scholarly journals Novel approach for CES1 genotyping: integrating single nucleotide variants and structural variation

2018 ◽  
Vol 19 (4) ◽  
pp. 349-359 ◽  
Author(s):  
Ditte Bjerre ◽  
Henrik Berg Rasmussen ◽  
The INDICES Consortium
Genes ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 1076
Author(s):  
Victor Jaravine ◽  
James Balmford ◽  
Patrick Metzger ◽  
Melanie Boerries ◽  
Harald Binder ◽  
...  

A novel approach is developed to address the challenge of annotating with phenotypic effects those exome variants for which relevant empirical data are lacking or minimal. The predictive annotation method is implemented as a stacked ensemble of supervised base-learners, including distributed random forest and gradient boosting machines. Ensemble models were trained and cross-validated on evidence-based categorical variant effect annotations from the ClinVar database, and were applied to 84 million non-synonymous single nucleotide variants (SNVs). The consensus model combined 39 functional mutation impacts, cross-species conservation score, and gene indispensability score. The indispensability score, accounting for differences in variant pathogenicities including in essential and mutation-tolerant genes, considerably improved the predictions. The consensus combination is consistent with as many input scores as possible while minimizing false predictions. The input scores are ranked based on their ability to predict effects. The score rankings and categorical phenotypic variant effect predictions are aimed for direct use in clinical and biological applications to prioritize human exome variants and mutations.


2019 ◽  
Author(s):  
Gonzalo Lopez ◽  
Karina L. Conkrite ◽  
Miriam Doepner ◽  
Komal S. Rathi ◽  
Apexa Modi ◽  
...  

ABSTRACTNeuroblastoma is a malignancy of the developing sympathetic nervous system that accounts for 12% of childhood cancer deaths. Like many childhood cancers, neuroblastoma exhibits a relative paucity of somatic single nucleotide variants (SNVs) and small insertions and deletions (indels) compared to adult cancers. Here, we assessed the contribution of somatic structural variation (SV) in neuroblastoma using a combination of whole genome sequencing (WGS; n=135) and single nucleotide polymorphism (SNP) genotyping (n=914) of matched tumor-normal pairs. Our study design allowed for orthogonal validation and replication across platforms. SV frequency, type, and localization varied significantly among high-risk tumors. MYCN non-amplified high-risk tumors harbored an increased SV burden overall, including a substantial excess of tandem-duplication events across the genome. Genes disrupted by SV breakpoints were enriched in neuronal lineages and autism spectrum disorder (ASD). The postsynaptic adapter protein-coding gene SHANK2, located on chromosome 11q13, was disrupted by SVs in 14% of MYCN non-amplified high-risk tumors based on WGS and 10% in the SNP array cohort. Expression of SHANK2 was low across human-derived neuroblastoma cell lines and high-risk neuroblastoma tumors. Forced expression of SHANK2 in neuroblastoma cell models resulted in significant growth inhibition (P=2.62×10-2 to 3.4×10-5) and accelerated neuronal differentiation following treatment with all-trans retinoic acid (P=3.08×10-13 to 2.38×10-30). These data further define the complex landscape of structural variation in neuroblastoma and suggest that events leading to deregulation of neurodevelopmental processes, such as inactivation of SHANK2, are key mediators of tumorigenesis in this childhood cancer.


Author(s):  
Renata Parissi Buainain ◽  
Matheus Negri Boschiero ◽  
Bruno Camporeze ◽  
Paulo Henrique Pires de Aguiar ◽  
Fernando Augusto Lima Marson ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
pp. 33
Author(s):  
Nayoung Han ◽  
Jung Mi Oh ◽  
In-Wha Kim

For predicting phenotypes and executing precision medicine, combination analysis of single nucleotide variants (SNVs) genotyping with copy number variations (CNVs) is required. The aim of this study was to discover SNVs or common copy CNVs and examine the combined frequencies of SNVs and CNVs in pharmacogenes using the Korean genome and epidemiology study (KoGES), a consortium project. The genotypes (N = 72,299) and CNV data (N = 1000) were provided by the Korean National Institute of Health, Korea Centers for Disease Control and Prevention. The allele frequencies of SNVs, CNVs, and combined SNVs with CNVs were calculated and haplotype analysis was performed. CYP2D6 rs1065852 (c.100C>T, p.P34S) was the most common variant allele (48.23%). A total of 8454 haplotype blocks in 18 pharmacogenes were estimated. DMD ranked the highest in frequency for gene gain (64.52%), while TPMT ranked the highest in frequency for gene loss (51.80%). Copy number gain of CYP4F2 was observed in 22 subjects; 13 of those subjects were carriers with CYP4F2*3 gain. In the case of TPMT, approximately one-half of the participants (N = 308) had loss of the TPMT*1*1 diplotype. The frequencies of SNVs and CNVs in pharmacogenes were determined using the Korean cohort-based genome-wide association study.


Author(s):  
Pauline Arnaud ◽  
Hélène Morel ◽  
Olivier Milleron ◽  
Laurent Gouya ◽  
Christine Francannet ◽  
...  

Abstract Purpose Individuals with mosaic pathogenic variants in the FBN1 gene are mainly described in the course of familial screening. In the literature, almost all these mosaic individuals are asymptomatic. In this study, we report the experience of our team on more than 5,000 Marfan syndrome (MFS) probands. Methods Next-generation sequencing (NGS) capture technology allowed us to identify five cases of MFS probands who harbored a mosaic pathogenic variant in the FBN1 gene. Results These five sporadic mosaic probands displayed classical features usually seen in Marfan syndrome. Combined with the results of the literature, these rare findings concerned both single-nucleotide variants and copy-number variations. Conclusion This underestimated finding should not be overlooked in the molecular diagnosis of MFS patients and warrants an adaptation of the parameters used in bioinformatics analyses. The five present cases of symptomatic MFS probands harboring a mosaic FBN1 pathogenic variant reinforce the fact that apparently asymptomatic mosaic parents should have a complete clinical examination and a regular cardiovascular follow-up. We advise that individuals with a typical MFS for whom no single-nucleotide pathogenic variant or exon deletion/duplication was identified should be tested by NGS capture panel with an adapted variant calling analysis.


2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Fatao Liu ◽  
Yongsheng Li ◽  
Dongjian Ying ◽  
Shimei Qiu ◽  
Yong He ◽  
...  

AbstractNeuroendocrine carcinoma (NEC) of the gallbladder (GB-NEC) is a rare but extremely malignant subtype of gallbladder cancer (GBC). The genetic and molecular signatures of GB-NEC are poorly understood; thus, molecular targeting is currently unavailable. In the present study, we applied whole-exome sequencing (WES) technology to detect gene mutations and predicted somatic single-nucleotide variants (SNVs) in 15 cases of GB-NEC and 22 cases of general GBC. In 15 GB-NECs, the C > T mutation was predominant among the 6 types of SNVs. TP53 showed the highest mutation frequency (73%, 11/15). Compared with neuroendocrine carcinomas of other organs, significantly mutated genes (SMGs) in GB-NECs were more similar to those in pulmonary large-cell neuroendocrine carcinomas (LCNECs), with driver roles for TP53 and RB1. In the COSMIC database of cancer-related genes, 211 genes were mutated. Strikingly, RB1 (4/15, 27%) and NAB2 (3/15, 20%) mutations were found specifically in GB-NECs; in contrast, mutations in 29 genes, including ERBB2 and ERBB3, were identified exclusively in GBC. Mutations in RB1 and NAB2 were significantly related to downregulation of the RB1 and NAB2 proteins, respectively, according to immunohistochemical (IHC) data (p values = 0.0453 and 0.0303). Clinically actionable genes indicated 23 mutated genes, including ALK, BRCA1, and BRCA2. In addition, potential somatic SNVs predicted by ISOWN and SomVarIUS constituted 6 primary COSMIC mutation signatures (1, 3, 30, 6, 7, and 13) in GB-NEC. Genes carrying somatic SNVs were enriched mainly in oncogenic signaling pathways involving the Notch, WNT, Hippo, and RTK-RAS pathways. In summary, we have systematically identified the mutation landscape of GB-NEC, and these findings may provide mechanistic insights into the specific pathogenesis of this deadly disease.


Transfusion ◽  
2021 ◽  
Author(s):  
Loann Raud ◽  
Marlène Le Tertre ◽  
Léonie Vigneron ◽  
Chandran Ka ◽  
Gaëlle Richard ◽  
...  

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Gavin W. Wilson ◽  
Mathieu Derouet ◽  
Gail E. Darling ◽  
Jonathan C. Yeung

AbstractIdentifying single nucleotide variants has become common practice for droplet-based single-cell RNA-seq experiments; however, presently, a pipeline does not exist to maximize variant calling accuracy. Furthermore, molecular duplicates generated in these experiments have not been utilized to optimally detect variant co-expression. Herein, we introduce scSNV designed from the ground up to “collapse” molecular duplicates and accurately identify variants and their co-expression. We demonstrate that scSNV is fast, with a reduced false-positive variant call rate, and enables the co-detection of genetic variants and A>G RNA edits across twenty-two samples.


2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Ianthe A. E. M. van Belzen ◽  
Alexander Schönhuth ◽  
Patrick Kemmeren ◽  
Jayne Y. Hehir-Kwa

AbstractCancer is generally characterized by acquired genomic aberrations in a broad spectrum of types and sizes, ranging from single nucleotide variants to structural variants (SVs). At least 30% of cancers have a known pathogenic SV used in diagnosis or treatment stratification. However, research into the role of SVs in cancer has been limited due to difficulties in detection. Biological and computational challenges confound SV detection in cancer samples, including intratumor heterogeneity, polyploidy, and distinguishing tumor-specific SVs from germline and somatic variants present in healthy cells. Classification of tumor-specific SVs is challenging due to inconsistencies in detected breakpoints, derived variant types and biological complexity of some rearrangements. Full-spectrum SV detection with high recall and precision requires integration of multiple algorithms and sequencing technologies to rescue variants that are difficult to resolve through individual methods. Here, we explore current strategies for integrating SV callsets and to enable the use of tumor-specific SVs in precision oncology.


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