Application of Forensic DNA Phenotyping for Prediction of Eye, Hair and Skin Colour in Highly Decomposed Bodies

Author:

Fabbri Matteo1ORCID,Alfieri Letizia1,Mazdai Leila2ORCID,Frisoni Paolo3,Gaudio Rosa Maria4ORCID,Neri Margherita1ORCID

Affiliation:

1. Department of Medical Sciences, University of Ferrara, 44121 Ferrara, Italy

2. Department of Neuroscience and Rehabilitation, University of Ferrara, 44121 Ferrara, Italy

3. Unit of Legal Medicine, Azienda USL di Ferrara, 44121 Ferrara, Italy

4. Department of Translational Medicine, University of Ferrara, 44121 Ferrara, Italy

Abstract

In the last few years, predicting externally visible characteristics (EVCs) by adopting informative DNA molecular markers has become a method in forensic genetics that has increased its value, giving rise to an interesting field called “Forensic DNA Phenotyping” (FDP). The most meaningful forensic applications of EVCs prediction are those in which, having only a DNA sample isolated from highly decomposed remains, it is essential to reconstruct the physical appearance of a person. Through this approach, we set out to evaluate 20 skeletal remains of Italian provenance in order to associate them with as many cases of missing persons as possible. To achieve the intended goal, in this work we applied the HIrisPlex-S multiplex system through the conventional short tandem repeats (STR) method to confirm the expected identity of subjects by evaluating phenotypic features. To investigate the reliability and accuracy of the DNA-based EVCs prediction, pictures of the cases were compared as they were available to researchers. Results showed an overall prediction accuracy greater than 90% for all three phenotypic features—iris, hair, and skin colour—at a probability threshold of 0.7. The experimental analysis showed inconclusive results in only two cases; this is probably due to the characteristics of subjects who had an intermediate eye and hair colour, for which the DNA-based system needs to improve the prediction accuracy.

Publisher

MDPI AG

Subject

Health Information Management,Health Informatics,Health Policy,Leadership and Management

Reference60 articles.

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