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Analysis of RNA in the estimation of post-mortem interval: a review of current evidence

International Journal of Legal Medicine volume 133, pages 1629–1640 (2019)Cite this article

Abstract

Post-mortem interval (PMI) determination is one of the most important issues in forensic sciences. In the past, forensic scientists provided different approaches (physical, chemical, and entomological) for the estimation of PMI without success.

However, advances in molecular biology over the last two decades have allowed us to assess the time-dependent degradation of biological markers (e.g., proteins, DNA, and RNA). Thus, the aim of the manuscript is to provide a review of the recent progress in the estimation of PMI using molecular biology methods, mainly focusing on the potential usefulness of RNA markers. To this end, 29 studies have been systematically reviewed, each one chosen according to specific inclusion/exclusion criteria. The selected studies evaluated the contribution of endogenous reference genes in different biological samples in order to determine the PMI based on post-mortem RNA degradation as a function of other influencing factors such as time, cause of death, and environmental conditions.

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Affiliations

  1. Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Via Falloppio 50, 35121, Padua, Italy

    Salvatore Scrivano & Matteo Sanavio

  2. Department of Molecular Medicine, Laboratory of Forensic Genetics, University of Padova, Via Falloppio 50, 35121, Padua, Italy

    Pamela Tozzo & Luciana Caenazzo

Authors
  1. Salvatore Scrivano
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  2. Matteo Sanavio
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  3. Pamela Tozzo
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  4. Luciana Caenazzo
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Correspondence to Salvatore Scrivano.

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Scrivano, S., Sanavio, M., Tozzo, P. et al. Analysis of RNA in the estimation of post-mortem interval: a review of current evidence. Int J Legal Med 133, 1629–1640 (2019). https://doi.org/10.1007/s00414-019-02125-x

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  • DOI: https://doi.org/10.1007/s00414-019-02125-x

Keywords

  • Post-mortem interval
  • Forensic genetics
  • Molecular biology
  • mRNA
  • Mathematical model