Messenger RNA (mRNA) profiling in post-mortem human tissue might reveal information about gene expression at the time point of death or close to it. When working with post-mortem human tissue, one is confronted with a natural RNA degradation caused by several parameters which are not yet fully understood. The aims of the present study were to analyse the influence of impaired RNA integrity on the reliability of quantitative gene expression data and to identify ante- and post-mortem parameters that might lead to reduced RNA integrities in post-mortem human brain, cardiac muscle and skeletal muscle tissues. Furthermore, this study determined the impact of several parameters like type of tissue, age at death, gender and body mass index (BMI), as well as duration of agony, cause of death and post-mortem interval on the RNA integrity. The influence of RNA integrity on the reliability of quantitative gene expression data was analysed by generating degradation profiles for three gene transcripts. Based on the deduced cycle of quantification data, this study shows that reverse transcription quantitative polymerase chain reaction (RT-qPCR) performance is affected by impaired RNA integrity. Depending on the transcript and tissue type, a shift in cycle threshold values of up to two cycles was observed. Determining RNA integrity number of 136 post-mortem samples revealed significantly different RNA qualities among the three tissue types with brain revealing significantly lower integrities compared to skeletal and cardiac muscle. The body mass index was found to influence RNA integrity in skeletal muscle tissue (M. iliopsoas). Samples originating from deceased with a BMI > 25 were of significantly lower integrity compared to samples from normal weight donors. Correct data normalisation was found to partly diminish the effects caused by impaired RNA quality. Nevertheless, it can be concluded that in post-mortem tissue with low RNA integrity numbers, the detection of large differences in gene expression activities might still be possible, whereas small expression differences are prone to misinterpretation due to degradation. Thus, when working with post-mortem samples, we recommend generating degradation profiles for all transcripts of interest in order to reveal detection limits of RT-qPCR assays.

Radioactivity is known to induce tumors, chromosome lesions, and minisatellite length mutations, but its effects on the DNA sequence have not previously been studied. A coastal peninsula in Kerala (India) contains the world's highest level of natural radioactivity in a densely populated area, offering an opportunity to characterize radiation-associated DNA mutations. We sampled 248 pedigrees (988 individuals) in the high-radiation peninsula and in nearby low-radiation islands as a control population. We sequenced their mtDNA, and found that the pedigrees living in the high-radiation area have significantly (P < 0.01) increased germ-line point mutations between mothers and their offspring. In each mutation case, we confirmed maternity by autosomal profiling. Strikingly, the radioactive conditions accelerate mutations at nucleotide positions that have been evolutionary hot spots for at least 60,000 years.

Recently, several authors described the observation that RNA degradation does not correlate with the postmortem interval (PMI), but rather with other parameters like environmental impact and the circumstances of death. Therefore, the question arose if the analysis of gene expression could be a valuable tool in forensic genetics to contribute to the determination of the cause of death. In our study, six human tissues obtained from six individuals with PMI varying between 15 and 118 h were used for total RNA extraction. Quantification was performed using a GAPDH real-time assay, and the quality of mRNA was checked by amplification of different fragment lengths of the GAPDH transcript. In our set of samples, nearly all tissues in all PMI revealed satisfactory results, while skeletal muscle, followed by brain and heart, gave the best results. No correlation between PMI and RNA degradation could be detected, as very good results were observed for all tissues from the individual with the longest PMI. The highly promising results obtained in this study raise hopes that in the near future several fields of forensic investigation may profit from additional information about gene expression patterns and their correlation with pathological findings.

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