scholarly journals Need for high-resolution Genetic Analysis in iPSC: Results and Lessons from the ForIPS Consortium Authors

2018 ◽  
Author(s):  
Bernt Popp ◽  
Mandy Krumbiegel ◽  
Janina Grosch ◽  
Annika Sommer ◽  
Steffen Uebe ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Neurological Diseases ◽  
Copy Number Variants ◽  
Molecular Karyotyping ◽  
Disease Genes ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Somatic Variant ◽  
Low Frequencies ◽  
Induced Pluripotent

ABSTRACTGenetic integrity of induced pluripotent stem cells (iPSCs) is essential for their validity as disease models and for potential therapeutic use. We describe the comprehensive analysis in the ForIPS consortium: an iPSC collection from donors with neurological diseases and healthy controls. Characterization included pluripotency confirmation, fingerprinting, conventional and molecular karyotyping in all lines. In the majority, somatic copy number variants (CNVs) were identified. A subset with available matched donor DNA was selected for comparative exome sequencing. We identified single nucleotide variants (SNVs) at different allelic frequencies in each clone with high variability in mutational load. Low frequencies of variants in parental fibroblasts highlight the importance of germline samples. Somatic variant number was independent from reprogramming, cell type and passage. Comparison with disease genes and prediction scores suggest biological relevance for some variants. We show that high-throughput sequencing has value beyond SNV detection and the requirement to individually evaluate each clone.

scholarly journals SomatoSim: precision simulation of somatic single nucleotide variants

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Marwan A. Hawari ◽  
Celine S. Hong ◽  
Leslie G. Biesecker
Keyword(s):  
High Throughput Sequencing ◽  
Variant Calling ◽  
Simulated Data ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Somatic Variant ◽  
Simulation Tools ◽  
Gold Standard Dataset ◽  
High Level

Abstract Background Somatic single nucleotide variants have gained increased attention because of their role in cancer development and the widespread use of high-throughput sequencing techniques. The necessity to accurately identify these variants in sequencing data has led to a proliferation of somatic variant calling tools. Additionally, the use of simulated data to assess the performance of these tools has become common practice, as there is no gold standard dataset for benchmarking performance. However, many existing somatic variant simulation tools are limited because they rely on generating entirely synthetic reads derived from a reference genome or because they do not allow for the precise customizability that would enable a more focused understanding of single nucleotide variant calling performance. Results SomatoSim is a tool that lets users simulate somatic single nucleotide variants in sequence alignment map (SAM/BAM) files with full control of the specific variant positions, number of variants, variant allele fractions, depth of coverage, read quality, and base quality, among other parameters. SomatoSim accomplishes this through a three-stage process: variant selection, where candidate positions are selected for simulation, variant simulation, where reads are selected and mutated, and variant evaluation, where SomatoSim summarizes the simulation results. Conclusions SomatoSim is a user-friendly tool that offers a high level of customizability for simulating somatic single nucleotide variants. SomatoSim is available at https://github.com/BieseckerLab/SomatoSim.

scholarly journals An integrative approach to investigate the respective roles of single-nucleotide variants and copy-number variants in Attention-Deficit/Hyperactivity Disorder

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Leandro de Araújo Lima ◽  
Ana Cecília Feio-dos-Santos ◽  
Sintia Iole Belangero ◽  
Ary Gadelha ◽  
Rodrigo Affonseca Bressan ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Copy Number ◽  
De Novo ◽  
Copy Number Variants ◽  
Integrative Approach ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Hyperactivity Disorder ◽  
New Genes

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.

Basic principles of genetic disease

ESC CardioMed ◽  
2018 ◽  
pp. 669-671
Author(s):  
Eric Schulze-Bahr
Keyword(s):  
Genetic Disease ◽  
Copy Number ◽  
Copy Number Variants ◽  
Single Nucleotide Variants ◽  
Individual Genome ◽  
Base Pairs ◽  
Single Nucleotide ◽  
Basic Principles ◽  
Bona Fide ◽  
Genomic Regions

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.

scholarly journals neoepiscope improves neoepitope prediction with multivariant phasing

2019 ◽  
Vol 36 (3) ◽  
pp. 713-720 ◽  
Author(s):  
Mary A Wood ◽  
Austin Nguyen ◽  
Adam J Struck ◽  
Kyle Ellrott ◽  
Abhinav Nellore ◽  
...  
Keyword(s):  
False Negative ◽  
Supplementary Information ◽  
Supplementary File ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Somatic Variant ◽  
Negative Results ◽  
Multiple Datasets ◽  
False Negative Results

Abstract Motivation The vast majority of tools for neoepitope prediction from DNA sequencing of complementary tumor and normal patient samples do not consider germline context or the potential for the co-occurrence of two or more somatic variants on the same mRNA transcript. Without consideration of these phenomena, existing approaches are likely to produce both false-positive and false-negative results, resulting in an inaccurate and incomplete picture of the cancer neoepitope landscape. We developed neoepiscope chiefly to address this issue for single nucleotide variants (SNVs) and insertions/deletions (indels). Results Herein, we illustrate how germline and somatic variant phasing affects neoepitope prediction across multiple datasets. We estimate that up to ∼5% of neoepitopes arising from SNVs and indels may require variant phasing for their accurate assessment. neoepiscope is performant, flexible and supports several major histocompatibility complex binding affinity prediction tools. Availability and implementation neoepiscope is available on GitHub at https://github.com/pdxgx/neoepiscope under the MIT license. Scripts for reproducing results described in the text are available at https://github.com/pdxgx/neoepiscope-paper under the MIT license. Additional data from this study, including summaries of variant phasing incidence and benchmarking wallclock times, are available in Supplementary Files 1, 2 and 3. Supplementary File 1 contains Supplementary Table 1, Supplementary Figures 1 and 2, and descriptions of Supplementary Tables 2–8. Supplementary File 2 contains Supplementary Tables 2–6 and 8. Supplementary File 3 contains Supplementary Table 7. Raw sequencing data used for the analyses in this manuscript are available from the Sequence Read Archive under accessions PRJNA278450, PRJNA312948, PRJNA307199, PRJNA343789, PRJNA357321, PRJNA293912, PRJNA369259, PRJNA305077, PRJNA306070, PRJNA82745 and PRJNA324705; from the European Genome-phenome Archive under accessions EGAD00001004352 and EGAD00001002731; and by direct request to the authors. Supplementary information Supplementary data are available at Bioinformatics online.

Genetics of Schizophrenia and Bipolar Disorder

2017 ◽  
Author(s):  
Alexander Charney ◽  
Pamela Sklar
Keyword(s):  
Bipolar Disorder ◽  
Copy Number ◽  
Psychotic Disorders ◽  
Copy Number Variants ◽  
Nucleotide Polymorphisms ◽  
Common Variants ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Number Variation

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.

scholarly journals Genetic Factors of Nitric Oxide’s System in Psychoneurologic Disorders

2020 ◽  
Vol 21 (5) ◽  
pp. 1604 ◽  
Author(s):  
Regina F. Nasyrova ◽  
Polina V. Moskaleva ◽  
Elena E. Vaiman ◽  
Natalya A. Shnayder ◽  
Nataliya L. Blatt ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Neurological Diseases ◽  
Small Sample ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Penile Erections ◽  
Genetic And Environmental Factors ◽  
Small Sample Sizes ◽  
Disease Modifying Treatment

According to the recent data, nitric oxide (NO) is a chemical messenger that mediates functions such as vasodilation and neurotransmission, as well as displaying antimicrobial and antitumoral activities. NO has been implicated in the neurotoxicity associated with stroke and neurodegenerative diseases; neural regulation of smooth muscle, including peristalsis; and penile erections. We searched for full-text English publications from the past 15 years in Pubmed and SNPedia databases using keywords and combined word searches (nitric oxide, single nucleotide variants, single nucleotide polymorphisms, genes). In addition, earlier publications of historical interest were included in the review. In our review, we have summarized information regarding all NOS1, NOS2, NOS3, and NOS1AP single nucleotide variants (SNVs) involved in the development of mental disorders and neurological diseases/conditions. The results of the studies we have discussed in this review are contradictory, which might be due to different designs of the studies, small sample sizes in some of them, and different social and geographical characteristics. However, the contribution of genetic and environmental factors has been understudied, which makes this issue increasingly important for researchers as the understanding of these mechanisms can support a search for new approaches to pathogenetic and disease-modifying treatment.

scholarly journals Recent Advances in Understanding the Genetic Architecture of Autism

2020 ◽  
Vol 21 (1) ◽  
pp. 289-304 ◽  
Author(s):  
Caroline M. Dias ◽  
Christopher A. Walsh
Keyword(s):  
Genetic Architecture ◽  
De Novo ◽  
Clinical Care ◽  
Copy Number Variants ◽  
Autism Spectrum ◽  
Loss Of Function ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Recent Advances ◽  
Insight Into

Recent advances in understanding the genetic architecture of autism spectrum disorder have allowed for unprecedented insight into its biological underpinnings. New studies have elucidated the contributions of a variety of forms of genetic variation to autism susceptibility. While the roles of de novo copy number variants and single-nucleotide variants—causing loss-of-function or missense changes—have been increasingly recognized and refined, mosaic single-nucleotide variants have been implicated more recently in some cases. Moreover, inherited variants (including common variants) and, more recently, rare recessive inherited variants have come into greater focus. Finally, noncoding variants—both inherited and de novo—have been implicated in the last few years. This work has revealed a convergence of diverse genetic drivers on common biological pathways and has highlighted the ongoing importance of increasing sample size and experimental innovation. Continuing to synthesize these genetic findings with functional and phenotypic evidence and translating these discoveries to clinical care remain considerable challenges for the field.

Circulating cell-free DNA (ctDNA) assessments before, during, and after neoadjuvant therapy (NAC) in nonmetastatic inflammatory breast cancer (IBC).

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e12113-e12113
Author(s):  
Carolyn S. Hall ◽  
Salyna Meas ◽  
Vanessa Nicole Sarli ◽  
Anthony Lucci
Keyword(s):  
Breast Cancer ◽  
Pathologic Complete Response ◽  
Copy Number Variants ◽  
Residual Tumor ◽  
Complete Response ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Cell Free Dna ◽  
Free Dna ◽  
Circulating Cell Free Dna

e12113 Background: : IBC is a rare and aggressive subtype of breast cancer. A significant number of IBC patients who achieve pathologic complete response (no residual tumor in breast and axillary nodes, pCR) relapse after NAC. We hypothesized that circulating cell-free DNA (ctDNA) identified in blood before, during, and after NAC would identify novel ctDNA targets. Methods: Plasma ctDNA was extracted from 43 non-metastatic IBC patients (IRB: LAB04-0698) pre, mid, and post-NAC. The Oncomine Pan Cancer ctDNA Assay (ThermoFisher) was used for library preparation, and high throughput next generation sequencing was performed on a GeneStudio S5XL System (ThermoFisher), following manufacturer’s directions. ThermoFisher Ion Reporter 5.10 Software was used to analyze single nucleotide variants (SNVs), and copy number variants (CNVs). Results: Seventeen patients had pre-NAC ctDNA assessments; 7/17 (41%) had PIK3CA SNVs; 5/7 also had MYC or FGFR2 CNVs. Five of 17 (29%) had TP53 SNVs; 2/5 also had FGFR2 CNVs. Ten patients had mid-NAC ctDNA assessments; 9/10 (90%) had PIK3CA SNVs; 5/9 also had FGFR2 CNVs, 2/9 had FGFR2 and FGFR3 CNVs, 2/9 also had TP53 SNVs, 1/9 had FGFR2 and ERB2 CNVs. Thirty-one patients had post-NAC ctDNA assessments; 5/31 (16%) had PIK3CA SNVs; 2/5 had FGFR2 CNVs, 1/5 also had a TP53 mutation and an FGFR2 CNV, 1/5 had FGFR2 CNV, and FGFR3 CNV. Six of 31 (19%) had TP53 SNVs, 1/6 had CCND1 CNVs, no CNVs were detected in 6 patients with TP53 SNVs. Six of 31 (19%) had MAP2K1 SNVs. Three of 31 (10%) had MET SNVs; 1/3 had CCND3 CNVs, no CNVs were detected in 2 patients with MET SNVs. No SNVs or CNVs were detected in 10/31 (32%) of patients post NAC. Conclusions: ctDNA assessments before, during, and after NAC identified novel targets that could be tested in future adjuvant therapies trials in IBC patients who remain at high risk for relapse.

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