ABSTRACT
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.
A NGS stand‐alone diagnostic test for hereditary cardio‐myopathies. Parallel analyses of 48 genes on a MiSeq identified ∼21,000 variants in 84 patients. The sensitivity and specificity of this test equals Sanger Sequencing. In total 168 variants were confirmed, no false‐positives or false‐negatives were detected.
ABSTRACT
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.
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 metric, that excludes or flags low quality exons. Since this quality control shows exactly which exons can be reliably analysed and which exons are in need of an alternative analysis method, CoNVaDING is also useful for CNV detection in clinical diagnostics.
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.
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 .
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.
Recently, an intronic biallelic (AAGGG)
n
repeat expansion in
RFC1
was shown to be a cause of CANVAS and adult-onset ataxia in multiple populations. As the prevalence of the
RFC1
repeat expansion in ...Dutch cases was unknown, we retrospectively tested 9 putative CANVAS cases and two independent cohorts (A and B) of 395 and 222 adult-onset ataxia cases, respectively, using the previously published protocol and, for the first time optical genome mapping to determine the size of the expanded
RFC1
repeat. We identified the biallelic (AAGGG)
n
repeat expansion in 5/9 (55%) putative CANVAS patients and in 10/617 (1.6%; cohorts A + B) adult-onset ataxia patients. In addition to the AAGGG repeat motif, we observed a putative GAAGG repeat motif in the repeat expansion with unknown significance in two adult-onset ataxia patients. All the expanded (AAGGG)
n
repeats identified were in the range of 800–1299 repeat units. The intronic biallelic
RFC1
repeat expansion thus explains a number of the Dutch adult-onset ataxia cases that display the main clinical features of CANVAS, and particularly when ataxia is combined with neuropathy. The yield of screening for
RFC1
expansions in unselected cohorts is relatively low. To increase the current diagnostic yield in ataxia patients, we suggest adding
RFC1
screening to the genetic diagnostic workflow by using advanced techniques that attain long fragments.
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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
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.
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.
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).
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.
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.
The spinocerebellar ataxias (SCAs) are a genetically heterogeneous group of neurodegenerative disorders generally caused by single nucleotide variants (SNVs) or indels in coding regions or by repeat ...expansions in coding and noncoding regions of SCA genes. Copy number variants (CNVs) have now also been reported for 3 genes-
,
, and
-but not all SCA genes have been screened for CNVs as the underlying cause of the disease in patients. In this study, we aim to assess the prevalence of CNVs encompassing 36 known SCA genes.
A cohort of patients with cerebellar ataxia who were referred to the University Medical Center Groningen for SCA genetic diagnostics was selected for this study. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed using the Infinium Global Screening Array. Following data processing, genotyping data were uploaded into NxClinical software to perform CNV analysis per patient and to visualize identified CNVs in 36 genes with allocated SCA symbols. The clinical relevance of detected CNVs was determined using evidence from studies based on PubMed literature searches for similar CNVs and phenotypic features.
Of the 338 patients with cerebellar ataxia, we identified putative clinically relevant CNV deletions in 3 patients: an identical deletion encompassing
in 2 patients, who turned out to be related, and a deletion involving
in another patient. Although the CNV deletion in
was clearly the underlying cause of SCA15 in the 2 related patients, the clinical significance of the deletion in
remained unknown.
We showed that CNVs detectable with the limited resolution of SNP array are a very rare cause of SCA. Nevertheless, we suggest adding CNV analysis alongside SNV analysis to SCA gene diagnostics using next-generation sequencing approaches, at least for
, to improve the genetic diagnostics for patients.
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