Article: Application of Forensic DNA Phenotyping for Prediction of Eye, Hair and Skin Colour in Highly Decomposed Bodies.
Healthcare (Basel, Switzerland)
2023 Volume 11, Issue 5
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 ... ...
| 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. |
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| Language | English |
| Publishing date | 2023-02-23 |
| Publishing country | Switzerland |
| Document type | Journal Article |
| ZDB-ID | 2721009-1 |
| ISSN | 2227-9032 |
| ISSN | 2227-9032 |
| DOI | 10.3390/healthcare11050647 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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