The use of DNA methylation (DNAm) to obtain additional information in forensic investigations showed to be a promising and increasing field of interest. Prediction of the chronological age based on age-dependent changes in the DNAm of specific CpG sites within the genome is one such potential application. Here we present an age-prediction tool for whole blood based on massive parallel sequencing (MPS) and a random forest machine learning algorithm. MPS allows accurate DNAm determination of pre-selected markers and neighboring CpG-sites to identify the best age-predictive markers for the age-prediction tool. 15 age-dependent markers of different loci were initially chosen based on publicly available 450K microarray data, and 13 finally selected for the age tool based on MPS (DDO, ELOVL2, F5, GRM2, HOXC4, KLF14, LDB2, MEIS1-AS3, NKIRAS2, RPA2, SAMD10, TRIM59, ZYG11A). Whole blood samples of 208 individuals were used for training of the algorithm and a further 104 individuals were used for model evaluation (age 18-69). In the case of KLF14, LDB2, SAMD10, and GRM2, neighboring CpG sites and not the initial 450K sites were chosen for the final model. Cross-validation of the training set leads to a mean absolute deviation (MAD) of 3.21 years and a root-mean square error (RMSE) of 3.97 years. Evaluation of model performance using the test set showed a comparable result (MAD 3.16 years, RMSE 3.93 years). A reduced model based on only the top 4 markers (ELOVL2, F5, KLF14, and TRIM59) resulted in a RMSE of 4.19 years and MAD of 3.24 years for the test set (cross validation training set: RMSE 4.63 years, MAD 3.64 years). The amplified region was additionally investigated for occurrence of SNPs in case of an aberrant DNAm result, which in some cases can be an indication for a deviation in DNAm. Our approach uncovered well-known DNAm age-dependent markers, as well as additional new age-dependent sites for improvement of the model, and allowed the creation of a reliable and accurate epigenetic tool for age-prediction without restriction to a linear change in DNAm with age.

In forensic science, the unequivocal identification of the cellular origin of crime scene samples used for DNA profiling can provide crucial information for crime scene reconstruction. We have previously shown that various mRNA markers from genes with expression patterns specific for blood and saliva can be established from whole-genome expression analysis of time-wise degraded samples and were stable enough to specifically identify blood and saliva stains up to 180 days of age. Here, we showed that nine blood-specific and five saliva-specific mRNA markers can be amplified successfully and reliably in much older blood (13-16 years) and saliva (2-6 years) stains, respectively, suggesting their suitability for tissue identification in forensic case work. Moreover, our findings imply that forensic RNA testing can be reliable and robust if degraded samples are considered in the marker ascertainment procedure, with promising expectations beyond tissue identification purposes.

Different regional populations from Poland were studied in order to assess the genetic heterogeneity within Poland, investigate the genetic relationships with other European populations and provide a population-specific reference database for anthropological and forensic studies. Nine Y-chromosomal microsatellites were analysed in a total of 919 unrelated males from six regions of Poland and in 1,273 male individuals from nine other European populations. AMOVA revealed that all of the molecular variation in the Polish dataset is due to variation within populations, and no variation was detected among populations of different regions of Poland. However, in the non-Polish European dataset 9.3% ( P<0.0001) of the total variation was due to differences among populations. Consequently, differences in R(ST)-values between all possible pairs of Polish populations were not statistically significant, whereas significant differences were observed in nearly all comparisons of Polish and non-Polish European populations. Phylogenetic analyses demonstrated tight clustering of Polish populations separated from non-Polish groups. Population clustering based on Y-STR haplotypes generally correlates well with the geography and history of the region. Thus, our data are consistent with the assumption of homogeneity of present-day paternal lineages within Poland and their distinctiveness from other parts of Europe, at least in respect to their Y-STR haplotypes. Electronic supplementary material to this paper can be obtained by using the Springer LINK server located at http://dx.doi.org/10.1007/s00439-002-0728-0.

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