Comprehensive reanalysis for CNVs in ES data from unsolved rare disease cases results in new diagnoses.

We report the results of a comprehensive copy number variant (CNV) reanalysis of 9171 exome sequencing datasets from 5757 families affected by a rare disease (RD). The data reanalysed was extremely heterogeneous, having been generated using 28 different enrichment kits by 42 different research groups across Europe partnering in the Solve-RD project. Each research group had previously undertaken their own analysis of the data but failed to identify disease-causing variants. We applied three CNV calling algorithms to maximise sensitivity, and rare CNVs overlapping genes of interest, provided by four partner European Reference Networks, were taken forward for interpretation by clinical experts. This reanalysis has resulted in a molecular diagnosis being provided to 51 families in this sample, with ClinCNV performing the best of the three algorithms. We also identified partially explanatory pathogenic CNVs in a further 34 individuals. This work illustrates the value of reanalysing ES cold cases for CNVs.

An interconnected data infrastructure to support large-scale rare disease research.

The Solve-RD project brings together clinicians, scientists, and patient representatives from 51 institutes spanning 15 countries to collaborate on genetically diagnosing ("solving") rare diseases (RDs). The project aims to significantly increase the diagnostic success rate by co-analyzing data from thousands of RD cases, including phenotypes, pedigrees, exome/genome sequencing, and multiomics data. Here we report on the data infrastructure devised and created to support this co-analysis. This infrastructure enables users to store, find, connect, and analyze data and metadata in a collaborative manner. Pseudonymized phenotypic and raw experimental data are submitted to the RD-Connect Genome-Phenome Analysis Platform and processed through standardized pipelines. Resulting files and novel produced omics data are sent to the European Genome-Phenome Archive, which adds unique file identifiers and provides long-term storage and controlled access services. MOLGENIS "RD3" and Café Variome "Discovery Nexus" connect data and metadata and offer discovery services, and secure cloud-based "Sandboxes" support multiparty data analysis. This successfully deployed and useful infrastructure design provides a blueprint for other projects that need to analyze large amounts of heterogeneous data.

Cas9-directed long-read sequencing to resolve optical genome mapping findings in leukemia diagnostics.

Leukemias are genetically heterogeneous and diagnostics therefore includes various standard-of-care (SOC) techniques, including karyotyping, SNP-array and FISH. Optical genome mapping (OGM) may replace these as it detects different types of structural aberrations simultaneously and additionally detects much smaller aberrations (500 bp vs 5-10 Mb with karyotyping). However, its resolution may still be too low to define clinical relevance of aberrations when they are located between two OGM labels or when labels are not distinct enough. Here, we test the potential of Cas9-directed long-read sequencing (LRS) as an additional technique to resolve such potentially relevant new findings. From an internal Bionano implementation study we selected ten OGM calls that could not be validated with SOC methods. Per variant we designed crRNAs for Cas9 enrichment, prepared libraries and sequenced them on a MinION/GridION device. We could confirm all aberrations and, importantly, the actual breakpoints of the OGM calls were located between 0.2 and 5.5 kb of the OGM-estimated breakpoints, confirming the high reliability of OGM. Furthermore, we show examples of redefinition of aberrations between labels that enable judgment of clinical relevance. Our results suggest that Cas9-directed LRS can be a relevant and flexible secondary technique in diagnostic workflows including OGM.

Ten quick tips for building FAIR workflows.

Research data is accumulating rapidly and with it the challenge of fully reproducible science. As a consequence, implementation of high-quality management of scientific data has become a global priority. The FAIR (Findable, Accesible, Interoperable and Reusable) principles provide practical guidelines for maximizing the value of research data; however, processing data using workflows-systematic executions of a series of computational tools-is equally important for good data management. The FAIR principles have recently been adapted to Research Software (FAIR4RS Principles) to promote the reproducibility and reusability of any type of research software. Here, we propose a set of 10 quick tips, drafted by experienced workflow developers that will help researchers to apply FAIR4RS principles to workflows. The tips have been arranged according to the FAIR acronym, clarifying the purpose of each tip with respect to the FAIR4RS principles. Altogether, these tips can be seen as practical guidelines for workflow developers who aim to contribute to more reproducible and sustainable computational science, aiming to positively impact the open science and FAIR community.

Diagnostic yield of targeted next generation sequencing in 2002 Dutch cardiomyopathy patients.

BACKGROUND: Next-generation sequencing (NGS) is increasingly used for clinical evaluation of cardiomyopathy patients as it allows for simultaneous screening of multiple cardiomyopathy-associated genes. Adding copy number variant (CNV) analysis of NGS data is not routine yet and may contribute to the diagnostic yield. OBJECTIVES: Determine the diagnostic yield of our targeted NGS gene panel in routine clinical diagnostics of Dutch cardiomyopathy patients and explore the impact of exon CNVs on diagnostic yield. METHODS: Patients (N = 2002) referred for clinical genetic analysis underwent diagnostic testing of 55-61 genes associated with cardiomyopathies. Samples were analyzed and evaluated for single nucleotide variants (SNVs), indels and CNVs. CNVs identified in the NGS data and suspected of being pathogenic based on type, size and location were confirmed by additional molecular tests. RESULTS: A (likely) pathogenic (L)P variant was detected in 22.7% of patients, including 3 with CNVs and 25 where a variant was identified in a gene currently not associated with the patient's cardiomyopathy subtype. Only 15 out of 2002 patients (0.8%) were found to carry two (L)P variants. CONCLUSION: The yield of routine clinical diagnostics of cardiomyopathies was relatively low when compared to literature. This is likely due to the fact that our study reports the outcome of patients in daily routine diagnostics, therefore also including patients not fully fulfilling (subtype specific) cardiomyopathy criteria. This may also explain why (L)P variants were identified in genes not associated with the reported subtype. The added value of CNV analysis was shown to be limited but not negligible.

Clinical Value of EGFR Copy Number Gain Determined by Amplicon-Based Targeted Next Generation Sequencing in Patients with EGFR-Mutated NSCLC.

BACKGROUND: The clinical relevance of epidermal growth factor receptor (EGFR) copy number gain in patients with EGFR mutated advanced non-small cell lung cancer on first-line tyrosine kinase inhibitor treatment has not been fully elucidated. OBJECTIVE: We aimed to estimate EGFR copy number gain using amplicon-based next generation sequencing data and explored its prognostic value. PATIENTS AND METHODS: Next generation sequencing data were obtained for 1566 patients with non-small cell lung cancer. EGFR copy number gain was defined based on an increase in EGFR read counts relative to internal reference amplicons and normal controls in combination with a modified z-score ≥ 3.5. Clinical follow-up data were available for 60 patients treated with first-line EGFR-tyrosine kinase inhibitors. RESULTS: Specificity and sensitivity of next generation sequencing-based EGFR copy number estimations were above 90%. EGFR copy number gain was observed in 27.9% of EGFR mutant cases and in 7.4% of EGFR wild-type cases. EGFR gain was not associated with progression-free survival but showed a significant effect on overall survival with an adjusted hazard ratio of 3.14 (95% confidence interval 1.46-6.78, p = 0.003). Besides EGFR copy number gain, osimertinib in second or subsequent lines of treatment and the presence of T790M at relapse revealed significant effects in a multivariate analysis with adjusted hazard ratio of 0.43 (95% confidence interval 0.20-0.91, p = 0.028) and 0.24 (95% confidence interval 0.1-0.59, p = 0.001), respectively. CONCLUSIONS: Pre-treatment EGFR copy number gain determined by amplicon-based next generation sequencing data predicts worse overall survival in EGFR-mutated patients treated with first-line EGFR-tyrosine kinase inhibitors. T790M at relapse and subsequent treatment with osimertinib predict longer overall survival.

Targeted RNA-Sequencing Enables Detection of Relevant Translocations and Single Nucleotide Variants and Provides a Method for Classification of Hematological Malignancies-RANKING.

BACKGROUND: Patients with hematological malignancies (HMs) carry a wide range of chromosomal and molecular abnormalities that impact their prognosis and treatment. Since no current technique can detect all relevant abnormalities, technique(s) are chosen depending on the reason for referral, and abnormalities can be missed. We tested targeted transcriptome sequencing as a single platform to detect all relevant abnormalities and compared it to current techniques. MATERIAL AND METHODS: We performed RNA-sequencing of 1385 genes (TruSight RNA Pan-Cancer, Illumina) in bone marrow from 136 patients with a primary diagnosis of HM. We then applied machine learning to expression profile data to perform leukemia classification, a method we named RANKING. Gene fusions for all the genes in the panel were detected, and overexpression of the genes EVI1, CCND1, and BCL2 was quantified. Single nucleotide variants/indels were analyzed in acute myeloid leukemia (AML), myelodysplastic syndrome and patients with acute lymphoblastic leukemia (ALL) using a virtual myeloid (54 genes) or lymphoid panel (72 genes). RESULTS: RANKING correctly predicted the leukemia classification of all AML and ALL samples and improved classification in 3 patients. Compared to current methods, only one variant was missed, c.2447A>T in KIT (RT-PCR at 10-4), and BCL2 overexpression was not seen due to a t(14; 18)(q32; q21) in 2% of the cells. Our RNA-sequencing method also identified 6 additional fusion genes and overexpression of CCND1 due to a t(11; 14)(q13; q32) in 2 samples. CONCLUSIONS: Our combination of targeted RNA-sequencing and data analysis workflow can improve the detection of relevant variants, and expression patterns can assist in establishing HM classification.

Detection of Fusion Genes to Determine Minimal Residual Disease in Leukemia Using Next-Generation Sequencing.

BACKGROUND: Measuring minimal residual disease (MRD), the persistence of leukemic cells after treatment, is important for monitoring leukemia recurrence. The current methods for monitoring MRD are flow cytometry, to assess aberrant immune phenotypes, and digital droplet PCR (ddPCR), to target genetic aberrations such as single-nucleotide variants and gene fusions. We present the performance of an RNA-based next-generation sequencing (NGS) method for MRD gene fusion detection compared with ddPCR. This method may have advantages, including the capacity to analyze different genetic aberrations and patients in 1 experiment. In particular, detection at the RNA level may be highly sensitive if the genetic aberration is highly expressed. METHODS: We designed a probe-based NGS panel targeting the breakpoints of 11 fusion genes previously identified in clinical patients and 2 fusion genes present in cell lines. Blocking probes were added to prevent nonspecific enrichment. Each patient RNA sample was diluted in background RNA, depleted for rRNA and globin mRNA, converted to cDNA, and prepared for sequencing. Unique sequence reads, identified by unique molecular identifiers, were aligned directly to reference transcripts. The same patient and cell-line samples were also analyzed with ddPCR for direct comparison. RESULTS: Our NGS method reached a maximum sensitivity of 1 aberrant cell in 10 000 cells and was mostly within a factor of 10 compared with ddPCR. CONCLUSIONS: Our detection limit was below the threshold of 1:1000 recommended by European Leukemia Net. Further optimizations are easy to implement and are expected to boost the sensitivity of our method to diagnostically obtained ddPCR thresholds.

A pipeline-friendly software tool for genome diagnostics to prioritize genes by matching patient symptoms to literature.

Despite an explosive growth of next-generation sequencing data, genome diagnostics only provides a molecular diagnosis to a minority of patients. Software tools that prioritize genes based on patient symptoms using known gene-disease associations may complement variant filtering and interpretation to increase chances of success. However, many of these tools cannot be used in practice because they are embedded within variant prioritization algorithms, or exist as remote services that cannot be relied upon or are unacceptable because of legal/ethical barriers. In addition, many tools are not designed for command-line usage, closed-source, abandoned, or unavailable. We present Variant Interpretation using Biomedical literature Evidence (VIBE), a tool to prioritize disease genes based on Human Phenotype Ontology codes. VIBE is a locally installed executable that ensures operational availability and is built upon DisGeNET-RDF, a comprehensive knowledge platform containing gene-disease associations mostly from literature and variant-disease associations mostly from curated source databases. VIBE's command-line interface and output are designed for easy incorporation into bioinformatic pipelines that annotate and prioritize variants for further clinical interpretation. We evaluate VIBE in a benchmark based on 305 patient cases alongside seven other tools. Our results demonstrate that VIBE offers consistent performance with few cases missed, but we also find high complementarity among all tested tools. VIBE is a powerful, free, open source and locally installable solution for prioritizing genes based on patient symptoms. Project source code, documentation, benchmark and executables are available at https://github.com/molgenis/vibe.

The ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research.

Copy number variations (CNVs) are major causative contributors both in the genesis of genetic diseases and human neoplasias. While "High-Throughput" sequencing technologies are increasingly becoming the primary choice for genomic screening analysis, their ability to efficiently detect CNVs is still heterogeneous and remains to be developed. The aim of this white paper is to provide a guiding framework for the future contributions of ELIXIR's recently established human CNV Community, with implications beyond human disease diagnostics and population genomics. This white paper is the direct result of a strategy meeting that took place in September 2018 in Hinxton (UK) and involved representatives of 11 ELIXIR Nodes. The meeting led to the definition of priority objectives and tasks, to address a wide range of CNV-related challenges ranging from detection and interpretation to sharing and training. Here, we provide suggestions on how to align these tasks within the ELIXIR Platforms strategy, and on how to frame the activities of this new ELIXIR Community in the international context.

A next-generation sequencing method for gene doping detection that distinguishes low levels of plasmid DNA against a background of genomic DNA.

Gene doping confers health risks for athletes and is a threat to fair competition in sports. Therefore the anti-doping community has given attention on its detection. Previously published polymerase chain reaction-based methodologies for gene doping detection are targeting exon-exon junctions in the intron-less transgene. However, because these junctions are known, it would be relatively easy to evade detection by tampering with the copyDNA sequences. We have developed a targeted next-generation sequencing based assay for the detection of all exon-exon junctions of the potential doping genes, EPO, IGF1, IGF2, GH1, and GH2, which is resistant to tampering. Using this assay, all exon-exon junctions of copyDNA of doping genes could be detected with a sensitivity of 1296 copyDNA copies in 1000 ng of genomic DNA. In addition, promotor regions and plasmid-derived sequences are readily detectable in our sequence data. While we show the reliability of our method for a selection of genes, expanding the panel to detect other genes would be straightforward. As we were able to detect plasmid-derived sequences, we expect that genes with manipulated junctions, promotor regions, and plasmid or virus-derived sequences will also be readily detected.

NIPTeR: an R package for fast and accurate trisomy prediction in non-invasive prenatal testing.

BACKGROUND: Various algorithms have been developed to predict fetal trisomies using cell-free DNA in non-invasive prenatal testing (NIPT). As basis for prediction, a control group of non-trisomy samples is needed. Prediction accuracy is dependent on the characteristics of this group and can be improved by reducing variability between samples and by ensuring the control group is representative for the sample analyzed. RESULTS: NIPTeR is an open-source R Package that enables fast NIPT analysis and simple but flexible workflow creation, including variation reduction, trisomy prediction algorithms and quality control. This broad range of functions allows users to account for variability in NIPT data, calculate control group statistics and predict the presence of trisomies. CONCLUSION: NIPTeR supports laboratories processing next-generation sequencing data for NIPT in assessing data quality and determining whether a fetal trisomy is present. NIPTeR is available under the GNU LGPL v3 license and can be freely downloaded from https://github.com/molgenis/NIPTeR or CRAN.

Genetic Screening Test to Detect Translocations in Acute Leukemias by Use of Targeted Locus Amplification.

BACKGROUND: Over 500 translocations have been identified in acute leukemia. To detect them, most diagnostic laboratories use karyotyping, fluorescent in situ hybridization, and reverse transcription PCR. Targeted locus amplification (TLA), a technique using next-generation sequencing, now allows detection of the translocation partner of a specific gene, regardless of its chromosomal origin. We present a TLA multiplex assay as a potential first-tier screening test for detecting translocations in leukemia diagnostics. METHODS: The panel includes 17 genes involved in many translocations present in acute leukemias. Procedures were optimized by using a training set of cell line dilutions and 17 leukemia patient bone marrow samples and validated by using a test set of cell line dilutions and a further 19 patient bone marrow samples. Per gene, we determined if its region was involved in a translocation and, if so, the translocation partner. To balance sensitivity and specificity, we introduced a gray zone showing indeterminate translocation calls needing confirmation. We benchmarked our method against results from the 3 standard diagnostic tests. RESULTS: In patient samples passing QC, we achieved a concordance with benchmarking tests of 81% in the training set and 100% in the test set, after confirmation of 4 and nullification of 3 gray zone calls (in total). In cell line dilutions, we detected translocations in 10% aberrant cells at several genetic loci. CONCLUSIONS: Multiplex TLA shows promising results as an acute leukemia screening test. It can detect cryptic and other translocations in selected genes. Further optimization may make this assay suitable for diagnostic use.

NIPTRIC: an online tool for clinical interpretation of non-invasive prenatal testing (NIPT) results.

To properly interpret the result of a pregnant woman's non-invasive prenatal test (NIPT), her a priori risk must be taken into account in order to obtain her personalised a posteriori risk (PPR), which more accurately expresses her true likelihood of carrying a foetus with trisomy. Our aim was to develop a tool for laboratories and clinicians to calculate easily the PPR for genome-wide NIPT results, using diploid samples as a control group. The tool takes the a priori risk and Z-score into account. Foetal DNA percentage and coefficient of variation can be given default settings, but actual values should be used if known. We tested the tool on 209 samples from pregnant women undergoing NIPT. For Z-scores < 5, the PPR is considerably higher at a high a priori risk than at a low a priori risk, for NIPT results with the same Z-score, foetal DNA percentage and coefficient of variation. However, the PPR is effectively independent under all conditions for Z-scores above 6. A high PPR for low a priori risks can only be reached at Z-scores > 5. Our online tool can assist clinicians in understanding NIPT results and conveying their true clinical implication to pregnant women, because the PPR is crucial for individual counselling and decision-making.

Whole-exome sequencing is a powerful approach for establishing the etiological diagnosis in patients with intellectual disability and microcephaly.

BACKGROUND: Clinical and genetic heterogeneity in monogenetic disorders represents a major diagnostic challenge. Although the presence of particular clinical features may aid in identifying a specific cause in some cases, the majority of patients remain undiagnosed. Here, we investigated the utility of whole-exome sequencing as a diagnostic approach for establishing a molecular diagnosis in a highly heterogeneous group of patients with varied intellectual disability and microcephaly. METHODS: Whole-exome sequencing was performed in 38 patients, including three sib-pairs, in addition to or in parallel with genetic analyses that were performed during the diagnostic work-up of the study participants. RESULTS: In ten out of these 35 families (29 %), we found mutations in genes already known to be related to a disorder in which microcephaly is a main feature. Two unrelated patients had mutations in the ASPM gene. In seven other patients we found mutations in RAB3GAP1, RNASEH2B, KIF11, ERCC8, CASK, DYRK1A and BRCA2. In one of the sib-pairs, mutations were found in the RTTN gene. Mutations were present in seven out of our ten families with an established etiological diagnosis with recessive inheritance. CONCLUSIONS: We demonstrate that whole-exome sequencing is a powerful tool for the diagnostic evaluation of patients with highly heterogeneous neurodevelopmental disorders such as intellectual disability with microcephaly. Our results confirm that autosomal recessive disorders are highly prevalent among patients with microcephaly.

CoNVaDING: Single Exon Variation Detection in Targeted NGS Data.

We have developed a tool for detecting single exon copy-number variations (CNVs) in targeted next-generation sequencing data: CoNVaDING (Copy Number Variation Detection In Next-generation sequencing Gene panels). CoNVaDING includes a stringent quality control (QC) metric, that excludes or flags low-quality exons. Since this QC shows exactly which exons can be reliably analyzed and which exons are in need of an alternative analysis method, CoNVaDING is not only useful for CNV detection in a research setting, but also in clinical diagnostics. During the validation phase, CoNVaDING detected all known CNVs in high-quality targets in 320 samples analyzed, giving 100% sensitivity and 99.998% specificity for 308,574 exons. CoNVaDING outperforms existing tools by exhibiting a higher sensitivity and specificity and by precisely identifying low-quality samples and regions.

Next-generation sequencing-based genome diagnostics across clinical genetics centers: implementation choices and their effects.

Implementation of next-generation DNA sequencing (NGS) technology into routine diagnostic genome care requires strategic choices. Instead of theoretical discussions on the consequences of such choices, we compared NGS-based diagnostic practices in eight clinical genetic centers in the Netherlands, based on genetic testing of nine pre-selected patients with cardiomyopathy. We highlight critical implementation choices, including the specific contributions of laboratory and medical specialists, bioinformaticians and researchers to diagnostic genome care, and how these affect interpretation and reporting of variants. Reported pathogenic mutations were consistent for all but one patient. Of the two centers that were inconsistent in their diagnosis, one reported to have found 'no causal variant', thereby underdiagnosing this patient. The other provided an alternative diagnosis, identifying another variant as causal than the other centers. Ethical and legal analysis showed that informed consent procedures in all centers were generally adequate for diagnostic NGS applications that target a limited set of genes, but not for exome- and genome-based diagnosis. We propose changes to further improve and align these procedures, taking into account the blurring boundary between diagnostics and research, and specific counseling options for exome- and genome-based diagnostics. We conclude that alternative diagnoses may infer a certain level of 'greediness' to come to a positive diagnosis in interpreting sequencing results. Moreover, there is an increasing interdependence of clinic, diagnostics and research departments for comprehensive diagnostic genome care. Therefore, we invite clinical geneticists, physicians, researchers, bioinformatics experts and patients to reconsider their role and position in future diagnostic genome care.

Targeted next-generation sequencing can replace Sanger sequencing in clinical diagnostics.

Mutation detection through exome sequencing allows simultaneous analysis of all coding sequences of genes. However, it cannot yet replace Sanger sequencing (SS) in diagnostics because of incomplete representation and coverage of exons leading to missing clinically relevant mutations. Targeted next-generation sequencing (NGS), in which a selected fraction of genes is sequenced, may circumvent these shortcomings. We aimed to determine whether the sensitivity and specificity of targeted NGS is equal to those of SS. We constructed a targeted enrichment kit that includes 48 genes associated with hereditary cardiomyopathies. In total, 84 individuals with cardiomyopathies were sequenced using 151 bp paired-end reads on an Illumina MiSeq sequencer. The reproducibility was tested by repeating the entire procedure for five patients. The coverage of ≥30 reads per nucleotide, our major quality criterion, was 99% and in total ∼21,000 variants were identified. Confirmation with SS was performed for 168 variants (155 substitutions, 13 indels). All were confirmed, including a deletion of 18 bp and an insertion of 6 bp. The reproducibility was nearly 100%. We demonstrate that targeted NGS of a disease-specific subset of genes is equal to the quality of SS and it can therefore be reliably implemented as a stand-alone diagnostic test.

Successful noninvasive trisomy 18 detection using single molecule sequencing.

BACKGROUND: Noninvasive trisomy 21 detection performed by use of massively parallel sequencing is achievable with high diagnostic sensitivity and low false-positive rates. Detection of fetal trisomy 18 and 13 has been reported as well but seems to be less accurate with the use of this approach. The reduced accuracy can be explained by PCR-introduced guanine-cytosine (GC) bias influencing sequencing data. Previously, we demonstrated that sequence data generated by single molecule sequencing show virtually no GC bias and result in a more pronounced noninvasive detection of fetal trisomy 21. In this study, single molecule sequencing was used for noninvasive detection of trisomy 18 and 13. METHODS: Single molecule sequencing was performed on the Helicos platform with free DNA isolated from maternal plasma from 11 weeks of gestation onward (n = 17). Relative sequence tag density ratios were calculated against male control plasma samples and results were compared to those of previous karyotyping. RESULTS: All trisomy 18 fetuses were identified correctly with a diagnostic sensitivity and specificity of 100%. However, low diagnostic sensitivity and specificity were observed for fetal trisomy 13 detection. CONCLUSIONS: We successfully applied single molecule sequencing in combination with relative sequence tag density calculations for noninvasive trisomy 18 detection using free DNA from maternal plasma. However, noninvasive trisomy 13 detection was not accurate and seemed to be influenced by more than just GC content.