Publications by authors named "Manfred Kayser"

238 Publications

Investigative DNA analysis of two-person mixed crime scene trace in a murder case.

Forensic Sci Int Genet 2021 Jun 20;54:102557. Epub 2021 Jun 20.

Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands. Electronic address:

It has been advocated before that appearance prediction of unknown suspects from crime scene DNA, in the context of Forensic DNA Phenotyping (FDP), is mostly suitable for single source DNA samples, whereas FDP from DNA mixtures to which more than one person contributed, is viewed challenging. With this report on a murder case, we practically demonstrate the feasibility of appearance DNA prediction of an unknown suspect from a mixed crime scene trace, to which the unknown suspect and the known victim had contributed. From this two-person DNA mixture, we successfully predicted eye, hair and skin color of the unknown suspect with the HIrisPlex-S system by applying targeted massively parallel sequencing (MPS). We argue that at least three factors benefit appearance DNA prediction of unknown suspects from mixed crime scene traces, which were met in this murder case: i) SNP genotype knowledge from reference DNA analysis for one of the two persons in the mixture (here the known victim), ii) about equal DNA contributions by both donors to the mixed crime scene stain, and iii) the use of MPS allowing quantitative SNP analysis. Moreover, we show that additionally analyzing animal DNA in this mixed crime scene trace provides further investigative information. We envision that the investigative DNA strategy that we applied here for analyzing a two-person mixed crime scene trace in a murder case, will be applied in the future to more criminal cases with two-person DNA mixtures, for instance sexual assault cases.
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http://dx.doi.org/10.1016/j.fsigen.2021.102557DOI Listing
June 2021

Estimating the Time Since Deposition of Saliva Stains With a Targeted Bacterial DNA Approach: A Proof-of-Principle Study.

Front Microbiol 2021 2;12:647933. Epub 2021 Jun 2.

Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.

Information on the time when a stain was deposited at a crime scene can be valuable in forensic investigations. It can link a DNA-identified stain donor with a crime or provide a post-mortem interval estimation in cases with cadavers. The available methods for estimating stain deposition time have limitations of different types and magnitudes. In this proof-of-principle study we investigated for the first time the use of microbial DNA for this purpose in human saliva stains. First, we identified the most abundant and frequent bacterial species in saliva using publicly available 16S rRNA gene next generation sequencing (NGS) data from 1,848 samples. Next, we assessed time-dependent changes in 15 identified species using de-novo 16S rRNA gene NGS in the saliva stains of two individuals exposed to indoor conditions for up to 1 year. We selected four bacterial species, i.e., , and showing significant time-dependent changes and developed a 4-plex qPCR assay for their targeted analysis. Then, we analyzed the saliva stains of 15 individuals exposed to indoor conditions for up to 1 month. Bacterial counts generally increased with time and explained 54.9% of the variation ( = <2.2E-16). Time since deposition explained ≥86.5% and ≥88.9% of the variation in each individual and species, respectively ( = <2.2E-16). Finally, based on sample duplicates we built and tested multiple linear regression models for predicting the stain deposition time at an individual level, resulting in an average mean absolute error (MAE) of 5 days (ranging 3.3-7.8 days). Overall, the deposition time of 181 (81.5%) stains was correctly predicted within 1 week. Prediction models were also assessed in stains exposed to similar conditions up to 1 month 7 months later, resulting in an average MAE of 8.8 days (ranging 3.9-16.9 days). Our proof-of-principle study suggests the potential of the DNA profiling of human commensal bacteria as a method of estimating saliva stains time since deposition in the forensic scenario, which may be expanded to other forensically relevant tissues. The study considers practical applications of this novel approach, but various forensic developmental validation and implementation criteria will need to be met in more dedicated studies in the future.
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http://dx.doi.org/10.3389/fmicb.2021.647933DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8206545PMC
June 2021

Epigenome-wide association meta-analysis of DNA methylation with coffee and tea consumption.

Nat Commun 2021 05 14;12(1):2830. Epub 2021 May 14.

Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, the Netherlands.

Coffee and tea are extensively consumed beverages worldwide which have received considerable attention regarding health. Intake of these beverages is consistently linked to, among others, reduced risk of diabetes and liver diseases; however, the mechanisms of action remain elusive. Epigenetics is suggested as a mechanism mediating the effects of dietary and lifestyle factors on disease onset. Here we report the results from epigenome-wide association studies (EWAS) on coffee and tea consumption in 15,789 participants of European and African-American ancestries from 15 cohorts. EWAS meta-analysis of coffee consumption reveals 11 CpGs surpassing the epigenome-wide significance threshold (P-value <1.1×10), which annotated to the AHRR, F2RL3, FLJ43663, HDAC4, GFI1 and PHGDH genes. Among them, cg14476101 is significantly associated with expression of the PHGDH and risk of fatty liver disease. Knockdown of PHGDH expression in liver cells shows a correlation with expression levels of genes associated with circulating lipids, suggesting a role of PHGDH in hepatic-lipid metabolism. EWAS meta-analysis on tea consumption reveals no significant association, only two CpGs annotated to CACNA1A and PRDM16 genes show suggestive association (P-value <5.0×10). These findings indicate that coffee-associated changes in DNA methylation levels may explain the mechanism of action of coffee consumption in conferring risk of diseases.
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http://dx.doi.org/10.1038/s41467-021-22752-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121846PMC
May 2021

Evaluation of supervised machine-learning methods for predicting appearance traits from DNA.

Forensic Sci Int Genet 2021 07 23;53:102507. Epub 2021 Mar 23.

Cologne Center for Genomics, University of Cologne, Cologne, Germany; Faculty of Medicine and the Cologne University Hospital, Cologne, Germany. Electronic address:

The prediction of human externally visible characteristics (EVCs) based solely on DNA information has become an established approach in forensic and anthropological genetics in recent years. While for a large set of EVCs, predictive models have already been established using multinomial logistic regression (MLR), the prediction performances of other possible classification methods have not been thoroughly investigated thus far. Motivated by the question to identify a potential classifier that outperforms these specific trait models, we conducted a systematic comparison between the widely used MLR and three popular machine learning (ML) classifiers, namely support vector machines (SVM), random forest (RF) and artificial neural networks (ANN), that have shown good performance outside EVC prediction. As examples, we used eye, hair and skin color categories as phenotypes and genotypes based on the previously established IrisPlex, HIrisPlex, and HIrisPlex-S DNA markers. We compared and assessed the performances of each of the four methods, complemented by detailed hyperparameter tuning that was applied to some of the methods in order to maximize their performance. Overall, we observed that all four classification methods showed rather similar performance, with no method being substantially superior to the others for any of the traits, although performances varied slightly across the different traits and more so across the trait categories. Hence, based on our findings, none of the ML methods applied here provide any advantage on appearance prediction, at least when it comes to the categorical pigmentation traits and the selected DNA markers used here.
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http://dx.doi.org/10.1016/j.fsigen.2021.102507DOI Listing
July 2021

Male-specific age estimation based on Y-chromosomal DNA methylation.

Aging (Albany NY) 2021 03 11;13(5):6442-6458. Epub 2021 Mar 11.

Department of Genetic Identification, Erasmus University Medical Center Rotterdam, Rotterdam 3000, CA, The Netherlands.

Although DNA methylation variation of autosomal CpGs provides robust age predictive biomarkers, no male-specific age predictor exists based on Y-CpGs yet. Since sex chromosomes play an important role in aging, a Y-chromosome-based age predictor would allow studying male-specific aging effects and would also be useful in forensics. Here, we used blood-based DNA methylation microarray data of 1,057 males from six cohorts aged 15-87 and identified 75 Y-CpGs with an interquartile range of ≥0.1. Of these, 22 and six were significantly hyper- and hypomethylated with age (p(cor)<0.05, Bonferroni), respectively. Amongst several machine learning algorithms, a model based on support vector machines with radial kernel performed best in male-specific age prediction. We achieved a mean absolute deviation (MAD) between true and predicted age of 7.54 years (cor=0.81, validation) when using all 75 Y-CpGs, and a MAD of 8.46 years (cor=0.73, validation) based on the most predictive 19 Y-CpGs. The accuracies of both age predictors did not worsen with increased age, in contrast to autosomal CpG-based age predictors that are known to predict age with reduced accuracy in the elderly. Overall, we introduce the first-of-its-kind male-specific epigenetic age predictor for future applications in aging research and forensics.
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http://dx.doi.org/10.18632/aging.202775DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7993701PMC
March 2021

Development of the VISAGE enhanced tool and statistical models for epigenetic age estimation in blood, buccal cells and bones.

Aging (Albany NY) 2021 03 11;13(5):6459-6484. Epub 2021 Mar 11.

Central Forensic Laboratory of the Police, Warsaw, Poland.

DNA methylation is known as a biomarker for age with applications in forensics. Here we describe the VISAGE (VISible Attributes through GEnomics) Consortium's enhanced tool for epigenetic age estimation in somatic tissues. The tool is based on eight DNA methylation markers (44 CpGs), bisulfite multiplex PCR followed by sequencing on the MiSeq FGx platform, and three statistical prediction models for blood, buccal cells and bones. The model for blood is based on six CpGs from , , , , and , and predicts age with a mean absolute error (MAE) of 3.2 years, while the model for buccal cells includes five CpGs from , , , and and predicts age with MAE of 3.7 years, and the model for bones has six CpGs from and and predicts age with MAE of 3.4 years. The VISAGE enhanced tool for age estimation in somatic tissues enables reliable collection of DNA methylation data from small amounts of DNA using a sensitive multiplex MPS assay that provides accurate estimation of age in blood, buccal swabs, and bones using the statistical model tailored to each tissue.
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http://dx.doi.org/10.18632/aging.202783DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7993733PMC
March 2021

Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color.

Sci Adv 2021 Mar 10;7(11). Epub 2021 Mar 10.

Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.

Human eye color is highly heritable, but its genetic architecture is not yet fully understood. We report the results of the largest genome-wide association study for eye color to date, involving up to 192,986 European participants from 10 populations. We identify 124 independent associations arising from 61 discrete genomic regions, including 50 previously unidentified. We find evidence for genes involved in melanin pigmentation, but we also find associations with genes involved in iris morphology and structure. Further analyses in 1636 Asian participants from two populations suggest that iris pigmentation variation in Asians is genetically similar to Europeans, albeit with smaller effect sizes. Our findings collectively explain 53.2% (95% confidence interval, 45.4 to 61.0%) of eye color variation using common single-nucleotide polymorphisms. Overall, our study outcomes demonstrate that the genetic complexity of human eye color considerably exceeds previous knowledge and expectations, highlighting eye color as a genetically highly complex human trait.
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http://dx.doi.org/10.1126/sciadv.abd1239DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7946369PMC
March 2021

A GWAS in Latin Americans identifies novel face shape loci, implicating VPS13B and a Denisovan introgressed region in facial variation.

Sci Adv 2021 Feb 5;7(6). Epub 2021 Feb 5.

Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA 15260, USA.

To characterize the genetic basis of facial features in Latin Americans, we performed a genome-wide association study (GWAS) of more than 6000 individuals using 59 landmark-based measurements from two-dimensional profile photographs and ~9,000,000 genotyped or imputed single-nucleotide polymorphisms. We detected significant association of 32 traits with at least 1 (and up to 6) of 32 different genomic regions, more than doubling the number of robustly associated face morphology loci reported until now (from 11 to 23). These GWAS hits are strongly enriched in regulatory sequences active specifically during craniofacial development. The associated region in 1p12 includes a tract of archaic adaptive introgression, with a Denisovan haplotype common in Native Americans affecting particularly lip thickness. Among the nine previously unidentified face morphology loci we identified is the VPS13B gene region, and we show that variants in this region also affect midfacial morphology in mice.
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http://dx.doi.org/10.1126/sciadv.abc6160DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864580PMC
February 2021

Equivalent DNA methylation variation between monozygotic co-twins and unrelated individuals reveals universal epigenetic inter-individual dissimilarity.

Genome Biol 2021 01 5;22(1):18. Epub 2021 Jan 5.

Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.

Background: Although the genomes of monozygotic twins are practically identical, their methylomes may evolve divergently throughout their lifetime as a consequence of factors such as the environment or aging. Particularly for young and healthy monozygotic twins, DNA methylation divergence, if any, may be restricted to stochastic processes occurring post-twinning during embryonic development and early life. However, to what extent such stochastic mechanisms can systematically provide a stable source of inter-individual epigenetic variation remains uncertain until now.

Results: We enriched for inter-individual stochastic variation by using an equivalence testing-based statistical approach on whole blood methylation microarray data from healthy adolescent monozygotic twins. As a result, we identified 333 CpGs displaying similarly large methylation variation between monozygotic co-twins and unrelated individuals. Although their methylation variation surpasses measurement error and is stable in a short timescale, susceptibility to aging is apparent in the long term. Additionally, 46% of these CpGs were replicated in adipose tissue. The identified sites are significantly enriched at the clustered protocadherin loci, known for stochastic methylation in developing neurons. We also confirmed an enrichment in monozygotic twin DNA methylation discordance at these loci in whole genome bisulfite sequencing data from blood and adipose tissue.

Conclusions: We have isolated a component of stochastic methylation variation, distinct from genetic influence, measurement error, and epigenetic drift. Biomarkers enriched in this component may serve in the future as the basis for universal epigenetic fingerprinting, relevant for instance in the discrimination of monozygotic twin individuals in forensic applications, currently impossible with standard DNA profiling.
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http://dx.doi.org/10.1186/s13059-020-02223-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7786996PMC
January 2021

Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modeling of human appearance traits.

Forensic Sci Int Genet 2021 01 4;50:102412. Epub 2020 Nov 4.

Cologne Center for Genomics, University of Cologne, Cologne, Germany; University Hospital Cologne, Cologne, Germany. Electronic address:

The prediction of appearance traits by use of solely genetic information has become an established approach and a number of statistical prediction models have already been developed for this purpose. However, given limited knowledge on appearance genetics, currently available models are incomplete and do not include all causal genetic variants as predictors. Therefore such prediction models may benefit from the inclusion of additional information that acts as a proxy for this unknown genetic background. Use of priors, possibly informed by trait category prevalence values in biogeographic ancestry groups, in a Bayesian framework may thus improve the prediction accuracy of previously predicted externally visible characteristics, but has not been investigated as of yet. In this study, we assessed the impact of using trait prevalence-informed priors on the prediction performance in Bayesian models for eye, hair and skin color as well as hair structure and freckles in comparison to the respective prior-free models. Those prior-free models were either similarly defined either very close to the already established ones by using a reduced predictive marker set. However, these differences in the number of the predictive markers should not affect significantly our main outcomes. We observed that such priors often had a strong effect on the prediction performance, but to varying degrees between different traits and also different trait categories, with some categories barely showing an effect. While we found potential for improving the prediction accuracy of many of the appearance trait categories tested by using priors, our analyses also showed that misspecification of those prior values often severely diminished the accuracy compared to the respective prior-free approach. This emphasizes the importance of accurate specification of prevalence-informed priors in Bayesian prediction modeling of appearance traits. However, the existing literature knowledge on spatial prevalence is sparse for most appearance traits, including those investigated here. Due to the limitations in appearance trait prevalence knowledge, our results render the use of trait prevalence-informed priors in DNA-based appearance trait prediction currently infeasible.
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http://dx.doi.org/10.1016/j.fsigen.2020.102412DOI Listing
January 2021

Smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic traits.

Clin Epigenetics 2020 10 22;12(1):157. Epub 2020 Oct 22.

Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, 3015 GB, Rotterdam, The Netherlands.

Background: Tobacco smoking is a well-known modifiable risk factor for many chronic diseases, including cardiovascular disease (CVD). One of the proposed underlying mechanism linking smoking to disease is via epigenetic modifications, which could affect the expression of disease-associated genes. Here, we conducted a three-way association study to identify the relationship between smoking-related changes in DNA methylation and gene expression and their associations with cardio-metabolic traits.

Results: We selected 2549 CpG sites and 443 gene expression probes associated with current versus never smokers, from the largest epigenome-wide association study and transcriptome-wide association study to date. We examined three-way associations, including CpG versus gene expression, cardio-metabolic trait versus CpG, and cardio-metabolic trait versus gene expression, in the Rotterdam study. Subsequently, we replicated our findings in The Cooperative Health Research in the Region of Augsburg (KORA) study. After correction for multiple testing, we identified both cis- and trans-expression quantitative trait methylation (eQTM) associations in blood. Specifically, we found 1224 smoking-related CpGs associated with at least one of the 443 gene expression probes, and 200 smoking-related gene expression probes to be associated with at least one of the 2549 CpGs. Out of these, 109 CpGs and 27 genes were associated with at least one cardio-metabolic trait in the Rotterdam Study. We were able to replicate the associations with cardio-metabolic traits of 26 CpGs and 19 genes in the KORA study. Furthermore, we identified a three-way association of triglycerides with two CpGs and two genes (GZMA; CLDND1), and BMI with six CpGs and two genes (PID1; LRRN3). Finally, our results revealed the mediation effect of cg03636183 (F2RL3), cg06096336 (PSMD1), cg13708645 (KDM2B), and cg17287155 (AHRR) within the association between smoking and LRRN3 expression.

Conclusions: Our study indicates that smoking-related changes in DNA methylation and gene expression are associated with cardio-metabolic risk factors. These findings may provide additional insights into the molecular mechanisms linking smoking to the development of CVD.
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http://dx.doi.org/10.1186/s13148-020-00951-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7579899PMC
October 2020

The impact of correlations between pigmentation phenotypes and underlying genotypes on genetic prediction of pigmentation traits.

Forensic Sci Int Genet 2021 01 24;50:102395. Epub 2020 Sep 24.

Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands; Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China. Electronic address:

Predicting appearance phenotypes from genotypes is relevant for various areas of human genetic research and applications such as genetic epidemiology, human history, anthropology, and particularly in forensics. Many appearance phenotypes, and thus their underlying genotypes, are highly correlated, with pigmentation traits serving as primary examples. However, all available genetic prediction models, including those for pigmentation traits currently used in forensic DNA phenotyping, ignore phenotype correlations. Here, we investigated the impact of appearance phenotype correlations on genetic appearance prediction in the exemplary case of three pigmentation traits. We used data for categorical eye, hair and skin colour as well as 41 DNA markers utilized in the recently established HIrisPlex-S system from 762 individuals with complete phenotype and genotype information. Based on these data, we performed genetic prediction modelling of eye, hair and skin colour via three different strategies, namely the established approach of predicting phenotypes solely based on genotypes while not considering phenotype correlations, and two novel approaches that considered phenotype correlations, either incorporating truly observed correlated phenotypes or DNA-predicted correlated phenotypes in addition to the DNA predictors. We found that using truly observed correlated pigmentation phenotypes as additional predictors increased the DNA-based prediction accuracies for almost all eye, hair and skin colour categories, with the largest increase for intermediate eye colour, brown hair colour, dark to black skin colour, and particularly for dark skin colour. Outcomes of dedicated computer simulations suggest that this prediction accuracy increase is due to the additional genetic information that is implicitly provided by the truly observed correlated pigmentation phenotypes used, yet not covered by the DNA predictors applied. In contrast, considering DNA-predicted correlated pigmentation phenotypes as additional predictors did not improve the performance of the genetic prediction of eye, hair and skin colour, which was in line with the results from our computer simulations. Hence, in practical applications of DNA-based appearance prediction where no phenotype knowledge is available, such as in forensic DNA phenotyping, it is not advised to use DNA-predicted correlated phenotypes as predictors in addition to the DNA predictors. In the very least, this is not recommended for the pigmentation traits and the established pigmentation DNA predictors tested here.
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http://dx.doi.org/10.1016/j.fsigen.2020.102395DOI Listing
January 2021

Development and validation of the VISAGE AmpliSeq basic tool to predict appearance and ancestry from DNA.

Forensic Sci Int Genet 2020 09 20;48:102336. Epub 2020 Jun 20.

Institute of Legal Medicine, Medical University of Innsbruck, Innsbruck, Austria; Forensic Science Program, The Pennsylvania State University, University Park, PA, USA. Electronic address:

Forensic DNA phenotyping is gaining interest as the number of applications increases within the forensic genetics community. The possibility of providing investigative leads in addition to conventional DNA profiling for human identification provides new insights into otherwise "cold" police investigations. The ability of reporting on the bio-geographical ancestry (BGA), appearance characteristics and age based on DNA obtained from a crime scene sample of an unknown donor makes the exploration of such markers and the development of new methods meaningful for criminal investigations. The VISible Attributes through GEnomics (VISAGE) Consortium aims to disseminate and broaden the use of predictive markers and develop fully optimized and validated prototypes for forensic casework implementation. Here, the first VISAGE appearance and ancestry tool development, performance and validation is reported. A total of 153 SNPs (96.84 % assay conversion rate) were successfully incorporated into a single multiplex reaction using the AmpliSeq™ design pipeline, and applied for massively parallel sequencing with the Ion S5 platform. A collaborative effort involving six VISAGE laboratory partners was devised to perform all validation tests. An extensive validation plan was carefully organized to explore the assay's overall performance with optimum and low-input samples, as well as with challenging and casework mock samples. In addition, forensic validation studies such as concordance and mixture tests recurring to the Coriell sample set with known genotypes were performed. Finally, inhibitor tolerance and specificity were also evaluated. Results showed a robust, highly sensitive assay with good overall concordance between laboratories.
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http://dx.doi.org/10.1016/j.fsigen.2020.102336DOI Listing
September 2020

Evaluation of the VISAGE Basic Tool for Appearance and Ancestry Prediction Using PowerSeq Chemistry on the MiSeq FGx System.

Genes (Basel) 2020 06 26;11(6). Epub 2020 Jun 26.

Institute of Legal Medicine, Medical University of Innsbruck, 6020 Innsbruck, Tirol, Austria.

The study of DNA to predict externally visible characteristics (EVCs) and the biogeographical ancestry (BGA) from unknown samples is gaining relevance in forensic genetics. Technical developments in Massively Parallel Sequencing (MPS) enable the simultaneous analysis of hundreds of DNA markers, which improves successful Forensic DNA Phenotyping (FDP). The EU-funded VISAGE (VISible Attributes through GEnomics) Consortium has developed various targeted MPS-based lab tools to apply FDP in routine forensic analyses. Here, we present an evaluation of the VISAGE Basic tool for appearance and ancestry prediction based on PowerSeq chemistry (Promega) on a MiSeq FGx System (Illumina). The panel consists of 153 single nucleotide polymorphisms (SNPs) that provide information about EVCs (41 SNPs for eye, hair and skin color from HIrisPlex-S) and continental BGA (115 SNPs; three overlap with the EVCs SNP set). The assay was evaluated for sensitivity, repeatability and genotyping concordance, as well as its performance with casework-type samples. This targeted MPS assay provided complete genotypes at all 153 SNPs down to 125 pg of input DNA and 99.67% correct genotypes at 50 pg. It was robust in terms of repeatability and concordance and provided useful results with casework-type samples. The results suggest that this MPS assay is a useful tool for basic appearance and ancestry prediction in forensic genetics for users interested in applying PowerSeq chemistry and MiSeq for this purpose.
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http://dx.doi.org/10.3390/genes11060708DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349024PMC
June 2020

Identification and characterization of novel rapidly mutating Y-chromosomal short tandem repeat markers.

Hum Mutat 2020 09 11;41(9):1680-1696. Epub 2020 Jul 11.

Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands.

Short tandem repeat polymorphisms on the male-specific part of the human Y-chromosome (Y-STRs) are valuable tools in many areas of human genetics. Although their paternal inheritance and moderate mutation rate (~10 mutations per marker per meiosis) allow detecting paternal relationships, they typically fail to separate male relatives. Previously, we identified 13 Y-STR markers with untypically high mutation rates (>10 ), termed rapidly mutating (RM) Y-STRs, and showed that they improved male relative differentiation over standard Y-STRs. By applying a newly developed in silico search approach to the Y-chromosome reference sequence, we identified 27 novel RM Y-STR candidates. Genotyping them in 1,616 DNA-confirmed father-son pairs for mutation rate estimation empirically highlighted 12 novel RM Y-STRs. Their capacity to differentiate males related by 1, 2, and 3 meioses was 27%, 47%, and 61%, respectively, while for all 25 currently known RM Y-STRs, it was 44%, 69%, and 83%. Of the 647 Y-STR mutations observed in total, almost all were single repeat changes, repeat gains, and losses were well balanced; allele length and fathers' age were positively correlated with mutation rate. We expect these new RM Y-STRs, together with the previously known ones, to significantly improving male relative differentiation in future human genetic applications.
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http://dx.doi.org/10.1002/humu.24068DOI Listing
September 2020

In Reply.

Authors:
Manfred Kayser

Dtsch Arztebl Int 2020 04;117(15):269-270

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http://dx.doi.org/10.3238/arztebl.2020.0269bDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268094PMC
April 2020

Microbiome-based body site of origin classification of forensically relevant blood traces.

Forensic Sci Int Genet 2020 07 20;47:102280. Epub 2020 Mar 20.

Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands. Electronic address:

Human blood traces are amongst the most commonly encountered biological stains collected at crime scenes. Identifying the body site of origin of a forensic blood trace can provide crucial information in many cases, such as in sexual and violent assaults. However, means for reliably and accurately identifying from which body site a forensic blood trace originated are missing, but would be highly valuable in crime scene investigations. With this study, we introduce a taxonomy-independent deep neural network approach based on massively parallel microbiome sequencing, which delivers accurate body site of origin classification of forensically-relevant blood samples, such as menstrual, nasal, fingerprick, and venous blood. A total of 50 deep neural networks were trained using a large 16S rRNA gene sequencing dataset from 773 reference samples, including 220 female urogenital tract, 190 nasal cavity, 213 skin, and 150 venous blood samples. Validation was performed with de-novo generated 16S rRNA gene massively parallel sequencing (MPS) data from 94 blood test samples of four different body sites, and achieved high classification accuracy with AUC values at 0.992 for menstrual blood (N = 23), 0.978 for nasal blood (N = 16), 0.978 for fingerprick blood (N = 30), and 0.990 for venous blood (N = 25). The obtained highly accurate classification of menstrual blood was independent of the day of the menses, as established in additional 86 menstrual blood test samples. Accurate body site of origin classification was also revealed for 45 fresh and aged mock casework blood samples from all four body sites. Our novel microbiome approach works based on the assumption that a sample is from blood, as can be obtained in forensic practise from prior presumptive blood testing, and provides accurate information on the specific body source of blood, with high potentials for future forensic applications.
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http://dx.doi.org/10.1016/j.fsigen.2020.102280DOI Listing
July 2020

Explaining sudden infant death with cardiac arrhythmias: Complete exon sequencing of nine cardiac arrhythmia genes in Dutch SIDS cases highlights new and known DNA variants.

Forensic Sci Int Genet 2020 05 27;46:102266. Epub 2020 Feb 27.

Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands. Electronic address:

Previous studies suggested that Sudden Infant Death Syndrome (SIDS) can partially be genetically explained by cardiac arrhythmias; however, the number of individuals and populations investigated remain limited. We report the first SIDS study on cardiac arrhythmias genes from the Netherlands, a country with the lowest SIDS incidence likely due to parent education on awareness of environmental risk factors. By using targeted massively parallel sequencing (MPS) in 142 Dutch SIDS cases, we performed a complete exon screening of all 173 exons from 9 cardiac arrhythmias genes SCN5A, KCNQ1, KCNH2, KCNE1, KCNE2, CACNA1C, CAV3, ANK2 and KCNJ2 (∼34,000 base pairs), that were selected to harbour previously established SIDS-associated DNA variants. Motivated by the poor DNA quality from the paraffin embedded material used, the application of a conservative sequencing quality control protocol resulted in 102 SIDS cases surviving quality control. Amongst the 102 SIDS cases, we identified a total of 40 DNA variants in 8 cardiac arrhythmia genes found in 60 (58.8 %) cases. Statistical analyses using ancestry-adjusted reference population data and multiple test correction revealed that 13 (32.5 %) of the identified DNA variants in 6 cardiac arrhythmia genes were significantly associated with SIDS, which were observed in 15 (14.7 %) SIDS cases. These 13, and another three, DNA variants were classified as likely pathogenic for cardiac arrhythmias using the American College of Medical Genetics guidelines for interpretation of sequence variants. The 16 likely pathogenic DNA variants were found in 16 (15.7 %) SIDS cases, including i) 3 novel DNA variants not recorded in public databases ii) 7 known DNA variants for which significant SIDS association established here was previously unknown, and iii) 6 known DNA variants for which LQTS association was reported previously. By having replicated previously reported SIDS-associated DNA variants located in cardiac arrhythmia genes and by having highlighting novel SIDS-associated DNA variants in such genes, our findings provide additional empirical evidence for the partial genetic explanation of SIDS by cardiac arrhythmias. On a wider note, our study outcome stresses the need for routine post-mortem genetic screening of assumed SIDS cases, particularly for cardiac arrhythmia genes. When put in practise, it will allow preventing further sudden deaths (not only in infants) in the affected families, thereby allowing forensic molecular autopsy not only to provide answers on the cause of death, but moreover to save lives.
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http://dx.doi.org/10.1016/j.fsigen.2020.102266DOI Listing
May 2020

The Use of Forensic DNA Phenotyping in Predicting Appearance and Biogeographic Ancestry.

Dtsch Arztebl Int 2019 12;51-52(51-52):873-880

Institute of Legal Medicine, University Hospital of Cologne, University of Cologne, Germany; Department of Political Science, University of Vienna, Austria; Department of Global Health & Social Medicine, King's College London, United Kingdom; Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Netherlands.

Background: Persons whose identifying DNA profile (STR profile) is not yet known to the ingvestigating authorities cannot be identified by standard forensic DNA analysis (STR profiling) as it is now practiced. In view of the current public debate, particularly in Germany, on the legalization of so-called forensic DNA phenotyping, we present its scientific basis, societal aspects, and forensic applications and describe the analytic techniques that are now available.

Methods: This review is based on pertinent publications that were retrieved by a selective search in PubMed and in public media, and on the authors' own research.

Results: Forensically validated DNA test systems are available for the categorization of eye, hair, and skin color and the inference of continental biogeographic ancestry. As for statistical measures of test accuracy, the AUC (area under the curve) values lie in the range 0.74-0.99 for eye color, 0.64-0.94 for hair color, and 0.72-0.99 for skin color, depending on the predictive model and color category used.The corre- sponding positive predictive values (PPV) are lower. Empirical social-scientific research on forensic DNA phenotyping has shown that preserving privacy and protecting against discrimination are major ethical and regulatory considerations.

Conclusion: All three methods of forensic DNA phenotyping-the predition of exter- nally visible characteristics, biogeographic ancestry, and the estimation of age from crime scene DNA-require a proper regulatory framework and should be used in conjunction with each other. Before forensic DNA phenotyping can be implemented in forensic practice, steps must be taken to minimize the risks of violation of privacy scrimination and to ensure that these methods are used transpar- ently and proportionately.
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http://dx.doi.org/10.3238/arztebl.2019.0873DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6976916PMC
December 2019

Novel genetic loci affecting facial shape variation in humans.

Elife 2019 11 26;8. Epub 2019 Nov 26.

Laboratorios de Investigacion y Desarrollo, Facultad de Ciencias y Filosofıa, Universidad Peruana Cayetano Heredia, Lima, Peru.

The human face represents a combined set of highly heritable phenotypes, but knowledge on its genetic architecture remains limited, despite the relevance for various fields. A series of genome-wide association studies on 78 facial shape phenotypes quantified from 3-dimensional facial images of 10,115 Europeans identified 24 genetic loci reaching study-wide suggestive association (p < 5 × 10), among which 17 were previously unreported. A follow-up multi-ethnic study in additional 7917 individuals confirmed 10 loci including six unreported ones (p < 2.1 × 10). A global map of derived polygenic face scores assembled facial features in major continental groups consistent with anthropological knowledge. Analyses of epigenomic datasets from cranial neural crest cells revealed abundant -regulatory activities at the face-associated genetic loci. Luciferase reporter assays in neural crest progenitor cells highlighted enhancer activities of several face-associated DNA variants. These results substantially advance our understanding of the genetic basis underlying human facial variation and provide candidates for future in-vivo functional studies.
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http://dx.doi.org/10.7554/eLife.49898DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6905649PMC
November 2019

Correction to: The Dutch Y-chromosomal landscape.

Eur J Hum Genet 2020 Mar;28(3):399

Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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http://dx.doi.org/10.1038/s41431-019-0528-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7028942PMC
March 2020

HIrisPlex-S system for eye, hair, and skin color prediction from DNA: Massively parallel sequencing solutions for two common forensically used platforms.

Forensic Sci Int Genet 2019 11 26;43:102152. Epub 2019 Aug 26.

Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands. Electronic address:

Forensic DNA Phenotyping (FDP) provides the ability to predict externally visible characteristics from minute amounts of crime scene DNA, which can help find unknown perpetrators who are typically unidentifiable via conventional forensic DNA profiling. Fundamental human genetics research has led to a better understanding of the specific DNA variants responsible for physical appearance characteristics, particularly eye, hair, and skin color. Recently, we introduced the HIrisPlex-S system for the simultaneous prediction of eye, hair, and skin color based on 41 DNA variants generated from two forensically validated SNaPshot multiplex assays using capillary electrophoresis (CE). Here we introduce massively parallel sequencing (MPS) solutions for the HIrisPlex-S (HPS) system on two MPS platforms commonly used in forensics, Ion Torrent and MiSeq, that cover all 41 DNA variants in a single assay, respectively. Additionally, we present the forensic developmental validation of the two HPS-MPS assays. The Ion Torrent MPS assay, based on Ion AmpliSeq technology, illustrated the successful generation of full HIrisPlex-S genotypic profiles from 100 pg of input control DNA, while the MiSeq MPS assay based on an in-house design yielded complete profiles from 250 pg of input DNA. Assessing simulated forensic casework samples such as saliva, hair (bulb), blood, semen, and low quantity touch DNA, as well as artificially damaged DNA samples, concordance testing, and samples from numerous species, all illustrated the ability of both versions of the HIrisPlex-S MPS assay to produce results that motivate forensic applications. By also providing an integrated bioinformatics analysis pipeline, MPS data can now be analyzed and a file generated for upload to the publically accessible HIrisPlex online webtool (https://hirisplex.erasmusmc.nl). In addition, we updated the website to accept VCF input data for those with genome sequence data. We thus provide a user-friendly and semi-automated MPS workflow from DNA sample to individual eye, hair, and skin color prediction probabilities. Furthermore, we present a 2-person mixture separation tool that not only assesses genotype reliability with regards genotyping confidence but also provides the most fitting mixture scenario for both minor and major contributors, including profile separation. We envision this MPS implementation of the HIrisPlex-S system for eye, hair, and skin color prediction from DNA as a starting point for further expanding MPS-based forensic DNA phenotyping. This may include the future addition of SNPs predictive for more externally visible characteristics, as well as SNPs for bio-geographic ancestry inference, provided the statistical framework for DNA prediction of these traits is in place.
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http://dx.doi.org/10.1016/j.fsigen.2019.102152DOI Listing
November 2019

Validated inference of smoking habits from blood with a finite DNA methylation marker set.

Eur J Epidemiol 2019 Nov 7;34(11):1055-1074. Epub 2019 Sep 7.

Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.

Inferring a person's smoking habit and history from blood is relevant for complementing or replacing self-reports in epidemiological and public health research, and for forensic applications. However, a finite DNA methylation marker set and a validated statistical model based on a large dataset are not yet available. Employing 14 epigenome-wide association studies for marker discovery, and using data from six population-based cohorts (N = 3764) for model building, we identified 13 CpGs most suitable for inferring smoking versus non-smoking status from blood with a cumulative Area Under the Curve (AUC) of 0.901. Internal fivefold cross-validation yielded an average AUC of 0.897 ± 0.137, while external model validation in an independent population-based cohort (N = 1608) achieved an AUC of 0.911. These 13 CpGs also provided accurate inference of current (average AUC 0.925 ± 0.021, AUC0.914), former (0.766 ± 0.023, 0.699) and never smoking (0.830 ± 0.019, 0.781) status, allowed inferring pack-years in current smokers (10 pack-years 0.800 ± 0.068, 0.796; 15 pack-years 0.767 ± 0.102, 0.752) and inferring smoking cessation time in former smokers (5 years 0.774 ± 0.024, 0.760; 10 years 0.766 ± 0.033, 0.764; 15 years 0.767 ± 0.020, 0.754). Model application to children revealed highly accurate inference of the true non-smoking status (6 years of age: accuracy 0.994, N = 355; 10 years: 0.994, N = 309), suggesting prenatal and passive smoking exposure having no impact on model applications in adults. The finite set of DNA methylation markers allow accurate inference of smoking habit, with comparable accuracy as plasma cotinine use, and smoking history from blood, which we envision becoming useful in epidemiology and public health research, and in medical and forensic applications.
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http://dx.doi.org/10.1007/s10654-019-00555-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6861351PMC
November 2019

The Dutch Y-chromosomal landscape.

Eur J Hum Genet 2020 03 5;28(3):287-299. Epub 2019 Sep 5.

Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.

Previous studies indicated existing, albeit limited, genetic-geographic population substructure in the Dutch population based on genome-wide data and a lack of this for mitochondrial SNP based data. Despite the aforementioned studies, Y-chromosomal SNP data from the Netherlands remain scarce and do not cover the territory of the Netherlands well enough to allow a reliable investigation of genetic-geographic population substructure. Here we provide the first substantial dataset of detailed spatial Y-chromosomal haplogroup information in 2085 males collected across the Netherlands and supplemented with previously published data from northern Belgium. We found Y-chromosomal evidence for genetic-geographic population substructure, and several Y-haplogroups demonstrating significant clinal frequency distributions in different directions. By means of prediction surface maps we could visualize (complex) distribution patterns of individual Y-haplogroups in detail. These results highlight the value of a micro-geographic approach and are of great use for forensic and epidemiological investigations and our understanding of the Dutch population history. Moreover, the previously noted absence of genetic-geographic population substructure in the Netherlands based on mitochondrial DNA in contrast to our Y-chromosome results, hints at different population histories for women and men in the Netherlands.
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http://dx.doi.org/10.1038/s41431-019-0496-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029002PMC
March 2020

Update on the predictability of tall stature from DNA markers in Europeans.

Forensic Sci Int Genet 2019 09 1;42:8-13. Epub 2019 Jun 1.

Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands. Electronic address:

Predicting adult height from DNA has important implications in forensic DNA phenotyping. In 2014, we introduced a prediction model consisting of 180 height-associated SNPs based on data from 10,361 Northwestern Europeans enriched with tall individuals (770 > 1.88 standard deviation), which yielded a mid-ranged accuracy (AUC = 0.75 for binary prediction of tall stature and R = 0.12 for quantitative prediction of adult height). Here, we provide an update on DNA-based height predictability considering an enlarged list of subsequently-published height-associated SNPs using data from the same set of 10,361 Europeans. A prediction model based on the full set of 689 SNPs showed an improved accuracy relative to previous models for both tall stature (AUC = 0.79) and quantitative height (R = 0.21). A feature selection analysis revealed a subset of 412 most informative SNPs while the corresponding prediction model retained most of the accuracy (AUC = 0.76 and R = 0.19) achieved with the full model. Over all, our study empirically exemplifies that the accuracy for predicting human appearance phenotypes with very complex underlying genetic architectures, such as adult height, can be improved by increasing the number of phenotype-associated DNA variants. Our work also demonstrates that a careful sub-selection allows for a considerable reduction of the number of DNA predictors that achieve similar prediction accuracy as provided by the full set. This is forensically relevant due to restrictions in the number of SNPs simultaneously analyzable with forensically suitable DNA technologies in the current days of targeted massively parallel sequencing in forensic genetics.
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http://dx.doi.org/10.1016/j.fsigen.2019.05.006DOI Listing
September 2019

Author Correction: Ancient genomes indicate population replacement in Early Neolithic Britain.

Nat Ecol Evol 2019 Jun;3(6):986-987

Department of Earth Sciences, Natural History Museum, London, UK.

In the version of this Article originally published, there were errors in the colour ordering of the legend in Fig. 5b, and in the positions of the target and surrogate populations in Fig. 5c. This has now been corrected. The conclusions of the study are in no way affected. The errors have been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41559-019-0912-4DOI Listing
June 2019

Forensic Y-SNP analysis beyond SNaPshot: High-resolution Y-chromosomal haplogrouping from low quality and quantity DNA using Ion AmpliSeq and targeted massively parallel sequencing.

Forensic Sci Int Genet 2019 07 27;41:93-106. Epub 2019 Apr 27.

Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Wytemaweg 80, 3000 CA, Rotterdam, the Netherlands. Electronic address:

Y-chromosomal haplogroups assigned from male-specific Y-chromosomal single nucleotide polymorphisms (Y-SNPs) allow paternal lineage identification and paternal bio-geographic ancestry inference, both being relevant in forensic genetics. However, most previously developed forensic Y-SNP tools did not provide Y haplogroup resolution on the high level needed in forensic applications, because the limited multiplex capacity of the DNA technologies used only allowed the inclusion of a relatively small number of Y-SNPs. In a proof-of-principle study, we recently demonstrated that high-resolution Y haplogrouping is feasible via two AmpliSeq PCR analyses and simultaneous massively parallel sequencing (MPS) of 530 Y-SNPs allowing the inference of 432 Y-haplogroups. With the current study, we present a largely improved Y-SNP MPS lab tool that we specifically designed for the analysis of low quality and quantity DNA often confronted with in forensic DNA analysis. Improvements include i) Y-SNP marker selection based on the "minimal reference phylogeny for the human Y chromosome" (PhyloTree Y), ii) strong increase of the number of targeted Y-SNPs allowing many more Y haplogroups to be inferred, iii) focus on short amplicon length enabling successful analysis of degraded DNA, and iv) combination of all amplicons in a single AmpliSeq PCR and simultaneous sequencing allowing single DNA aliquot use. This new MPS tool simultaneously analyses 859 Y-SNPs and allows inferring 640 Y haplogroups. Preliminary forensic developmental validation testing revealed that this tool performs highly accurate, is sensitive and robust. We also provide a revised software tool for analysing the sequencing data produced by the new MPS lab tool including final Y haplogroup assignment. We envision the tools introduced here for high-resolution Y-chromosomal haplogrouping to determine a man's paternal lineage and/or paternal bio-geographic ancestry to become widely used in forensic Y-chromosome DNA analysis and other applications were Y haplogroup information from low quality / quantity DNA samples is required.
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http://dx.doi.org/10.1016/j.fsigen.2019.04.001DOI Listing
July 2019

Novel taxonomy-independent deep learning microbiome approach allows for accurate classification of different forensically relevant human epithelial materials.

Forensic Sci Int Genet 2019 07 4;41:72-82. Epub 2019 Apr 4.

Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, Rotterdam, the Netherlands. Electronic address:

Correct identification of different human epithelial materials such as from skin, saliva and vaginal origin is relevant in forensic casework as it provides crucial information for crime reconstruction. However, the overlap in human cell type composition between these three epithelial materials provides challenges for their differentiation and identification when using previously proposed human cell biomarkers, while their microbiota composition largely differs. By using validated 16S rRNA gene massively parallel sequencing data from the Human Microbiome Project of 1636 skin, oral and vaginal samples, 50 taxonomy-independent deep learning networks were trained to classify these three tissues. Validation testing was performed in de-novo generated high-throughput 16S rRNA gene sequencing data using the Ion Torrent Personal Genome Machine from 110 test samples: 56 hand skin, 31 saliva and 23 vaginal secretion specimens. Body-site classification accuracy of these test samples was very high as indicated by AUC values of 0.99 for skin, 0.99 for oral, and 1 for vaginal secretion. Misclassifications were limited to 3 (5%) skin samples. Additional forensic validation testing was performed in mock casework samples by de-novo high-throughput sequencing of 19 freshly-prepared samples and 22 samples aged for 1 up to 7.6 years. All of the 19 fresh and 20 (91%) of the 22 aged mock casework samples were correctly tissue-type classified. Moreover, comparing the microbiome results with outcomes from previous human mRNA-based tissue identification testing in the same 16 aged mock casework samples reveals that our microbiome approach performs better in 12 (75%), similarly in 2 (12.5%), and less good in 2 (12.5%) of the samples. Our results demonstrate that this new microbiome approach allows for accurate tissue-type classification of three human epithelial materials of skin, oral and vaginal origin, which is highly relevant for future forensic investigations.
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http://dx.doi.org/10.1016/j.fsigen.2019.03.015DOI Listing
July 2019

Ancient genomes indicate population replacement in Early Neolithic Britain.

Nat Ecol Evol 2019 05 15;3(5):765-771. Epub 2019 Apr 15.

Department of Earth Sciences, Natural History Museum, London, UK.

The roles of migration, admixture and acculturation in the European transition to farming have been debated for over 100 years. Genome-wide ancient DNA studies indicate predominantly Aegean ancestry for continental Neolithic farmers, but also variable admixture with local Mesolithic hunter-gatherers. Neolithic cultures first appear in Britain circa 4000 BC, a millennium after they appeared in adjacent areas of continental Europe. The pattern and process of this delayed British Neolithic transition remain unclear. We assembled genome-wide data from 6 Mesolithic and 67 Neolithic individuals found in Britain, dating 8500-2500 BC. Our analyses reveal persistent genetic affinities between Mesolithic British and Western European hunter-gatherers. We find overwhelming support for agriculture being introduced to Britain by incoming continental farmers, with small, geographically structured levels of hunter-gatherer ancestry. Unlike other European Neolithic populations, we detect no resurgence of hunter-gatherer ancestry at any time during the Neolithic in Britain. Genetic affinities with Iberian Neolithic individuals indicate that British Neolithic people were mostly descended from Aegean farmers who followed the Mediterranean route of dispersal. We also infer considerable variation in pigmentation levels in Europe by circa 6000 BC.
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http://dx.doi.org/10.1038/s41559-019-0871-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6520225PMC
May 2019
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