Impact of using validated or standard reference genes for miRNA qPCR data normalization in cell type identification

A Comprehensive Characterization of Small RNA Profiles by Massively Parallel Sequencing in Six Forensic Body Fluids/Tissue

Body fluids/tissue identification (BFID) is an essential procedure in forensic practice, and RNA profiling has become one of the most important methods. Small non-coding RNAs, being expressed in high copy numbers and resistant to degradation, have great potential in BFID but have not been comprehensively characterized in common forensic stains. In this study, the miRNA, piRNA, snoRNA, and snRNA were sequenced in 30 forensic relevant samples (menstrual blood, saliva, semen, skin, venous blood, and vaginal secretion) using the BGI platform. Based on small RNA profiles, relative specific markers (RSM) and absolute specific markers (ASM) were defined, which can be used to identify a specific body fluid/tissue out of two or six, respectively. A total of 5204 small RNAs were discovered including 1394 miRNAs (including 236 novel miRNA), 3157 piRNAs, 636 snoRNAs, and 17 snRNAs. RSMs for 15 pairwise body fluid/tissue groups were discovered by differential RNA analysis. In addition, 90 ASMs that were specifically expressed in a certain type of body fluid/tissue were screened, among them, snoRNAs were reported first in forensic genetics. In brief, our study deepened the understanding of small RNA profiles in forensic stains and offered potential BFID markers that can be applied in different forensic scenarios.

Feasibility of using probabilistic methods to analyse microRNA quantitative data in forensically relevant body fluids: a proof-of-principle study

Several studies have confirmed that microRNAs (miRNAs) are promising markers for body fluid identification since they were introduced to this field. However, there is no consensus on the choice of reference genes and identification strategies. In this study, 13 potential candidate miRNAs were screened from three forensically relevant body fluid datasets, and the expression of 12 markers in five body fluids was determined using a real-time quantitative method. Two probabilistic approaches, Naive Bayes (NB) and partial least squares discriminant analysis (PLS-DA), were then applied to predict the origin of the samples to determine whether probabilistic methods are helpful in body fluid identification using miRNA quantitative data. Furthermore, 14 reference combinations were used to validate the influence of different reference choices on the predicted results simultaneously. Our results showed that in the NB model, leave-one-out cross-validation (LOOCV) achieved 100% accuracy and the prediction accuracy of the test set was 100% in most reference combinations. In the PLS-DA model, the first two components could interpret about 80% expression variance and LOOCV achieved 100% accuracy when miR-92a-3p was used as the reference. This study preliminarily proved that probabilistic approaches hold huge potential in miRNA-based body fluid identification, and the choice of references influences the prediction results to a certain extent.

Expression profile analysis and stability evaluation of 18 small RNAs in the Chinese Han population

In recent years, differentially expressed small RNAs have been widely used to identify the compositions of forensically relevant biological samples, and a vast number of such RNA candidates have been proposed. Nevertheless, when assessing the expression levels of target small RNAs using relative quantitative analysis methods, credible internal controls are usually required for reliable data normalization. Therefore, the identification of optimal reference genes is an important task. In this study, the expression profile of 18 small RNA reference genes was characterized in the Chinese Han population using TaqMan real-time quantitative PCR. Systematic evaluations of these candidate genes were performed based on their expression levels and stability in several common types of body fluids (i.e., venous blood, menstrual blood, saliva, semen, and vaginal secretions). Analysis results from the ΔCq method, BestKeeper, NormFinder, and geNorm were integrated by RefFinder for ranking and comparing the candidates in each type of body fluid. Among all the candidates, miR-191 was identified as the most suitable reference gene because it had a favorable ranking value in all tested samples. In addition, miR-423, miR-93, miR-484, and let-7i were also shown to be applicable reference genes. Overall, this study provides detailed assessment results of these candidate genes in different body fluids; thus, it could be used as a guide for the selection of reference genes according to their performance in the sample of choice.

Optimal small-molecular reference RNA for RT-qPCR-based body fluid identification

MicroRNA (miRNA) -based body fluid identification (BFID) plays a prominent role in a forensic practice, and the selected reference RNA is indispensable for a robust normalization in BFID performed using reverse transcription-quantitative PCR. In this study, we first examined sample quality using RNA integrity number, then evaluated the consistency of expression of candidate reference RNAs in 4 forensically relevant body fluids using NormFinder and BestKeeper, and lastly used each rank and index output from these tools for selecting the optimal reference RNA and the combination of the multiple RNAs using the RankAggreg package of R. We found that RNA integrity number was small in our samples, despite the use of pristine body fluids; 5S-rRNA was the optimal reference RNA for the identification of forensically relevant body fluids; and the combination of 5S-rRNA and miR-92a-3p and/or miR-484 enhanced the normalization quality. Our findings enable us to perform stringent normalization of the expression of body fluid-specific RNAs, and thus, can contribute to the development of small RNA-based BFID systems.

A capillary electrophoresis method for identifying forensically relevant body fluids using miRNAs

Body fluid identification (BFID) can provide crucial information during the course of an investigation. In recent years, microRNAs (miRNAs) have shown considerable body fluid specificity, are able to be co-extracted with DNA, and their small size (18-25 nucleotides) make them ideal for analyzing highly degraded forensic samples. In this study, we designed a preliminary 8-marker system for BFID including an endogenous reference gene (let-7g) to differentiate between venous blood (miR-451a and miR-142-3p), menstrual blood (miR-141-3p and miR-412-3p), semen (miR-891a and miR-10b), and saliva (miR-205) using a capillary electrophoresis approach. This panel uses a linear primer system in order to incorporate additional miRNA markers by forming a multiplex system. The miRNA system was able to distinguish between venous blood, menstrual blood, semen, and saliva using a rudimentary data interpretation strategy. All STR amplifications from co-extracted DNA yielded complete profiles from human identification purposes.

Evaluating the forensic application of 19 target microRNAs as biomarkers in body fluid and tissue identification

RNA-based body fluid and tissue identification has evolved as a promising and reliable new technique to classify type and source of biological evidence in crime cases. In particular, mRNA-based approaches are currently on the rise to replace conventional protein-based methods and are increasingly implemented into forensic casework. However, degradation of these nucleic acid molecules can cause issues on laboratory scale and need to be considered for a credible investigation. For this reason, the analysis of miRNAs using qPCR has been proposed to be a sensitive and specific approach to identify the origin of a biological trace taking advantage of their small size and resistance to degradation. Despite the straightforward workflow of this method, suitable endogenous controls are inevitable when performing real-time PCR to ensure accurate normalization of gene expression data in order to allow a meaningful interpretation. In this regard, we have validated reference genes for a set of forensically relevant body fluids and tissues (blood, saliva, semen, vaginal secretions, menstrual blood and skin) and tested 15 target genes aiming to identify abovementioned sample types. Our data showed that preselected endogenous controls (miR26b, miR92 and miR484) and miR144, initially selected as potential marker for the detection of menstrual blood, were the most stable expressed genes among our set of samples. Normalizing qPCR data with these four validated references revealed that only five miRNA markers are necessary to differentiate between the six different cell types selected in this study. Nevertheless, our observations in the present study indicate that miRNA analysis methods may not provide straightforward data interpretation strategies required for an implementation in forensic casework.