1. RNA degradation as described by a mathematical model for postmortem interval determination
- Author
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Aimin Xue, Long Chen, Ye-Hui Lv, Hui Pan, Heng Zhang, Kaijun Ma, Wen-Can Li, Huijun Wang, and Jianlong Ma
- Subjects
Adult ,Male ,Ribosomal Proteins ,0301 basic medicine ,Pathology ,medicine.medical_specialty ,Adolescent ,RNA Stability ,Interval (mathematics) ,Biology ,Transcript level ,Real-Time Polymerase Chain Reaction ,Pathology and Forensic Medicine ,Rats, Sprague-Dawley ,03 medical and health sciences ,0302 clinical medicine ,medicine ,Animals ,Humans ,030216 legal & forensic medicine ,Muscle, Skeletal ,Lung ,Models, Statistical ,General Medicine ,Rna degradation ,Middle Aged ,Actins ,MicroRNAs ,Pmi estimation ,030104 developmental biology ,RNA, Ribosomal ,Child, Preschool ,Postmortem Changes ,Female ,Glyceraldehyde-3-Phosphate Dehydrogenase (Phosphorylating) ,Law - Abstract
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.
- Published
- 2016