scholarly journals Multisite verification of the accuracy of a multi-gene next generation sequencing panel for detection of mutations and copy number alterations in solid tumours

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258188
Author(s):  
John Bartlett ◽  
Yutaka Amemiya ◽  
Heleen Arts ◽  
Jane Bayani ◽  
Barry Eng ◽  
...  

Molecular variants including single nucleotide variants (SNVs), copy number variants (CNVs) and fusions can be detected in the clinical setting using deep targeted sequencing. These assays support low limits of detection using little genomic input material. They are gaining in popularity in clinical laboratories, where sample volumes are limited, and low variant allele fractions may be present. However, data on reproducibility between laboratories is limited. Using a ring study, we evaluated the performance of 7 Ontario laboratories using targeted sequencing panels. All laboratories analysed a series of control and clinical samples for SNVs/CNVs and gene fusions. High concordance was observed across laboratories for measured CNVs and SNVs. Over 97% of SNV calls in clinical samples were detected by all laboratories. Whilst only a single CNV was detected in the clinical samples tested, all laboratories were able to reproducibly report both the variant and copy number. Concordance for information derived from RNA was lower than observed for DNA, due largely to decreased quality metrics associated with the RNA components of the assay, suggesting that the RNA portions of comprehensive NGS assays may be more vulnerable to variations in approach and workflow. Overall the results of this study support the use of the OFA for targeted sequencing for testing of clinical samples and suggest specific internal quality metrics that can be reliable indicators of assay failure. While we believe this evidence can be interpreted to support deep targeted sequencing in general, additional studies should be performed to confirm this.

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Leandro de Araújo Lima ◽  
Ana Cecília Feio-dos-Santos ◽  
Sintia Iole Belangero ◽  
Ary Gadelha ◽  
Rodrigo Affonseca Bressan ◽  
...  

Abstract Many studies have attempted to investigate the genetic susceptibility of Attention-Deficit/Hyperactivity Disorder (ADHD), but without much success. The present study aimed to analyze both single-nucleotide and copy-number variants contributing to the genetic architecture of ADHD. We generated exome data from 30 Brazilian trios with sporadic ADHD. We also analyzed a Brazilian sample of 503 children/adolescent controls from a High Risk Cohort Study for the Development of Childhood Psychiatric Disorders, and also previously published results of five CNV studies and one GWAS meta-analysis of ADHD involving children/adolescents. The results from the Brazilian trios showed that cases with de novo SNVs tend not to have de novo CNVs and vice-versa. Although the sample size is small, we could also see that various comorbidities are more frequent in cases with only inherited variants. Moreover, using only genes expressed in brain, we constructed two “in silico” protein-protein interaction networks, one with genes from any analysis, and other with genes with hits in two analyses. Topological and functional analyses of genes in this network uncovered genes related to synapse, cell adhesion, glutamatergic and serotoninergic pathways, both confirming findings of previous studies and capturing new genes and genetic variants in these pathways.


ESC CardioMed ◽  
2018 ◽  
pp. 669-671
Author(s):  
Eric Schulze-Bahr

The human genome consists of approximately 3 billion (3 × 109) base pairs of DNA (around 20,000 genes), organized as 23 chromosomes (diploid parental set), and a small mitochondrial genome (37 genes, including 13 proteins; 16,589 base pairs) of maternal origin. Most human genetic variation is natural, that is, common or rare (minor allele frequency >0.1%) and does not cause disease—apart from every true disease-causing (bona fide) mutation each individual genome harbours more than 3.5 million single nucleotide variants (including >10,000 non-synonymous changes causing amino acid substitutions) and 200–300 large structural or copy number variants (insertions/deletions, up to several thousands of base-pairs) that are non-disease-causing variations and scattered throughout coding and non-coding genomic regions.


2016 ◽  
Vol 15 ◽  
pp. CIN.S36612 ◽  
Author(s):  
Lun-Ching Chang ◽  
Biswajit Das ◽  
Chih-Jian Lih ◽  
Han Si ◽  
Corinne E. Camalier ◽  
...  

With rapid advances in DNA sequencing technologies, whole exome sequencing (WES) has become a popular approach for detecting somatic mutations in oncology studies. The initial intent of WES was to characterize single nucleotide variants, but it was observed that the number of sequencing reads that mapped to a genomic region correlated with the DNA copy number variants (CNVs). We propose a method RefCNV that uses a reference set to estimate the distribution of the coverage for each exon. The construction of the reference set includes an evaluation of the sources of variability in the coverage distribution. We observed that the processing steps had an impact on the coverage distribution. For each exon, we compared the observed coverage with the expected normal coverage. Thresholds for determining CNVs were selected to control the false-positive error rate. RefCNV prediction correlated significantly ( r = 0.96–0.86) with CNV measured by digital polymerase chain reaction for MET (7q31), EGFR (7p12), or ERBB2 (17q12) in 13 tumor cell lines. The genome-wide CNV analysis showed a good overall correlation (Spearman's coefficient = 0.82) between RefCNV estimation and publicly available CNV data in Cancer Cell Line Encyclopedia. RefCNV also showed better performance than three other CNV estimation methods in genome-wide CNV analysis.


Author(s):  
Alexander Charney ◽  
Pamela Sklar

Schizophrenia and bipolar disorder are the classic psychotic disorders. Both diseases are strongly familial, but have proven recalcitrant to genetic methodologies for identifying the etiology until recently. There is now convincing genetic evidence that indicates a contribution of many DNA changes to the risk of becoming ill. For schizophrenia, there are large contributions of rare copy number variants and common single nucleotide variants, with an overall highly polygenic genetic architecture. For bipolar disorder, the role of copy number variation appears to be much less pronounced. Specific common single nucleotide polymorphisms are associated, and there is evidence for polygenicity. Several surprises have emerged from the genetic data that indicate there is significantly more molecular overlap in copy number variants between autism and schizophrenia, and in common variants between schizophrenia and bipolar disorder.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4207-4207
Author(s):  
Brian S White ◽  
Irena Lanc ◽  
Daniel Auclair ◽  
Robert Fulton ◽  
Mark A Fiala ◽  
...  

Abstract Background: Multiple myeloma (MM) is a hematologic cancer characterized by a diversity of genetic lesions-translocations, copy number alterations (CNAs), and single nucleotide variants (SNVs). The prognostic value of translocations and of CNAs has been well established. Determining the clinical significance of SNVs, which are recurrently mutated at much lower frequencies, and how this significance is impacted by translocations and CNAs requires additional, large-scale correlative studies. Such studies can be facilitated by cost-effective targeted sequencing approaches. Hence, we designed a single-platform targeted sequencing approach capable of detecting all three variant types. Methods: We designed oligonucleotide probes complementary to the coding regions of 467 genes and to the IgH and MYC loci, allowing a probe to closely match at most 5 regions within the genome. Genes were selected if they were expressed in an independent RNA-seq MM data set and harbored germline SNP-filtered variants that: (1) occurred with frequency >3%, (2) were clustered in hotspots, (3) occurred in recurrently mutated "cancer genes" (as annotated in COSMIC or MutSig), or (4) occurred in genes involved in DNA repair and/or B-cell biology. IgH and MYC tiling was unbiased (with respect to annotated features within the loci) and spanned from 50 kilobasepairs (kbps) upstream of both regions to 50 kbps downstream of IgH and 100 kbps downstream of MYC. Results: We performed targeted sequencing of 96 CD138-enriched samples derived from MM patients, as well as matched peripheral blood leukocyte normal controls. Sequencing depth (mean 107X) was commensurate with that of available exome sequencing data from these samples (mean 71X). Samples harbored a mean of 25 non-silent variants, including those in known MM-associated genes: NRAS (24%), KRAS (22%), FAM46C (17%), TP53 (10%), DIS3 (8%), and BRAF (3%). Variants detected by both platforms showed a strong correlation (r^2 = 0.8). The capture array detected activating, oncogenic variants in NRAS Q61K (n=3 patients) and KRAS G12C/D/R/V (n=5) that were not detected in exome data. Additionally, we found non-silent, capture-specific variants in MTOR (3%) and in two transcription-related genes that have been previously implicated in cancer: ZFHX4 (5%) and CHD3 (5%). To assess the potential role of deep subclonal variants and our ability to detect them, we performed additional sequencing (mean 565X) on six of the tumor/normal pairs. This revealed 14 manually-reviewed, non-silent variants that were not detected by the initial targeted sequencing. These had a mean variant allele frequency of 2.8% and included mutations in DNMT3A and FAM46C. At least one of these 14 variants occurred in five of the six re-sequenced samples. This highlights the importance of this additional depth, which will be used in future studies. Our approach successfully detected CNAs near expected frequencies, including hyperdiploidy (52%), del(13) (43%), and gain of 1q (35%). Similarly, it inferred IgH translocations at expected frequencies: t(4;14) (14%), t(6;14) (3%), t(11;14) (15%), and t(14;20) (1%). As expected, translocations occur predominantly within the IgH constant region, but also frequently 5' (i.e., telomeric) of the IGHM switch region, and occasionally within the V and D regions. We detected MYC -associated translocations, whose frequencies have been the subject of debate, at 10% (n=9 patients), with five involving IgH, three having both partners in or near MYC, and one having both types. Finally, our platform detected novel IgH translocations with partners near DERL3 (n=2), MYCN (n=1), and FLT3 (n=1). Additional evidence suggests that DERL3 and MYCN may be targets of IgH-induced overexpression: of 84 RNA-seq patient samples, six exhibited outlying expression of DERL3, including one sample in which we detected the translocation in corresponding DNA, and one exhibited outlying expression of MYCN. Conclusion: Our MM-specific targeted sequencing strategy is capable of detecting deeply subclonal SNVs, in addition to CNAs and IgH and MYC translocations. Though additional validation is required, particularly with respect to translocation detection, we anticipate that such technology will soon enable clinical testing on a single sequencing platform. Disclosures Vij: Celgene, Onyx, Takeda, Novartis, BMS, Sanofi, Janssen, Merck: Consultancy; Takeda, Onyx: Research Funding.


2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16054-e16054
Author(s):  
Xingwei Zhang ◽  
Yonghua Cai ◽  
Yujie Hou ◽  
Huanxin Hu ◽  
Yaoxu Chen ◽  
...  

e16054 Background: Several studies have displayed a sustained clinical response to immune checkpoint inhibitors with profound clinical improvement in patients with microsatellite instability-high (MSI-H) metastatic colorectal cancer (CRC). MSI-H tumors may display higher numbers of TILs, many of which can be directed against tumor-related neoantigens. We set out to examine the underline mechanism in gene level to further explain the differences between MSI-H and MSS CRC. Methods: Whole exome sequencing(WES) was performed on 68 CRC patient.MSI status of these patients were determined using a targeted next generation sequencing panel covering 100 MSI loci. TCGA database was used to analyze WES data of 364 CRC patients with different MSI states, and immune signature was used to analyze the corresponding relationship of immune cell expression in different populations. Results: Of 56 MSS patients, 58.9% (33/56) had copy number variants (CNV) in DIDO1, and 1.8 (1/56) had single nucleotide variants(SNV) in DIDO1. Of 12 MSI-H patients, 33.3% (4/12) had SNV in DIDO1 gene, None had CNV in DIDO1. TCGA database showed that of 308 MSS patients, 8% (24/308) had CNV in DIDO1 and 3% (9/308) had SNV in DIDO1. Of 56 MSI-H patient, 39% (22/56) had SNV in DIDO1 and only one patent had both SNV and CNV in DIDO1. Gene variation of DIDO1 of 68 CRC patients showed a correlation with TCGA database. Gene variation of DIDO1 in MSI-H patients are mainly SNV, and the incidence of CNV is very small (4.3% of DIDO variation).While, gene variation of DIDO1 in MSS patients are mainly CNV, followed by SNV, indicating DIDO1 CNV are highly possible occurring in MSS patients. Furthermore we analyzed the relationship between the copy number of DIDO1 and immune signature through CRC TCGA database. The results showed increase of DIDO1 copy number was negatively correlated with the abundance of NK cells (P = 0.00048), T cells (P = 8.23×10-5) and macrophages (P = 1.75×10-8). Conclusions: Our results showed that different MSI status display unique patent of DIDO1 gene variation, which may be related to different immune micro environment among MSI-H/MSS patients.


2018 ◽  
Author(s):  
Whitney Whitford ◽  
Klaus Lehnert ◽  
Russell G. Snell ◽  
Jessie C. Jacobsen

AbstractBackgroundThe popularisation and decreased cost of genome resequencing has resulted in an increased use in molecular diagnostics. While there are a number of established and high quality bioinfomatic tools for identifying small genetic variants including single nucleotide variants and indels, currently there is no established standard for the detection of copy number variants (CNVs) from sequence data. The requirement for CNV detection from high throughput sequencing has resulted in the development of a large number of software packages. These tools typically utilise the sequence data characteristics: read depth, split reads, read pairs, and assembly-based techniques. However the additional source of information from read balance, defined as relative proportion of reads of each allele at each position, has been underutilised in the existing applications.ResultsWe present Read Balance Validator (RBV), a bioinformatic tool which uses read balance for prioritisation and validation of putative CNVs. The software simultaneously interrogates nominated regions for the presence of deletions or multiplications, and can differentiate larger CNVs from diploid regions. Additionally, the utility of RBV to test for inheritance of CNVs is demonstrated in this report.ConclusionsRBV is a CNV validation and prioritisation bioinformatic tool for both genome and exome sequencing available as a python package from https://github.com/whitneywhitford/RBV


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