We present Gene-Aware Variant INterpretation (GAVIN), a new method that accurately classifies variants for clinical diagnostic purposes. Classifications are based on gene-specific calibrations of allele frequencies from the ExAC database, likely variant impact using SnpEff, and estimated deleteriousness based on CADD scores for >3000 genes. In a benchmark on 18 clinical gene sets, we achieve a sensitivity of 91.4% and a specificity of 76.9%. This accuracy is unmatched by 12 other tools. We provide GAVIN as an online MOLGENIS service to annotate VCF files and as an open source executable for use in bioinformatic pipelines. It can be found at http://molgenis.org/gavin .

Non-invasive prenatal testing (NIPT) of cell-free DNA in maternal plasma, which is a mixture of maternal DNA and a low percentage of fetal DNA, can detect fetal aneuploidies using massively parallel sequencing. Because of the low percentage of fetal DNA, methods with high sensitivity and precision are required. However, sequencing variation lowers sensitivity and hampers detection of trisomy samples. Therefore, we have developed three algorithms to improve sensitivity and specificity: the chi-squared-based variation reduction (χ²VR), the regression-based Z-score (RBZ) and the Match QC score. The χ²VR reduces variability in sequence read counts per chromosome between samples, the RBZ allows for more precise trisomy prediction, and the Match QC score shows if the control group used is representative for a specific sample. We compared the performance of χ²VR to that of existing variation reduction algorithms (peak and GC correction) and that of RBZ to trisomy prediction algorithms (standard Z-score, normalized chromosome value and median-absolute-deviation-based Z-score). χ²VR and the RBZ both reduce variability more than existing methods, and thereby increase the sensitivity of the NIPT analysis. We found the optimal combination of algorithms was to use both GC correction and χ²VR for pre-processing and to use RBZ as the trisomy prediction method.

In this study, we compare next-generation sequencing (NGS) approaches (targeted panel (tNGS), whole exome sequencing (WES), and whole genome sequencing (WGS)) for application in newborn screening (NBS). DNA was extracted from dried blood spots (DBS) from 50 patients with genetically confirmed inherited metabolic disorders (IMDs) and 50 control samples. One hundred IMD-related genes were analyzed. Two data-filtering strategies were applied: one to detect only (likely) pathogenic ((L)P) variants, and one to detect (L)P variants in combination with variants of unknown significance (VUS). The variants were filtered and interpreted, defining true/false positives (TP/FP) and true/false negatives (TN/FN). The variant filtering strategies were assessed in a background cohort (BC) of 4833 individuals. Reliable results were obtained within 5 days. TP results (47 patient samples) for tNGS, WES, and WGS results were 33, 31, and 30, respectively, using the (L)P filtering, and 40, 40, and 38, respectively, when including VUS. FN results were 11, 13, and 14, respectively, excluding VUS, and 4, 4, and 6, when including VUS. The remaining FN were mainly samples with a homozygous VUS. All controls were TN. Three BC individuals showed a homozygous (L)P variant, all related to a variable, mild phenotype. The use of NGS-based workflows in NBS seems promising, although more knowledge of data handling, automated variant interpretation, and costs is needed before implementation.

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. 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. 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.

Inherited neurological disorders, such as spinocerebellar ataxia (SCA) and fragile X (FraX), are frequently caused by short tandem repeat (STR) expansions. The detection and assessment of STRs is important for diagnostics and prognosis. We tested the abilities of nanopore long-read sequencing (LRS) using a custom panel including the nine most common SCA-related genes and FraX and created raw data to report workflow. Using known STR lengths for 23 loci in 12 patients, a pipeline was validated to detect and report STR lengths. In addition, we assessed the capability to detect SNVs, indels, and the methylation status in the same test. For the 23 loci, 22 were concordant with known STR lengths, while for the last, one of three replicates differed, indicating an artefact. All positive control STRs were detected as likely pathogenic, with no additional findings after a visual assessment of repeat motifs. Out of 226 SNV and Indel variants, two were false positive and one false negative (accuracy 98.7%). In all FMR1 controls, a methylation status could be determined. In conclusion, LRS is suitable as a diagnostic workflow for STR analysis in neurological disorders and can be generalized to other diseases. The addition of SNV/Indel and methylation detection promises to allow for a one-test-fits-all workflow.

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.