Single-Nucleotide Variants in microRNAs Sequences or in their Target Genes Might Influence the Risk of Epilepsy: A Review

2021 ◽  
Author(s):  
Renata Parissi Buainain ◽  
Matheus Negri Boschiero ◽  
Bruno Camporeze ◽  
Paulo Henrique Pires de Aguiar ◽  
Fernando Augusto Lima Marson ◽  
...  
Keyword(s):  
Target Genes ◽  
Single Nucleotide Variants ◽  
Single Nucleotide

scholarly journals Identification of Novel Single-Nucleotide Variants With Potential of Mediating Malfunction of MicroRNA in Congenital Heart Disease

2021 ◽  
Vol 8 ◽  
Author(s):  
Wangkai Liu ◽  
Liangping Cheng ◽  
Ken Chen ◽  
Jialing Wu ◽  
Rui Peng ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
Congenital Heart ◽  
Target Genes ◽  
Heart Defects ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Downstream Target ◽  
Gene Dysregulation ◽  
Great Vessels

Congenital heart defects (CHDs) represent the most common human birth defects. Our previous study indicates that the malfunction of microRNAs (miRNAs) in cardiac neural crest cells (NCCs), which contribute to the development of the heart and the connected great vessels, is likely linked to the pathogenesis of human CHDs. In this study, we attempt to further search for causative single-nucleotide variants (SNVs) from CHD patients that mediate the mis-regulating of miRNAs on their downstream target genes in the pathogenesis of CHDs. As a result, a total of 2,925 3′UTR SNVs were detected from a CHD cohort. In parallel, we profiled the expression of miRNAs in cardiac NCCs and found 201 expressed miRNAs. A combined analysis with these data further identified three 3′UTR SNVs, including NFATC1 c.*654C>T, FGFRL1 c.*414C>T, and CTNNB1 c.*729_*730insT, which result in the malfunction of miRNA-mediated gene regulation. The dysregulations were further validated experimentally. Therefore, our study indicates that miRNA-mediated gene dysregulation in cardiac NCCs could be an important etiology of congenital heart disease, which could lead to a new direction of diagnostic and therapeutic investigation on congenital heart disease.

scholarly journals MACSNVdb: a high-quality SNV database for interspecies genetic divergence investigation among macaques

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Lianming Du ◽  
Tao Guo ◽  
Qin Liu ◽  
Jing Li ◽  
Xiuyue Zhang ◽  
...  
Keyword(s):  
Genetic Divergence ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Biomedical Application ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
High Quality ◽  
Single Nucleotide ◽  
Phenotypic Differences ◽  
Flanking Sequences

Abstract Macaques are the most widely used non-human primates in biomedical research. The genetic divergence between these animal models is responsible for their phenotypic differences in response to certain diseases. However, the macaque single nucleotide polymorphism resources mainly focused on rhesus macaque (Macaca mulatta), which hinders the broad research and biomedical application of other macaques. In order to overcome these limitations, we constructed a database named MACSNVdb that focuses on the interspecies genetic diversity among macaque genomes. MACSNVdb is a web-enabled database comprising ~74.51 million high-quality non-redundant single nucleotide variants (SNVs) identified among 20 macaque individuals from six species groups (muttla, fascicularis, sinica, arctoides, silenus, sylvanus). In addition to individual SNVs, MACSNVdb also allows users to browse and retrieve groups of user-defined SNVs. In particular, users can retrieve non-synonymous SNVs that may have deleterious effects on protein structure or function within macaque orthologs of human disease and drug-target genes. Besides position, alleles and flanking sequences, MACSNVdb integrated additional genomic information including SNV annotations and gene functional annotations. MACSNVdb will facilitate biomedical researchers to discover molecular mechanisms of diverse responses to diseases as well as primatologist to perform population genetic studies. We will continue updating MACSNVdb with newly available sequencing data and annotation to keep the resource up to date. Database URL: http://big.cdu.edu.cn/macsnvdb/

Nuclear receptors in disease: the oestrogen receptors

2004 ◽  
Vol 40 ◽  
pp. 157-167 ◽  
Author(s):  
Maria Nilsson ◽  
Karin Dahlman-Wright ◽  
Jan-Åke Gustafsson
Keyword(s):  
Nuclear Receptors ◽  
Target Genes ◽  
Receptor Subtype ◽  
Target Tissue ◽  
Oestrogen Receptors ◽  
Nucleotide Polymorphisms ◽  
Cell Type ◽  
Single Nucleotide ◽  
Beneficial Effects ◽  
The Family

For several decades, it has been known that oestrogens are essential for human health. The discovery that there are two oestrogen receptors (ERs), ERalpha and ERbeta, has facilitated our understanding of how the hormone exerts its physiological effects. The ERs belong to the family of ligand-activated nuclear receptors, which act by modulating the expression of target genes. Studies of ER-knockout (ERKO) mice have been instrumental in defining the relevance of a given receptor subtype in a certain tissue. Phenotypes displayed by ERKO mice suggest diseases in which dysfunctional ERs might be involved in aetiology and pathology. Association between single-nucleotide polymorphisms (SNPs) in ER genes and disease have been demonstrated in several cases. Selective ER modulators (SERMs), which are selective with regard to their effects in a certain cell type, already exist. Since oestrogen has effects in many tissues, the goal with a SERM is to provide beneficial effects in one target tissue while avoiding side effects in others. Refined SERMs will, in the future, provide improved therapeutic strategies for existing and novel indications.

scholarly journals Combination of Genome-Wide Polymorphisms and Copy Number Variations of Pharmacogenes in Koreans

2021 ◽  
Vol 11 (1) ◽  
pp. 33
Author(s):  
Nayoung Han ◽  
Jung Mi Oh ◽  
In-Wha Kim
Keyword(s):  
Copy Number ◽  
Genome Wide Association Study ◽  
Copy Number Gain ◽  
Copy Number Variations ◽  
Gene Gain ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Haplotype Blocks ◽  
Genome Wide ◽  
Control And Prevention

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.

scholarly journals Unsuspected somatic mosaicism for FBN1 gene contributes to Marfan syndrome

2021 ◽  
Author(s):  
Pauline Arnaud ◽  
Hélène Morel ◽  
Olivier Milleron ◽  
Laurent Gouya ◽  
Christine Francannet ◽  
...  
Keyword(s):  
Marfan Syndrome ◽  
Somatic Mosaicism ◽  
Variant Calling ◽  
Copy Number Variations ◽  
Pathogenic Variant ◽  
Single Nucleotide Variants ◽  
Bioinformatics Analyses ◽  
Single Nucleotide ◽  
Fbn1 Gene ◽  
Pathogenic Variants

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.

scholarly journals Whole-exome mutational landscape of neuroendocrine carcinomas of the gallbladder

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Fatao Liu ◽  
Yongsheng Li ◽  
Dongjian Ying ◽  
Shimei Qiu ◽  
Yong He ◽  
...  
Keyword(s):  
Gene Mutations ◽  
Large Cell ◽  
Molecular Signatures ◽  
Single Nucleotide Variants ◽  
Oncogenic Signaling ◽  
Single Nucleotide ◽  
Whole Exome ◽  
Deadly Disease ◽  
Oncogenic Signaling Pathways ◽  
Neuroendocrine Carcinomas

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.

scholarly journals Missense RHD single nucleotide variants induce weakened D antigen expression by altering splicing and/or protein expression

Transfusion ◽  
2021 ◽  
Author(s):  
Loann Raud ◽  
Marlène Le Tertre ◽  
Léonie Vigneron ◽  
Chandran Ka ◽  
Gaëlle Richard ◽  
...  
Keyword(s):  
Protein Expression ◽  
Antigen Expression ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
D Antigen

scholarly journals scSNV: accurate dscRNA-seq SNV co-expression analysis using duplicate tag collapsing

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Gavin W. Wilson ◽  
Mathieu Derouet ◽  
Gail E. Darling ◽  
Jonathan C. Yeung
Keyword(s):  
Genetic Variants ◽  
False Positive ◽  
Variant Calling ◽  
Call Rate ◽  
Rna Seq ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Variant Call ◽  
Two Samples ◽  
Co Detection

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.

scholarly journals Structural variant detection in cancer genomes: computational challenges and perspectives for precision oncology

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Ianthe A. E. M. van Belzen ◽  
Alexander Schönhuth ◽  
Patrick Kemmeren ◽  
Jayne Y. Hehir-Kwa
Keyword(s):  
Intratumor Heterogeneity ◽  
Precision Oncology ◽  
Single Nucleotide Variants ◽  
Full Spectrum ◽  
Single Nucleotide ◽  
Sequencing Technologies ◽  
Cancer Genomes ◽  
Genomic Aberrations

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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