Targeted DNA methylation analysis and prediction of smoking habits in blood based on massively parallel sequencing.

Tobacco smoking is a frequent habit sustained by > 1.3 billion people in 2020 and the leading preventable factor for health risk and premature mortality worldwide. In the forensic context, predicting smoking habits from biological samples may allow broadening DNA phenotyping. In this study, we aimed to implement previously published smoking habit classification models based on blood DNA methylation at 13 CpGs. First, we developed a matching lab tool based on bisulfite conversion and multiplex PCR followed by amplification-free library preparation and targeted paired-end massively parallel sequencing (MPS). Analysis of six technical duplicates revealed high reproducibility of methylation measurements (Pearson correlation of 0.983). Artificially methylated standards uncovered marker-specific amplification bias, which we corrected via bi-exponential models. We then applied our MPS tool to 232 blood samples from Europeans of a wide age range, of which 90 were current, 71 former and 71 never smokers. On average, we obtained 189,000 reads/sample and 15,000 reads/CpG, without marker drop-out. Methylation distributions per smoking category roughly corresponded to previous microarray analysis, showcasing large inter-individual variation but with technology-driven bias. Methylation at 11 out of 13 smoking-CpGs correlated with daily cigarettes in current smokers, while solely one was weakly correlated with time since cessation in former smokers. Interestingly, eight smoking-CpGs correlated with age, and one displayed weak but significant sex-associated methylation differences. Using bias-uncorrected MPS data, smoking habits were relatively accurately predicted using both two- (current/non-current) and three- (never/former/current) category model, but bias correction resulted in worse prediction performance for both models. Finally, to account for technology-driven variation, we built new, joint models with inter-technology corrections, which resulted in improved prediction results for both models, with or without PCR bias correction (e.g. MPS cross-validation F1-score > 0.8; 2-categories). Overall, our novel assay takes us one step closer towards the forensic application of viable smoking habit prediction from blood traces. However, future research is needed towards forensically validating the assay, especially in terms of sensitivity. We also need to further shed light on the employed biomarkers, particularly on the mechanistics, tissue specificity and putative confounders of smoking epigenetic signatures.

Advancing FDSTools by integrating STRNaming 1.1.

The introduction of massively parallel sequencing in forensic analysis has been facilitated with typing kits, analysis software and allele naming tools such as the ForenSeq DNA Signature Prep (DSP) kit, FDSTools and STRNaming respectively. Here we describe how FDSTools 2.0 with integrated and refined STRNaming nomenclature was validated for implementation under ISO 17025 accreditation for the ForenSeq DSP kit. Newly-added options result in efficient automatic allele calling for the majority of markers while specific settings are applied for 'novel' sequence variants to avoid the calling of remaining variable noise observed in samples sequenced with the ForenSeq DSP kit that seem to arise in the PCR. Genome-wide built-in reference data allows for greatly simplified configuration of allele naming for human targets.

Evaluation of the VISAGE basic tool for appearance and ancestry inference using ForenSeq® chemistry on the MiSeq FGx® system.

The possibility of providing investigative leads when conventional DNA identification methods fail to solve a case can be of extreme relevance to law enforcement. Therefore, the forensic genetics community has focused research towards the broadened use of DNA, particularly for prediction of appearance traits, bio-geographical ancestry and age. The VISible Attributes through GEnomics (VISAGE) Consortium expanded the use of DNA phenotyping by developing new molecular and statistical tools for appearance, age and ancestry prediction. The VISAGE basic tool for appearance (EVC) and ancestry (BGA) prediction was initially developed using Ampliseq chemistry, but here is being evaluated using ForenSeq chemistry. The VISAGE basic tool offers a total of 41 EVC and 115 BGA SNPs and thus provides more predictions, i.e., skin color, than achieved with the ForenSeq DNA Signature Prep kit that is based on 24 EVC and 56 BGA SNPs. Five VISAGE laboratories participated in collaborative experiments to provide foreground for developmental validation of the assay. Assessment of assay performance and quality metrics, reproducibility, sensitivity, inhibitor tolerance and species specificity are described. Furthermore, the assay was tested using challenging samples such as mock casework samples and artificially degraded DNA. Two different analysis strategies were applied for this study and output on genotype calls and read depth was compared. Overall, inter-laboratory, inter-method and concordance with publicly available data were analysed and compared. Finally, the results showed a reliable and robust tool, which can be easily applied for laboratories already using a MiSeq FGx with ForenSeq reagents.

Application of a probabilistic genotyping software to MPS mixture STR data is supported by similar trends in LRs compared with CE data.

The interpretation of short tandem repeat (STR) profiles can be challenging when, for example, alleles are masked due to allele sharing among contributors and/or when they are subject to drop-out, for instance from sample degradation. Mixture interpretation can be improved by increasing the number of STRs and/or loci with a higher discriminatory power. Both capillary electrophoresis (CE, 6-dye) and massively parallel sequencing (MPS) provide a platform for analysing relatively large numbers of autosomal STRs. In addition, MPS enables distinguishing between sequence variants, resulting in enlarged discriminatory power. Also, MPS allows for small amplicon sizes for all loci as spacing is not an issue, which is beneficial with degraded DNA. Altogether, MPS has the potential to increase the weights of evidence for true contributors to (complex) DNA profiles. In this study, likelihood ratio (LR) calculations were performed using STR profiles obtained with two different MPS systems and analysed using different settings: 1) MPS PowerSeq™ Auto System profiles analysed using FDSTools equipped with optimized settings such as noise correction, 2) ForenSeq™ DNA Signature Prep Kit profiles analysed using the default settings in the Universal Analysis Software (UAS), and 3) ForenSeq™ DNA Signature Prep Kit profiles analysed using FDSTools empirically adapted to cope with one-directional reads and provisional, basic settings. The LR calculations used genotyping data for two- to four-person mixtures varying for mixture proportion, level of drop-out and allele sharing and were generated with the continuous model EuroForMix. The LR results for the over 2000 sets of propositions were affected by the variation for the number of markers and analysis settings used in the three approaches. Nevertheless, trends for true and non-contributors, effects of replicates, assigned number of contributors, and model validation results were comparable for the three MPS approaches and alike the trends known for CE data. Based on this analogy, we regard the probabilistic interpretation of MPS STR data fit for forensic DNA casework. In addition, guidelines were derived on when to apply LR calculations to MPS autosomal STR data and report the corresponding results.

STRNaming: Generating simple, informative names for sequenced STR alleles in a standardised and automated manner.

The introduction of Massively Parallel Sequencing in the forensic domain has exposed the need for comprehensive nomenclature of sequenced Short Tandem Repeat (STR) alleles. In general, three strategies are at hand: 1) the full sequence mapped to the human genome reference sequence, which ensures exact data exchange; 2) shortened, human-readable formats for forensic reporting and data presentation and 3) very short codes that enable compact figures and tables but do not convey any sequence information. Here, we describe an algorithm of the second type: STRNaming, which generates human-readable names for sequenced STR alleles. STRNaming is guided by a reference sequence at each locus and then functions independently to automatically assign a unique, sequence-descriptive name that also includes the capillary electrophoresis allele number. STRNaming settings were established based on preferences that were surveyed internationally in the forensic community. These settings ensure that a small change in the sequence corresponds to a small change in the allele name, which is helpful for recognising for instance stutter products. Sequence variants outside of the repeat units are indicated as simple variant calls. Since the STR name is sequence-descriptive, the sequence can be traced back from the allele name. Because STRNaming is fully guided by an assignable reference sequence, no central coordination or configuration is required and the method will work for any STR locus, be it autosomal, Y-, X-chromosomal in current or future use. The algorithm is publicly available online and offline.

The Dutch Y-chromosomal landscape.

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.

Correction to: The Dutch Y-chromosomal landscape.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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

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.

Towards broadening Forensic DNA Phenotyping beyond pigmentation: Improving the prediction of head hair shape from DNA.

Human head hair shape, commonly classified as straight, wavy, curly or frizzy, is an attractive target for Forensic DNA Phenotyping and other applications of human appearance prediction from DNA such as in paleogenetics. The genetic knowledge underlying head hair shape variation was recently improved by the outcome of a series of genome-wide association and replication studies in a total of 26,964 subjects, highlighting 12 loci of which 8 were novel and introducing a prediction model for Europeans based on 14 SNPs. In the present study, we evaluated the capacity of DNA-based head hair shape prediction by investigating an extended set of candidate SNP predictors and by using an independent set of samples for model validation. Prediction model building was carried out in 9674 subjects (6068 from Europe, 2899 from Asia and 707 of admixed European and Asian ancestries), used previously, by considering a novel list of 90 candidate SNPs. For model validation, genotype and phenotype data were newly collected in 2415 independent subjects (2138 Europeans and 277 non-Europeans) by applying two targeted massively parallel sequencing platforms, Ion Torrent PGM and MiSeq, or the MassARRAY platform. A binomial model was developed to predict straight vs. non-straight hair based on 32 SNPs from 26 genetic loci we identified as significantly contributing to the model. This model achieved prediction accuracies, expressed as AUC, of 0.664 in Europeans and 0.789 in non-Europeans; the statistically significant difference was explained mostly by the effect of one EDAR SNP in non-Europeans. Considering sex and age, in addition to the SNPs, slightly and insignificantly increased the prediction accuracies (AUC of 0.680 and 0.800, respectively). Based on the sample size and candidate DNA markers investigated, this study provides the most robust, validated, and accurate statistical prediction models and SNP predictor marker sets currently available for predicting head hair shape from DNA, providing the next step towards broadening Forensic DNA Phenotyping beyond pigmentation traits.

Short hypervariable microhaplotypes: A novel set of very short high discriminating power loci without stutter artefacts.

Since two decades, short tandem repeats (STRs) are the preferred markers for human identification, routinely analysed by fragment length analysis. Here we present a novel set of short hypervariable autosomal microhaplotypes (MH) that have four or more SNPs in a span of less than 70 nucleotides (nt). These MHs display a discriminating power approaching that of STRs and provide a powerful alternative for the analysis;1;is of forensic samples that are problematic when the STR fragment size range exceeds the integrity range of severely degraded DNA or when multiple donors contribute to an evidentiary stain and STR stutter artefacts complicate profile interpretation. MH typing was developed using the power of massively parallel sequencing (MPS) enabling new powerful, fast and efficient SNP-based approaches. MH candidates were obtained from queries in data of the 1000 Genomes, and Genome of the Netherlands (GoNL) projects. Wet-lab analysis of 276 globally dispersed samples and 97 samples of nine large CEPH families assisted locus selection and corroboration of informative value. We infer that MHs represent an alternative marker type with good discriminating power per locus (allowing the use of a limited number of loci), small amplicon sizes and absence of stutter artefacts that can be especially helpful when unbalanced mixed samples are submitted for human identification.

Length and repeat-sequence variation in 58 STRs and 94 SNPs in two Spanish populations.

We have genotyped the 58 STRs (27 autosomal, 24 Y-STRs and 7 X-STRs) and 94 autosomal SNPs in Illumina ForenSeq™ Primer Mix A in 88 Spanish Roma (Gypsy) samples and 143 Catalans. Since this platform is based in massive parallel sequencing, we have used simple R scripts to uncover the sequence variation in the repeat region. Thus, we have found, across 58 STRs, 541 length-based alleles, which, after considering repeat-sequence variation, became 804 different alleles. All loci in both populations were in Hardy-Weinberg equilibrium. FST between both populations was 0.0178 for autosomal SNPs, 0.0146 for autosomal STRs, 0.0101 for X-STRs and 0.1866 for Y-STRs. Combined a priori statistics showed quite large; for instance, pooling all the autosomal loci, the a priori probabilities of discriminating a suspect become 1-(2.3×10-70) and 1-(5.9×10-73), for Roma and Catalans respectively, and the chances of excluding a false father in a trio are 1-(2.6×10-20) and 1-(2.0×10-21).

FDSTools: A software package for analysis of massively parallel sequencing data with the ability to recognise and correct STR stutter and other PCR or sequencing noise.

Massively parallel sequencing (MPS) is on the advent of a broad scale application in forensic research and casework. The improved capabilities to analyse evidentiary traces representing unbalanced mixtures is often mentioned as one of the major advantages of this technique. However, most of the available software packages that analyse forensic short tandem repeat (STR) sequencing data are not well suited for high throughput analysis of such mixed traces. The largest challenge is the presence of stutter artefacts in STR amplifications, which are not readily discerned from minor contributions. FDSTools is an open-source software solution developed for this purpose. The level of stutter formation is influenced by various aspects of the sequence, such as the length of the longest uninterrupted stretch occurring in an STR. When MPS is used, STRs are evaluated as sequence variants that each have particular stutter characteristics which can be precisely determined. FDSTools uses a database of reference samples to determine stutter and other systemic PCR or sequencing artefacts for each individual allele. In addition, stutter models are created for each repeating element in order to predict stutter artefacts for alleles that are not included in the reference set. This information is subsequently used to recognise and compensate for the noise in a sequence profile. The result is a better representation of the true composition of a sample. Using Promega Powerseq™ Auto System data from 450 reference samples and 31 two-person mixtures, we show that the FDSTools correction module decreases stutter ratios above 20% to below 3%. Consequently, much lower levels of contributions in the mixed traces are detected. FDSTools contains modules to visualise the data in an interactive format allowing users to filter data with their own preferred thresholds.

Massively parallel sequencing of short tandem repeats-Population data and mixture analysis results for the PowerSeq™ system.

Current forensic DNA analysis predominantly involves identification of human donors by analysis of short tandem repeats (STRs) using Capillary Electrophoresis (CE). Recent developments in Massively Parallel Sequencing (MPS) technologies offer new possibilities in analysis of STRs since they might overcome some of the limitations of CE analysis. In this study 17 STRs and Amelogenin were sequenced in high coverage using a prototype version of the Promega PowerSeq™ system for 297 population samples from the Netherlands, Nepal, Bhutan and Central African Pygmies. In addition, 45 two-person mixtures with different minor contributions down to 1% were analysed to investigate the performance of this system for mixed samples. Regarding fragment length, complete concordance between the MPS and CE-based data was found, marking the reliability of MPS PowerSeq™ system. As expected, MPS presented a broader allele range and higher power of discrimination and exclusion rate. The high coverage sequencing data were used to determine stutter characteristics for all loci and stutter ratios were compared to CE data. The separation of alleles with the same length but exhibiting different stutter ratios lowers the overall variation in stutter ratio and helps in differentiation of stutters from genuine alleles in mixed samples. All alleles of the minor contributors were detected in the sequence reads even for the 1% contributions, but analysis of mixtures below 5% without prior information of the mixture ratio is complicated by PCR and sequencing artefacts.

Analysis of 36 Y-STR marker units including a concordance study among 2085 Dutch males.

The genotypes of 36 Y-chromosomal short tandem repeat (Y-STR) marker units were analysed in a Dutch population sample of 2085 males. Profiling results were compared for several partially overlapping kits, i.e. PowerPlex Y, Yfiler, PowerPlex Y23, and two in-house designed multiplexes with rapidly mutating Y-STRs. Nineteen Y-STR marker units, of which two are rapidly mutating, reside in at least two of these multiplexes, and for these markers concordance testing was performed. Two samples showed discordant genotyping results and the probable causative base change was revealed by Sanger sequencing. In addition, we encountered concordant, but aberrant genotyping results including one allele with low peak height and several null alleles. For 12 samples, this involved a null allele in two adjacent loci suggesting a large and recurrent deletion as the samples represent three distinct haplogroups. For each marker unit, the allele counts and frequencies are presented, as are the haplotype counts and haplotype diversities for several combinations of markers.

Data concatenation, Bayesian concordance and coalescent-based analyses of the species tree for the rapid radiation of Triturus newts.

The phylogenetic relationships for rapid species radiations are difficult to disentangle. Here we study one such case, namely the genus Triturus, which is composed of the marbled and crested newts. We analyze data for 38 genetic markers, positioned in 3-prime untranslated regions of protein-coding genes, obtained with 454 sequencing. Our dataset includes twenty Triturus newts and represents all nine species. Bayesian analysis of population structure allocates all individuals to their respective species. The branching patterns obtained by data concatenation, Bayesian concordance analysis and coalescent-based estimations of the species tree differ from one another. The data concatenation based species tree shows high branch support but branching order is considerably affected by allele choice in the case of heterozygotes in the concatenation process. Bayesian concordance analysis expresses the conflict between individual gene trees for part of the Triturus species tree as low concordance factors. The coalescent-based species tree is relatively similar to a previously published species tree based upon morphology and full mtDNA and any conflicting internal branches are not highly supported. Our findings reflect high gene tree discordance due to incomplete lineage sorting (possibly aggravated by hybridization) in combination with low information content of the markers employed (as can be expected for relatively recent species radiations). This case study highlights the complexity of resolving rapid radiations and we acknowledge that to convincingly resolve the Triturus species tree even more genes will have to be consulted.

The contribution of DNA metabarcoding to fungal conservation: diversity assessment, habitat partitioning and mapping red-listed fungi in protected coastal Salix repens communities in the Netherlands.

Western European coastal sand dunes are highly important for nature conservation. Communities of the creeping willow (Salix repens) represent one of the most characteristic and diverse vegetation types in the dunes. We report here the results of the first kingdom-wide fungal diversity assessment in S. repens coastal dune vegetation. We carried out massively parallel pyrosequencing of ITS rDNA from soil samples taken at ten sites in an extended area of joined nature reserves located along the North Sea coast of the Netherlands, representing habitats with varying soil pH and moisture levels. Fungal communities in Salix repens beds are highly diverse and we detected 1211 non-singleton fungal 97% sequence similarity OTUs after analyzing 688,434 ITS2 rDNA sequences. Our comparison along a north-south transect indicated strong correlation between soil pH and fungal community composition. The total fungal richness and the number OTUs of most fungal taxonomic groups negatively correlated with higher soil pH, with some exceptions. With regard to ecological groups, dark-septate endophytic fungi were more diverse in acidic soils, ectomycorrhizal fungi were represented by more OTUs in calcareous sites, while detected arbuscular mycorrhizal genera fungi showed opposing trends regarding pH. Furthermore, we detected numerous red listed species in our samples often from previously unknown locations, indicating that some of the fungal species currently considered rare may be more abundant in Dutch S. repens communities than previously thought.

Comparing six commercial autosomal STR kits in a large Dutch population sample.

Regularly, STR results obtained with different PCR amplification kits are compared, for instance with old cases, when revisiting cold cases or when addressing cross-border crimes. It is known that differences in primer design for the same loci in different kits may give rise to null alleles or shifted alleles. In this study, the genotyping results of 2085 Dutch male samples were compared for six autosomal STR kits (Promega's PowerPlex(®) 16, ESX-16 and ESI-17 Systems, Qiagen's Investigator(®) ESSplex Kit and Applied Biosystems' AmpFlSTR(®) Identifiler and NGM PCR Amplification Kits). A total of 19 discordant autosomal genotyping results were obtained that were examined by sequence analysis using Roche-454 next generation sequencing and/or Sanger sequencing. A further 25 discordances were found and sequenced for the Amelogenin locus. The 24 samples showing the same primer binding site mutation at the Amelogenin locus were subjected to X-STR analysis in order to assess whether they could share a common origin, which appeared not to be the case. Based on the sequencing results, we set the final genotypes and determined the allele frequencies of 23 autosomal STRs for the Dutch reference database.

A linguistically informed autosomal STR survey of human populations residing in the greater Himalayan region.

The greater Himalayan region demarcates two of the most prominent linguistic phyla in Asia: Tibeto-Burman and Indo-European. Previous genetic surveys, mainly using Y-chromosome polymorphisms and/or mitochondrial DNA polymorphisms suggested a substantially reduced geneflow between populations belonging to these two phyla. These studies, however, have mainly focussed on populations residing far to the north and/or south of this mountain range, and have not been able to study geneflow patterns within the greater Himalayan region itself. We now report a detailed, linguistically informed, genetic survey of Tibeto-Burman and Indo-European speakers from the Himalayan countries Nepal and Bhutan based on autosomal microsatellite markers and compare these populations with surrounding regions. The genetic differentiation between populations within the Himalayas seems to be much higher than between populations in the neighbouring countries. We also observe a remarkable genetic differentiation between the Tibeto-Burman speaking populations on the one hand and Indo-European speaking populations on the other, suggesting that language and geography have played an equally large role in defining the genetic composition of present-day populations within the Himalayas.

TSSV: a tool for characterization of complex allelic variants in pure and mixed genomes.

MOTIVATION: Advances in sequencing technologies and computational algorithms have enabled the study of genomic variants to dissect their functional consequence. Despite this unprecedented progress, current tools fail to reliably detect and characterize more complex allelic variants, such as short tandem repeats (STRs). We developed TSSV as an efficient and sensitive tool to specifically profile all allelic variants present in targeted loci. Based on its design, requiring only two short flanking sequences, TSSV can work without the use of a complete reference sequence to reliably profile highly polymorphic, repetitive or uncharacterized regions. RESULTS: We show that TSSV can accurately determine allelic STR structures in mixtures with 10% representation of minor alleles or complex mixtures in which a single STR allele is shared. Furthermore, we show the universal utility of TSSV in two other independent studies: characterizing de novo mutations introduced by transcription activator-like effector nucleases (TALENs) and profiling the noise and systematic errors in an IonTorrent sequencing experiment. TSSV complements the existing tools by aiding the study of highly polymorphic and complex regions and provides a high-resolution map that can be used in a wide range of applications, from personal genomics to forensic analysis and clinical diagnostics. AVAILABILITY AND IMPLEMENTATION: We have implemented TSSV as a Python package that can be installed through the command-line using pip install TSSV command. Its source code and documentation are available at https://pypi.python.org/pypi/tssv and http://www.lgtc.nl/tssv.

Quality assessment of the genetic test for familial hypercholesterolemia in the Netherlands.

Introduction. Familial hypercholesterolemia (FH) is an inherited disorder associated with a severely increased risk of cardiovascular disease. Although DNA test results in FH are associated with important medical and ethical consequences, data on accuracy of genetic tests is scarce. Methods. Therefore, we performed a prospective study to assess the overall accuracy of the DNA test used in the genetic cascade screening program for FH in The Netherlands. Individuals aged 18 years and older tested for one of the 5 most prevalent FH mutations, were included consecutively. DNA samples were analyzed by the reference and a counter-expertise laboratory following a standardized procedure. Results. 1003 cases were included. In the end, 317 (32%) carried an FH mutation, whereas in 686 (69%) samples no mutation was found. The overall accuracy of the reference laboratory was 99.8%, with two false positive results identified by the counter-expertise laboratory. Conclusion. The currently used mutation analysis is associated with a very low error rate. Therefore, we do not recommend routine use of duplicate testing.