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

A multi-class support vector machine classification model based on 14 microRNAs for forensic body fluid identification

MicroRNAs (miRNAs) are promising biomarkers for forensic body fluid identification owing to their small size, stability against degradation, and differential expression patterns. However, the expression of most body fluid-miRNAs is relative (differentially expressed in certain body fluids) rather than absolute (exclusively expressed in a specific body fluid). Moreover, different body fluids contain heterogeneous cell types, complicating their identification. Therefore, appropriate normalization strategies to eliminate non-biological variations and robust models to interpret expression levels accurately are necessary prerequisites for applying miRNAs in body fluid identification. In this study, the expression stability of six candidate reference genes (RGs) across five body fluids was validated using geNorm, NormFinder, BestKeeper and RankAggreg, and the most suitable combination of RGs (hsa-miR-484 and hsa-miR-191-5p) was identified under our experimental conditions. Subsequently, we systematically evaluated the expression patterns of the 28 most promising body fluid-specific miRNA markers using TaqMan RT-qPCR and selected the optimal combination of markers (12 miRNAs) to establish a multi-class support vector machine (MSVM) classification model. An independent test set (60 samples) was used to validate the accuracy of the proposed classification model, while an additional 30 casework samples were used to assess its robustness. The MSVM model accurately predicted the body fluid origin for almost all (59/60) single-source samples. Moreover, this model demonstrated the capability to identify aged forensic samples and to predict the primary components of mixed stains to a certain extent. In summary, this study presented a miRNA-based MSVM classification model for forensic body fluid identification using the qPCR platform. However, extensive validation, especially inter-laboratory collaborative exercises, is necessary before miRNA can be routinely applied in forensic identification practice.

Benchmarking miRNA reference genes in B-cell precursor acute lymphoblastic leukemia

MicroRNAs (miRNAs) play dual roles in acute lymphoblastic leukemia (ALL) as both tumor suppressors and oncogenes, and miRNA expression profiles can be used for patient risk stratification. Precise assessment of miRNA levels is crucial for understanding their role and function in gene regulation. Quantitative real-time polymerase chain reaction (qPCR) is a reliable, rapid, and cost-effective method for analyzing miRNA expression, assuming that appropriate normalization to stable references is performed to ensure valid data. In this study, we evaluated the stability of six commonly used miRNA references (5sRNA, SNORD44, RNU6, RNU1A1, miR-103a-3p, and miR-532-5p) across nine B-cell precursor (BCP) ALL cell lines, 22 patient-derived xenograft (PDX) BCP ALL samples from different organ compartments of leukemia bearing mice, and peripheral blood mononuclear cells (PBMCs) from six healthy donors. We used four different algorithms (Normfinder, ∆CT, geNorm, and BestKeeper) to assess the most stably expressed reference across all samples. Moreover, we validated our data in an additional set of 13 PDX ALL samples and six healthy controls, identifying miR-103a-3p and miR-532-5p as the most stable references for miRNA normalization in BCP ALL studies. Additionally, we demonstrated the critical importance of using a stable reference to accurately interpret miRNA data.

Comprehensive body fluid identification and contributor assignment by combining targeted sequencing of mRNA and coding region SNPs

Forensic genetic analyses aim to retrieve as much information as possible from biological trace material recovered from crime scenes. While standard short tandem repeat (STR) profiling is essential to individualize biological traces, its significance is diminished in crime scenarios where the presence of a suspect's DNA is acknowledged by all parties. In such cases, forensic (m)RNA analysis can provide crucial contextualizing information on the source level about a trace's composition, i.e., body fluids/tissues, and has therefore emerged as a powerful tool for modern forensic investigations. However, the question which of several suspects contributed a specific component (body fluid) to a mixed trace cannot be answered by RNA analysis using conventional methods. This individualizing information is stored within the sequence of the mRNA transcripts. Massively parallel sequencing (MPS) represents a promising alternative, offering not only higher multiplex capacity, but also the typing of individual coding region SNPs (cSNPs) to enable the assignment of contributors to mixture components, thereby reducing the risk of association fallacies. Herein, we describe the development of an extensive mRNA/cSNP panel for targeted sequencing on the IonTorrent S5 platform. Our panel comprises 30 markers for the detection of six body fluids/tissues (blood, saliva, semen, skin, vaginal and menstrual secretion), along with 70 linkage-controlled cSNPs for contributor assignment. It exhibited high reliable detection sensitivity with RNA inputs down to 0.75 ng and a conservatively calculated probability of identity of 0.03 - 6 % for individual body fluid-specific cSNP profiles. Limitations and areas for future work include RNA-related allele imbalances, inclusion of markers to correctly identify rectal mucosa and the optimization of specific markers. In summary, our new panel is intended to be a major step forward to interpret biological evidence at sub-source and source level based on cSNP attribution of a body fluid component to a suspect and victim, respectively.

Differentiation of five forensically relevant body fluids using a small set of microRNA markers

In forensic investigations, identifying the type of body fluid allows for the interpretation of biological evidence at the activity level. Over the past two decades, significant research efforts have focused on developing molecular methods for this purpose. MicroRNAs (miRNAs) hold great promise due to their tissue-specific expression, abundance, lack of splice variants, and relative stability. Although initial findings are promising, achieving consistent results across studies is still challenging, underscoring the necessity for both original and replication studies. To address this, we selected 18 miRNA candidates and tested them on 6 body fluids commonly encountered in forensic cases: peripheral blood, menstrual blood, saliva, semen, vaginal secretion, and skin. Using reverse transcription quantitative PCR analysis, we confirmed eight miRNA candidates (miR-144-3p, miR-451a, miR-205-5p, miR-214-3p, miR-888-5p, miR-891a-5p, miR-193b-3p, miR-1260b) with high tissue specificity and four (miR-203a-3p, miR-141-3p, miR-200b-3p, miR-4286) with lesser discrimination ability but still contributing to body fluid differentiation. Through principal component analysis and hierarchical clustering, the set of 12 miRNAs successfully distinguished all body fluids, including the challenging discrimination of blood from menstrual blood and saliva from vaginal secretion. In conclusion, our results provide additional data supporting the use of a small set of miRNAs for predicting common body fluids in forensic contexts. Large population data need to be gathered to develop a body fluid prediction model and assess its accuracy.

A combined molecular approach utilizing microbial DNA and microRNAs in a qPCR multiplex for the classification of five forensically relevant body fluids

Body fluid identification is an essential step in the forensic biology workflow that can assist DNA analysts in determining where to collect DNA evidence. Current presumptive tests lack the specificity that molecular techniques can achieve; therefore, molecular methods, including microRNA (miRNA) and microbial signature characterization, have been extensively researched in the forensic community. Limitations of each method suggest combining molecular markers to increase the discrimination efficiency of multiple body fluids from a single assay. While microbial signatures have been successful in identifying fluids with high bacterial abundances, microRNAs have shown promise in fluids with low microbial abundance (blood and semen). This project synergized the benefits of microRNAs and microbial DNA to identify multiple body fluids using DNA extracts. A reverse transcription (RT)-qPCR duplex targeting miR-891a and let-7g was validated, and miR-891a differential expression was significantly different between blood and semen. The miRNA duplex was incorporated into a previously reported qPCR multiplex targeting 16S rRNA genes of Lactobacillus crispatus, Bacteroides uniformis, and Streptococcus salivarius to presumptively identify vaginal/menstrual secretions, feces, and saliva, respectively. The combined classification regression tree model resulted in the presumptive classification of five body fluids with 94.6% overall accuracy, now including blood and semen identification. These results provide proof of concept that microRNAs and microbial DNA can classify multiple body fluids simultaneously at the quantification step of the current forensic DNA workflow.

Screening and evaluation of endogenous reference genes for miRNA expression analysis in forensic body fluid samples

MicroRNA (miRNA)-based methods for body fluid identification are promising tools in the practice of forensic science. The selection of appropriate endogenous reference genes as normalizers for the relative quantification of miRNA expression levels using quantitative reverse transcription-polymerase chain reaction (RTqPCR) is essential to avoid errors and improve the comparability of miRNA expression level data among different body fluids. In this study, small RNAs were isolated from individual donations of five forensically relevant body fluids (peripheral blood, menstrual blood, saliva, semen and vaginal secretions). Thirty-seven samples were subjected to high-throughput miRNA sequencing. By combining our results with those obtained through a literature investigation, 28 candidate RNAs were identified. Following RTqPCR validation, the candidate RNAs were preliminarily evaluated in 15 samples to exclude miRNAs with low expression and high variation. Then, the expression levels of 10 relatively stable candidate reference RNAs in 100 samples were determined and further analysed using four commonly employed programs (geNorm, NormFinder, BestKeeper and ΔCq). According to the comprehensive stability rankings of the four algorithms, miR-320a-3p was validated as the most stable endogenous reference gene among the five forensically relevant body fluids, followed by miR-484, SNORD43, miR-320c and RNU6b. Moreover, the combined application of miR-320a-3p with RNU6b could increase the normalization effect. In addition, a total of 56 mock samples placed outdoors and indoors for different times were prepared to further evaluate the stability of candidate reference RNAs, and miR-320a-3p remained the preferred reference gene. Furthermore, the relative expression levels of publicly accepted body fluid-specific miRNAs were determined in 30 samples to verify the practicality and effectiveness of the reference genes. Our results revealed a set of alternative reference genes and could promote the development and application of miRNA-based body fluid identification by determining optional reference genes for strict normalization.

Improved Bladder Tumor RNA Isolation from Archived Tissues Using Methylene Blue for Normalization, Multiplex RNA Hybridization, Sequencing and Subtyping

Methylene blue (MB) is a dye used for histology with clinical importance and intercalates into nucleic acids. After MB staining of formalin fixed paraffin embedded (FFPE) muscle invasive bladder cancer (MIBC) and normal urothelium, specific regions could be microdissected. It is not known if MB influences RNA used for gene expression studies. Therefore, we analyzed MIBC using five different RNA isolation methods comparing patient matched FFPE and fresh frozen (FF) tissues pre-stained with or without MB. We demonstrate a positive impact of MB on RNA integrity with FF tissues using real time PCR with no interference of its chemical properties. FFPE tissues showed no improvement of RNA integrity, which we propose is due to formalin induced nucleotide crosslinks. Using direct multiplex RNA hybridization the best genes for normalization of MIBC and control tissues were identified from 34 reference genes. In addition, 5SrRNA and 5.8SrRNA were distinctive reference genes detecting <200 bp fragments important for mRNA analyses. Using these normalized RNAs from MB stained MIBC and applying multiplex RNA hybridization and mRNA sequencing, a minimal gene expression panel precisely identified luminal and basal MIBC tumor subtypes, important for diagnosis, prognosis and chemotherapy response.

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.

Identification of five types of forensic body fluids based on stepwise discriminant analysis

Peripheral blood, menstrual blood, semen, saliva and vaginal secretions are the five most common body fluids found at crime scenes, and the identification of these five body fluids is of great significance to the reconstruction of a crime scene and resolution of the case. However, accurate identification of these five body fluids is still a challenge. To address this problem, a mathematical model for differentiating five types of forensic body fluids based on the differential expression characteristics of multiple miRNAs in five body fluids (peripheral blood, menstrual blood, semen, saliva and vaginal secretions) was developed. A total of 350 forensic body fluids (70 of each type) were collected and tested, and relative expression of 10 miRNAs (miR-451a, miR-205-5p, miR-203-3p, miR-214-3p, miR-144-3p, miR-144-5p, miR-654-5p, miR-888-5p, miR-891a-5p, miR-124a-3p) in all samples was detected by SYBR Green real-time qPCR. Three hundred samples (60 samples of each body fluid) were used as the training set to screen meaningful identification markers by stepwise discriminant analysis, and a discriminant function was established. Fifty samples (10 samples of each body fluid) were used as a validation set to examine the accuracy of the model, and 25 samples (the types of samples were unknown to the experimenter) were used for a blind test. Except for miR-144-3p, the other miRNAs were selected to construct discriminant analysis models. The self-validation accuracy of the model was 99.7 %, cross-validation accuracy was 99.3 %, accuracy of the identification validation set was 100 %, and accuracy of the blind test result was 100 %. This study provides a reliable and accurate identification strategy for five common body fluids (peripheral blood, menstrual blood, semen, saliva, and vaginal secretions) in forensic medicine.

A systemic approach to screening high-throughput RT-qPCR data for a suitable set of reference circulating miRNAs

Background

The consensus on how to choose a reference gene for serum or plasma miRNA expression qPCR studies has not been reached and none of the potential candidates have yet been convincingly validated. We proposed a new in silico approach of finding a suitable reference for human, circulating miRNAs and identified a new set of endogenous reference miRNA based on miRNA profiling experiments from Gene Expression Omnibus. We used 3 known normalization algorithms (NormFinder, BestKeeper, GeNorm) to calculate a new normalization score. We searched for a universal set of endogenous miRNAs and validated our findings on 2 new datasets using our approach.

Results

We discovered and validated a set of 13 miRNAs (miR-222, miR-92a, miR-27a, miR-17, miR-24, miR-320a, miR-25, miR-126, miR-19b, miR-199a-3p, miR-30b, miR-30c, miR-374a) that can be used to create a reliable reference combination of 3 miRNAs. We showed that on average the mean of 3 miRNAs (p = 0.0002) and 2 miRNAs (p = 0.0031) were a better reference than single miRNA. The arithmetic means of 3 miRNAs: miR-24, miR-222 and miR-27a was shown to be the most stable combination of 3 miRNAs in validation sets.

Conclusions

No single miRNA was suitable as a universal reference in serum miRNA qPCR profiling, but it was possible to designate a set of miRNAs, which consistently contributed to most stable combinations.

Distinct spectrum of microRNA expression in forensically relevant body fluids and probabilistic discriminant approach

MicroRNA is attracting worldwide attention as a new marker for the identification of forensically relevant body fluids. A probabilistic discriminant model was constructed to identify venous blood, saliva, semen, and vaginal secretion, based on microRNA expression assessed via RT-qPCR. We quantified 15 candidate microRNAs in four types of body fluids by RT-qPCR and found that miR-144-3p, miR-451a-5p, miR-888-5p, miR-891a-5p, miR-203a-3p, miR-223-3p and miR-1260b were helpful to discriminate body fluids. Using the relative expression of seven candidate microRNAs in each body fluid, we implemented a partial least squares-discriminant analysis (PLS-DA) as a probabilistic discriminant model and distinguished four types of body fluids. Of 14 testing samples, 13 samples were correctly identified with >90% posterior probability. We also investigated the effects of microRNA expression in skin, semen infertility, and vaginal secretion during different menstrual phases. Semen infertility and menstrual phases did not affect our body fluid identification system. Therefore, the selected microRNAs were effective in identifying the four types of body fluids, indicating that probabilistic evaluation may be practical in forensic casework.

The expression of 10 candidate specific microRNA markers for human body fluid identification in animal buccal swabs

MicroRNAs (miRNAs) have been of interest in forensic science for body fluid identification with recent years. However, there is no study investigating the species specificity of miRNA markers by the SYBR Green method. Due to the conservation of miRNAs across species, miRNA markers maybe less species-specific than mRNA markers, and in forensic cases, animal buccal swabs are more likely to appear. Therefore, in this study we addressed the influence of 8 kinds of animal buccal swabs on human saliva, semen, vaginal secretion swabs and blood identification with 10 candidate specific miRNA markers by the SYBR Green quantitative PCR. Our data showed that the expression levels of the candidate specific miRNA markers miR-124a and 372 in the cat, dog, mouse and rabbit buccal swabs were in the same range as the human vaginal secretion swabs; buccal swabs from these animals also showed similar expression levels to human saliva for the candidate specific miRNA markers miR-200c, 205 and 658. These results indicated that biomaterials of buccal swabs from cats, dogs, mice and rabbits may be mistaken for human saliva or human vaginal secretion swabs, both of which could result in false positives for human body fluids. Thus, the interpretation of these miRNA profiles for human body fluid identification can be inaccurate in the presence of these animal buccal swabs. Therefore, we suggested performing species tests before human body identification with miRNA markers.