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.
Keywords: Mathematical models; Postmortem interval (PMI); circRNAs; miRNAs.
Copyright © 2019. Published by Elsevier B.V.