Age estimation using bloodstain miRNAs based on massive parallel sequencing and machine learning: A pilot study

Forensic stability evaluation of selected miRNA and circRNA markers in human bloodstained samples exposed to different environmental conditions

Recently, RNA markers have been used to identify tissue origins of different kinds of body fluids. Herein, circRNA and miRNA markers were carried out to examine the presence or absence of peripheral blood (PB) in bloodstained samples exposed to different external environmental conditions, which mimicked PB samples left at the crime scenes. PB samples were placed on sterile swabs and then exposed to different high temperatures (37°C, 55°C and 95°C) and ultraviolet light irradiation for 0 d, 0.5 d, 1 d, 3 d, and 7 d, ultra-low and low temperatures (-80°C, -20°C, and 4°C) for 30 d, 180 d and 365 d and different kinds of disinfectants. Total RNA was extracted from bloodstained samples under the above different conditions, and the expressions of target RNAs (including miR16-5p, miR451a, circ0000095, and two reference genes RNU6b and 18 S rRNA) were detected by the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) method. Results showed that these selected RNA markers could be successfully measured at all observation points with their unique degradation rates, which exhibited relative stability in degraded bloodstained samples exposed to different environmental conditions. This study provides insights into the applications of these studied miRNA and circRNA markers in forensic science.

From flesh to bones: Multi-omics approaches in forensic science

Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.

RNA quality score evaluation: A preliminary study of RNA integrity number (RIN) and RNA integrity and quality number (RNA IQ)

In the past several years, with the in-depth development of RNA-related research, exploring the application of transcriptome and corresponding RNA biomarkers has become one of the research hotspots in the field of forensic science. High-quality RNA is essential for successful downstream workflows, especially in the steps of screening biomarkers by microarray or RNA sequencing (RNA-seq). Thus, accurately evaluating the quality of RNA samples is a critical step in obtaining meaningful expression data. The RNA integrity number (RIN) generated from the Agilent Bioanalyzer system has been widely used for RNA quality control in the past two decades. Recently, Thermo Fisher Scientific launched a ratiometric fluorescence-based method to quickly check whether an RNA sample has degraded, and the results are presented as RNA integrity and quality number (RNA IQ). Both quality score systems determine RNA quality using a numerical system based on a scale of 1-10, with 1 denoting significantly degraded specimens and 10 representing high-quality, intact RNA samples. In this preliminary study, we evaluated the consistency, reproducibility and linearity of two quality scores in RNA quality determination by analyzing heat- and RNase- artificially degraded samples. Meanwhile, the expression levels of three microRNAs (hsa-let-7 g-5p, hsa-miR-93-5p and hsa-miR-191-5p) in intact and severely degraded RNA samples were estimated by TaqMan-qPCR and droplet digital PCR. Overall, both quality scores showed good repeatability and reproducibility in their respective tests. In the samples subjected to thermal degradation, RIN showed a trend corresponding to heating time, while RNA IQ value showed almost no change on the time gradient. However, in RNase A mediated degradation, RNA IQ value observed better linearity. Furthermore, the expression levels of three microRNAs in the severely degraded samples did not show significant changes compared to the intact RNA samples. RNA degradation is a very complex and highly variable process, which is difficult to comprehensively evaluate through any one index and cannot directly compare these two parameters. Nevertheless, combined with previous research results and the expression levels of three microRNAs in this study, analyzing RNA biomarkers with stable regions or small sizes in challenged samples may be a conservative and reliable approach.

Selecting mRNA markers in blood for age estimation of the donor of a biological stain

RNA has gained a substantial amount of attention within the forensic field over the last decade. There is evidence that RNAs are differentially expressed with biological age. Since RNA can be co-extracted with DNA from the same piece of evidence, RNA-based analysis appears as a promising molecular alternative for predicting the biological age and hence inferring the chronological age of a person. Using RNA-Seq data we searched for markers in blood potentially associated with age. We used our own RNA-Seq data from dried blood stains as well as publicly available RNA-Seq data from whole blood, and compared two different approaches to select candidate markers. The first approach focused on individual gene analysis with DESeq2 to select the genes most correlated with age, while the second approach employed lasso regression to select a set of genes for optimal prediction of age. We present two lists with 270 candidate markers, one for each approach.

Development of a novel forensic age estimation strategy for aged blood samples by combining piRNA and miRNA markers

In forensic investigations, age estimation is vital for determining whether a suspect is under or over the legally defined adult age. With breakthroughs in RNA sequencing technology, small noncoding RNAs have provided new ways to solve problems related to the age estimation of trace or aged samples, owing to their small molecular weight and better stability. In our previous study, we had applied miRNAs for the age estimation of bloodstains; however, further improvement of the existing model is needed. PIWI-interacting RNAs (PiRNAs), which are 24-32 nt noncoding small RNA molecules involved in the PIWI-piRNA pathway, play an important role in the aging process. In this study, we explored the possibility of simultaneously analyzing piRNAs and miRNAs for better age estimation purpose. Through massively parallel sequencing, five age-related piRNAs were identified in blood samples that had been stored for eight years. Further real-time PCR analysis revealed that two piRNAs (piR-000753 and piR-020548) showed relatively higher efficiency in age estimation. Additionally, two age-related miRNAs (miR-324-3p and miR-330-5p) were used to build the estimation model. Among all algorithms tested, gradient boosting showed the lowest mean absolute error (MAE) and root mean square error (RMSE) values (3.171 and 4.403 years, respectively) for the validation dataset (n = 110). The errors of the model were less than 5 years and 10 years for 81.82% and 96.36% of the samples, respectively. The results suggest that the combined use of piRNA and miRNA markers may increase the accuracy of age estimation, and our new model has great potential for application in forensic casework.

Suitable biomarkers for post-mortem differentiation of cardiac death causes: Quantitative analysis of miR-1, miR-133a and miR-26a in heart tissue and whole blood

Cardiovascular diseases are the most common causes of death worldwide. Cardiac death can occur as reaction to myocardial infarction (MI). A diagnostic challenge arises for sudden unexpected death (SUD) cases with structural abnormalities (SA) or without any structural abnormalities (without SA). Therefore, the identification of reliable biomarkers to differentiate cardiac cases from each other is necessary. In the current study, the potential of different microRNAs (miRNAs) as biomarkers in tissue and blood samples of cardiac death cases was analyzed. Blood and tissue samples of 24 MI, 21 SUD and 5 control (C) cases were collected during autopsy. Testing for significance and receiver operating characteristic analysis (ROC) were performed. The results show that miR-1, miR-133a and miR-26a possess a high diagnostic power to discriminate between different cardiac death causes in whole blood and in tissue.

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.

Forensic age estimation from human blood using age-related microRNAs and circular RNAs markers

Aging is a complicated process characterized by progressive and extensive changes in physiological homeostasis at the organismal, tissue, and cellular levels. In modern society, age estimation is essential in a large variety of legal rights and duties. Accumulating evidence suggests roles for microRNAs (miRNAs) and circular RNAs (circRNAs) in regulating numerous processes during aging. Here, we performed circRNA sequencing in two age groups and analyzed microarray data of 171 healthy subjects (17-104 years old) downloaded from Gene Expression Omnibus (GEO) and ArrayExpress databases with integrated bioinformatics methods. A total of 1,403 circular RNAs were differentially expressed between young and old groups, and 141 circular RNAs were expressed exclusively in elderly samples while 10 circular RNAs were expressed only in young subjects. Based on their expression pattern in these two groups, the circular RNAs were categorized into three classes: age-related expression between young and old, age-limited expression-young only, and age-limited expression-old only. Top five expressed circular RNAs among three classes and a total of 18 differentially expressed microRNAs screened from online databases were selected to validate using RT-qPCR tests. An independent set of 200 blood samples (20-80 years old) was used to develop age prediction models based on 15 age-related noncoding RNAs (11 microRNAs and 4 circular RNAs). Different machine learning algorithms for age prediction were applied, including regression tree, bagging, support vector regression (SVR), random forest regression (RFR), and XGBoost. Among them, random forest regression model performed best in both training set (mean absolute error = 3.68 years, r = 0.96) and testing set (MAE = 6.840 years, r = 0.77). Models using one single type of predictors, circular RNAs-only or microRNAs-only, result in bigger errors. Smaller prediction errors were shown in males than females when constructing models according to different-sex separately. Putative microRNA targets (430 genes) were enriched in the cellular senescence pathway and cell homeostasis and cell differentiation regulation, indirectly indicating that the microRNAs screened in our study were correlated with development and aging. This study demonstrates that the noncoding RNA aging clock has potential in predicting chronological age and will be an available biological marker in routine forensic investigation to predict the age of biological samples.

Systematic Selection of Age-Associated mRNA Markers and the Development of Predicted Models for Forensic Age Inference by Three Machine Learning Methods

Aging is usually accompanied by the decline of physiological function and dysfunction of cellular processes. Genetic markers related to aging not only reveal the biological mechanism of aging but also provide age information in forensic research. In this study, we aimed to screen age-associated mRNAs based on the previously reported genome-wide expression data. In addition, predicted models for age estimations were built by three machine learning methods. We identified 283 differentially expressed mRNAs between two groups with different age ranges. Nine mRNAs out of 283 mRNAs showed different expression patterns between smokers and non-smokers and were eliminated from the following analysis. Age-associated mRNAs were further screened from the remaining mRNAs by the cross-validation error analysis of random forest. Finally, 14 mRNAs were chosen to build the model for age predictions. These 14 mRNAs showed relatively high correlations with age. Furthermore, we found that random forest showed the optimal performance for age prediction in comparison to the generalized linear model and support vector machine. To sum up, the 14 age-associated mRNAs identified in this study could be viewed as valuable markers for age estimations and studying the aging process.

A new strategy for distinguishing menstrual blood from peripheral blood by the miR-451a/miR-21-5p ratio

Distinction between menstrual blood and peripheral blood is vital for forensic casework, as it could provide strong evidence to figure out the nature of some criminal cases. However, to date no single blood-specific gene, including the most variable microRNAs (miRNAs) could work well in identification of blood source. In this study, we developed a new strategy for identification of human blood samples by using the copy number ratios of miR-451a to miR-21-5p based on 133 samples, including 56 menstrual blood and 47 peripheral blood, as well as 30 non-blood samples of saliva (10), semen (10) and vaginal secretion (10). The cut-off value and efficacy of the identification strategy were determined through receiver operating characteristic (ROC) analysis. Our results showed that when the miR-451a/miR-21-5p ratio below 0.929, the sample should be non-blood. In contrast, when the miR-451a/miR-21-5p ratio above 0.929 and below 10.201, the sample should be menstrual blood; and when this ratio above 10.201, the sample should be peripheral blood. External validation using 86 samples (62 menstrual blood and 24 peripheral blood samples) fully supported this strategy with the 100% sensitivity and 100% specificity. We confirmed that this result accuracy was not affected by various potential confounding factors of samples and different experimental platforms. We showed that 0.2 ng of total RNA from menstrual blood and peripheral blood was sufficient for qPCR quantification. In conclusion, our results provide an accurate reference to distinguish menstrual blood from peripheral blood for forensic authentication.

Forensic transcriptome analysis using massively parallel sequencing

The application of transcriptome analyses in forensic genetics has experienced tremendous growth and development in the past decade. The earliest studies and main applications were body fluid and tissue identification, using targeted RNA transcripts and a reverse transcription endpoint PCR method. A number of markers have been identified for the forensically most relevant body fluids and tissues and the method has been successfully used in casework. The introduction of Massively Parallel Sequencing (MPS) opened up new perspectives and opportunities to advance the field. Contrary to genomic DNA where two copies of an autosomal DNA segment are present in a cell, abundant RNA species are expressed in high copy numbers. Even whole transcriptome sequencing (RNA-Seq) of forensically relevant body fluids and of postmortem material was shown to be possible. This review gives an overview on forensic transcriptome analyses and applications. The methods cover whole transcriptome as well as targeted MPS approaches. High resolution forensic transcriptome analyses using MPS are being applied to body fluid/ tissue identification, determination of the age of stains and the age of the donor, the estimation of the post-mortem interval and to post mortem death investigations.