Project description:The post-mortem interval (PMI) is the time that elapses since the death of an individual until the body is found. Different molecules have been analyzed to better estimate the PMI with variable results. The miRNAs draw attention in the forensic field to estimate the PMI, since they can better support degradation. To find potential biomarkers for PMI estimation, we analyzed the miRNome at early PMI in rat skeletal muscle using the Affymetrix GeneChip™ miRNA 4.0 micoarrays. In this dataset, we include the expression of 1218 rat miRNAs at early postmortem interval.
Project description:The postmortem interval (PMI) is the time elapsing since the death of an individual until the body is examined. Different molecules have been analyzed to better estimate the PMI with variable results. The miRNAs draw attention in the forensic field to estimate the PMI as they can better support degradation. In the present work, we analyzed the miRNome at early PMI in rats' skeletal muscle using the Affymetrix GeneChip™ miRNA 4.0 microarrays. We found 156 dysregulated miRNAs in rats' skeletal muscle at 24 h of PMI, out of which 84 were downregulated, and 72 upregulated. The miRNA most significantly downregulated was miR-139-5p (FC = -160, p = 9.97 × 10-11), while the most upregulated was rno-miR-92b-5p (FC = 241.18, p = 2.39 × 10-6). Regarding the targets of these dysregulated miRNAs, the rno-miR-125b-5p and rno-miR-138-5p were the miRNAs with more mRNA targets. The mRNA targets that we found in the present study participate in several biological processes such as interleukin secretion regulation, translation regulation, cell growth, or low oxygen response. In addition, we found a downregulation of SIRT1 mRNA and an upregulation of TGFBR2 mRNA at 24 h of PMI. These results suggest there is an active participation of miRNAs at early PMI which could be further explored to identify potential biomarkers for PMI estimation.
Project description:Accurate estimation of the postmortem interval is critical in forensic investigations to determine the time since death. While traditional methods offer limited precision, molecular approaches based on gene expression have shown promise. mRNA retains detectable and quantifiable expression changes that reflect biological processes occurring after death. In this study, we analyzed the transcriptome of rat skeletal muscle at 0 hours (control) and 48 hours of post mortem interval to identify differentially expressed mRNAs that may serve as potential biomarkers, aiming to enhance the accuracy and reliability of PMI estimation in forensic science. Microarray analysis using the Affymetrix Clariom S Rat array (Affymetrix) facilitated a comprehensive overview of the skeletal muscle transcriptome at 48 hours of postmortem interval. This platform allowed for the simultaneous quantification of thousands of transcripts, revealing widespread gene expression alterations associated with the postmortem interval. The resulting transcriptomic profile not only provided insight into molecular changes occurring after death but also highlighted specific mRNAs as potential biomarker candidates for PMI estimation in forensic contexts.
Project description:Attempts to establish a tissue bank from autopsy samples have led to uncovering of the secrets of many diseases. Here, we examined the length of time that the RNA from postmortem tissues is available for microarray analysis and reported the gene expression profile for up- and down-regulated genes during the postmortem interval (PMI). We extracted RNA from fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) brains and livers of three different groups of mice: 1) mice immediately after death, 2) mice that were stored at room temperature for 3 h after death, and 3) mice that were stored at 4°C for 18 h after death, as this storage resembles the human autopsy process in Japan. Based on the microarray analysis, we selected genes that were altered by >1.3-fold or <0.77-fold and classified these genes using hierarchical cluster analysis following DAVID (database for annotation, visualization, and integrated discovery) gene ontology analysis. These studies revealed that cytoskeleton-related genes were enriched in the set of up-regulated genes, while serine protease inhibitors were enriched in the set of down-regulated genes. Interestingly, although the RNA quality was maintained, up-regulated genes were not validated by quantitative PCR, suggesting that these genes may become fragmented or modified by an unknown mechanism. We extracted RNA from fresh-frozen (FF) brains and livers from mice under three different conditions: 1) mice just after death as a control, 2) mice that were stored at room temperature for 3 h after death, and 3) mice that were stored at 4°C for 18 h after death to resemble the human autopsy process. We also created formalin-fixed paraffin-embedded (FFPE) tissue blocks at the same time using mouse organs obtained under the three conditions described above. We then purified RNA from the FFPE tissue blocks. Furthermore, we performed microarray analysis to examine changes in the gene expression profiles during the postmortem interval in FF samples and to compare ene expression profiles between FF and FFPE samples at three different postmortem times as described for the FF samples.
Project description:This study investigates mRNA degradation in human dental pulp to explore its utility for estimating the late postmortem interval (LPMI). Morphological changes in pulp tissue at 0, 7, 14, 21 and 28 days postmortem were observed via HE staining, showing progressive cellular degradation. High-throughput sequencing of samples at 0, 7, and 21 days identified candidate mRNAs. Five mRNA biomarkers were obtained , namely SRSF5, FGFR1, ACADVL, FOS, and LRP1. Their expression levels at 0, 3, 7, 10, 14, 21 and 28 days were quantified using RT–qPCR with 18S rRNA as the reference gene. Results demonstrated a consistent decrease in all five mRNAs over time. Mathematical models correlating mRNA levels with LPMI were established. Multi-index models exhibited superior fitting accuracy and predictive performance compared to single-index models, as validated using samples from 10, 18 and 25 days postmortem intervals, indicating greater practical applicability. This approach provides a new direction for forensic LPMI estimation research and contributes to the development of forensic pathology.
Project description:Attempts to establish a tissue bank from autopsy samples have led to uncovering of the secrets of many diseases. Here, we examined the length of time that the RNA from postmortem tissues is available for microarray analysis and reported the gene expression profile for up- and down-regulated genes during the postmortem interval (PMI). We extracted RNA from fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) brains and livers of three different groups of mice: 1) mice immediately after death, 2) mice that were stored at room temperature for 3 h after death, and 3) mice that were stored at 4°C for 18 h after death, as this storage resembles the human autopsy process in Japan. Based on the microarray analysis, we selected genes that were altered by >1.3-fold or <0.77-fold and classified these genes using hierarchical cluster analysis following DAVID (database for annotation, visualization, and integrated discovery) gene ontology analysis. These studies revealed that cytoskeleton-related genes were enriched in the set of up-regulated genes, while serine protease inhibitors were enriched in the set of down-regulated genes. Interestingly, although the RNA quality was maintained, up-regulated genes were not validated by quantitative PCR, suggesting that these genes may become fragmented or modified by an unknown mechanism.
Project description:Bovine longissimus lumborum (LL) and psoas major (PM) muscles biopsy samples were collected from four carcasses (n = 4) at 45 min, 12 h, and 36 h postmortem from a commercial beef processing facility. Proteome profile variation between beef LL and PM during the early postmortem period were evaluated by tandem mass tag labeling containing ten different isobaric compounds.