International Journal of Molecular Sciences· 2026Q1
Postmortem Gene Expression and the Thanatotranscriptome: Postmortem Interval Estimation, Forensic Applications, and Future Perspectives
- 0citations
- Q1SCImago
- 2026year
Short summary
Postmortem RNA dynamics, termed the thanatotranscriptome, can estimate postmortem interval (PMI) with a root mean square error of 4.75 hours in human blood, offering molecular insights beyond passive cellular cessation.
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Key points
- Certain RNA transcripts persist after death, exhibiting dynamic changes that can be quantified.
- The thanatotranscriptome concept leverages these postmortem RNA dynamics for postmortem interval (PMI) estimation.
- A human blood study achieved a PMI estimation model with a root mean square error of 4.75 hours.
- Factors like tissue type, temperature, cause of death, and sample handling influence RNA profiles.
AI-generated from the title and abstract; the full text is not read.
Abstract
Postmortem molecular changes are more complex than a passive, uniform cessation of all cellular activity. Human and animal studies have demonstrated that certain RNA transcripts remain detectable for defined periods after death and that transcript levels exhibit tissue- and time-dependent changes. These postmortem RNA dynamics underpin the concept of the thanatotranscriptome and may provide molecular information relevant to postmortem interval (PMI) estimation. Postmortem changes have been reported in the abundance of transcripts associated with apoptosis, cellular stress, immune responses, and DNA damage response and repair pathways. However, observed transcript levels may reflect the combined effects of antemortem RNA stability, selective RNA degradation, and potentially residual transcriptional activity. A longitudinal study of human blood reported a root mean square error (RMSE) of 4.75 h for a PMI estimation model based on multiple transcripts, illustrating the quantitative potential of this approach. Nevertheless, RNA profiles may be influenced by tissue type, temperature, cause of death and agonal processes, interindividual biological variability, and sampling and storage conditions. Methodological heterogeneity and the lack of independent external validation further limit the translation of these approaches into routine forensic practice. This review critically evaluates the molecular basis of postmortem gene expression and RNA dynamics, messenger RNA (mRNA) and microRNA (miRNA) biomarkers, transcriptome-based models for PMI estimation, and their potential forensic applications, with particular emphasis on the need for standardization, independent validation, and multi-biomarker approaches.
The authors' abstract, as published at the source. International Journal of Molecular Sciences, 2026 · DOI ↗
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Field: Insect Science
Insect ScienceAgricultural and Biological Sciences