Evaluation of mRNA markers for estimating blood deposition time: Towards alibi testing from human forensic stains with rhythmic biomarkers

Construction of the time since deposition (TsD) model in saliva stains with 16S rRNA full-length sequencing technology and microbial markers

Determining the time since deposition (TsD) and sex of saliva stains is crucial for revealing the time of the crime's occurrence and clarifying the nature of the crime. This process not only shortens the time required to solve the case but also helps narrow down the scope of investigation, thereby enhancing the efficiency of case resolution. Currently, the forensic study of the microbial composition in long-term saliva stains remains a relatively underexplored field. The purpose of this study was to explore the succession pattern of long-placed human saliva stains microbial communities and identify relevant microbial markers for estimating TsD and identifying the sex of the donor, in order to be an effective alternative tool for solving practical forensic cases. Therefore, in this study, saliva stains exposed to indoor environmental conditions for up to 140 days were collected and 16S rRNA full-length sequencing was performed using single-molecule real-time sequencing technology based on the PacBio sequencing platform. The study reveals that after 140 days of placement, the relative abundance of Firmicutes significantly decreased (p = 0.00304). At the genus level, the relative abundances of Streptococcus (p = 0.0008), Rothia (p = 0.0448), Gemella (p = 0.016), and Veillonella (p = 0.0208) also significantly decreased. Additionally, significant differences were found in the microbial communities between saliva stains from males and females (p = 0.00013). Then, we constructed a TsD estimating model for microbial community markers based on random forest, and the results showed that the mean absolute error was 9.59 days, and the accuracy of sex classification model based on stepwise logistic regression model and 4 bacterial markers was 84.21%. This indicates that saliva stains that have been in place for a long time still retain significant forensic value, and microbial markers can be used to determine the time since deposition (TsD) of dried saliva stains as well as to identify the sex of the donor.

Forensic investigative genetic genealogy using genotypes generated or imputed from transcriptomes

The utility of transcriptome analysis in forensic genetics is steadily increasing. The transcriptome, with its ability to reflect both transcript levels and their nucleotide sequences, is proving to be useful for a variety of different applications, including body fluid identification and donor assignment, thereby providing both genetic and contextual information. Furthermore, the substantial single nucleotide polymorphism (SNP) coverage obtainable with whole transcriptome sequencing may prove useful for additional applications. In this study, we expand the current knowledge of transcriptomics in forensic genetics by showing how RNA can be used for forensic investigative genetic genealogy (FIGG) purposes and inference of distant relationships. Genetic data was simulated for relationships ranging from full siblings (first-degree relatives) to third cousins (seventh-degree relatives). The sets of SNP genotypes were subsequently reduced to only include observed and imputed SNP genotypes at loci covered by transcriptome sequencing of whole blood. The relationships of relatives as distant as second cousins could be reliably classified based on an average of 99,548 SNPs. Appropriate thresholds for sequence quality parameters limited the rate of erroneous genotype calls, with the remaining errors proving to have little to no effect on relationship inference. In conclusion, we present a proof-of-concept study on how transcriptome-based genotypes, in combination with imputed genotypes, may be used for reliable relationship inference for FIGG purposes.

From dual nucleic acid co-extraction to co-sequencing: A highly integrated next-generation forensic DNA and RNA sequencing experimental workflow

DNA and RNA markers are significant in forensic practices, such as individual and body fluid identification. However, forensic DNA and RNA markers were separately analyzed in most forensic experiments, which resulted in large amounts of sample consumption, complex procedures, and weak inter-evidence correlation. While several integrated methods based on capillary electrophoresis and next-generation sequencing technologies were reported, integrated procedures were mostly on nucleic acid co-extraction, co-electrophoresis, or co-sequencing, and the number and type of markers co-tested were limited. Four studies were conducted in this work to co-analyze DNA and RNA with a highly integrated next-generation sequencing-based workflow. First, six commercial kits for DNA and RNA co-extraction were compared, and two kits more suitable for total nucleic acid extraction were selected. Second, the feasibility of an experimental methodology for reverse transcription with total nucleic acid was investigated, and the results showed that reverse transcription reactions have no significant impact on DNA fragments used for forensic short tandem repeat and single nucleotide polymorphism genotyping. Third, a method for DNA and RNA library co-preparation was developed. Through the three studies, a highly integrated experimental workflow for targeted next-generation DNA and RNA sequencing was developed, including DNA and RNA co-extraction, reverse transcription with total nucleic acid, library co-preparation with genomic DNA and complementary DNA, co-sequencing, and data analysis. Fourth, to evaluate the workflow, we developed a multiplex panel consisting of 55 DNA markers (10 autosomal short tandem repeats and 45 autosomal single nucleotide polymorphisms) and eight messenger RNA markers (two peripheral blood-specific, four saliva-specific, and two housekeeping markers), and carried out validation experiments. High accuracy of DNA genotypes and RNA expression results were observed. Taken together, the novel integrated workflow could be used to sequence forensic DNA and RNA markers, which provides a promising method to comprehensively reveal DNA and RNA bioinformation with limited crime scene bio-materials.

The Role of Molecular Investigations in Estimating the Time since Deposition (TSD) of Bloodstains: A Systematic Review of the Literature

At many crime scenes, investigators are able to trace and find traces of blood. For many years, it was believed that such traces could only be subjected to genetic investigations, such as those aimed at comparing DNA profiling with a suspect to verify his identity, and that it was therefore not possible to backdate the traces. In recent years, various works have used experimental models to investigate the possibility of identifying markers and methodologies for estimating the time since deposition (TSD) of bloodstains. Despite the results, these methods are still not part of standard procedures, and there is no univocal analysis methodology. In this work we carried out a systematic literature review of all the papers published in the last ten years on this topic, comparing the experimental models created. This review demonstrates the potential that different molecular approaches, such as transcriptomics, metabolomics, proteomics, and spectrometry, can have in the analysis of TSD, with notable sensitivity and specificity. This paper also analyzes the intrinsic and extrinsic limits of these models and emphasizes the need to continue research work on this topic, considering the importance that this parameter can assume in forensic investigations against a suspect.

RNA Analysis in Forensic Molecular Biology

BACKGROUND

Different types of RNA take on multiple crucial functions in living cells and tissues. Messenger RNA (mRNA) is a temporary molecular carrier of genetic information. Analysis of the composition of all mRNA contained in a cell at a given moment, the so-called transcriptome, enables the determination of the type of cell and its condition, e.g., in pathologically altered states.

METHODS

This review is based on pertinent publications retrieved by a selective literature search.

RESULTS

The analysis of differential gene expression has already been used in forensic molecular biology to determine the type of tissue contained in biological specimens. It is also being used in criminal investigations to determine the composition of mixed traces of various bodily fluids and/or organ tissues. The method is limited by degradation of the mRNA molecules through environmental influences. The use of newly developed molecular biological methods such as massive parallel sequencing can expand the information obtainable by this investigative method. Current research also addresses the forensic potential of deriving relevant information about the crime-e.g., its timing, or the condition of the involved persons-from the totality of mRNA species present in the specimens.

CONCLUSION

Forensic RNA analysis can yield a great deal of relevant information. It is likely to be applicable in a much wider variety of forensic situations in the near future.

Spitting in the wind?-The challenges of RNA sequencing for biomarker discovery from saliva

Forensic trace contextualization, i.e., assessing information beyond who deposited a biological stain, has become an issue of great and steadily growing importance in forensic genetic casework and research. The human transcriptome encodes a wide variety of information and thus has received increasing interest for the identification of biomarkers for different aspects of forensic trace contextualization over the past years. Massively parallel sequencing of reverse-transcribed RNA ("RNA sequencing") has emerged as the gold standard technology to characterize the transcriptome in its entirety and identify RNA markers showing significant expression differences not only between different forensically relevant body fluids but also within a single body fluid between forensically relevant conditions of interest. Here, we analyze the quality and composition of four RNA sequencing datasets (whole transcriptome as well as miRNA sequencing) from two different research projects (the RNAgE project and the TrACES project), aiming at identifying contextualizing forensic biomarker from the forensically relevant body fluid saliva. We describe and characterize challenges of RNA sequencing of saliva samples arising from the presence of oral bacteria, the heterogeneity of sample composition, and the confounding factor of degradation. Based on these observations, we formulate recommendations that might help to improve RNA biomarker discovery from the challenging but forensically relevant body fluid saliva.

Indirect DNA Transfer and Forensic Implications: A Literature Review

Progress in DNA profiling techniques has made it possible to detect even the minimum amount of DNA at a crime scene (i.e., a complete DNA profile can be produced using as little as 100 pg of DNA, equivalent to only 15-20 human cells), leading to new defense strategies. While the evidence of a DNA trace is seldom challenged in court by a defendant's legal team, concerns are often raised about how the DNA was transferred to the location of the crime. This review aims to provide an up-to-date overview of the experimental work carried out focusing on indirect DNA transfer, analyzing each selected paper, the experimental method, the sampling technique, the extraction protocol, and the main results. Scopus and Web of Science databases were used as the search engines, including 49 papers. Based on the results of this review, one of the factors that influence secondary transfer is the amount of DNA shed by different individuals. Another factor is the type and duration of contact between individuals or objects (generally, more intimate or prolonged contact results in more DNA transfer). A third factor is the nature and quality of the DNA source. However, there are exceptions and variations depending on individual characteristics and environmental conditions. Considering that secondary transfer depends on multiple factors that interact with each other in unpredictable ways, it should be considered a complex and dynamic phenomenon that can affect forensic investigation in various ways, for example, placing a subject at a crime scene who has never been there. Correct methods and protocols are required to detect and prevent secondary transfer from compromising forensic evidence, as well as the correct interpretation through Bayesian networks. In this context, the definition of well-designed experimental studies combined with the use of new forensic techniques could improve our knowledge in this challenging field, reinforcing the value of DNA evidence in criminal trials.

TrACES of time: Transcriptomic analyses for the contextualization of evidential stains - Identification of RNA markers for estimating time-of-day of bloodstain deposition

Obtaining forensically relevant information beyond who deposited a biological stain on how and under which circumstances it was deposited is a question of increasing importance in forensic molecular biology. In the past few years, several studies have been produced on the potential of gene expression analysis to deliver relevant contextualizing information, e.g. on nature and condition of a stain as well as aspects of stain deposition timing. However, previous attempts to predict the time-of-day of sample deposition were all based on and thus limited by previously described diurnal oscillators. Herein, we newly approached this goal by applying current sequencing technologies and statistical methods to identify novel candidate markers for forensic time-of-day predictions from whole transcriptome analyses. To this purpose, we collected whole blood samples from ten individuals at eight different time points throughout the day, performed whole transcriptome sequencing and applied biostatistical algorithms to identify 81 mRNA markers with significantly differential expression as candidates to predict the time of day. In addition, we performed qPCR analysis to assess the characteristics of a subset of 13 candidate predictors in dried and aged blood stains. While we demonstrated the general possibility of using the selected candidate markers to predict time-of-day of sample deposition, we also observed notable variation between different donors and storage conditions, highlighting the relevance of employing accurate quantification methods in combination with robust normalization procedures.This study's results are foundational and may be built upon when developing a targeted assay for time-of-day predictions from forensic blood samples in the future.

Discovery and validation of metabolite markers in bloodstains for bloodstain age estimation

Bloodstain age estimation involves measuring time-dependent changes in the levels of biomolecules in bloodstains. Although several studies have identified bloodstain metabolites as markers for estimating bloodstain age, none have considered sex, age-related metabolomic differences, or long-time bloodstain age. Therefore, we aimed to identify metabolite markers for estimating the age of bloodstains at weekly intervals within 28 days and validate them through multiple reaction monitoring. Adenosine 5'-monophosphate, choline, and pyroglutamic acid were selected as markers. Seven metabolites were validated, including five previously reported metabolites, ergothioneine, hypoxanthine, L-isoleucine, L-tryptophan, and pyroglutamic acid. Choline and hypoxanthine can be used to differentiate bloodstains between days 0 and 14 after deposition at weekly intervals, whereas L-isoleucine and L-tryptophan can help distinguish bloodstains between 7 days before and 14 days after deposition. Evaluation of the changes in metabolite levels according to sex and age revealed that the average levels of all seven metabolites were higher in women on day 0. Moreover, the level of ergothioneine was significantly higher in elderly individuals than in young individuals at all time points. In this study, we confirmed the potential effectiveness of metabolites in bloodstains as forensic markers and provided a new perspective on metabolomic approaches linked to forensic science.

Estimation of bloodstain deposition time within a 24-h day-night cycle with rhythmic mRNA based on a machine learning algorithm

Estimating the time that bloodstains are left at a crime scene can provide invaluable evidence for law enforcement investigations, including determining the time of the crime, linking the perpetrator to the crime scene, narrowing the pool of possible suspects, and verifying witness statements. There have been some attempts to estimate the time since deposition of bloodstains, i.e., how much time has passed since the bloodstain was left at a crime scene. However, most studies focus on the time interval of days. As far as we know, previous study have been conducted to estimate the deposition time of blood within a 24-h day-night cycle. To date, there is a lack of studies on whether rhythmic mRNA of blood is suitable for bloodstain samples. In this study, we estimated the bloodstain deposition time within a 24-h day-night cycle based on the expression of messenger RNAs (mRNAs) by real-time quantitative polymerase chain reaction. Bloodstain samples were prepared from eight individuals at eight time points under real and uncontrolled conditions. Four mRNAs expressed rhythmically and were used to construct a regression model using the k-nearest neighbor (KNN) algorithm, resulting in a mean absolute error of 3.92 h. Overall, using the rhythmic mRNAs, a machine learning model was developed which has allowed us to predict the deposition time of bloodstains within the 24-h day-night cycle in East Asian populations. This study demonstrates that mRNA biomarkers can be used to estimate the bloodstain deposition time within a 24-h period. Furthermore, rhythmic mRNA biomarkers provide a potential method and perspective for estimating the deposition time of forensic traces in forensic investigation. Case samples in forensic analysis are usually limited or degraded, so the stability and sensitivity of rhythmic biomarkers need to be further investigated.

Machine learning estimation of human body time using metabolomic profiling

Circadian rhythms influence physiology, metabolism, and molecular processes in the human body. Estimation of individual body time (circadian phase) is therefore highly relevant for individual optimization of behavior (sleep, meals, sports), diagnostic sampling, medical treatment, and for treatment of circadian rhythm disorders. Here, we provide a partial least squares regression (PLSR) machine learning approach that uses plasma-derived metabolomics data in one or more samples to estimate dim light melatonin onset (DLMO) as a proxy for circadian phase of the human body. For this purpose, our protocol was aimed to stay close to real-life conditions. We found that a metabolomics approach optimized for either women or men under entrained conditions performed equally well or better than existing approaches using more labor-intensive RNA sequencing-based methods. Although estimation of circadian body time using blood-targeted metabolomics requires further validation in shift work and other real-world conditions, it currently may offer a robust, feasible technique with relatively high accuracy to aid personalized optimization of behavior and clinical treatment after appropriate validation in patient populations.

Common Ground between Biological Rhythms and Forensics

Simple Summary

Biological clocks regulate the timing of numerous body functions in adaption to daily repeating cycles in the environment, such as the sleep–wake phases that are trained by the cycling changes of night and day light. The identification of a deceased victim is a critical component in a forensic investigation, but it can be significantly hampered by the condition of the dead body and the lack of personal records and documents. This review links current knowledge on the molecular mechanisms of biological rhythms to forensically relevant aspects, including the time period since death, cause of death, the use of insects for forensics, sex and age of a person, ethnic background and development. Putting these findings in context demonstrates how the analysis of molecular clock analysis could be used as tool for future personal identification in forensic investigations.

Abstract

Biological clocks set the timing for a large number of essential processes in the living human organism. After death, scientific evidence is required in forensic investigations in order to collect as much information as possible on the death circumstances and personal identifiers of the deceased victim. We summarize the associations between the molecular mechanisms of biological rhythms and forensically relevant aspects, including post-mortem interval and cause of death, entomological findings, sex, age, ethnicity and development. Given their importance during lifetime, biological rhythms could be potential tools to draw conclusions on the death circumstances and the identity of a deceased person by mechanistic investigations of the different biological clocks in a forensic context. This review puts the known effects of biological rhythms on the functions of the human organism in context with potential applications in forensic fields of interest, such as personal identification, entomology as well as the determination of the post-mortem interval and cause of death.

Using total RNA quality metrics for time since deposition estimates in degrading bloodstains

The physicochemical changes occurring in biomolecules in degrading bloodstains can be used to approximate the time since deposition (TSD) of bloodstains. This would provide forensic scientists with critical information regarding the timeline of the events involving bloodshed. Our study aims to quantify the timewise degradation trends and temperature dependence found in total RNA from bloodstains without the use of amplification, expanding the scope of the RNA TSD research which has traditionally targeted mRNA and miRNA. Bovine blood with ACD-A anticoagulant was deposited and stored in plastic microcentrifuge tubes at 21 or 4°C and tested over different timepoints spanning 1 week. Total RNA was extracted from each sample and analyzed using automated high sensitivity gel electrophoresis. Nine RNA metrics were visually assessed and quantified using linear and mixed models. The RNA Integrity Number equivalent (RINe) and DV200 were not influenced by the addition of anticoagulant and demonstrated strong negative trends over time. The RINe model fit was high (R²  = 0.60), and while including the biological replicate as a random effect increased the fit for all RNA metrics, no significant differences were found between biological replicates stored at the same temperature for the RINe and DV200. This suggests that these standardized metrics can be directly compared between scenarios and individuals, with DV200 having an inflection point at approximately 28 h. This study provides a novel approach for blood TSD research, revealing metrics that are not affected by inter-individual variation, and improving our understanding of the rapid RNA degradation occurring in bloodstains.

Unlocking the potential of forensic traces: Analytical approaches to generate investigative leads

Forensic investigation involves gathering the information necessary to understand the criminal events as well as linking objects or individuals to an item, location or other individual(s) for investigative purposes. For years techniques such as presumptive chemical tests, DNA profiling or fingermark analysis have been of great value to this process. However, these techniques have their limitations, whether it is a lack of confidence in the results obtained due to cross-reactivity, subjectivity and low sensitivity; or because they are dependent on holding reference samples in a pre-existing database. There is currently a need to devise new ways to gather as much information as possible from a single trace, particularly from biological traces commonly encountered in forensic casework. This review outlines the most recent advancements in the forensic analysis of biological fluids, fingermarks and hair. Special emphasis is placed on analytical methods that can expand the information obtained from the trace beyond what is achieved in the usual practices. Special attention is paid to those methods that accurately determine the nature of the sample, as well as how long it has been at the crime scene, along with individualising information regarding the donor source of the trace.

Time-dependent expression of high-mobility group box-1 and toll-like receptors proteins as potential determinants of skin wound age in rats: Forensic implication

The skin wound age determination in living subjects is an imperative task for forensic experts. In this study, we investigated the time-dependent expression of high-mobility group box-1 (HMGB1) and toll-like receptors 2 and 4 (TLR2 and 4) in rat skin wounds using real-time PCR and seek their forensic potentials during the skin wound repair process. In addition, the levels of serum pro-inflammatory cytokines (tumor necrosis factor-alpha (TNF-α) and interleukin 6 (IL-6)), as well as nitric oxide (NO) production, were measured. The wound tissue and serum samples were collected after 30 min, 2 h, 6 h, 12 h, 1 day, 3 days, 5 days, and 7 days after incision. As a control (zero time), skin specimens and blood samples were collected without incision. The results reveal that the HMGB1, TLR2, and TLR4 expression levels were increased in a time-dependent manner until the first day where the peak level was achieved for the three tested genes compared with the zero time. On the 7^th day, the statistical significance was lost for TLR2 and TLR4 but persisted for HMGB1. The serum TNF-α, IL6, and NO levels peaked within 30 min and 1^st and 3^rd day after injury, respectively. On the 7^th day after incision, no significant differences exist in the TNF-α serum level compared to the control group, but the statistical significance persisted for IL6 and NO. It was apparent that the analyzed genes in the wound tissues showed higher R2 values rather than the serum biochemical indicators. Of note, a strong positive correlation was evident between the HMGB1 and that of TLR2 and TLR4 relative expression as well as IL-6 serum level. Conclusively, based on the observed changes in the analyzed markers in wound tissues and serum and R2 values obtained from mathematical models established to determine the wound age, the relative expression of HMGB1, TLR2, and TLR4 could be a reliable indicator for wound age determination in living subjects. Further investigation of these markers and mathematical models in human tissues is necessary.

Cell survival and DNA damage repair are promoted in the human blood thanatotranscriptome shortly after death

RNA analysis of post-mortem tissues, or thanatotranscriptomics, has become a topic of interest in forensic science due to the essential information it can provide in forensic investigations. Several studies have previously investigated the effect of death on gene transcription, but it has never been conducted with samples of the same individual. For the first time, a longitudinal mRNA expression analysis study was performed with post-mortem human blood samples from individuals with a known time of death. The results reveal that, after death, two clearly differentiated groups of up- and down-regulated genes can be detected. Pathway analysis suggests active processes that promote cell survival and DNA damage repair, rather than passive degradation, are the source of early post-mortem changes of gene expression in blood. In addition, a generalized linear model with an elastic net restriction predicted post-mortem interval with a root mean square error of 4.75 h. In conclusion, we demonstrate that post-mortem gene expression data can be used as biomarkers to estimate the post-mortem interval though further validation using independent sample sets is required before use in forensic casework.

Post deposition aging of bloodstains probed by steady-state fluorescence spectroscopy

Blood is one of the most common body fluids discovered at crime scenes involving violent actions. It is one of the most important types of forensic evidence since it allows for the identification of the individual providing that there is a match with a known DNA profile. Determining the time since deposition (TSD) can assist investigators in establishing when the crime occurred or if a bloodstain present is actually related to the investigated event. To develop a forensically sound method for determining the TSD of a bloodstain, it is necessary to understand the underlying biochemical mechanisms occurring during aging. As biochemical processes occurring in blood are necessary for the continued survival of living organisms, they are important subjects of human biology and biomedicine and are well understood. However, the biochemistry of bloodstain aging ex vivo is primarily of interest to forensic scientists and has not yet been thoroughly researched. This preliminary study utilizes steady-state fluorescence spectroscopy to probe the changes in fluorescence properties of peripheral and menstrual blood up to 24-h post deposition. Peripheral and menstrual blood exhibited similar kinetic changes over time, assigned to the presence of the fluorophores: tryptophan, nicotinamide adenine dinucleotide (NADH), and flavins in both biological fluids. The biochemical mechanism of blood aging ex vivo is discussed.

Analytical Strategy for MS-Based Thanatochemistry to Estimate Postmortem Interval

An analytical strategy for a matrix-assisted laser desorption mass spectrometry-based untargeted metabolomic study on vitreous humor (VH) was developed, looking for statistically significant parameters correlated to death time estimation. Five incubation stages of VH, 0, 24, 48, 72, and 96 h, at physiological pH and controlled temperature, were adopted to monitor time-dependent changes and correlate them with the postmortem interval (PMI). Using two multivariate statistical approaches, principal component regression (PCR) and partial least squares regression (PLSR), the PMI was assessed, considering the m/z values from mass spectra and the incubation time (ISt) as predictors. An independent validation set was used to evaluate the predictive capability of the models through the coefficient of determination (R2) and the root-mean-square error (RMSE). Different pre-treatments were applied to the raw mass spectra, and their performance in assessing PMI was evaluated. Based on the best outcomes in terms of both R2 and RMSE, multiplicative scatter correction combined with a logarithmic transformation was chosen. The results of PCR and PLSR based on the selected pre-treatment are encouraging because validation R2 is about 0.95 for both models. Moreover, the prediction error is 6 h for both models, when PMI is lower than 1 day. Although these results are obtained by the uncritical application of the models, they are comparable to or even better than those reported in the literature. Notwithstanding, we consider that many in situ influences, such as passive diffusion, functional loss of tissues, and advanced autolytic processes, could not get captured in vitro. However, the developed approach was optimized using VH samples and overcomes the limitations of the vast majority of methods that require validation for serum and/or urine samples.

Ten years of molecular ballistics-a review and a field guide

Molecular ballistics combines molecular biological, forensic ballistic, and wound ballistic insights and approaches in the description, collection, objective investigation, and contextualization of the complex patterns of biological evidence that are generated by gunshots at biological targets. Setting out in 2010 with two seminal publications proving the principle that DNA from backspatter collected from inside surfaces of firearms can be retreived and successfully be analyzed, molecular ballistics covered a lot of ground until today. In this review, 10 years later, we begin with a comprehensive description and brief history of the field and lay out its intersections with other forensic disciplines like wound ballistics, forensic molecular biology, blood pattern analysis, and crime scene investigation. In an application guide section, we aim to raise consciousness to backspatter traces and the inside surfaces of firearms as sources of forensic evidence. Covering crime scene practical as well as forensic genetic aspects, we introduce operational requirements and lay out possible procedures, including forensic RNA analysis, when searching for, collecting, analyzing, and contextualizing such trace material. We discuss the intricacies and rationales of ballistic model building, employing different tissue, skin, and bone simulants and the advantages of the “triple-contrast” method in molecular ballistics and give advice on how to stage experimental shootings in molecular ballistic research. Finally, we take a look at future applications and prospects of molecular ballistics.

Working Time Society consensus statements: Circadian time structure impacts vulnerability to xenobiotics-relevance to industrial toxicology and nonstandard work schedules

The circadian time structure (CTS) has long been the subject of research in occupational medicine, but not to industrial toxicology, including methods of setting threshold limit values (TLVs) and employee biological monitoring. Numerous animal and human investigations document vulnerability to chemical, contagion, and other xenobiotics varies according to the circadian time of encounter. Permanent and rotating nightshift personnel are exposed to industrial contaminants in the same or higher concentration as dayshift personnel, and because of incomplete CTS adjustment to night work, contact with contaminants occurs during a different biological time than day workers. Thus, the amount of protection afforded by certain TLVs, especially for employees of high-risk settings who work night and other nonstandard shift schedules, might be inadequate. The CTS seems additionally germane to procedures of employee biological monitoring in that high-amplitude 24 h rhythms in biomarkers indicative of xenobiotic exposure may result in misjudgment of health risks when data are not gathered in sufficient frequency over time and properly interpreted. Biological reference values time-qualified for their rhythmic variation, currently of interest to laboratory medicine practice, are seemingly important to industrial medicine as circadian time and work-shift specific biological exposure indices to improve surveillance of personnel, particularly those working nonstandard shift schedules.

Massively parallel sequencing of microRNA in bloodstains and evaluation of environmental influences on miRNA candidates using realtime polymerase chain reaction

MicroRNAs (miRNA) are small (22-24 nucleotides) non-coding RNAs with potential application in forensic science because of their anti-degradation property and tissue specificity. Recent studies on the use of miRNA in forensic applications have mainly focused on body fluid identification using realtime polymerase chain reaction or microarray analysis. However, the exploration of miRNA in bloodstains, which are the most valuable source of biological evidence during case investigations, is currently lacking, particularly for aged and environmentally compromised forensic samples. Recent developments in massively parallel sequencing (MPS) technology provide the opportunity to establish a whole-genome miRNA profile with high throughput and efficiency. However, MPS analysis of genome-wide miRNA profiles from bloodstains has not been reported to date. In this study, the whole-genome miRNA profiles of bloodstains were examined using MPS, revealing 633 known miRNAs and 266 novel miRNAs. To further explore the stability of miRNAs in bloodstains under various circumstances, the expression levels of six miRNAs (miR-16-5p, miR-20a-5p, miR-486-5p, miR-148a-3p, miR-151a-3p, and miR-451a) that were abundant in blood/bloodstains were examined. The results showed that freezing/thawing and a high concentration of oxidant solution affects the absolute expression of miRNA significantly, while storage for up to 5 months and a temperature of 37 °C did not have any observed effects. This study not only provides a novel method to explore miRNA profiles in bloodstains using MPS, but also points to the circumstantial influences on miRNA expression, which are an important consideration for practical application. Collectively, our work may shed light on MPS-based approaches with miRNA analysis of bloodstains in forensics.

Early postmortem interval estimation based on Cdc25b mRNA in rat cardiac tissue

PURPOSE

The postmortem interval (PMI) is the amount of time that has elapsed since the time of death. Over the years, many approaches have been developed to assess PMI, but their time frame of applicability has been only days to weeks. Our present pilot study aimed to find the sensitive mRNA marker if the degradation of mRNA could be used to estimate the early postmortem interval (up to 24 h).

METHODS

In our study, we use the microarray to screen 217 mRNAs markers of rat cardiac tissue. Then, real-time fluorescent quantitative PCR (qPCR) was used to validate of the candidate markers at 7 time points within 24 h and at temperatures of 25 °C and 35 °C. Another 27 rats were then used to verify the model.

RESULTS

Among all of the candidate markers, △Cq (cell division cycle 25 homolog B(Cdc25b)) had the best correlation coefficient with early postmortem interval and was used to build a new model using the R software. The results of verification testing demonstrated that the error rate was less than 15%, demonstrating the high predictive power of our mathematical model.

CONCLUSION

In this study, Cdc25b was found to be the sensitive marker to estimate early postmortem interval, and Rpl27 was found to be suitable for use as the endogenous control. Our work provided new leads for molecular approaches to early postmortem interval estimation using the significant mRNA markers established here.

A SNP panel for identification of DNA and RNA specimens

BACKGROUND

SNP panels that uniquely identify an individual are useful for genetic and forensic research. Previously recommended SNP panels are based on DNA profiles and mostly contain intragenic SNPs. With the increasing interest in RNA expression profiles, we aimed for establishing a SNP panel for both DNA and RNA-based genotyping.

RESULTS

To determine a small set of SNPs with maximally discriminative power, genotype calls were obtained from DNA and blood-derived RNA sequencing data belonging to healthy, geographically dispersed, Dutch individuals. SNPs were selected based on different criteria like genotype call rate, minor allele frequency, Hardy-Weinberg equilibrium and linkage disequilibrium. A panel of 50 SNPs was sufficient to identify an individual uniquely: the probability of identity was 6.9 × 10^- 20 when assuming no family relations and 1.2 × 10^- 10 when accounting for the presence of full sibs. The ability of the SNP panel to uniquely identify individuals on DNA and RNA level was validated in an independent population dataset. The panel is applicable to individuals from European descent, with slightly lower power in non-Europeans. Whereas most of the genes containing the 50 SNPs are expressed in various tissues, our SNP panel needs optimization for other tissues than blood.

CONCLUSIONS

This first DNA/RNA SNP panel will be useful to identify sample mix-ups in biomedical research and for assigning DNA and RNA stains in crime scenes to unique individuals.

Investigation of metabolites for estimating blood deposition time

Trace deposition timing reflects a novel concept in forensic molecular biology involving the use of rhythmic biomarkers for estimating the time within a 24-h day/night cycle a human biological sample was left at the crime scene, which in principle allows verifying a sample donor’s alibi. Previously, we introduced two circadian hormones for trace deposition timing and recently demonstrated that messenger RNA (mRNA) biomarkers significantly improve time prediction accuracy. Here, we investigate the suitability of metabolites measured using a targeted metabolomics approach, for trace deposition timing. Analysis of 171 plasma metabolites collected around the clock at 2-h intervals for 36 h from 12 male participants under controlled laboratory conditions identified 56 metabolites showing statistically significant oscillations, with peak times falling into three day/night time categories: morning/noon, afternoon/evening and night/early morning. Time prediction modelling identified 10 independently contributing metabolite biomarkers, which together achieved prediction accuracies expressed as AUC of 0.81, 0.86 and 0.90 for these three time categories respectively. Combining metabolites with previously established hormone and mRNA biomarkers in time prediction modelling resulted in an improved prediction accuracy reaching AUCs of 0.85, 0.89 and 0.96 respectively. The additional impact of metabolite biomarkers, however, was rather minor as the previously established model with melatonin, cortisol and three mRNA biomarkers achieved AUC values of 0.88, 0.88 and 0.95 for the same three time categories respectively. Nevertheless, the selected metabolites could become practically useful in scenarios where RNA marker information is unavailable such as due to RNA degradation. This is the first metabolomics study investigating circulating metabolites for trace deposition timing, and more work is needed to fully establish their usefulness for this forensic purpose.

Blood transcriptome based biomarkers for human circadian phase

Diagnosis and treatment of circadian rhythm sleep-wake disorders both require assessment of circadian phase of the brain’s circadian pacemaker. The gold-standard univariate method is based on collection of a 24-hr time series of plasma melatonin, a suprachiasmatic nucleus-driven pineal hormone. We developed and validated a multivariate whole-blood mRNA-based predictor of melatonin phase which requires few samples. Transcriptome data were collected under normal, sleep-deprivation and abnormal sleep-timing conditions to assess robustness of the predictor. Partial least square regression (PLSR), applied to the transcriptome, identified a set of 100 biomarkers primarily related to glucocorticoid signaling and immune function. Validation showed that PLSR-based predictors outperform published blood-derived circadian phase predictors. When given one sample as input, the R² of predicted vs observed phase was 0.74, whereas for two samples taken 12 hr apart, R² was 0.90. This blood transcriptome-based model enables assessment of circadian phase from a few samples.

DOI:http://dx.doi.org/10.7554/eLife.20214.001