Exploration of the R code-based mathematical model for PMI estimation using profiling of RNA degradation in rat brain tissue at different temperatures

Estimation of the post-mortem interval: a review

Determination of the time of death and post-mortem interval (PMI) is a major task for Legal and Forensic Medicine, given the implications it entails. In this respect, depending on the proximity to the moment of death, this PMI estimation will be simpler or more complex. Traditionally, the estimation of the PMI has centred upon the analysis of corporeal rigidity, body temperature and the concentration of potassium within the vitreous humour. However, in recent years, innovative methodologies that facilitate an increasingly precise prediction of the PMI have been developed. Therefore, this article aims to compile and present a comprehensive overview of these PMI estimation techniques, in order to serve as a basic guide and reference point to understand the latest advances in this area, as well as to identify their limitations and to explore the potential future directions of this discipline.

A novel approach for estimating postmortem intervals under varying temperature conditions using pathology images and artificial intelligence models

Estimating the postmortem interval (PMI) is a critical yet complex task in forensic investigations, with accurate and timely determination playing a key role in case resolution and legal outcomes. Traditional methods often suffer from environmental variability and subjective biases, emphasizing the need for more reliable and objective approaches. In this study, we present a novel predictive model for PMI estimation, introduced here for the first time, that leverages pathological tissue images and artificial intelligence (AI). The model is designed to perform under three temperature conditions: 25 °C, 37 °C, and 4 °C. Using a ResNet50 neural network, patch-level images were analyzed to extract deep learning-derived features, which were integrated with machine learning algorithms for whole slide image (WSI) classification. The model achieved strong performance, with micro and macro AUC values of at least 0.949 at the patch-level and 0.800 at the WSI-level in both training and testing sets. In external validation, micro and macro AUC values at the patch-level exceeded 0.960. These results highlight the potential of AI to improve the accuracy and efficiency of PMI estimation. As AI technology continues to advance, this approach holds promise for enhancing forensic investigations and supporting more precise case resolutions.

Advances in Genotyping Detection of Fragmented Nucleic Acids

Single nucleotide variant (SNV) detection is pivotal in various fields, including disease diagnosis, viral screening, genetically modified organism (GMO) identification, and genotyping. However, detecting SNVs presents significant challenges due to the fragmentation of nucleic acids caused by cellular apoptosis, molecular shearing, and physical degradation processes such as heating. Fragmented nucleic acids often exhibit variable lengths and inconsistent breakpoints, complicating the accurate detection of SNVs. This article delves into the underlying causes of nucleic acid fragmentation and synthesizes the strengths and limitations of next-generation sequencing technology, high-resolution melting curves, molecular probes, and CRISPR-based approaches for SNV detection in fragmented nucleic acids. By providing a detailed comparative analysis, it seeks to offer valuable insights for researchers working to overcome the challenges of SNV detection in fragmented samples, ultimately advancing the accurate and efficient detection of single nucleotide variants across diverse applications.

microRNAs as New Biomolecular Markers to Estimate Time since Death: A Systematic Review

Estimating the post-mortem interval is still one of the most complex challenges in forensics. In fact, the main tools currently used are burdened by numerous limitations, which sometimes allow the time of death to be placed only within too large time intervals. In recent years, researchers have tried to identify new tools to try to narrow down the interval within which to place the time of death; among these, the analysis of microRNAs seems to be promising. An evidence-based systematic review of the literature has been conducted to evaluate the state of the art of knowledge, focusing on the potential correlation between miRNA degradation and PMI estimation. The research has been performed using the electronic databases PubMed, Scopus, and WOS. The results allowed us to highlight the usefulness of miRNAs both as markers for PMI estimation and for normalization, especially due to their stability. In fact, some miRNAs remain particularly stable for long periods and in different tissues, while others degrade faster. Furthermore, there are numerous factors capable of influencing the behavior of these molecules, among which the type of tissue, the cause of death, and the circadian rhythm appear to be the most relevant. Despite the promising results of the few articles present in the literature, because of the numerous limitations they are burdened by, further research is still necessary to achieve more solid and shareable results.

Potential Role of mRNA in Estimating Postmortem Interval: A Systematic Review

Although the postmortem interval estimation still represents one of the main goals of forensic medicine, there are still several limitations that weigh on the methods most used for its determination: for this reason, even today, precisely estimating the postmortem interval remains one of the most important challenges in the forensic pathology field. To try to overcome these limitations, in recent years, numerous studies have been conducted on the potential use of the mRNA degradation time for reaching a more precise post mortem interval (PMI) estimation. An evidence-based systematic review of the literature has been conducted to evaluate the state of the art of the knowledge focusing on the potential correlation between mRNA degradation and PMI estimation. The research has been performed using the electronic databases PubMed and Scopus. The analysis conducted made it possible to confirm the potential applicability of mRNA for reaching a more precise PMI estimation. The analysis of the results highlighted the usefulness of some mRNAs, such as β-actin and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA, especially in short time frames, within a few hours or days of death. The matrices on which these analyses were conducted were also analyzed, resulting in less exposure to the external environment, including the heart, brain, and dental pulp. The major limitations were also reported, including the short time intervals analyzed in most of the articles, the lack of mathematical models, and the failure to report the error rate between the mRNA degradation time and PMI. Given the still small number of published articles, the lack of globally recognized standardized methods, and the numerous techniques used to evaluate the mRNA degradation times, numerous and larger studies are still necessary to reach more solid and shared evidence.

miR-26a/30d/152 are reliable reference genes for miRNA quantification in skin wound age estimation

MicroRNAs (miRNAs) are a class of small non-coding RNAs that exert their biological functions as negative regulators of gene expression. They are involved in the skin wound healing process with a dynamic expression pattern and can therefore potentially serve as biomarkers for skin wound age estimation. However, no reports have described any miRNAs as suitable reference genes (RGs) for miRNA quantification in wounded skin or samples with post-mortem changes. Here, we aimed to identify specific miRNAs as RGs for miRNA quantification to support further studies of skin wound age estimation. Overall, nine miRNAs stably expressed in mouse skin at certain posttraumatic intervals (PTIs) were preselected by next-generation sequencing as candidate RGs. These nine miRNAs and the commonly used reference genes (comRGs: U6, GAPDH, ACTB, 18S, 5S, LC-Ogdh) were quantitatively examined using quantitative real-time reverse-transcription polymerase chain reaction at different PTIs during skin wound healing in mice. The stabilities of these genes were evaluated using four independent algorithms: GeNorm, NormFinder, BestKeeper, and comparative Delta Ct. Stability was further evaluated in mice with different post-mortem intervals (PMIs). Overall, mmu-miR-26a-5p, mmu-miR-30d-5p, and mmu-miR-152-3p were identified as the most stable genes at both different PTIs and PMIs. These three miRNA RGs were additionally validated and compared with the comRGs in human samples. After assessing using one, two, or three miRNAs in combination for stability at different PTIs, PMIs, or in human samples, the set of miR-26a/30d/152 was approved as the best normalizer. In conclusion, our data suggest that the combination of miR-26a/30d/152 is recommended as the normalization strategy for miRNA qRT-PCR quantification in skin wound age estimation.

KEY POINTS

The small size of miRNAs makes them less susceptible to post-mortem autolysis or putrefaction, leading to their potential use in wound age estimation.Studying miRNAs as biological indicators of skin wound age estimation requires the selection and validation of stable reference genes because commonly used reference genes, such as U6, ACTB, GAPDH, 5S, 18S, and LC-Ogdh, are not stable.miR-26a/30d/152 are stable and reliable as reference genes and their use in combination is a recommended normalization strategy for miRNA quantitative analysis in wounded skin.

A small RNA, microRNA as a potential biomolecular marker to estimate post mortem interval in forensic science: a systematic review

BACKGROUND

Post-mortem interval (PMI) is the cornerstone of the forensic field to investigate. The examination technique by seeing the changes in the body such as algor mortis, rigor mortis, and livor mortis is a traditional technique in which accuracy is influenced by many factors. A biomolecular technique that uses microRNA (miRNA) biomarkers is developing because miRNA has good stability than other RNA, so it meets the requirements to be used for PMI estimation.

METHOD

Following the PRISMA guidelines, journals were taken from 5 databases: Scopus, Science Direct, PubMed, Embase, and Springer. The review was carried out by two people. Inclusion criteria in this review are original research, published in the last 10 years, discussing miRNA as a biomarker for PMI estimation, and free full access. While exclusion criteria are not original research and not using English.

RESULT

Eighteen journals were reviewed in this study. The study was conducted using test animals (rats) and human samples with tissue sources taken from the liver, skeletal muscle, blood, bone, heart, skin, saliva, semen, brain, lung, vitreous humor, spleen, and kidney. miRNA expression levels after death showed different results based on miRNA target, tissue source, and others.

DISCUSSION

The results of each study are different due to the use of different types of miRNA targets and tissue sources. miRNA has great potential to estimate PMI in forensic science, but it is necessary to control the influencing factors to obtain an accurate conclusion.

The impact of RNA stability and degradation in different tissues to the determination of post-mortem interval: A systematic review

Postmortem interval (PMI) in legal medicine is extremely important for both criminal and civil cases, and several sorts of techniques have been recommended. This systematic review solely focuses on approaches linked to RNA analysis, instead of including all proposed methods for determining the PMI. The term PMI will be used in this review to indicate the time between a person's death and the postmortem examination of the body. We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Guidelines when conducting this systematic review. The majority of studies on various tissues at various time intervals at various temperatures are non-human, and just a small number are on humans. The results are then provided using various statistical approaches. To calculate the PMI, post-mortem RNA degradation was examined using several tissues. The result so obtained had an opposite polarity. While some studies show that RNA stability in various tissues remained constant for several days after death, the other group of studies showed evident RNA degradation over time post-mortem, which was significantly influenced by temperature and other agonal factors. These factors have an impact on the multi-parametric mathematical model of ante and post-mortem factors on RNA degradation, as well as its applicability and feasibility. The estimation of PMI using RNA degradation can prove to be highly objective and efficient after controlling for the various factors and challenges that pose the estimation of RNA in forensic samples difficult.

The potential of using non-coding RNAs in forensic science applications

With the continuous development and integration of molecular biology and forensic science, non-coding RNAs (ncRNAs), especially ncRNAs with regulatory functions such as microRNA, long non-coding RNA, and circular RNA, have recently been actively explored by forensic scholars. In this study, we review the literature on these ncRNAs in various fields of forensic science, including postmortem interval determination, wound age estimation, forensic age assessment, cause of death analysis, and body fluid identification, aiming to evaluate the current research and provide a perspective for future applications.

Review of the current and potential use of biological and molecular methods for the estimation of the postmortem interval in animals and humans

We provide here an overview of the state of applied techniques in the estimation of the early period of the postmortem interval (PMI). The biological methods included consist of body cooling, CSF potassium, body cooling combined with CSF potassium, and tissue autolysis. For each method, we present its application in human and veterinary medicine and provide current methodology, strengths, and weaknesses, as well as target areas for improvement. We examine current and future molecular methods as they pertain to DNA and primarily to messenger RNA degradation for the estimation of the PMI, as well as the use of RNA in aging wounds, aging blood stains, and the identification of body fluids. Various types of RNA have different lengths, structures, and functions in cells. These differences in RNAs determine various intrinsic properties, such as their half-lives in cells, and, hence, their decay rate as well as their unique use for specific forensic tests. Future applications and refinements of RNA-based techniques provide opportunities for the use of molecular methods in the estimation of PMI and other general forensic applications.

Estimating the Postmortem Interval of Carcasses in the Water Using the Carrion Insect, Brain Tissue RNA, Bacterial Biofilm, and Algae

The accurate estimation of postmortem interval (PMI) is crucial in the investigation of homicide cases. Unlike carcasses on land, various biological and abiotic factors affect the decomposition of carcasses in water. In addition, the insect evidence (e.g., blow flies) that is commonly used to estimate the PMI are unavailable before the carcasses float on water. Therefore, it is difficult to estimate the PMI of a carcass in water. This study aimed to explore an effective way of estimating the PMI of a carcass in water. Carrion insects, brain tissue RNA, bacterial biofilm on the skin surface, and algae in water with PMI were studied using 45 rat carcasses in a small river. The results showed that carrion insects might not be suitable for the estimation of PMI of a carcass in water since they do not have a regular succession pattern as a carcass on land, and the flies only colonized six of the carcasses. The target genes (β-actin, GAPDH, and 18S) in the brain tissue were associated with the PMI in a time-dependent manner within 1 week after death. A polynomial regression analysis was used to assess the relationship between the gene expression profiles and PMI. The correlation coefficient R² of each regression equation was ≥ 0.924. A third-generation sequencing analysis showed that the bacteria on the skin surface of the carcass and the algae in the water samples around the carcass had a regular succession pattern, where Cryptomonas and Placoneis incased and decreased, respectively, within first 9 days. The results of this study provide a promising way to use the brain tissue RNA, bacterial biofilm, and algae to estimate the PMI of a carcass in water.

Dynamics of insects, microorganisms and muscle mRNA on pig carcasses and their significances in estimating PMI

The accurate estimate of the postmortem interval (PMI) is of vital significance in the investigation of homicide cases. In this study, three pig carcasses were placed in the field to study the pattern of insect succession, the change of microorganisms and the degradation of muscle tissue RNA during the decomposition process. The results showed that insects could quickly colonize the carcasses and still exist on them until the end of the experiment (41 days). Their development and succession patterns are useful indicators for PMI estimation. The diversity of rectal microorganisms decreased with the decomposition time. In different decomposition periods, significant differences in the rectal and soil microbial composition and relative abundance were found, which could be used to estimate the PMI with an accuracy of 3-4 days. The RNA of muscle tissue was found to have a time-dependent relationship with the PMI. Ppia and Gapdh showed a linear upward trend within 10 h after the death, followed by a gradual downward trend from 10 to 240 h. The expression of β-actin gene showed a gradual downward trend during 0-240 h. This is the first study in China to analyze the changes of insects, muscle RNA and microorganisms on pig carcasses in the same natural environment, which provide basic data for the PMI estimation.

Role of molecular techniques in PMI estimation: An update

The time frames between death and reporting of the cadaver, known as post Mortem interval (PMI), is essential in investigation of homicide deaths, suspicious deaths, or other untimely deaths as well as natural deaths. Such information helps to connect the missing links in homicide or other relevant cases. Over the time several methods are developed which depends upon factors as several methods physiological, biochemical, entomological, and archaeological for the estimation of degradation of body with time. These methods lack precision, require expertise to achieve worthy results or authentic estimate. Although these methods are currently in use but, these evaluations are still unreliable and imprecise. Hence, we still need new methods for better estimation of PMI. Initially, the predictable morphological and chemical changes in cadaver are used as PMI indicators but, as the time since death increases, the above methods become less useful for as they can't pin point the time of death rather give a ballpark idea. With the advent of the field of molecular biology, the estimation of PMI is proposed to be executed by evaluating the degradation pattern of the biological markers (DNA, RNA, and Proteins). It is now proved that the DNA is fairly unwavering over long post-mortem phases, RNA is much more labile in nature, and sensitive to degradation in a tissue-specific manner. Thus, the main purpose (aim, agenda) of this document is to provide review that mainly focuses on potential use of RNA markers in estimation of PMI. For this Critical Review, the systematic evaluation of 47 studies is executed according to the chosen inclusion and exclusion criteria.

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.

Insights into how environment shapes post-mortem RNA transcription in mouse brain

Most biological features that occur on the body after death were already deciphered by traditional medicine. However, the molecular mechanisms triggered in the cellular microenvironment are not fully comprehended yet. Previous studies reported gene expression alterations in the post-mortem condition, but little is known about how the environment could influence RNA degradation and transcriptional regulation. In this work, we analysed the transcriptome of mouse brain after death under three concealment simulations (air exposed, buried, and submerged). Our analyses identified 2,103 genes differentially expressed in all tested groups 48 h after death. Moreover, we identified 111 commonly upregulated and 497 commonly downregulated genes in mice from the concealment simulations. The gene functions shared by the individuals from the tested environments were associated with RNA homeostasis, inflammation, developmental processes, cell communication, cell proliferation, and lipid metabolism. Regarding the altered biological processes, we identified that the macroautophagy process was enriched in the upregulated genes and lipid metabolism was enriched in the downregulated genes. On the other hand, we also described a list of biomarkers associated with the submerged and buried groups, indicating that these environments can influence the post-mortem RNA abundance in its particular way.

Model for the prediction of mechanical asphyxia as the cause of death based on four biological indexes in human cardiac tissue

Determination of mechanical asphyxia as the cause of death has always been difficult for forensic pathologists, particularly when signs of asphyxia are not obvious on the body. Currently, depending on only physical examination of corpses, pathologists must be cautious when making cause-of-death appraisals. In a previous study, four biomarkers-dual-specificity phosphatase 1 (DUSP1), potassium voltage-gated channel subfamily J member 2 (KCNJ2), miR-122, and miR-3185-were screened in human cardiac tissue from cadavers that died from mechanical asphyxia compared with those that died from craniocerebral injury, hemorrhagic shock, or other causes. Expression of the markers correlated with death from mechanical asphyxia regardless of age, environmental temperature, and postmortem interval. However, a single biological index is not an accurate basis for the identification of the cause of death. In this study, receiver operating characteristic curves of the ΔCq values of the four indexes were generated. The diagnostic accuracy of the indexes was judged according to their area under the curve (DUSP1: 0.773, KCNJ2: 0.775, miR-122: 0.667, and miR-3185: 0.801). Finally, a nomogram was generated, and single blind experiment was conducted to verify the cause of death of mechanical asphyxia.

MicroRNAs as Useful Tools to Estimate Time Since Death. A Systematic Review of Current Literature

Estimating the time of death remains the most challenging question in forensic medicine, because post-mortem interval (PMI) estimation can be a remarkably difficult goal to achieve. The aim of this review is to analyze the potential of microRNAs (miRNAs) to evaluate PMI. MiRNAs have been studied as hallmarks and biomarkers in several pathologies and have also showed interesting applications in forensic science, such as high sensible biomarkers in body fluid and tissue, for wound age determination and PMI evaluation due to their low molecular weight and tissue-specific expression. The present systematic review was carried out according to the Preferred Reporting Items for Systematic Review (PRISMA) standards. We performed an electronic search of PubMed, Science Direct Scopus, and Excerpta Medica Database (EMBASE) from the inception of these databases to 12 August 2020. The search terms were ("PMI miRNA" or "PMI micro RNA") and ("miRNA" and "time of death") in the title, abstract and keywords. Through analysis of scientific literature regarding forensic uses of miRNAs, has emerged that the intrinsic characteristics of such molecules, and their subsequent resistance to degradation, make them suitable as endogenous markers in order to determine PMI. However, further and larger studies with human samples and standardized protocols are still needed.

MicroRNAs: An Update of Applications in Forensic Science

MicroRNAs (miRNAs) are a class of non-coding RNAs containing 18–24 nucleotides that are involved in the regulation of many biochemical mechanisms in the human body. The level of miRNAs in body fluids and tissues increases because of altered pathophysiological mechanisms, thus they are employed as biomarkers for various diseases and conditions. In recent years, miRNAs obtained a great interest in many fields of forensic medicine given their stability and specificity. Several specific miRNAs have been studied in body fluid identification, in wound vitality in time of death determination, in drowning, in the anti-doping field, and other forensic fields. However, the major problems are (1) lack of universal protocols for diagnostic expression testing and (2) low reproducibility of independent studies. This review is an update on the application of these molecular markers in forensic biology.

Postmortem expression of apoptosis-related genes in the liver of mice and their use for estimation of the time of death

PURPOSE

A major challenge in forensic medicine is to estimate the postmortem interval (PMI). Several approaches had been tried to determine the time of death, including physical and chemical changes. This study aims to explore the postmortem changes in the expression of apoptosis-related genes in the liver of mice and to use these changes for estimation of the PMI.

METHODS

Hepatic tissue was collected from sacrificed mice immediately after death (the control group) and at 3, 6, 9, 12, 18, and 24 hours after death. Four apoptosisrelated genes were selected as target genes, which are Caspase 3 (Casp3), B cell leukemia/ lymphoma 2 (Bcl2), BCL2-associated X protein (Bax), and Transformation related protein 53 (Trp53), and their relative expression was measured using quantitative PCR. miR-122 was used as a reference gene for normalization of the Ct (threshold cycle) values of the target genes.

RESULTS

The results revealed that the postmortem expression of Casp3 increased in a time-dependent manner; the expression of Bax increased from 3 to 18 hours followed by a decrease at 24 hours after death; the expression of Bcl2 decreased in a time-dependent manner after death; the expression of Trp53 increased from 3 to 6 hours and then started to decrease from 9 to 24 hours after death.

CONCLUSION

Based on the observed changes in the expression level of these genes, mathematical models were established to estimate the PMI. Further research is needed to investigate these markers and mathematical models in human tissues.

Identification of the miRNA-3185/CYP4A11 axis in cardiac tissue as a biomarker for mechanical asphyxia

Death by mechanical asphyxia is one of the most difficult conclusions to make in forensic science, especially in corpses displaying slight or no trauma to the surface of the body. Therefore, death by mechanical asphyxia is difficult to prove in medico-legal practice. MicroRNAs (miRNAs) are a class of small, non-coding RNAs involved in the regulation of numerous physiological and pathological cellular processes. In the present study, we demonstrate that significantly increased expression of miR-3185 in cardiac tissues was detected among cases of mechanical asphyxia compared to case of craniocerebral injury, hemorrhagic shock, sudden cardiac death and poisoning. We observed no correlation between the expression of miR-3185 and postmortem interval, age or temperature. Further work indicated that CYP4A11 is a putative target gene of miR-3185 and expressed at a relatively low level in cardiac tissue specimens from cases of mechanical asphyxia compared with specimens from cases of craniocerebral injury, hemorrhagic shock, sudden cardiac death and poisoning. Our results suggest that the miRNA-3185/CYP4A11 axis is associated with mechanical asphyxia-induced death and may provide new insight into asphyxial death investigations.

Life and death: A systematic comparison of antemortem and postmortem gene expression

Gene expression is the process by which DNA is decoded to produce a functional transcript. The collection of all transcripts is referred to as the transcriptome and has extensively been used to evaluate differentially expressed genes in a certain cell or tissue type. In response to internal or external stimuli, the transcriptome is greatly regulated by epigenetic changes. Many studies have elucidated that antemortem gene expression (transcriptome) may be linked to an array of disease etiologies as well as potential targets for drug discovery; on the other hand, a number of studies have utilized postmortem gene expression (thanatotranscriptome) patterns to determine cause and time of death. The "transcriptome after death" involves the study of mRNA transcripts occurring in human tissues after death (thanatos, Greek for death). While antemortem gene expression can provide a wide range of important information about the host, the determination of the communication of genes after a human dies has recently been explored. After death a plethora of genes are regulated via activation versus repression as well as diverse regulatory factors such as the absence or presence of stimulated feedback. Even postmortem transcriptional regulation contains many more cellular constituents and is massively more complicated. The rates of degradation of mRNA transcripts vary depending on the types of postmortem tissues and their combinatorial gene expression signatures. mRNA molecules have been shown to persist for extended time frames; nevertheless, they are highly susceptible to degradation, with half-lives of selected mRNAs varying between minutes to weeks for specifically induced genes. Furthermore, postmortem genetic studies may be used to improve organ transplantation techniques. This review is the first of its kind to fully explore both gene expression and mRNA stability after death and the trove of information that can be provided about phenotypical characteristics of specific genes postmortem.

Quantitative analysis of noncoding RNA from paired fresh and formalin-fixed paraffin-embedded brain tissues

Formalin-fixed paraffin-embedded (FFPE) tissues are commonly used both clinically and in forensic pathology. Recently, noncoding RNA (ncRNA) has attracted interest among molecular medical researchers. However, it remains unclear whether newly identified ncRNAs, such as long noncoding RNA (lncRNA) and circular RNA (circRNA), remain stable for downstream molecular analysis in FFPE tissues. Here, we assessed the feasibility of using autoptic FFPE brain tissues from eight individuals to perform quantitative molecular analyses. Selected RNA targets (9 mRNAs and 15 ncRNAs) with different amplicon lengths were studied by RT-qPCR in paired fresh and FFPE specimens. For RNA quality assessment, RNA purity and yield were comparable between the two sample cohorts; however, the RNA integrity number decreased significantly during FFPE sampling. Amplification efficiency also displayed certain variability related with amplicon length and RNA species. We found molecular evidence that short amplicons of mRNA, lncRNA, and circRNA were amplified more efficiently than long amplicons. With the assistance of RefFinder, 5S, SNORD48, miR-103a, and miR-125b were selected as reference genes given their high stability. After normalization, we found that short amplicon markers (e.g., ACTB mRNA and MALAT1 lncRNA) exhibited high consistency of quantification in paired fresh/FFPE samples. In particular, circRNAs (XPO1, HIPK3, and TMEM56) presented relatively consistent and stable expression profiles in FFPE tissues compared with their corresponding linear transcripts. Additionally, we evaluated the influence of prolonged storage time on the amplification of gene transcripts and found that short amplicons still work effectively in archived FFPE biospecimens. In conclusion, our findings demonstrate the possibility of performing accurate quantitative analysis of ncRNAs using short amplicons and standardized RT-qPCR assays in autopsy-derived FFPE samples.

Early postmortem interval (EPMI) estimation using differentially expressed gene transcripts

Genes differentially expressed after death were selected to construct a mathematical model for early postmortem interval estimation. Sprague Dawley rats were sacrificed and placed at temperatures of 4 °C, 15 °C, 25 °C, and 35 °C. Brain tissues were collected at 0, 6, 12, 18, and 24 h after death and total RNA was extracted. Changes in gene transcript levels after death were detected using microarray expression profiling and differentially expressed genes was screened. Expanded experiments were performed to validate gene transcript levels at different temperatures using the reverse transcription real-time quantitative polymerase chain reaction. Six genes with high coefficients of determination were chosen for construction of mathematical models. Optimal ternary cubic equations were built using R software with temperature, postmortem interval and ΔCq defined as the independent variable x, y and z, respectively. Equations were converted into a three-dimensional visual statistical model using MATLAB. Animal samples were used to validate the mathematical models. Results showed that the 5srRNA showed best stability at four temperatures. The genes Ninj2, Grifin, Arpp19, and Hopx showed high coefficients of determination (>80%) and low error (<3h) in verification experiments which indicate that they are potential markers for early postmortem interval estimation.

Using miRNAs and circRNAs to estimate PMI in advanced stage

In our previous study, we evaluated the stability of multi-RNA markers in heart, liver and skeletal muscle tissues of mice within 8 days after death and concluded that microRNAs (miRNAs) and circular (circRNAs) were more stable as reference genes in dead bodies than other kinds of RNAs. Based on their tissue-specific expression, we obtained reference genes for three kinds of tissues: miR-122, miR-133a and 18S in heart tissues; LC-Ogdh, circ-AFF1 and miR-122 in liver tissues; and miR-133a, circ-AFF1 in skeletal muscle tissues. For the estimation of post mortem interval (PMI), we also selected suitable biomarkers, which exhibited the best correlation coefficient with PMI. In our stability analysis of multi-RNA markers, Gapdh, Rps18, U6 and β-actin were unstable and selected as candidate target biomarkers. By analyzing the correlation between the expression levels of candidate target biomarkers and PMI, we obtained suitable target biomarkers for the three kinds of tissues, respectively. Finally, we established mathematical models of PMI estimation using the above selected reference genes and target biomarkers. The low estimated error in the validated samples demonstrated that PMI in advanced stage could be accurately predicted by real-time quantitative polymerase chain reaction (qPCR) through systematically selected effective reference genes and target biomarkers. Besides, combining the estimated results of various tissues and multi-biomarkers could improve the accuracy of PMI estimation.

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.

Evaluating the potential of housekeeping genes, rRNAs, snRNAs, microRNAs and circRNAs as reference genes for the estimation of PMI

The precise estimation of postmortem interval (PMI) is a critical step in death investigation of forensic cases. Detecting the degradation of RNA in tissues by real time quantitative polymerase chain reaction (RT-qPCR) technology provides a new theoretical basis for estimation of PMI. However, most commonly used reference genes degrade over time, while previous studies seldom consider this when selecting suitable reference genes for the estimation of PMI. Studies have shown microRNAs (miRNAs) are very stable and circular RNAs (circRNAs) have recently emerged as a novel class of RNAs with high stability. We aimed to evaluate the stability of the two kinds of RNAs and normal reference genes using geNorm and NormFinder algorithms to identify tissue-specific reference genes for PMI estimation. The content of candidate RNAs from mouse heart, liver and skeletal muscle tissues were dynamically examined in 8 consecutive days after death. Among the 11 candidate genes (β-actin, Gapdh, Rps18, 5S, 18S, U6, miR-133a, miR-122, circ-AFF1, LC-Ogdh and LC-LRP6), the following genes showed prioritized stability: miR-122, miR-133a and 18S in heart tissues; LC-Ogdh, circ-AFF1 and miR-122 in liver tissues; and miR-133a, circ-AFF1 and LC-LRP6 in skeletal muscle tissues. Our results suggested that miRNAs and circRNAs were more stable as reference genes than other kinds of RNAs regarding PMI estimation. The appropriate internal control genes were not completely the same across tissue types.

G6PC3, ALDOA and CS induction accompanies mir-122 down-regulation in the mechanical asphyxia and can serve as hypoxia biomarkers

Hypoxia influences different cellular biological processes. To reveal the dynamics of hypoxia's effects on miRNA regulation in vivo, we examined the expression levels of all miRNAs in human brain and heart specimens from cases of mechanical asphyxia compared with those from cases of craniocerebral injury and hemorrhagic shock. We further validated differently expressed miRNAs in another 84 human specimens and rat models. We found that mir-122 was significantly down-regulated and that its putative targets G6PC3, ALDOA and CS were increased in the brain and cardiac tissues in cases of mechanical asphyxia compared with craniocerebral injury and hemorrhagic shock. Our data indicate that mir-122 and its targets G6PC3, ALDOA and CS play roles in the hypoxia responses that regulate glucose and energy metabolism and can serve as hypoxia biomarkers.

Gene expression in the twilight of death: The increase of thousands of transcripts has implications to transplantation, cancer, and forensic research

After a vertebrate dies, many of its organ systems, tissues, and cells remain functional while its body no longer works as a whole. We define this state as the "twilight of death" - the transition from a living body to a decomposed corpse. We claim that the study of the twilight of death is important to ethical, legal and medical science. We examined gene expression at the twilight of death in the zebrafish and mouse reaching the conclusion that apparently thousands of transcripts significantly increase in abundance from life to several hours/days postmortem relative to live controls. Transcript dynamics of different genes provided "proof-of-principle" that models accurately predict an individual's elapsed-time-of-death (i.e. postmortem interval). While many transcripts were associated with survival and stress compensation, others were associated with epigenetic factors, developmental control, and cancer. Future studies are needed to determine whether the high incidence of cancer in transplant recipients is due to the postmortem processes in donor organs.

Systematic analysis of gene expression patterns associated with postmortem interval in human tissues

Postmortem mRNA degradation is considered to be the major concern in gene expression research utilizing human postmortem tissues. A key factor in this process is the postmortem interval (PMI), which is defined as the interval between death and sample collection. However, global patterns of postmortem mRNA degradation at individual gene levels across diverse human tissues remain largely unknown. In this study, we performed a systematic analysis of alteration of gene expression associated with PMI in human tissues. From the Genotype-Tissue Expression (GTEx) database, we evaluated gene expression levels of 2,016 high-quality postmortem samples from 316 donors of European descent, with PMI ranging from 1 to 27 hours. We found that PMI-related mRNA degradation is tissue-specific, gene-specific, and even genotype-dependent, thus drawing a more comprehensive picture of PMI-associated gene expression across diverse human tissues. Additionally, we also identified 266 differentially variable (DV) genes, such as DEFB4B and IFNG, whose expression is significantly dispersed between short PMI (S-PMI) and long PMI (L-PMI) groups. In summary, our analyses provide a comprehensive profile of PMI-associated gene expression, which will help interpret gene expression patterns in the evaluation of postmortem tissues.

DUSP1 and KCNJ2 mRNA upregulation can serve as a biomarker of mechanical asphyxia-induced death in cardiac tissue

The incidence of death by asphyxia is second to the incidence of death by mechanical injury; however, death by mechanical asphyxia may be difficult to prove in court, particularly in cases in which corpses do not exhibit obvious signs of asphyxia. To identify a credible biomarker of asphyxia, we first examined the expression levels of 47,000 mRNAs in human cardiac tissue specimens from individuals who died of mechanical asphyxia and compared the expression levels with the levels of the corresponding mRNAs in specimens from individuals who died of craniocerebral injury using microarray. We selected 119 differentially expressed mRNAs, examined the expression levels of these mRNAs in 44 human cardiac tissue specimens of individuals who died of mechanical asphyxia, craniocerebral injury, hemorrhagic shock, or other causes. That the expression of dual-specificity phosphatase 1 (DUSP1) and potassium voltage-gated channel subfamily J member 2 (KCNJ2) was upregulated in human cardiac tissues from the mechanical asphyxia group compared with control tissues, regardless of age, environmental temperature, and postmortem interval (PMI), indicating that DUSP1 and KCNJ2 may be associated with mechanical asphyxia-induced death and can thus serve as useful biomarkers of death by mechanical asphyxia.

Accurate predictions of postmortem interval using linear regression analyses of gene meter expression data

In criminal and civil investigations, postmortem interval is used as evidence to help sort out circumstances at the time of human death. Many biological, chemical, and physical indicators can be used to determine the postmortem interval - but most are not accurate. Here, we sought to validate an experimental design to accurately predict the time of death by analyzing the expression of hundreds of upregulated genes in two model organisms, the zebrafish and mouse. In a previous study, the death of healthy adults was conducted under strictly controlled conditions to minimize the effects of confounding factors such as lifestyle and temperature. A total of 74,179 microarray probes were calibrated using the Gene Meter approach and the transcriptional profiles of 1063 genes that significantly increased in abundance were assembled into a time series spanning from life to 48 or 96h postmortem. In this study, the experimental design involved splitting the transcription profiles into training and testing datasets, randomly selecting groups of profiles, determining the modeling parameters of the genes to postmortem time using over- and/or perfectly-defined linear regression analyses, and calculating the fit (R²) and slope of predicted versus actual postmortem times. This design was repeated several thousand to million times to find the top predictive groups of gene transcription profiles. A group of eleven zebrafish genes yielded R² of 1 and a slope of 0.99, while a group of seven mouse liver genes yielded a R² of 0.98 and a slope of 0.97, and seven mouse brain genes yielded a R² of 0.95 and a slope of 0.87. In all cases, groups of gene transcripts yielded better postmortem time predictions than individual gene transcripts. The significance of this study is two-fold: selected groups of gene transcripts provide accurate prediction of postmortem time, and the successfully validated experimental design can now be used to accurately predict postmortem time in cadavers.

Estimation of the human postmortem interval using an established rat mathematical model and multi-RNA markers

In our previous study, a R code-based mathematical model using RNA degradation patterns was developed for PMI determination in rat brain specimens. However, the postmortem changes of RNA are much more complicated in real cases, and there is still a huge challenge in efficiently applying information in animal data to real cases. In the present study, different RNA markers in both rat and human tissues were collected to screen valid biomarkers and the corresponding mathematical models were established and validated. With the same methodology, multi-RNA markers of myocardium and liver tissues were detected by qPCR and the Ct values of ten biomarkers generally increased with prolonged PMIs. 5S, miR-1 and miR-133a were shown to be optimum reference biomarkers that were not affected by a PMI of up to 5 or more days; however, liver-specific miR-122 began to degrade under higher temperatures and only 5S was selected as an endogenous control in the liver. Among the tested target RNAs, similar to our previous study in brain tissue, β-actin (ΔCt) was found to exhibit the best correlation coefficient with PMI and was employed to build mathematical models using R software. Following validation, the relatively low estimated error demonstrated that PMIs can be accurately predicted in human cases through comprehensive consideration of various factors and using effective biomarkers.