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When bodies are highly decomposed and identification based on morphologic features is no longer possible, short tandem repeat (STR) genotyping has been proved as a convenient and reliable alternative. However, at very advanced decomposition stages postmortal tissue putrefaction processes can affect microsatellite instability and therefore not all types of post mortem tissues are still equally suitable for STR genotyping and subsequent forensic identification. In many cases bone or dental material is used but here reprocessing is very elaborate and expensive. Thus, multiple studies have focused on the eligibility of soft tissue and organs where DNA extraction is a lot easier and faster. In this study different cases were evaluated in which a successful forensic identification was only possible with DNA material extracted from specific tissues. By doing so we aim to compare differential suitability of soft tissues for DNA analysis of highly decomposed bodies. This was achieved by a systematic classification of decomposed bodies and the analysis of multiple organs to evaluate the qualification of soft tissue for DNA profiling in respect to the degree of decomposition. In summary, we detected differences in the suitability of various soft tissues for DNA-based identification. Cerebral matter turned out to be one of the most useful targets in highly decomposed bodies. [ABSTRACT FROM AUTHOR]

Abstract: A badly decomposed body required identification by means of DNA analysis. A brother and sister of the deceased were available as reference subjects. Although investigation of Y-chromosomal markers established an exclusion condition, autosomal markers suggested a positive identification. In order to increase the reliability of the tests, X-chromosomal markers were also investigated. This analysis showed the body to have an XXY genotype (Klinefelter''s syndrome). A number of hypotheses were assessed using biostatistical methods, ultimately resulting in a definite identification. The special aspect of Klinefelter''s syndrome proved highly useful for biostatistical analysis. [Copyright &y& Elsevier]