Forensic evaluation of the Asia Pacific ancestry-informative MAPlex assay

DNA intelligence, and particularly the inference of biogeographical ancestry (BGA) is increasing in interest, and relevance within the forensic genetics community. The majority of current MPS-based forensic ancestry-informative assays focus on the differentiation of major global populations. The recently published MAPlex (Multiplex for the Asia Pacific) panel contains 144 SNPs and 20 microhaplotypes and aims to improve the differentiation of populations in the Asia Pacific region. This study reports the first forensic evaluation of the MAPlex panel using AmpliSeq technology and Ion S5 sequencing. This study reports on the overall performance of MAPlex including the assay’s sequence coverage distribution and stability, baseline noise and description of problematic SNPs. Dilution series, artificially degraded and mixed DNA samples were also analysed to evaluate the sensitivity of the panel with challenging or compromised forensic samples. As the first panel to combine biallelic SNPs, multiple-allele SNPs and microhaplotypes, the MAPlex assay demonstrated an enhanced capacity for mixture detection, not easily performed with common binary SNPs. This performance evaluation indicates that MAPlex is a robust, stable and highly sensitive assay that is applicable to forensic casework for the prediction of BGAMdlP is supported by a postdoctoral fellowship awarded by the Consellería de Cultura, Educación e Ordenación Universitaria and the Consellería de Economía, Emprego e Industria from Xunta de Galicia (Modalidade A, ED481B 2017/088). CP, AFA, AMM, MdlP, MVL are supported by MAPA, Multiple Allele Polymorphism Analysis (BIO2016-78525-R), a research project funded by the Spanish Research State Agency (AEI), and co-financed with ERDF funds. AFA is supported by a post-doctorate grant funded by the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria from Xunta de Galicia, Spain (Modalidade B, ED481B 2018/010). The 1000 Genomes high coverage sequence data were generated at the New York Genome Center with funds provided by NHGRI Grant 3UM1HG008901-03S1S

Evaluation of DNA variants associated with androgenetic alopecia and their potential to predict male pattern baldness

Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near AR, rs1998076 in the 20p11 region, rs929626 in EBF1, rs12565727 in TARDBP and rs756853 in HDAC9. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics

Evaluation of autosomal and mitochondrial markers for forensic identification

Ziel in der forensischen Genetik ist es, aus in DNA Proben enthaltener genetischer Information, Informationen über die der DNA zugehörigen Person zu erhalten, um diese gegebenenfalls vor Gericht verwenden zu können. Diese genetische Information wird vor allem zur Identifizierung verwendet, einerseits zur individuellen Identifizierung von Personen, sowie der nicht-exklusiven Identifizierung von Personen. Letzteres können Verwandtschaftsanalysen wie Vaterschaftstests oder Vorhersagen von sichtbar äußeren Merkmalen, wie Augen und Haarfarbe sein. Die Identifikation von Personen stellt hierbei jedoch die am häufigsten angewendete Methode in der forensischen Genetik dar. Da die Resultate aus den Verfahren die in der forensischen Genetik angewendet werden, vor Gericht standhalten müssen, werden diese aufwendigen und strengen Validierungsverfahren unterzogen. Aus diesem Grund ist die Implementierung neuer Methoden im Gebiet der forensischen Genetik zumeist ein langsamer und zeitintensiver Prozess. In den letzten Jahren sind jedoch neue genetische Marker untersucht, sowie neue DNA Typisierungstechnologien entwickelt worden, die insbesondere in der forensisch-genetischen Identifikation von Vorteil und Nutzen sein könnten. In dieser Arbeit wurden drei dieser neuen Ansätze evaluiert: ein Panel mit Einzelnukleotidpolymorphismen zur individuellen Identitätsfeststellung, typisiert mit einer der neuen NGS (Next Generation Sequencing) Technologien und dessen Analyse in gemischten DNA Proben; massenspektrometrische Analyse der mitochondrialen Kontrollregion; Analyse des mitochondrialen Gesamtgenoms aus Haarschäften mittels neuer NGS Technologie.Forensic Genetics is a scientific discipline that investigates how to use the genetic information contained in a DNA sample to gain more information about the sample donor, which can ultimately be used in court. Information gained from a DNA sample is mainly used for identification purposes which range from identity testing, including individual identification or exclusion testing, paternity determination and kinship analysis, to identifying sample source attributes, such as hair and eye color. In general, however, identity testing is the most widely used and routinely applied forensic genetic application. Since results should be able to be used in court, efforts spent on validation and standardization of markers and their typing methods are considerable. As a result, a change in markers and technologies often occurs at a slow rate and pace. In recent years, however, novel genetic markers and methods have emerged which are very suitable for identity testing. Three of which have been tested and evaluated in the publications described in this thesis: Single Nucleotide Polymorphisms (SNPs) for individual identification (II) using a Next Generation Sequencing (NGS) technology and their use in mixture analysis; mass spectrometric DNA profiling of the mitochondrial control region; whole mitochondrial genome sequencing from hair shafts using Next Generation Sequencing (NGS) technology.by Mag. biol. Mayra Alexandra Mayr-EduardoffKumulative Dissertation aus vier ArtikelnAbweichender Titel laut Übersetzung der Verfasserin/des VerfassersIm Titel ist TM hochgestelltMedical University of Innsbruck, Dissertation, 2016OeBB(VLID)134497

Optimized mtDNA Control Region Primer Extension Capture Analysis for Forensically Relevant Samples and Highly Compromised mtDNA of Different Age and Origin

The analysis of mitochondrial DNA (mtDNA) has proven useful in forensic genetics and ancient DNA (aDNA) studies, where specimens are often highly compromised and DNA quality and quantity are low. In forensic genetics, the mtDNA control region (CR) is commonly sequenced using established Sanger-type Sequencing (STS) protocols involving fragment sizes down to approximately 150 base pairs (bp). Recent developments include Massively Parallel Sequencing (MPS) of (multiplex) PCR-generated libraries using the same amplicon sizes. Molecular genetic studies on archaeological remains that harbor more degraded aDNA have pioneered alternative approaches to target mtDNA, such as capture hybridization and primer extension capture (PEC) methods followed by MPS. These assays target smaller mtDNA fragment sizes (down to 50 bp or less), and have proven to be substantially more successful in obtaining useful mtDNA sequences from these samples compared to electrophoretic methods. Here, we present the modification and optimization of a PEC method, earlier developed for sequencing the Neanderthal mitochondrial genome, with forensic applications in mind. Our approach was designed for a more sensitive enrichment of the mtDNA CR in a single tube assay and short laboratory turnaround times, thus complying with forensic practices. We characterized the method using sheared, high quantity mtDNA (six samples), and tested challenging forensic samples (n = 2) as well as compromised solid tissue samples (n = 15) up to 8 kyrs of age. The PEC MPS method produced reliable and plausible mtDNA haplotypes that were useful in the forensic context. It yielded plausible data in samples that did not provide results with STS and other MPS techniques. We addressed the issue of contamination by including four generations of negative controls, and discuss the results in the forensic context. We finally offer perspectives for future research to enable the validation and accreditation of the PEC MPS method for final implementation in forensic genetic laboratories

Mass spectrometric base composition profiling: Implications for forensic mtDNA databasing

In forensic genetics mitochondrial DNA (mtDNA) is usually analyzed by direct Sanger-type sequencing (STS). This method is known to be laborious and sometimes prone to human error. Alternative methods have been proposed that lead to faster results. Among these are methods that involve mass-spectrometry resulting in base composition profiles that are, by definition, less informative than the full nucleotide sequence. Here, we applied a highly automated electrospray ionization mass spectrometry (ESI-MS) system (PLEX-ID) to an mtDNA population study to compare its performance with respect to throughput and concordance to STS. We found that the loss of information power was relatively low compared to the gain in speed and analytical standardization. The detection of point and length heteroplasmy turned out to be roughly comparable between the technologies with some individual differences related to the processes. We confirm that ESI-MS provides a valuable platform for analyzing mtDNA variation that can also be applied in the forensic context. (C) 2013 The Authors. Published by Elsevier Ireland Ltd. All rights reserved

Evaluation of the predictive capacity of DNA variants associated with straight hair in Europeans

DNA-based prediction of hair morphology, defined as straight, curly or wavy hair, could contribute to an improved description of an unknown offender and allow more accurate forensic reconstructions of physical appearance in the field of forensic DNA phenotyping. Differences in scalp hair morphology are significant at the worldwide scale and within Europe. The only genome-wide association study made to date revealed the Trichohyalin gene (TCHH) to be significantly associated with hair morphology in Europeans and reported weaker associations for WNT10A and FRAS1 genes. We conducted a study that centered on six SNPs located in these three genes with a sample of 528 individuals from Poland. The predictive capacity of the candidate DNA variants was evaluated using logistic regression; classification and regression trees; and neural networks, by applying a 10-fold cross validation procedure. Additionally, an independent test set of 142 males from six European populations was used to verify performance of the developed prediction models. Our study confirmed association of rs11803731 (TCHH), rs7349332 (WNT10A) and rs1268789 (FRAS1) SNPs with hair morphology. The combined genotype risk score for straight hair had an odds ratio of 2.7 and these predictors explained similar to 8.2% of the total variance. The selected three SNPs were found to predict straight hair with a high sensitivity but low specificity when a 10-fold cross validation procedure was applied and the best results were obtained using the neural networks approach (AUC = 0.688, sensitivity = 91.2%, specificity = 23.0%). Application of the neural networks model with 65% probability threshold on an additional test set gave high sensitivity (81.4%) and improved specificity (50.0%) with a total of 78.7% correct calls, but a high non-classification rate (66.9%). The combined TTGGGG SNP genotype for rs11803731, rs7349332, rs1268789 (European frequency = 4.5%) of all six straight hair-associated alleles was identified as the best predictor, giving >80% probability of straight hair. Finally, association testing of 44 SNPs previously identified to be associated with male pattern baldness revealed a suggestive association with hair morphology for rs4679955 on 3q25.1. The study results reported provide the starting point for the development of a predictive test for hair morphology in Europeans. More studies are now needed to discover additional determinants of hair morphology to improve the predictive accuracy of this trait in forensic analysis. (C) 2015 Elsevier Ireland Ltd. All rights reserved

Evaluation of DNA Variants Associated with Androgenetic Alopecia and Their Potential to Predict Male Pattern Baldness

<div><p>Androgenetic alopecia, known in men as male pattern baldness (MPB), is a very conspicuous condition that is particularly frequent among European men and thus contributes markedly to variation in physical appearance traits amongst Europeans. Recent studies have revealed multiple genes and polymorphisms to be associated with susceptibility to MPB. In this study, 50 candidate SNPs for androgenetic alopecia were analyzed in order to verify their potential to predict MPB. Significant associations were confirmed for 29 SNPs from chromosomes X, 1, 5, 7, 18 and 20. A simple 5-SNP prediction model and an extended 20-SNP model were developed based on a discovery panel of 305 males from various European populations fitting one of two distinct phenotype categories. The first category consisted of men below 50 years of age with significant baldness and the second; men aged 50 years or older lacking baldness. The simple model comprised the five best predictors: rs5919324 near <i>AR</i>, rs1998076 in the 20p11 region, rs929626 in <i>EBF1</i>, rs12565727 in <i>TARDBP</i> and rs756853 in <i>HDAC9</i>. The extended prediction model added 15 SNPs from five genomic regions that improved overall prevalence-adjusted predictive accuracy measured by area under the receiver characteristic operating curve (AUC). Both models were evaluated for predictive accuracy using a test set of 300 males reflecting the general European population. Applying a 65% probability threshold, high prediction sensitivity of 87.1% but low specificity of 42.4% was obtained in men aged <50 years. In men aged ≥50, prediction sensitivity was slightly lower at 67.7% while specificity reached 90%. Overall, the AUC=0.761 calculated for men at or above 50 years of age indicates these SNPs offer considerable potential for the application of genetic tests to predict MPB patterns, adding a highly informative predictive system to the emerging field of forensic analysis of externally visible characteristics.</p></div

Genotype risk score associated with the risk of male pattern baldness.

<p>Genotype risk score associated with the risk of male pattern baldness.</p

Parameters describing the accuracy of prediction of MPB using 20-SNP logistic regression prediction model.

<p>^*Four samples from phenotype categories 3 and 4 lacked data in one of the following SNPs: rs1160312, rs6625150, rs4679955 and therefore were excluded from the analyses.</p><p>Parameters describing the accuracy of prediction of MPB using 20-SNP logistic regression prediction model.</p