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Recommendations for the successful identification of altered human remains using standard and emerging technologies: Results of a systematic approach. | LitMetric

AI Article Synopsis

Article Abstract

Successful DNA-based identification of altered human remains relies on the condition of the corpses and varies between tissue types. Therefore, the aim of this prospective multicenter study was to generate evidence-based recommendations for the successful identification of altered remains. For this, 19 commonly used soft and hard tissues from 102 altered human bodies were investigated. The corpses' condition was categorized into three anatomical regions using a practical scoring system. Besides other data, DNA yields, degradation indices, and short tandem repeat (STR) profile completeness were determined in 949 tissue samples. Additionally, varying degrees of alteration and tissue-specific differences were evaluated using the Next Generation Sequencing (NGS) platform MiSeq FGx™. Selected challenging samples were sequenced in parallel with the Ion S5™ platform to assess platform-specific performances in the prediction of the deceased's phenotype and the biogeographic ancestry. Differences between tissue types and DNA extraction methods were found, revealing, for example, the lowest degradation for vertebral disc samples from corpses with initiating, advanced and high degrees of decomposition. With respect to STR profile completeness, blood samples outperformed all other tissues including even profoundly degraded corpses. NGS results revealed higher profile completeness compared to standard capillary electrophoresis (CE) genotyping. Per sample, material and degradation degree, a probability for its genotyping success, including the "extended" European Standard Set (eESS) loci, was provided for the forensic community. Based on the observations, recommendations for the alteration-specific optimal tissue types were made to improve the first-attempt identification success of altered human remains for forensic casework.

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Source
http://dx.doi.org/10.1016/j.fsigen.2022.102790DOI Listing

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