RESUMO
DNA methylation has become one of the most useful biomarkers for age prediction and body fluid identification in the forensic field. Therefore, several assays have been developed to detect age-associated and body fluid-specific DNA methylation changes. Among the many methods developed, SNaPshot-based assays should be particularly useful in forensic laboratories, as they permit multiplex analysis and use the same capillary electrophoresis instrumentation as STR analysis. However, technical validation of any developed assays is crucial for their proper integration into routine forensic workflow. In the present collaborative exercise, two SNaPshot multiplex assays for age prediction and a SNaPshot multiplex for body fluid identification were tested in twelve laboratories. The experimental set-up of the exercise was designed to reflect the entire workflow of SNaPshot-based methylation analysis and involved four increasingly complex tasks designed to detect potential factors influencing methylation measurements. The results of body fluid identification from each laboratory provided sufficient information to determine appropriate age prediction methods in subsequent analysis. In age prediction, systematic measurement differences resulting from the type of genetic analyzer used were identified as the biggest cause of DNA methylation variation between laboratories. Also, the use of a buffer that ensures a high ratio of specific to non-specific primer binding resulted in changes in DNA methylation measurement, especially when using degenerate primers in the PCR reaction. In addition, high input volumes of bisulfite-converted DNA often caused PCR failure, presumably due to carry-over of PCR inhibitors from the bisulfite conversion reaction. The proficiency of the analysts and experimental conditions for efficient SNaPshot reactions were also important for consistent DNA methylation measurement. Several bisulfite conversion kits were used for this study, but differences resulting from the use of any specific kit were not clearly discerned. Even when different experimental settings were used in each laboratory, a positive outcome of the study was a mean absolute age prediction error amongst participant's data of only 2.7 years for semen, 5.0 years for blood and 3.8 years for saliva.
Assuntos
Líquidos Corporais , Metilação de DNA , Pré-Escolar , Ilhas de CpG/genética , Genética Forense/métodos , Humanos , SalivaRESUMO
We detail the development of the ancestry informative single nucleotide polymorphisms (SNPs) panel forming part of the VISAGE Basic Tool (BT), which combines 41 appearance predictive SNPs and 112 ancestry predictive SNPs (three SNPs shared between sets) in one massively parallel sequencing (MPS) multiplex, whereas blood-based age analysis using methylation markers is run in a parallel MPS analysis pipeline. The selection of SNPs for the BT ancestry panel focused on established forensic markers that already have a proven track record of good sequencing performance in MPS, and the overall SNP multiplex scale closely matched that of existing forensic MPS assays. SNPs were chosen to differentiate individuals from the five main continental population groups of Africa, Europe, East Asia, America, and Oceania, extended to include differentiation of individuals from South Asia. From analysis of 1000 Genomes and HGDP-CEPH samples from these six population groups, the BT ancestry panel was shown to have no classification error using the Bayes likelihood calculators of the Snipper online analysis portal. The differentiation power of the component ancestry SNPs of BT was balanced as far as possible to avoid bias in the estimation of co-ancestry proportions in individuals with admixed backgrounds. The balancing process led to very similar cumulative population-specific divergence values for Africa, Europe, America, and Oceania, with East Asia being slightly below average, and South Asia an outlier from the other groups. Comparisons were made of the African, European, and Native American estimated co-ancestry proportions in the six admixed 1000 Genomes populations, using the BT ancestry panel SNPs and 572,000 Affymetrix Human Origins array SNPs. Very similar co-ancestry proportions were observed down to a minimum value of 10%, below which, low-level co-ancestry was not always reliably detected by BT SNPs. The Snipper analysis portal provides a comprehensive population dataset for the BT ancestry panel SNPs, comprising a 520-sample standardised reference dataset; 3445 additional samples from 1000 Genomes, HGDP-CEPH, Simons Foundation and Estonian Biocentre genome diversity projects; and 167 samples of six populations from in-house genotyping of individuals from Middle East, North and East African regions complementing those of the sampling regimes of the other diversity projects.
Assuntos
Etnicidade/genética , Genética Forense , Genética Populacional , Grupos Raciais/genética , África , América , Europa (Continente) , Feminino , Frequência do Gene , Genótipo , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Masculino , Oceania , Polimorfismo de Nucleotídeo Único/genéticaRESUMO
The development of microhaplotype (MH) panels for massively parallel sequencing (MPS) platforms is gaining increasing relevance for forensic analysis. Here, we expand the applicability of a 102 autosomal and 11 X-chromosome panel of MHs, previously validated with both MiSeq and Ion S5 MPS platforms and designed for identification purposes. We have broadened reference population data for identification purposes, including data from 240 HGDP-CEPH individuals of native populations from North Africa, the Middle East, Oceania and America. Using the enhanced population data, the panel was evaluated as a marker set for bio-geographical ancestry (BGA) inference, providing a clear differentiation of the five main continental groups of Africa, Europe, East Asia, Native America, and Oceania. An informative degree of differentiation was also achieved for the population variation encompassing North Africa, Middle East, Europe, South Asia, and East Asia. In addition, we explored the potential for individual BGA inference from simple mixed DNA, by simulation of mixed profiles followed by deconvolution of mixture components.