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, ß-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.

RNA degradation as described by a mathematical model for postmortem interval determination.

Precisely determining the postmortem interval (PMI) is crucial to civil, criminal and forensic cases. A technique to exploit the postmortem RNA transcript level was developed to increase the accuracy and practicality of PMI estimation. For this purpose, lung tissues and muscle tissues were removed at twelve time points (0-144 h) from rat corpses that had been stored at three different temperatures (10, 20 and 30 °C). Human tissues were collected at autopsy from twelve real cases with known PMI values and other parameters. After the RNA was extracted from all these samples, the transcript levels of nine biomarkers were analyzed by real-time quantitative PCR (RT-qPCR). With the assistance of geNorm, miR-195, miR-200c, 5S, U6 and RPS29 were selected as reference biomarkers for lung specimens; miR-1, miR-206, 5S and RPS29 were chosen as control markers for muscle tissues. On the contrary, ACTB and GAPDH were significantly correlated with the PMI. The mathematical models using these target biomarkers were constructed to describe the characteristic relationship between △Ct values (normalized to reference biomarkers) and the observed PMI for each temperature group. Following validation, the relatively low error rates (7.4% and 12.5% for rat and human samples, respectively) demonstrated the accuracy and reliability of the mathematical model. We believe these results indicate that the multi-parametric mathematical model can become a practical tool for PMI estimation.

Postmortem interval determination using 18S-rRNA and microRNA.

The importance of determining postmortem interval (PMI) is crucial to criminal, civil and forensic cases. The precise estimation of PMI is a critical step in many death investigations. A technique exploiting the level of RNA, 18S rRNA and microRNA to estimate PMI was investigated. 18S-rRNA is a main ribosomal RNA presented as part of the ribosomal protein complex, while microRNA is a class of small non-coding single-stranded RNA, only 21-25 nucleotides, which has a strong conservation between different species. In this study, heart tissues were removed from adult rats at various postmortem intervals. An efficient extraction and detection protocol to analyze the level of 18S-rRNA and microRNA in postmortem tissue was carried out. The process consists of total RNA extraction, transcription and visualization by quantitative real time PCR. The result indicates a characteristic parabola relationship between postmortem period and Ct values for 18S-rRNA in dead rat hearts. The result indicates that the degradation pattern of tissue 18S-rRNA and microRNA is useful in the determination of the postmortem interval within seven days.

A time course study demonstrating mRNA, microRNA, 18S rRNA, and U6 snRNA changes to estimate PMI in deceased rat's spleen.

Determining the postmortem interval (PMI) is important in criminal, civil, and forensic cases. We examined the feasibility of using the transcript abundances of mRNAs, 18S rRNA, U6 snRNA, and microRNAs as a means to estimate the PMI. We removed spleen tissues from rats at different PMIs under 4°C or 25°C and examined gene transcript abundances in these samples by RT-qPCR. Using the algorithm geNorm, we found that microRNAs to be appropriate control markers because they were less affected by PMI and temperature. We also characterized relationships between observed PMI and the transcript levels of the above-mentioned RNAs. GAPDH1 and ACTB1 fluctuated slightly like cubic curves, while GAPDH2 and ACTB2 decreased rapidly. 18S rRNA transcript level exhibited a parabolic-like trend at 25°C and exponential growth at 4°C, while U6 transcript level exhibited exponential decay at 25°C and a parabolic-like trend at 4°C. Following validation, we conclude that GAPDH2, ACTB2, and 18S rRNA are suitable makers in the accurate determination of PMI.

The selection of endogenous genes in human postmortem tissues.

Precisely determining the postmortem interval (PMI), which is crucial to criminal and forensic cases, is a research in which quantitative RT-PCR (also known as qRT-PCR or real-time RT-PCR) has been used to analyse gene expression levels and data normalisation should be required to eliminate the differences among the samples. Therefore, it is quite necessary to find stable molecular biological markers in PMI determination research. In this study, we compared nine commonly used endogenous markers (containing ACTB, GAPDH, B2M, U6, 18S rRNA, hsa-mir-1, hsa-mir-9, hsa-mir-194-1 and hsa-mir-203) in the 109 human tissue samples obtained from autopsy at the aim of finding stable markers in human tissues with consideration of the impact of parameters (PMI and cause of death). After RNA was extracted from four tissues (heart, brain, kidney, skin), the Ct values of nine endogenous markers were obtained by qRT-PCR and assessed by geNorm software. The results showed that U6, GAPDH and 18S rRNA were the suitable markers in our set of samples in various corpse conditions, that B2M and ACTB were reliable internal controls in heart tissue only, and that microRNAs had such high M values that they should not be chosen for endogenous control genes.