Finding new information from old bones

Predicting externally visible characteristics of the deceased using just genetic information is an extremely difficult task, and one that has only become possible in recent years. New investigative technologies and techniques that improve the accuracy and efficiency of identifying  phenotypes from DNA samples are likely to have a huge impact on the fields of forensics and archaeology.


New research published in Investigative Genetics by Jolanta Draus-Barini et al. reports a novel technique to predict hair and eye colour from just skeletal remains. The technology involved, the HIrisPlex system, has previously been demonstrated to do this using DNA samples from live individuals. Using information from these previous studies the study authors characterised 24 polymorphisms that they could identify from skeletal DNA.


The study looked at 26 tooth or bone DNA extracts, ranging between 1 and approximately 800 years of age. One of the oldest samples was DNA from a medieval skeleton, where the individual, found in the Benedictine Abbey just outside Kraków (Poland), was identified to be a female with dark blonde/brown hair and brown eyes.


With current forensic knowledge, hair and eye colour are two externally visible characteristics that we can more accurately predict from DNA samples, owing to low genetic complexity of the traits and limited environmental impact to the samples. The anthropological and forensic genetic community are encouraged by the authors of this study to use the HIrisPlex system for DNA-based hair and eye colour prediction in future evolutionary and anthropological studies, and for forensic case work involving skeletal remains.


You can read the full article on the website, where you can also sign up for article alerts from the journal. For more information on Investigative Genetics, or to submit a manuscript, please visit the journal website or contact the Editorial Office.

Sam Rose

Journal Development Manager at BioMed Central
Sam studied Biomedical Sciences at the University of Manchester, and is responsible for the development of BioMed Central's genetics journal portfolio.
Sam Rose

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