Concentrations and distribution of chlorinated paraffins in Belgian foods.

This study reports on concentrations of short- and medium-chain chlorinated paraffins (SCCPs and MCCPs, respectively) in a wide range of food samples (n = 211) purchased in Belgium during 2020. Samples were analysed by gas chromatography-mass spectrometry (GC-MS) and quantified using chlorine content calibration. ∑SCCPs were present above LOQ in 25% of samples with an overall range of

Whole-genome-based phylogenomic analysis of the Belgian 2016-2017 influenza A(H3N2) outbreak season allows improved surveillance.

Seasonal influenza epidemics are associated with high mortality and morbidity in the human population. Influenza surveillance is critical for providing information to national influenza programmes and for making vaccine composition predictions. Vaccination prevents viral infections, but rapid influenza evolution results in emerging mutants that differ antigenically from vaccine strains. Current influenza surveillance relies on Sanger sequencing of the haemagglutinin (HA) gene. Its classification according to World Health Organization (WHO) and European Centre for Disease Prevention and Control (ECDC) guidelines is based on combining certain genotypic amino acid mutations and phylogenetic analysis. Next-generation sequencing technologies enable a shift to whole-genome sequencing (WGS) for influenza surveillance, but this requires laboratory workflow adaptations and advanced bioinformatics workflows. In this study, 253 influenza A(H3N2) positive clinical specimens from the 2016-2017 Belgian season underwent WGS using the Illumina MiSeq system. HA-based classification according to WHO/ECDC guidelines did not allow classification of all samples. A new approach, considering the whole genome, was investigated based on using powerful phylogenomic tools including beast and Nextstrain, which substantially improved phylogenetic classification. Moreover, Bayesian inference via beast facilitated reassortment detection by both manual inspection and computational methods, detecting intra-subtype reassortants at an estimated rate of 15 %. Real-time analysis (i.e. as an outbreak is ongoing) via Nextstrain allowed positioning of the Belgian isolates into the globally circulating context. Finally, integration of patient data with phylogenetic groups and reassortment status allowed detection of several associations that would have been missed when solely considering HA, such as hospitalized patients being more likely to be infected with A(H3N2) reassortants, and the possibility to link several phylogenetic groups to disease severity indicators could be relevant for epidemiological monitoring. Our study demonstrates that WGS offers multiple advantages for influenza monitoring in (inter)national influenza surveillance, and proposes an improved methodology. This allows leveraging all information contained in influenza genomes, and allows for more accurate genetic characterization and reassortment detection.

A Bioinformatics Whole-Genome Sequencing Workflow for Clinical Mycobacterium tuberculosis Complex Isolate Analysis, Validated Using a Reference Collection Extensively Characterized with Conventional Methods and In Silico Approaches.

The use of whole-genome sequencing (WGS) for routine typing of bacterial isolates has increased substantially in recent years. For Mycobacterium tuberculosis (MTB), in particular, WGS has the benefit of drastically reducing the time required to generate results compared to most conventional phenotypic methods. Consequently, a multitude of solutions for analyzing WGS MTB data have been developed, but their successful integration in clinical and national reference laboratories is hindered by the requirement for their validation, for which a consensus framework is still largely absent. We developed a bioinformatics workflow for (Illumina) WGS-based routine typing of MTB complex (MTBC) member isolates allowing complete characterization, including (sub)species confirmation and identification (16S, csb/RD, hsp65), single nucleotide polymorphism (SNP)-based antimicrobial resistance (AMR) prediction, and pathogen typing (spoligotyping, SNP barcoding, and core genome multilocus sequence typing). Workflow performance was validated on a per-assay basis using a collection of 238 in-house-sequenced MTBC isolates, extensively characterized with conventional molecular biology-based approaches supplemented with public data. For SNP-based AMR prediction, results from molecular genotyping methods were supplemented with in silico modified data sets, allowing us to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics of >99% for all assays, except for spoligotyping, where sensitivity dropped to ∼90%. The validation framework for our WGS-based bioinformatics workflow can aid in the standardization of bioinformatics tools by the MTB community and other SNP-based applications regardless of the targeted pathogen(s). The bioinformatics workflow is available for academic and nonprofit use through the Galaxy instance of our institute at https://galaxy.sciensano.be.

Phylogenomic Investigation of Increasing Fluoroquinolone Resistance among Belgian Cases of Shigellosis between 2013 and 2018 Indicates Both Travel-Related Imports and Domestic Circulation.

Shigellosis is an acute enteric infection caused mainly by the species Shigella flexneri and Shigella sonnei. Since surveillance of these pathogens indicated an increase in ciprofloxacin-resistant samples collected in Belgium between 2013 and 2018, a subset of 148 samples was analyzed with whole genome sequencing (WGS) to investigate their dispersion and underlying genomic features associated with ciprofloxacin resistance. A comparison between observed phenotypes and WGS-based resistance prediction to ciprofloxacin revealed perfect correspondence for all samples. Core genome multi-locus sequence typing and single nucleotide polymorphism-typing were used for phylogenomic investigation to characterize the spread of these infections within Belgium, supplemented with data from international reference collections to place the Belgian isolates within their global context. For S. flexneri, substantial diversity was observed with ciprofloxacin-resistant isolates assigned to several phylogenetic groups. Besides travel-related imports, several clusters of highly similar Belgian isolates could not be linked directly to international travel suggesting the presence of domestically circulating strains. For S. sonnei, Belgian isolates were all limited to lineage III, and could often be traced back to travel to countries in Asia and Africa, sometimes followed by domestic circulation. For both species, several clusters of isolates obtained exclusively from male patients were observed. Additionally, we illustrated the limitations of conventional serotyping of S. flexneri, which was impacted by serotype switching. This study contributes to a better understanding of the spread of shigellosis within Belgium and internationally, and highlights the added value of WGS for the surveillance of this pathogen.

Validation strategy of a bioinformatics whole genome sequencing workflow for Shiga toxin-producing Escherichia coli using a reference collection extensively characterized with conventional methods.

Whole genome sequencing (WGS) enables complete characterization of bacterial pathogenic isolates at single nucleotide resolution, making it the ultimate tool for routine surveillance and outbreak investigation. The lack of standardization, and the variation regarding bioinformatics workflows and parameters, however, complicates interoperability among (inter)national laboratories. We present a validation strategy applied to a bioinformatics workflow for Illumina data that performs complete characterization of Shiga toxin-producing Escherichia coli (STEC) isolates including antimicrobial resistance prediction, virulence gene detection, serotype prediction, plasmid replicon detection and sequence typing. The workflow supports three commonly used bioinformatics approaches for the detection of genes and alleles: alignment with blast+, kmer-based read mapping with KMA, and direct read mapping with SRST2. A collection of 131 STEC isolates collected from food and human sources, extensively characterized with conventional molecular methods, was used as a validation dataset. Using a validation strategy specifically adopted to WGS, we demonstrated high performance with repeatability, reproducibility, accuracy, precision, sensitivity and specificity above 95 % for the majority of all assays. The WGS workflow is publicly available as a 'push-button' pipeline at https://galaxy.sciensano.be. Our validation strategy and accompanying reference dataset consisting of both conventional and WGS data can be used for characterizing the performance of various bioinformatics workflows and assays, facilitating interoperability between laboratories with different WGS and bioinformatics set-ups.

Evaluation of a commercial exogenous internal process control for diagnostic RNA virus metagenomics from different animal clinical samples.

Metagenomic next generation sequencing (mNGS) is increasingly recognized as an important complementary tool to targeted human and animal infectious disease diagnostics. It is, however, sensitive to biases and errors that are currently not systematically evaluated by the implementation of quality controls (QC) for the diagnostic use of mNGS. We evaluated a commercial reagent (Mengovirus extraction control kit, CeraamTools, bioMérieux) as an exogenous internal control for mNGS. It validates the integrity of reagents and workflow, the efficient isolation of viral nucleic acids and the absence of inhibitors in individual samples (verified using a specific qRT-PCR). Moreover, it validates the efficient generation of viral sequence data in individual samples (verified by normalized mengoviral read counts in the metagenomic analysis). We show that when using a completely random metagenomics workflow: (1) Mengovirus RNA can be reproducibly detected in different animal sample types (swine feces and sera, wild bird cloacal swabs), except for tissue samples (swine lung); (2) the Mengovirus control kit does not contain other contaminating viruses that may affect metagenomic experiments (using a cutoff of minimum 1 Kraken classified read per million (RPM)); (3) the addition of 2.17 × 106Mengovirus copies/mL of sample does not affect the virome composition of pig fecal samples or wild bird cloacal swab samples; (4) Mengovirus Cq values (using as cutoff the upper limit of the 99 % confidence interval of Cq values for a given sample matrix) allow the identification of samples with poor viral RNA extraction or high inhibitor load; (5) Mengovirus normalized read counts (cutoff RPM > 1) allow the identification of samples where the viral sequences are outcompeted by host or bacterial target sequences in the random metagenomic workflow. The implementation of two QC testing points, a first one after RNA extraction (Mengoviral qRT-PCR) and a second one after metagenomic data analysis provide valuable information for the validation of individual samples and results. Their implementation in addition to external controls validating runs or experiments should be carefully considered for a given sample type and workflow.

Identification of an unauthorized genetically modified bacteria in food enzyme through whole-genome sequencing.

Recently, the unexpected presence of a viable unauthorized genetically modified bacterium in a commercialized food enzyme (protease) product originating from a microbial fermentation process has been notified at the European level (RASFF 2019.3332). This finding was made possible thanks to the use of the next-generation sequencing technology, as reported in this study. Whole-genome sequencing was used to characterize the genetic modification comprising a sequence from the pUB110 shuttle vector (GenBank: M19465.1), harbouring antimicrobial resistance genes conferring a resistance to kanamycine, neomycin and bleomycin, flanked on each side by a sequence coding for a protease (GenBank: WP_032874795.1). In addition, based on these data, two real-time PCR methods, that can be used by enforcement laboratories, specific to this unauthorized genetically modified bacterium were developed and validated. The present study emphasizes the key role that whole-genome sequencing can take for detection of unknown and unauthorized genetically modified microorganisms in commercialized microbial fermentation products intended for the food and feed chain. Moreover, current issues encountered by the Competent Authorities and enforcement laboratories with such unexpected contaminations and the importance of performing official controls were highlighted.

Combining short and long read sequencing to characterize antimicrobial resistance genes on plasmids applied to an unauthorized genetically modified Bacillus.

Antimicrobial resistance (AMR) is a major public health threat. Plasmids are able to transfer AMR genes among bacterial isolates. Whole genome sequencing (WGS) is a powerful tool to monitor AMR determinants. However, plasmids are difficult to reconstruct from WGS data. This study aimed to improve the characterization, including the localization of AMR genes using short and long read WGS strategies. We used a genetically modified (GM) Bacillus subtilis isolated as unexpected contamination in a feed additive, and therefore considered unauthorized (RASFF 2014.1249), as a case study. In GM organisms, AMR genes are used as selection markers. Because of the concern of spread of these AMR genes when present on mobile genetic elements, it is crucial to characterize their location. Our approach resulted in an assembly of one chromosome and one plasmid, each with several AMR determinants of which five are against critically important antibiotics. Interestingly, we found several plasmids, containing AMR genes, integrated in the chromosome in a repetitive region of at least 53 kb. Our findings would have been impossible using short reads only. We illustrated the added value of long read sequencing in addressing the challenges of plasmid reconstruction within the context of evaluating the risk of AMR spread.

Strategy for the identification of micro-organisms producing food and feed products: Bacteria producing food enzymes as study case.

Recent European regulations require safety assessments of food enzymes (FE) before their commercialization. FE are mainly produced by micro-organisms, whose viable strains nor associated DNA can be present in the final products. Currently, no strategy targeting such impurities exists in enforcement laboratories. Therefore, a generic strategy of first line screening was developed to detect and identify, through PCR amplification and sequencing of the 16S-rRNA gene, the potential presence of FE producing bacteria in FE preparations. First, the specificity was verified using all microbial species reported to produce FE. Second, an in-house database, with 16S reference sequences from bacteria producing FE, was constructed for their fast identification through blast analysis. Third, the sensitivity was assessed on a spiked FE preparation. Finally, the applicability was verified using commercial FE preparations. Using straightforward PCR amplifications, Sanger sequencing and blast analysis, the proposed strategy was demonstrated to be convenient for implementation in enforcement laboratories.

Validation of a Bioinformatics Workflow for Routine Analysis of Whole-Genome Sequencing Data and Related Challenges for Pathogen Typing in a European National Reference Center: Neisseria meningitidis as a Proof-of-Concept.

Despite being a well-established research method, the use of whole-genome sequencing (WGS) for routine molecular typing and pathogen characterization remains a substantial challenge due to the required bioinformatics resources and/or expertise. Moreover, many national reference laboratories and centers, as well as other laboratories working under a quality system, require extensive validation to demonstrate that employed methods are "fit-for-purpose" and provide high-quality results. A harmonized framework with guidelines for the validation of WGS workflows does currently, however, not exist yet, despite several recent case studies highlighting the urgent need thereof. We present a validation strategy focusing specifically on the exhaustive characterization of the bioinformatics analysis of a WGS workflow designed to replace conventionally employed molecular typing methods for microbial isolates in a representative small-scale laboratory, using the pathogen Neisseria meningitidis as a proof-of-concept. We adapted several classically employed performance metrics specifically toward three different bioinformatics assays: resistance gene characterization (based on the ARG-ANNOT, ResFinder, CARD, and NDARO databases), several commonly employed typing schemas (including, among others, core genome multilocus sequence typing), and serogroup determination. We analyzed a core validation dataset of 67 well-characterized samples typed by means of classical genotypic and/or phenotypic methods that were sequenced in-house, allowing to evaluate repeatability, reproducibility, accuracy, precision, sensitivity, and specificity of the different bioinformatics assays. We also analyzed an extended validation dataset composed of publicly available WGS data for 64 samples by comparing results of the different bioinformatics assays against results obtained from commonly used bioinformatics tools. We demonstrate high performance, with values for all performance metrics >87%, >97%, and >90% for the resistance gene characterization, sequence typing, and serogroup determination assays, respectively, for both validation datasets. Our WGS workflow has been made publicly available as a "push-button" pipeline for Illumina data at https://galaxy.sciensano.be to showcase its implementation for non-profit and/or academic usage. Our validation strategy can be adapted to other WGS workflows for other pathogens of interest and demonstrates the added value and feasibility of employing WGS with the aim of being integrated into routine use in an applied public health setting.

TARGETING THE 16S RRNA GENE FOR BACTERIAL IDENTIFICATION IN COMPLEX MIXED SAMPLES: COMPARATIVE EVALUATION OF SECOND (ILLUMINA) AND THIRD (OXFORD NANOPORE TECHNOLOGIES) GENERATION SEQUENCING TECHNOLOGIES.

Rapid, accurate bacterial identification in biological samples is an important task for microbiology laboratories, for which 16S~rRNA gene Sanger sequencing of cultured isolates is frequently used. In contrast, next-generation sequencing does not require intermediate culturing steps and can be directly applied on communities, but its performance has not been extensively evaluated. We present a comparative evaluation of second (Illumina) and third (Oxford Nanopore Technologies (ONT)) generation sequencing technologies for 16S targeted genomics using a well-characterized reference sample. Different 16S gene regions were amplified and sequenced using the Illumina MiSeq, and analyzed with Mothur. Correct classification was variable, depending on the region amplified. Using a majority vote over all regions, most false positives could be eliminated at the genus level but not the species level. Alternatively, the entire 16S gene was amplified and sequenced using the ONT MinION, and analyzed with Mothur, EPI2ME, and GraphMap. Although >99\% of reads were correctly classified at the genus level, up to $\approx$40\% were misclassified at the species level. Both~technologies, therefore, allow reliable identification of bacterial genera, but can potentially misguide identification of bacterial species, and constitute viable alternatives to Sanger sequencing for rapid analysis of mixed samples without requiring any culturing steps.

Nanopore sequencing technology: a new route for the fast detection of unauthorized GMO.

In order to strengthen the current genetically modified organism (GMO) detection system for unauthorized GMO, we have recently developed a new workflow based on DNA walking to amplify unknown sequences surrounding a known DNA region. This DNA walking is performed on transgenic elements, commonly found in GMO, that were earlier detected by real-time PCR (qPCR) screening. Previously, we have demonstrated the ability of this approach to detect unauthorized GMO via the identification of unique transgene flanking regions and the unnatural associations of elements from the transgenic cassette. In the present study, we investigate the feasibility to integrate the described workflow with the MinION Next-Generation-Sequencing (NGS). The MinION sequencing platform can provide long read-lengths and deal with heterogenic DNA libraries, allowing for rapid and efficient delivery of sequences of interest. In addition, the ability of this NGS platform to characterize unauthorized and unknown GMO without any a priori knowledge has been assessed.

Methylome analysis for spina bifida shows SOX18 hypomethylation as a risk factor with evidence for a complex (epi)genetic interplay to affect neural tube development.

BACKGROUND: Neural tube defects (NTDs) are severe congenital malformations that arise from failure of neurulation during early embryonic development. The molecular basis underlying most human NTDs still remains largely unknown. Based on the hypothesis that folic acid prevents NTDs by stimulating methylation reactions, DNA methylation changes could play a role in NTDs. We performed a methylome analysis for patients with myelomeningocele (MMC). Using a candidate CpG analysis for HOX genes, a significant association between HOXB7 hypomethylation and MMC was found. METHODS: In the current study, we analyzed leukocyte methylome data of ten patients with MMC and six controls using Illumina Methylation Analyzer and WateRmelon R-packages and performed validation studies using larger MMC and control cohorts with Sequenom EpiTYPER. RESULTS: The methylome analysis showed 75 CpGs in 45 genes that are significantly differentially methylated in MMC patients. CpG-specific methylation differences were next replicated for the top six candidate genes ABAT, CNTNAP1, SLC1A6, SNED1, SOX18, and TEPP but only for the SOX18 locus a significant overall hypomethylation was observed (P value = 0.0003). Chemically induced DNA demethylation in HEK cells resulted in SOX18 hypomethylation and increased expression. Injection of sox18 mRNA in zebrafish resulted in abnormal neural tube formation. Quantification of DNA methylation for the SOX18 locus was also determined for five families where parents had normal methylation values compared to significant lower values for both the MMC as their non-affected child. SOX18 methylation studies were performed for a MMC patient with a paternally inherited chromosomal deletion that includes BMP4. The patient showed extreme SOX18 hypomethylation similar to his healthy mother while his father had normal methylation values. CONCLUSIONS: This is the first genome-wide methylation study in leukocytes for patients with NTDs. We report SOX18 as a novel MMC risk gene but our findings also suggest that SOX18 hypomethylation must interplay with environmental and (epi)genetic factors to cause NTDs. Further studies are needed that combine methylome data with next-generation sequencing approaches to unravel NTD etiology.

Assessing transmissibility of HIV-1 drug resistance mutations from treated and from drug-naive individuals.

OBJECTIVES: Surveillance drug resistance mutations (SDRMs) in drug-naive patients are typically used to survey HIV-1-transmitted drug resistance (TDR). We test here how SDRMs in patients failing treatment, the original source of TDR, contribute to assessing TDR, transmissibility and transmission source of SDRMs. DESIGN: This is a retrospective observational study analyzing a Portuguese cohort of HIV-1-infected patients. METHODS: The prevalence of SDRMs to protease inhibitors, nucleoside reverse transcriptase inhibitors (NRTIs) and nonnucleoside reverse transcriptase inhibitors (NNRTIs) in drug-naive and treatment-failing patients was measured for 3554 HIV-1 subtype B patients. Transmission ratio (prevalence in drug-naive/prevalence in treatment-failing patients), average viral load and robust linear regression with outlier detection (prevalence in drug-naive versus in treatment-failing patients) were analyzed and used to interpret transmissibility. RESULTS: Prevalence of SDRMs in drug-naive and treatment-failing patients were linearly correlated, but some SDRMs were classified as outliers - above (PRO: D30N, N88D/S, L90 M, RT: G190A/S/E) or below (RT: M184I/V) expectations. The normalized regression slope was 0.073 for protease inhibitors, 0.084 for NRTIs and 0.116 for NNRTIs. Differences between SDRMs transmission ratios were not associated with differences in viral loads. CONCLUSION: The significant linear correlation between prevalence of SDRMs in drug-naive and in treatment-failing patients indicates that the prevalence in treatment-failing patients can be useful to predict levels of TDR. The slope is a cohort-dependent estimate of rate of TDR per drug class and outlier detection reveals comparative persistence of SDRMs. Outlier SDRMs with higher transmissibility are more persistent and more likely to have been acquired from drug-naive patients. Those with lower transmissibility have faster reversion dynamics after transmission and are associated with acquisition from treatment-failing patients.

DNA methylation analysis of Homeobox genes implicates HOXB7 hypomethylation as risk factor for neural tube defects.

Neural tube defects (NTDs) are common birth defects of complex etiology. Though family- and population-based studies have confirmed a genetic component, the responsible genes for NTDs are still largely unknown. Based on the hypothesis that folic acid prevents NTDs by stimulating methylation reactions, epigenetic factors, such as DNA methylation, are predicted to be involved in NTDs. Homeobox (HOX) genes play a role in spinal cord development and are tightly regulated in a spatiotemporal and collinear manner, partly by epigenetic modifications. We have quantified DNA methylation for the different HOX genes by subtracting values from a genome-wide methylation analysis using leukocyte DNA from 10 myelomeningocele (MMC) patients and 6 healthy controls. From the 1575 CpGs profiled for the 4 HOX clusters, 26 CpGs were differentially methylated (P-value < 0.05; ß-difference > 0.05) between MMC patients and controls. Seventy-seven percent of these CpGs were located in the HOXA and HOXB clusters, with the most profound difference for 3 CpGs within the HOXB7 gene body. A validation case-control study including 83 MMC patients and 30 unrelated healthy controls confirmed a significant association between MMC and HOXB7 hypomethylation (-14.4%; 95% CI: 11.9-16.9%; P-value < 0.0001) independent of the MTHFR 667C>T genotype. Significant HOXB7 hypomethylation was also present in 12 unaffected siblings, each related to a MMC patient, suggestive of an epigenetic change induced by the mother. The inclusion of a neural tube formation model using zebrafish showed that Hoxb7a overexpression but not depletion resulted in deformed body axes with dysmorphic neural tube formation. Our results implicate HOXB7 hypomethylation as risk factor for NTDs and highlight the importance for future genome-wide DNA methylation analyses without preselecting candidate pathways.

dendsort: modular leaf ordering methods for dendrogram representations in R.

Dendrograms are graphical representations of binary tree structures resulting from agglomerative hierarchical clustering. In Life Science, a cluster heat map is a widely accepted visualization technique that utilizes the leaf order of a dendrogram to reorder the rows and columns of the data table. The derived linear order is more meaningful than a random order, because it groups similar items together. However, two consecutive items can be quite dissimilar despite proximity in the order. In addition, there are 2 (n-1) possible orderings given n input elements as the orientation of clusters at each merge can be flipped without affecting the hierarchical structure. We present two modular leaf ordering methods to encode both the monotonic order in which clusters are merged and the nested cluster relationships more faithfully in the resulting dendrogram structure. We compare dendrogram and cluster heat map visualizations created using our heuristics to the default heuristic in R and seriation-based leaf ordering methods. We find that our methods lead to a dendrogram structure with global patterns that are easier to interpret, more legible given a limited display space, and more insightful for some cases. The implementation of methods is available as an R package, named "dendsort", from the CRAN package repository. Further examples, documentations, and the source code are available at [https://bitbucket.org/biovizleuven/dendsort/].

In vitro screening of embryos by whole-genome sequencing: now, in the future or never?

STUDY QUESTION: What are the analytical and clinical validity and the clinical utility of in vitro screening of embryos by whole-genome sequencing? SUMMARY ANSWER: At present there are still many limitations in terms of analytical and clinical validity and utility and many ethical questions remain. WHAT IS KNOWN ALREADY: Whole-genome sequencing of IVF/ICSI embryos is technically possible. Many loss-of-function mutations exist in the general population without serious effects on the phenotype of the individual. Moreover, annotations of genes and the reference genome are still not 100% correct. STUDY DESIGN, SIZE, DURATION: We used publicly available samples from the 1000 Genomes project and Complete Genomics, together with 42 samples from in-house research samples of parents from trios to investigate the presence of loss-of-function mutations in healthy individuals. PARTICIPANTS/MATERIALS, SETTING, METHODS: In the samples, we looked for mutations in genes that are associated with a selection of severe Mendelian disorders with a known molecular basis. We looked for mutations predicted to be damaging by PolyPhen and SIFT and for mutations annotated as disease causing in Human Genome Mutation Database (HGMD). MAIN RESULTS AND THE ROLE OF CHANCE: More than 40% of individuals who can be considered healthy have mutations that are predicted to be damaging in genes associated with severe Mendelian disorders or are annotated as disease causing. LIMITATIONS, REASONS FOR CAUTION: The analysis relies on current knowledge and databases are continuously updated to reflect our increasing knowledge about the genome. In the process of our analysis several updates were already made. WIDER IMPLICATIONS OF THE FINDINGS: At this moment it is not advisable to use whole-genome sequencing as a tool to set up health profiles to select embryos for transfer. We also raise some ethical questions that have to be addressed before this technology can be used for embryo selection. TRIAL REGISTRATION NUMBER: N/A.