scholarly journals Exome sequencing in patients with antiepileptic drug exposure and complex phenotypes

2019 ◽  
Vol 105 (4) ◽  
pp. 384-389 ◽  
Author(s):  
Adam Jackson ◽  
Heather Ward ◽  
Rebecca Louise Bromley ◽  
Charulata Deshpande ◽  
Pradeep Vasudevan ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Copy Number ◽  
Developmental Disorders ◽  
Drug Exposure ◽  
Genetic Disorders ◽  
Copy Number Variants ◽  
Copy Number Variant ◽  
In Utero ◽  
Developmental Problems ◽  
Number Of Children

IntroductionFetal anticonvulsant syndrome (FACS) describes the pattern of physical and developmental problems seen in those children exposed to certain antiepileptic drugs (AEDs) in utero. The diagnosis of FACS is a clinical one and so excluding alternative diagnoses such as genetic disorders is essential.MethodsWe reviewed the pathogenicity of reported variants identified on exome sequencing in the Deciphering Developmental Disorders (DDD) Study in 42 children exposed to AEDs in utero, but where a diagnosis other than FACS was suspected. In addition, we analysed chromosome microarray data from 10 patients with FACS seen in a Regional Genetics Service.ResultsSeven children (17%) from the DDD Study had a copy number variant or pathogenic variant in a developmental disorder gene which was considered to explain or partially explain their phenotype. Across the AED exposure types, variants were found in 2/15 (13%) valproate exposed cases and 3/14 (21%) carbamazepine exposed cases. No pathogenic copy number variants were identified in our local sample (n=10).ConclusionsThis study is the first of its kind to analyse the exomes of children with developmental disorders who were exposed to AEDs in utero. Though we acknowledge that the results are subject to bias, a significant number of children were identified with alternate diagnoses which had an impact on counselling and management. We suggest that consideration is given to performing whole exome sequencing as part of the diagnostic work-up for children exposed to AEDs in utero.

scholarly journals Copy number variants in clinical WGS: deployment and interpretation for rare and undiagnosed disease

2018 ◽  
Author(s):  
Andrew M Gross ◽  
Subramanian S. Ajay ◽  
Vani Rajan ◽  
Carolyn Brown ◽  
Krista Bluske ◽  
...  
Keyword(s):  
Copy Number ◽  
De Novo ◽  
Genetic Disorders ◽  
Diagnostic Testing ◽  
Copy Number Variants ◽  
Uniparental Disomy ◽  
Copy Number Variant ◽  
Break Point ◽  
Clinically Significant ◽  
Family Based

AbstractPurposeCurrent diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, whole genome sequencing (WGS) has the potential to detect all genomic mutation types on a single platform and workflow. Here we sought to evaluate copy number variant (CNV) calling as part of a clinically accredited WGS test.MethodsUsing a depth-based copy number caller we performed analytical validation of CNV calling on a reference panel of 17 samples, compared the sensitivity of WGS-based variants to those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis, annotation, filtering, visualization of WGS based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases.ResultsWe found that CNV calls from WGS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed. This pipeline also enabled identification of cases of uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of some CNVs enabled break-point level resolution of genomic rearrangements and phasing of de-novo CNVs.ConclusionRobust identification of CNVs by WGS is possible within a clinical testing environment, and further developments will bring improvements in resolution of smaller and more complex CNVs.

scholarly journals Detection of clinically relevant copy-number variants by exome sequencing in a large cohort of genetic disorders

2016 ◽  
Vol 19 (6) ◽  
pp. 667-675 ◽  
Author(s):  
Rolph Pfundt ◽  
Marisol del Rosario ◽  
Lisenka E.L.M. Vissers ◽  
Michael P. Kwint ◽  
Irene M. Janssen ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Copy Number ◽  
Genetic Disorders ◽  
Copy Number Variants ◽  
Large Cohort

scholarly journals Detection and characterization of copy number variants based on whole-genome sequencing by DNBSEQ platforms

2019 ◽  
Author(s):  
Junhua Rao ◽  
Lihua Peng ◽  
Fang Chen ◽  
Hui Jiang ◽  
Chunyu Geng ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Copy Number Variant ◽  
Whole Genome ◽  
Genome Wide ◽  
Wide Range ◽  
Distribution Sensitivity ◽  
Cnv Detection

AbstractBackgroundNext-generation sequence (NGS) has rapidly developed in past years which makes whole-genome sequencing (WGS) becoming a more cost- and time-efficient choice in wide range of biological researches. We usually focus on some variant detection via WGS data, such as detection of single nucleotide polymorphism (SNP), insertion and deletion (Indel) and copy number variant (CNV), which playing an important role in many human diseases. However, the feasibility of CNV detection based on WGS by DNBSEQ™ platforms was unclear. We systematically analysed the genome-wide CNV detection power of DNBSEQ™ platforms and Illumina platforms on NA12878 with five commonly used tools, respectively.ResultsDNBSEQ™ platforms showed stable ability to detect slighter more CNVs on genome-wide (average 1.24-fold than Illumina platforms). Then, CNVs based on DNBSEQ™ platforms and Illumina platforms were evaluated with two public benchmarks of NA12878, respectively. DNBSEQ™ and Illumina platforms showed similar sensitivities and precisions on both two benchmarks. Further, the difference between tools for CNV detection was analyzed, and indicated the selection of tool for CNV detection could affected the CNV performance, such as count, distribution, sensitivity and precision.ConclusionThe major contribution of this paper is providing a comprehensive guide for CNV detection based on WGS by DNBSEQ™ platforms for the first time.

scholarly journals HandyCNV: Standardized Summary, Annotation, Comparison, and Visualization of Copy Number Variant, Copy Number Variation Region, and Runs of Homozygosity

2021 ◽  
Vol 12 ◽  
Author(s):  
Jinghang Zhou ◽  
Liyuan Liu ◽  
Thomas J. Lopdell ◽  
Dorian J. Garrick ◽  
Yuangang Shi
Keyword(s):  
Copy Number ◽  
Copy Number Variants ◽  
Copy Number Variant ◽  
R Package ◽  
Copy Number Variation Region ◽  
Runs Of Homozygosity ◽  
Number Variation ◽  
Genomic Studies ◽  
Computing Platforms ◽  
Analysis System

Detection of CNVs (copy number variants) and ROH (runs of homozygosity) from SNP (single nucleotide polymorphism) genotyping data is often required in genomic studies. The post-analysis of CNV and ROH generally involves many steps, potentially across multiple computing platforms, which requires the researchers to be familiar with many different tools. In order to get around this problem and improve research efficiency, we present an R package that integrates the summarization, annotation, map conversion, comparison and visualization functions involved in studies of CNV and ROH. This one-stop post-analysis system is standardized, comprehensive, reproducible, timesaving, and user-friendly for researchers in humans and most diploid livestock species.

scholarly journals Copy number variant detection with low-coverage whole-genome sequencing is a viable replacement for the traditional array-CGH

2020 ◽  
Author(s):  
Marcel Kucharik ◽  
Jaroslav Budis ◽  
Michaela Hyblova ◽  
Gabriel Minarik ◽  
Tomas Szemes
Keyword(s):  
In Silico ◽  
Copy Number ◽  
Normal Population ◽  
Genetic Disorders ◽  
Prenatal Testing ◽  
In Silico Analysis ◽  
Copy Number Variant ◽  
Detection Algorithm ◽  
Copy Number Variations ◽  
Cnv Detection

Copy number variations (CNVs) are a type of structural variant involving alterations in the number of copies of specific regions of DNA, which can either be deleted or duplicated. CNVs contribute substantially to normal population variability; however, abnormal CNVs cause numerous genetic disorders. Nowadays, several methods for CNV detection are used, from the conventional cytogenetic analysis through microarray-based methods (aCGH) to next-generation sequencing (NGS). We present GenomeScreen - NGS based CNV detection method based on a previously described CNV detection algorithm used for non-invasive prenatal testing (NIPT). We determined theoretical limits of its accuracy and confirmed it with extensive in-silico study and already genotyped samples. Theoretically, at least 6M uniquely mapped reads are required to detect CNV with a length of 100 kilobases (kb) or more with high confidence (Z-score > 7). In practice, the in-silico analysis showed the requirement at least 8M to obtain >99% accuracy (for 100 kb deviations). We compared GenomeScreen with one of the currently used aCGH methods in diagnostic laboratories, which has a 200 kb mean resolution. GenomeScreen and aCGH both detected 59 deviations, GenomeScreen furthermore detected 134 other (usually) smaller variations. Furthermore, the overall cost per sample is about 2-3x lower in the case of GenomeScreen.

scholarly journals The prenatal diagnosis and clinical outcomes of fetuses with 15q11.2 copy number variants: a case series of 36 patients

2021 ◽  
Author(s):  
Jessica Kang ◽  
Chien Nan Lee ◽  
Yi-Ning Su ◽  
Ming-Wei Lin ◽  
Yi-Yun Tai ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Developmental Delay ◽  
Copy Number ◽  
De Novo ◽  
Copy Number Variants ◽  
Case Series ◽  
Copy Number Variant ◽  
University Hospital ◽  
Limited Information ◽  
Ultrasound Findings

Objective: The prenatal genetic counseling of fetus diagnosed with the 15q11.2 copy number variant (CNV) involving the BP1-BP2 region has been difficult due to limited information and controversial opinion on prognosis. Design: Case series. Setting: This study uses data from National Taiwan University Hospital. Sample: Data of 36 pregnant women who underwent prenatal microarray analysis from 2012 to 2017 and were assessed at National Taiwan University Hospital. Methods: Data were collected by reviewing patients’ medical record. Comparison of patient characteristics, prenatal ultrasound findings and postnatal outcomes between different cases involving the 15q11.2 BP1-BP2 region were presented. Main outcome measured: Postnatal prognosis. Results: Out of the 36 patients diagnosed with CNVs involving the BP1-BP2 region, 5 were diagnosed with microduplication and 31 with microdeletion. Abnormal ultrasound findings were recorded in 12 cases prenatally. De novo microduplications were observed in 25% of the cases and microdeletions were found in 14%. Amongst the cases, 10 pregnant women received termination of pregnancy and 26 gave birth to healthy individuals (27 babies in total). Conclusion: The prognoses of 15q11.2 CNVs were controversial and recent studies have revealed its connection with developmental delay and autism. In our study, no obvious developmental delay or neurological disorders were detected postnatally in the 1 case of 15q11.2 microduplication and 25 cases of microdeletion.

scholarly journals RefCNV: Identification of Gene-Based Copy Number Variants Using Whole Exome Sequencing

2016 ◽  
Vol 15 ◽  
pp. CIN.S36612 ◽  
Author(s):  
Lun-Ching Chang ◽  
Biswajit Das ◽  
Chih-Jian Lih ◽  
Han Si ◽  
Corinne E. Camalier ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Estimation Methods ◽  
Single Nucleotide Variants ◽  
False Positive Error ◽  
Reference Set ◽  
Genome Wide ◽  
Whole Exome

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.

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