microRNA expression in forensic body fluid identification.
      ,
      • Pfaffl M.W.
      A new mathematical model for relative quantification in real-time RT-PCR.
      ]. Relative fold-change was calculated according to our previous study [
      • Wang Z.
      • Luo H.B.
      • Pan X.F.
      • Liao M.
      • Hou Y.P.
      A model for data analysis of microRNA expression in forensic body fluid identification.
      ].

      2.7 Analytical sensitivity of miRNA TaqMan assays

      To evaluate the detection sensitivity of TaqMan RT-PCR assays for the confirmed specific miRNAs, serial dilutions of total RNA (ranging from 10 ng to 0.01 ng) were used as input for cDNA synthesis.

      3. Results

      3.1 TaqMan® Array data analysis

      After removing the low-expression values across all body fluids from analysis, values of the remaining 177 of 754 (23.5%) miRNAs were normalized. Unsupervised hierarchical clustering of normalized Cq (ΔCq = CqmiRNA − CqRG) values was carried out as bottom-up complete linkage clustering using the Euclidean distance as a measure. This revealed that different body fluids displayed distinct miRNA expression signatures (Fig. 1). The numerical value of the ΔCq is inversely related to the amount of target miRNA in the reaction (i.e., the lower the ΔCq, the greater the amount of target miRNA). Only miR891a was identified as the truly body fluid-specific miRNA that showed expression of high-abundance (Cq ≤ 25) in a single body fluid, and no expression (Cq > 35) in the other body fluids. Based on the absolute expression levels in target body fluid and fold change (at least 10-fold change) of differential expression between target fluid and other body fluids, we manually ascertained the most promising candidate markers and obtained six additional candidate markers for validation in TaqMan-based quantitative RT-PCR assays (Table 1).
      Figure thumbnail gr1
      Fig. 1Unsupervised hierarchical cluster map of 177 miRNAs from qPCR-array analysis of five forensically relevant body fluids, i.e., semen (SE), saliva (SA), vaginal secretions (VS), menstrual blood (MB), and venous blood (VB).
      Table 1Reported miRNA markers for forensic body fluid identification, and screened and confirmed miRNA markers by our group.
      GroupsHanson et al.
      • Hanson E.K.
      • Lubenow H.
      • Ballantyne J.
      Identification of forensically relevant body fluids using a panel of differentially expressed microRNAs.
      Zubakov et al.
      • Zubakov D.
      • Boersma A.W.
      • Choi Y.
      • Kuijk P.F.V.
      • Wiemer E.A.
      • Kayser M.
      MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation.
      Courts et al.
      • Courts C.
      • Madea B.
      Specific micro-RNA signatures for the detection of saliva and blood in forensic body-fluid identification.
      Our group
      Body fluids452 miRNAsSYBR Green-qPCRLNA™-modified Microarray (Sanger miRBase v10.1)TaqMan-qPCRGeniom® Biochips (Sanger miRBase v14)SYBR Green-qPCRqPCR-array (Sanger miRBase v14)TaqMan-qPCR
      Venous bloodmiR451; miR16miR451; miR16miR20a; miR106a; miR185miR20a; miR106a; miR185; miR144miR126; miR150; miR451miR126; miR150; miR451miR486; miR16miR486; miR16
      SemenmiR135b; miR10bmiR135b; miR10bmiR943; miR135a; miR10a; miR507miR943; miR135a; miR10a; miR507; miR891amiR888; miR891amiR888; miR891a
      Menstrual bloodmiR451; miR412miR451; miR412miR185*; miR144miR214miR214
      Vaginal secretionsmiR124a; miR372miR124a; miR372miR617; miR891amiR124a
      SalivamiR658; miR205miR658; miR205miR583; miR518c*; miR208bmiR200c; miR203; miR205miR200c; miR203; miR205miR138 -2

      3.2 Validation of reference genes

      The results of the BestKeeper analysis show that the expressions of RNU44, RNU48, and U6b in different body fluids are unstable (Supplemental Fig. 1) and cannot be used as RG. One-way analysis of variance (ANOVA) suggests that the differences between the expression levels of U6 in five body fluids are not statistically significant. As such, U6 was subsequently used as the RG to calculate the relative expression ratios.

      3.3 Validation of candidate miRNA markers

      Using the TaqMan® Array dataset, the seven more promising candidate markers were selected and validated with the TaqMan-based quantitative RT-PCR assays (Supplemental Table 1). Relative abundance values of these seven miRNAs to U6 were presented and average Cq values of ten unrelated individuals were tabulated (Supplemental Table 2).
      Over-expression of candidate miRNAs was confirmed by both TaqMan® Array and TaqMan-qPCR in venous blood, semen, and menstrual blood. The abundance values show that miR16 and miR486 are over-expressed in both menstrual and venous blood; however, in venous blood, the expression levels of miR16 and miR486 afford an approximate 4-ΔΔCq (ΔΔCq = ΔCqtargetbodyfluid − ΔCqotherbodyfluids) difference when compared to other body fluids. Two candidate miRNAs for semen are strongly over-expressed in the target body fluid; miR891a was below the detection level in all other body fluids, while miR888 was undetectable in both venous blood and vaginal secretions. In menstrual blood, miR214 had a 6-ΔΔCq difference when compared to other body fluids.
      However, less concordance between the results of TaqMan® Array and TaqMan-qPCR was achieved in both vaginal secretions and saliva. The expression of miR124a, which was not detectable in semen, was higher (4-ΔΔCq) in vaginal secretions and menstrual blood than in saliva and venous blood, but only showed approximately 1-ΔΔCq difference between vaginal secretions and menstrual blood. The TaqMan® Array candidate marker for saliva, miR-138-2, showed non-specific and low expression across all body fluids in the qPCR results, which was inconsistent with the TaqMan® Array results.
      Having attained these results, miR16, miR486, miR888, miR891a and miR214 were selected as potential body fluid-specific miRNAs for further study. The Cq values were plotted against the log of the dilution cDNA, and linear regressions were performed, from which the mean E could be derived (Fig. 2). Calculation values of E from target and RG were between 0.924 and 1.041 in forensically relevant body fluid. The relative expression ratios of fluid-specific miRNAs in different body fluids were compared (Fig. 3). As shown in Fig. 3, these five miRNAs appeared over-expressed in the target body fluid relative to other body fluids.
      Figure thumbnail gr2
      Fig. 2Determination of qPCR efficiencies from the slopes of the calibration curve, according to the equation: E = 10[−1/slope] − 1. Cq values versus cDNA concentration input (log scale) were plotted to calculate the slope (mean ± SD; n = 3).
      Figure thumbnail gr3
      Fig. 3Relative expression ratio of five miRNA markers in body fluids, i.e., venous blood (VB), vaginal secretions (VS), menstrual blood (MB), semen (SE), saliva (SA). Values underwent log10 transformation (error bars reflect variation between ten unrelated individuals).

      3.4 Time-wise stability of miRNA markers

      The effect of 1-month storage on the detection of miRNAs was tested by TaqMan-qPCR. Stability of miR16 and miR486 in venous blood, miR888 and miR891a in semen, and miR214 in menstrual blood were examined. Results revealed that absolute expression levels were slightly decreased (∼2–3 Cq) in 1-month-old samples, while ΔCq (Cqtarget − CqU6) values remained unchanged (Supplemental Fig. 2).

      3.5 Sensitivity of miRNA TaqMan assays

      Serial dilutions of total RNA were used as an input for cDNA synthesis to evaluate the detection sensitivity of TaqMan RT-PCR assays for the confirmed body fluid-specific miRNAs. As shown in Supplemental Fig. 3, all five markers were detectable in the target body fluid using an amount as low as 10 pg total RNA.

      4. Discussion

      Correct identification of the origin of the body fluid(s) left at crime scene can be significant to determining the nature of a crime. Characteristics of miRNA can overcome limitations of conventional serological and mRNA-based methods for body fluid identification [
      • Hanson E.K.
      • Lubenow H.
      • Ballantyne J.
      Identification of forensically relevant body fluids using a panel of differentially expressed microRNAs.
      ,
      • Zubakov D.
      • Boersma A.W.
      • Choi Y.
      • Kuijk P.F.V.
      • Wiemer E.A.
      • Kayser M.
      MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation.
      ,
      • Courts C.
      • Madea B.
      Specific micro-RNA signatures for the detection of saliva and blood in forensic body-fluid identification.
      ,
      • Wang Z.
      • Luo H.B.
      • Pan X.F.
      • Liao M.
      • Hou Y.P.
      A model for data analysis of microRNA expression in forensic body fluid identification.
      ]. Today, in the forensic community, differentially expressed miRNAs have been investigated as a means of body fluid identification. Two publications reported their preliminary application in forensic identification of body fluids [
      • Hanson E.K.
      • Lubenow H.
      • Ballantyne J.
      Identification of forensically relevant body fluids using a panel of differentially expressed microRNAs.
      ,
      • Zubakov D.
      • Boersma A.W.
      • Choi Y.
      • Kuijk P.F.V.
      • Wiemer E.A.
      • Kayser M.
      MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation.
      ]. But the body fluid specificity of miRNAs identified by the two teams did not overlap (Table 1). By employing the Geniom® Biochips, Courts et al. [
      • Courts C.
      • Madea B.
      Specific micro-RNA signatures for the detection of saliva and blood in forensic body-fluid identification.
      ] identified six miRNAs in venous blood and saliva, but did not investigate miRNA markers for menstrual blood, vaginal secretions and semen. Notably, 3 out of 7 candidate markers were also reported by other groups: miR16 and miR124a, Hanson et al. [
      • Hanson E.K.
      • Lubenow H.
      • Ballantyne J.
      Identification of forensically relevant body fluids using a panel of differentially expressed microRNAs.
      ], and miR891a, Zubakov et al. [
      • Zubakov D.
      • Boersma A.W.
      • Choi Y.
      • Kuijk P.F.V.
      • Wiemer E.A.
      • Kayser M.
      MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation.
      ]. Given our problems in screening other reported miRNA markers for forensically relevant body fluids, we examined these reported miRNA markers in our qPCR-array experiment and demonstrated that most of them were over-expressed in target body fluids (Supplemental Fig. 4). There may be several explanations for the observed discrepancies between our and published findings. First, different groups utilized different screening platforms, which imply differing sets of miRNAs and capture probes. Second, the relatively small sample size for screening, especially in our study, does not rule out the natural variation existing between individuals. Third, candidate miRNAs selected from microarray expression data to qPCR validation always retains some degree of arbitrariness, and there are no fixed rules as to which criteria have to be met for a miRNA to be chosen as a candidate. In the current study, for the purpose of finding the best candidate miRNA, we focused on the highly abundant (Cq ≤ 25), and thus, might have missed some moderately but specifically expressed miRNAs. All candidate miRNA markers selected from qPCR-array screening are the most over-expressed miRNAs in the respective body fluid (Supplemental Fig. 4), e.g., miR891a was only detectable in semen and was confirmed as a truly body fluid-specific miRNA by qPCR. This result is consistent with a research report that miR891a was present only in epididymis tissue and was practically absent from any other tissue analyzed [
      • Landgraf P.
      • Rusu M.
      • Sheridan R.
      • Sewer A.
      • Iovino N.
      • Aravin A.
      • et al.
      A mammalian microRNA expression atlas based on small RNA library sequencing.
      ].
      Obviously, variant miRNA microarray platforms and verification methodologies might result in discrepant candidate markers and slightly different amplification efficiencies, and therefore differing results from comparable samples. To our knowledge, the critical steps of investigating miRNA expression in body fluid identification are microarray screening, RGs validation, and data analysis.
      Microarrays have been widely used in miRNA profiling and can determine simultaneously the expression levels for large numbers of miRNAs in a single experiment [
      • Yin J.Q.
      • Zhao R.C.
      • Morris K.V.
      Profiling microRNA expression with microarrays.
      ]. However, the short length of miRNAs with inherently different melting temperatures (Tm) and the highly similar sequences between miRNA family members make probe design more difficult than mRNA arrays [
      • Saba R.
      • Booth S.A.
      Target labelling for the detection and profiling of microRNAs expressed in CNS tissue using microarrays.
      ]. The current lineup of commercially available miRNA microarray systems fails to show a good inter-platform concordance. The data generated from different microarray platforms and probing chemistries are inconsistent with those obtained from TaqMan-qPCR, which is a golden standard of miRNA measurement [
      • Sato F.
      • Tsuchiya S.
      • Terasawa K.
      • Tsujimoto G.
      Intra-platform repeatability and inter-platform comparability of microRNA microarray technology.
      ,
      • Chen Y.
      • Gelfond J.A.
      • McManus L.M.
      • Shireman P.K.
      Reproducibility of quantitative RT-PCR array in miRNA expression profiling and comparison with microarray analysis.
      ]. Zubakov et al. explained that they did not succeed in confirming their miRNA candidates for saliva, menstrual blood, and vaginal secretions because they used LNA™-modified oligonucleotides as capture probes, which may not be able to discriminate mature and unprocessed miRNA [
      • Zubakov D.
      • Boersma A.W.
      • Choi Y.
      • Kuijk P.F.V.
      • Wiemer E.A.
      • Kayser M.
      MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation.
      ]. Thus, in this study, we chose a TaqMan probe based-qPCR-array, which is based on the same founding principle of TaqMan-qPCR, to search potential body fluid-specific miRNAs candidates. Nevertheless, less concordance between qPCR-array and TaqMan-qPCR results was observed for saliva and vaginal secretions in this study. For example, miR138-2 was suggested as the best marker in saliva by the qPCR-Array (Supplemental Fig. 4E), but it cannot be validated by the TaqMan-qPCR. A possible explanation is that the saliva sample in array experiment underwent pre-amplification in our study. Although most of the miRNAs were uniformly pre-amplified, high variation associated with pre-amplification was observed for low abundant miRNAs [
      • Chen Y.
      • Gelfond J.A.
      • McManus L.M.
      • Shireman P.K.
      Reproducibility of quantitative RT-PCR array in miRNA expression profiling and comparison with microarray analysis.
      ]. Furthermore miR124a, the candidate marker for vaginal secretions, could not be effectively distinguished from menstrual blood according the TaqMan-qPCR results, possibly due to menstrual blood being a complex mixture containing products that also are detectable in vaginal secretions.
      The accuracy and success of qPCR analysis depends on proper normalization of data, which minimizes potential variation that can exaggerate or mask biologically meaningful changes. Several normalization strategies have been proposed, but the use of one or more RGs is the currently preferred method [
      • Vandesompele J.
      • Preter K.D.
      • Pattyn F.
      • Poppe B.
      • Roy N.V.
      • Paepe A.D.
      • et al.
      Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.
      ]. While RGs constitute the best possible normalizers, these genes have no constant expression under all experimental conditions, which poses a major problem. With the increased sensitivity, reproducibility and large dynamic range of real-time RT-PCR methods, the requirements for a proper RG have become increasingly stringent. Researchers therefore need to carefully assess whether a particular RG is stably expressed in the experimental system under study. Recently, Hruz et al. [
      • Hruz T.
      • Wyss M.
      • Docquier M.
      • Pfaffl M.W.
      • Masanetz S.
      • Borghi L.
      • et al.
      RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization.
      ] developed a tool named RefGenes for search RGs from a genome-wide background using microarray data. However, the data from our qPCR-array revealed that there were no miRNA RGs with universally stable expression across any type of body fluid. One possible explanation is that the sets of miRNA microarray data from forensically relevant body fluids were limited. Thus, we selected RNU44, RNU48, U6 and U6b as possible RGs due to their high abundance (P/N: 044972, Applied Biosystems) and literature reports [
      • Hanson E.K.
      • Lubenow H.
      • Ballantyne J.
      Identification of forensically relevant body fluids using a panel of differentially expressed microRNAs.
      ,
      • Zubakov D.
      • Boersma A.W.
      • Choi Y.
      • Kuijk P.F.V.
      • Wiemer E.A.
      • Kayser M.
      MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation.
      ,
      • Courts C.
      • Madea B.
      Specific micro-RNA signatures for the detection of saliva and blood in forensic body-fluid identification.
      ,
      • Wang Z.
      • Luo H.B.
      • Pan X.F.
      • Liao M.
      • Hou Y.P.
      A model for data analysis of microRNA expression in forensic body fluid identification.
      ,
      • Li Y.
      • Wang Z.
      • Hou Y.P.
      MiR16 as a microRNA marker applied in species identification.
      ]. Results from the BestKeeper software revealed that only U6 could be a proper RG in our study. However, we should keep in mind that, in order to remove the non-biological variation as much as possible, and to measure accurate expression levels, a joint use of multiple RGs is necessary [
      • Vandesompele J.
      • Preter K.D.
      • Pattyn F.
      • Poppe B.
      • Roy N.V.
      • Paepe A.D.
      • et al.
      Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.
      ]. The study of miRNAs in forensically relevant body fluids is still at an exploratory stage and more research for searching the generally accepted RGs for forensically relevant body fluids is intensively needed.
      How to present the qPCR data is essential in miRNA expression study. One simple method to process qPCR, currently known as the ΔΔCq method, is based solely on Cq values [
      • Livak K.J.
      • Schmittgen T.D.
      Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) method.
      ]. This method assumes that all amplification efficiencies are equal to 1, which does not take into consideration possible variations of amplification efficiencies. Different tissues exhibit different PCR efficiencies due to RT inhibitors, PCR inhibitors, and variations in the total extracted RNA fraction. Numerous published studies reported that the PCR efficiency has a major impact on the accuracy of calculated expression values [
      • Karlen Y.
      • McNair A.
      • Perseguers S.
      • Mazza C.
      • Mermod N.
      Statistical significance of quantitative PCR.
      ,
      • Huggett J.
      • Dheda K.
      • Bustin S.
      • Zumla A.
      Real-time RT-PCR normalisation; strategies and considerations.
      ], and similar results were found in our previous study [
      • Wang Z.
      • Luo H.B.
      • Pan X.F.
      • Liao M.
      • Hou Y.P.
      A model for data analysis of microRNA expression in forensic body fluid identification.
      ]. However, its ease of use makes it ideal to screen changes rapidly in the expression level, after which a finer analysis on the genes displaying interesting expression profiles may be performed using a more accurate model. Soong et al. [
      • Soong R.
      • Ruschoff J.
      • Tabiti K.
      Detection of Colorectal Micrometastasis by Quantitative RT-PCR of Cytokeratin 20 mRNA.
      ] proposed an efficiency-calibrated mathematical method for the relative expression ratio in qPCR. The advantage of the efficiency-calibrated method is that the PCR efficiencies of targets and RGs are included in the equation, making the data analysis more accurate [
      • Wang Z.
      • Luo H.B.
      • Pan X.F.
      • Liao M.
      • Hou Y.P.
      A model for data analysis of microRNA expression in forensic body fluid identification.
      ,
      • Pfaffl M.W.
      A new mathematical model for relative quantification in real-time RT-PCR.
      ,
      • Soong R.
      • Ruschoff J.
      • Tabiti K.
      Detection of Colorectal Micrometastasis by Quantitative RT-PCR of Cytokeratin 20 mRNA.
      ]. In our study, we utilized the gradient dilution cDNA method to test the amplification efficiencies of target and RG in body fluids. Results showed that the amplification efficiencies were not always equal to 1 (Fig. 2).
      Currently, over 1000 mature miRNAs have been identified in the human genome (miRBase v18, November 2011). It remains necessary to search for suitable miRNA markers and stable RGs for forensically relevant body fluids. During the initial screening experiments of the current study, pooled samples were used to account for the possible inter-individual variation of miRNA expression, variations in the total extracted RNA fraction, and varied RT efficiency. However, it may not effectively rule out the natural variation between individuals and may lead to omission of some body fluid-specific miRNAs. Biological replicates array experiments will be required for further screening of body fluid-specific miRNAs (related research is in progress in our lab).
      Biological stains from forensic casework are often challenged by ambient moisture and temperature, UV light, suboptimal environmental pH, affecting the detection of the aged samples. We established artificial environment to test degradation stability of miRNA markers in this study. We found that absolute expression levels of selected miRNAs were slightly decreased but their ΔCq values remained unchanged. Whether the aged samples contained small fragments degraded from large molecules affecting the amplification efficiency (inhibitors) or the miRNA degraded due to environmental factors, validation studies must still be performed.
      Although this study failed to identify miRNA specific to saliva and vaginal secretions, we were able to screen and confirm five body fluid-specific miRNAs, three of which were new miRNA markers: miR486, miR888, and miR214.

      5. Conclusions

      With qPCR-array screening and subsequent TaqMan-qPCR validation, five body fluid-specific miRNAs were proposed for body fluid identification (miR16 and miR486 for venous blood, miR888 and miR891a for semen, and miR214 for menstrual blood) and their detection were highly sensitive. Our results highlight three new miRNA markers (miR486, miR888, and miR214) and a suitable RG (U6) for body fluid identification. Although current studies support the potential use of these miRNAs to identify the body fluid origin of forensic biological samples, we failed to identify saliva- and vaginal secretions-specific miRNAs. Additional work must be performed to further search for suitable miRNA markers and stable RGs for forensic body fluid identification. Moreover, a profound analysis of potential environmental impacts, such as humidity, UV radiation, and bacterial contamination, remains necessary.

      Conflict of interest

      The authors declare that they have no conflict of interest.

      Acknowledgments

      This study was supported by grants from the National Nature Science Foundation of China (No. 81072510), the Research Fund for the Doctoral Program of Higher Education of China (No. 20100181110047) and the Five-twelfth’ National Science and Technology Support Program of China.

      Appendix A. Supplementary data

      The following are the supplementary data to this article:
      Figure thumbnail mmc1
      Supplemental Fig. 1Descriptive statistics of four candidate RGs (housekeeping genes in software) based on their Cq values. Any RGs with the SD higher than 1 (=starting template variation by the factor 2) can be considered inconsistent according the manual of BestKeeper.
      Figure thumbnail mmc2
      Supplemental Fig. 2The changes of expression level of miR486, miR16, miR888, miR891a, miR214 and U6 in time-wise-degraded samples (mean ± SD; n = 3).
      Figure thumbnail mmc3
      Supplemental Fig. 3Serial dilutions of total RNA (ranging from 10 ng to 0.01 ng) isolated from body fluids sample as input for cDNA synthesis to establish the detection sensitivity of TaqMan RT-PCR assays.
      Figure thumbnail mmc4
      Supplemental Fig. 4The relative expression level of reported body fluid-specific miRNAs in our initial screening experiments. Values underwent log2 transformation. (A) Reported venous blood-specific miRNAs, venous blood was designated as the normalizer, (B) reported menstrual blood-specific miRNAs, menstrual blood was designated as the normalizer, (C) reported semen-specific miRNAs, semen was designated as the normalizer, (D) reported vaginal secretions-specific miRNAs, vaginal secretions was designated as the normalizer, (E) reported saliva-specific miRNAs, saliva was designated as the normalizer.

      References

        • Gaensslen R.E.
        Sourcebook in Forensic Serology, Immunology, and Biochemistry.
        U.S. Department of Justice, Washington, DC1983
        • Ponce A.C.
        • Pascual F.A.V.
        Critical revision of presumptive tests for bloodstains.
        Forensic Sci. Commun. 1999; 1: 1-15
        • Khaldi N.
        • Miras A.
        • Botti K.
        • Benali L.
        • Gromb S.
        Evaluation of three rapid detection methods for the forensic identification of seminal fluid in rape cases.
        J. Forensic Sci. 2004; 49: 749-753
        • Tobe S.S.
        • Watson N.
        • Daéid N.N.
        Evaluation of six presumptive tests for blood, their specificity, sensitivity, and effect on high molecular-weight DNA.
        J. Forensic Sci. 2007; 52: 102-109
        • Mayers J.R.
        • Adkins W.K.
        Comparison of modern techniques for saliva screening.
        J. Forensic Sci. 2008; 53: 862-867
        • Juusola J.
        • Ballantyne J.
        Messenger RNA profiling: a prototype method to supplant conventional methods for body fluid identification.
        Forensic Sci. Int. 2003; 135: 85-96
        • Juusola J.
        • Ballantyne J.
        Multiplex mRNA profiling for the identification of body fluids.
        Forensic Sci. Int. 2005; 152: 1-12
        • Juusola J.
        • Ballantyne
        mRNA profiling for body fluid identification by multiplex quantitative RT-PCR.
        J. Forensic Sci. 2007; 52: 1252-1262
        • Setzer M.
        • Juusola J.
        • Ballantyne J.
        Recovery and stability of RNA in vaginal swabs and blood, semen, and saliva stains.
        J. Forensic Sci. 2008; 53: 296-305
        • Zubakov D.
        • Kokshoorn M.
        • Kloosterman A.
        • Kayser M.
        New markers for old stains: stable mRNA markers for blood and saliva identification from up to 16-year-old stains.
        Int. J. Legal Med. 2009; 123: 71-74
        • Bartel D.P.
        MicroRNAs: genomics, biogenesis, mechanism, and function.
        Cell. 2004; 116: 281-297
        • Kim V.N.
        MicroRNA biogenesis: coordinated cropping and dicing.
        Nat. Rev. Mol. Cell Biol. 2005; 6: 376-385
        • Kim V.N.
        • Han J.
        • Siomi M.C.
        Biogenesis of small RNAs in animals.
        Nat. Rev. Mol. Cell Biol. 2009; 10: 126-139
        • Gu S.
        • Jin L.
        • Zhang F.
        • Sarnow P.
        • Kay M.A.
        Biological basis for restriction of microRNA targets to the 3′ untranslated region in mammalian mRNAs.
        Nat. Struct. Mol. Biol. 2009; 16: 144-150
        • Rana T.M.
        Illuminating the silence: understanding the structure and function of small RNAs.
        Nat. Rev. Mol. Cell Biol. 2007; 8: 23-36
        • Tavazoie S.F.
        • Alarcón C.
        • Oskarsson T.
        • Padua D.
        • Wang Q.
        • Bos P.D.
        • et al.
        Endogenous human microRNAs that suppress breast cancer metastasis.
        Nature. 2008; 451: 147-152
        • Hwang H.W.
        • Mendell J.T.
        MicroRNAs in cell proliferation, cell death, and tumorigenesis.
        Br. J. Cancer. 2006; 94: 776-780
        • Sood P.
        • Krek A.
        • Zavolan M.
        • Macino G.
        • Rajewsky N.
        Cell-type-specific signatures of microRNAs on target mRNA expression.
        Proc. Natl. Acad. Sci. U. S. A. 2006; 103: 2746-2751
        • Liang Y.
        • Ridzon D.
        • Wong L.
        • Chen C.
        Characterization of microRNA expression profiles in normal human tissues.
        BMC Genomics. 2007; 8: 166
        • Leite K.R.
        • Canavez J.M.
        • Reis S.T.
        • Tomiyama A.H.
        • Piantino C.B.
        • Sañudo A.
        • et al.
        miRNA analysis of prostate cancer by quantitative real time PCR: comparison between formalin-fixed paraffin embedded and fresh-frozen tissue.
        Urol. Oncol. 2011; 19: 533-537
        • Hui A.B.
        • Shi W.
        • Boutros P.C.
        • Miller N.
        • Pintilie M.
        • Fyles T.
        • et al.
        Robust global micro-RNA profiling with formalin-fixed paraffin-embedded breast cancer tissues.
        Lab. Invest. 2009; 89: 597-606
        • Hanson E.K.
        • Lubenow H.
        • Ballantyne J.
        Identification of forensically relevant body fluids using a panel of differentially expressed microRNAs.
        Anal. Biochem. 2009; 387: 303-314
        • Zubakov D.
        • Boersma A.W.
        • Choi Y.
        • Kuijk P.F.V.
        • Wiemer E.A.
        • Kayser M.
        MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation.
        Int. J. Legal Med. 2010; 124: 217-226
        • Courts C.
        • Madea B.
        Specific micro-RNA signatures for the detection of saliva and blood in forensic body-fluid identification.
        J. Forensic Sci. 2011; 56: 1464-1470
        • Wang Z.
        • Luo H.B.
        • Pan X.F.
        • Liao M.
        • Hou Y.P.
        A model for data analysis of microRNA expression in forensic body fluid identification.
        Forensic Sci. Int. Genet. 2012; 6: 419-423
        • Li Y.
        • Wang Z.
        • Hou Y.P.
        MiR16 as a microRNA marker applied in species identification.
        Forensic Sci. Int. Genet. Suppl. Ser. 2011; 1: e313-e314
        • Guthrie J.L.
        • Seah C.
        • Brown S.
        • Tang P.
        • Jamieson F.
        • Drews S.J.
        Use of Bordetella pertussis BP3385 to establish a cutoff value for an IS481-targeted real-time PCR assay.
        J. Clin. Microbiol. 2008; 46: 3798-3799
        • Pfaffl M.W.
        • Tichopad A.
        • Prgomet C.
        • Neuvians T.P.
        Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper – Excel-based tool using pair-wise correlations.
        Biotechnol. Lett. 2004; 26: 509-515
        • Pfaffl M.W.
        A new mathematical model for relative quantification in real-time RT-PCR.
        Nucleic Acids Res. 2001; 29: e45
        • Soong R.
        • Ruschoff J.
        • Tabiti K.
        Detection of Colorectal Micrometastasis by Quantitative RT-PCR of Cytokeratin 20 mRNA.
        Roche Diagnostics Internal Publication, 2000
        • Landgraf P.
        • Rusu M.
        • Sheridan R.
        • Sewer A.
        • Iovino N.
        • Aravin A.
        • et al.
        A mammalian microRNA expression atlas based on small RNA library sequencing.
        Cell. 2007; 129: 1401-1414
        • Yin J.Q.
        • Zhao R.C.
        • Morris K.V.
        Profiling microRNA expression with microarrays.
        Trends Biotechnol. 2008; 26: 70-76
        • Saba R.
        • Booth S.A.
        Target labelling for the detection and profiling of microRNAs expressed in CNS tissue using microarrays.
        BMC Biotechnol. 2006; 6: 47
        • Sato F.
        • Tsuchiya S.
        • Terasawa K.
        • Tsujimoto G.
        Intra-platform repeatability and inter-platform comparability of microRNA microarray technology.
        PLoS One. 2009; 5: e5540
        • Chen Y.
        • Gelfond J.A.
        • McManus L.M.
        • Shireman P.K.
        Reproducibility of quantitative RT-PCR array in miRNA expression profiling and comparison with microarray analysis.
        BMC Genomics. 2009; 10: 407
        • Vandesompele J.
        • Preter K.D.
        • Pattyn F.
        • Poppe B.
        • Roy N.V.
        • Paepe A.D.
        • et al.
        Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.
        Genome Biol. 2002; 3: 34
        • Hruz T.
        • Wyss M.
        • Docquier M.
        • Pfaffl M.W.
        • Masanetz S.
        • Borghi L.
        • et al.
        RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization.
        BMC Genomics. 2011; 12: 156
        • Livak K.J.
        • Schmittgen T.D.
        Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) method.
        Methods. 2001; 25: 402-408
        • Karlen Y.
        • McNair A.
        • Perseguers S.
        • Mazza C.
        • Mermod N.
        Statistical significance of quantitative PCR.
        BMC Bioinformatics. 2007; 20: 131
        • Huggett J.
        • Dheda K.
        • Bustin S.
        • Zumla A.
        Real-time RT-PCR normalisation; strategies and considerations.
        Genes Immunity. 2005; 4: 279-284