Eye and hair color prediction of human DNA recovered from Lucilia sericata larvae.
Emre DeymenciIlksen Sari OGonul FilogluErdal PolatÖzlem BülbülPublished in: International journal of legal medicine (2023)
Forensic entomological evidence is employed to estimate minimum postmortem interval (PMImin), location, and identification of fly samples or human remains. Traditional forensic DNA analysis (i.e., STR, mitochondrial DNA) has been used for human identification from the larval gut contents. Forensic DNA phenotyping (FDP), predicting human appearance from DNA-based crime scene evidence, has become an established approach in forensic genetics in the past years. In this study, we aimed to recover human DNA from Lucilia sericata (Meigen 1826) (Diptera: Calliphoridae) gut contents and predict the eye and hair color of individuals using the HIrisPlex system. Lucilia sericata larvae and reference blood samples were collected from 30 human volunteers who were under maggot debridement therapy. The human DNA was extracted from the crop contents and quantified. HIrisPlex multiplex analysis was performed using the SNaPshot minisequencing procedure. The HIrisPlex online tool was used to assess the prediction of the eye and hair color of the larval and reference samples. We successfully genotyped 25 out of 30 larval samples, and the most SNP genotypes (87.13%) matched those of reference samples, though some alleles were dropped out, producing partial profiles. The prediction of the eye colors was accurate in 17 out of 25 larval samples, and only one sample was misclassified. Fourteen out of 25 larval samples were correctly predicted for hair color, and eight were misclassified. This study shows that SNP analysis of L. sericata gut contents can be used to predict eye and hair color of a corpse.
Keyphrases
- endothelial cells
- induced pluripotent stem cells
- circulating tumor
- pluripotent stem cells
- single molecule
- mitochondrial dna
- cell free
- drosophila melanogaster
- gene expression
- stem cells
- mass spectrometry
- genome wide
- mesenchymal stem cells
- high resolution
- dna methylation
- nucleic acid
- smoking cessation
- bioinformatics analysis