scholarly journals Protein Subdomain Enrichment of NUP155 Variants Identify a Novel Predicted Pathogenic Hotspot

2020 ◽  
Vol 7 ◽  
Author(s):  
Riley J. Leonard ◽  
Claudia C. Preston ◽  
Melanie E. Gucwa ◽  
Yohannes Afeworki ◽  
Arielle S. Selya ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Cardiac Disease ◽  
Molecular Transport ◽  
Bioinformatic Analysis ◽  
Rna Helicases ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Sequencing Project ◽  
Blood Institute ◽  
Functional Variants

Functional variants in nuclear envelope genes are implicated as underlying causes of cardiopathology. To examine the potential association of single nucleotide variants of nucleoporin genes with cardiac disease, we employed a prognostic scoring approach to investigate variants of NUP155, a nucleoporin gene clinically linked with atrial fibrillation. Here we implemented bioinformatic profiling and predictive scoring, based on the gnomAD, National Heart Lung and Blood Institute-Exome Sequencing Project (NHLBI-ESP) Exome Variant Server, and dbNSFP databases to identify rare single nucleotide variants (SNVs) of NUP155 potentially associated with cardiopathology. This predictive scoring revealed 24 SNVs of NUP155 as potentially cardiopathogenic variants located primarily in the N-terminal crescent-shaped domain of NUP155. In addition, a predicted NUP155 R672G variant prioritized in our study was mapped to a region within the alpha helical stack of the crescent domain of NUP155. Bioinformatic analysis of inferred protein-protein interactions of NUP155 revealed over representation of top functions related to molecular transport, RNA trafficking, and RNA post-transcriptional modification. Topology analysis revealed prioritized hubs critical for maintaining network integrity and informational flow that included FN1, SIRT7, and CUL7 with nodal enrichment of RNA helicases in the topmost enriched subnetwork. Furthermore, integration of the top 5 subnetworks to capture network topology of an expanded framework revealed that FN1 maintained its hub status, with elevation of EED, CUL3, and EFTUD2. This is the first study to report novel discovery of a NUP155 subdomain hotspot that enriches for allelic variants of NUP155 predicted to be clinically damaging, and supports a role for RNA metabolism in cardiac disease and development.

scholarly journals VarQ: a tool for the structural analysis of Human Protein Variants

2018 ◽  
Author(s):  
Leandro Radusky ◽  
Carlos Modenutti ◽  
Javier Delgado ◽  
Juan P. Bustamante ◽  
Sebastian Vishnopolska ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Protein Function ◽  
Single Amino Acid ◽  
Disease Development ◽  
Functional Effect ◽  
Single Nucleotide Variants ◽  
Protein Activity ◽  
Single Nucleotide ◽  
Online Tool ◽  
Protein Variants

AbstractUnderstanding the functional effect of Single Amino acid Substitutions (SAS), derived from the occurrence of single nucleotide variants (SNVs), and their relation to disease development is a major issue in clinical genomics. Even though there are several bioinformatic algorithms and servers that predict if a SAS can be pathogenic or not they give little or non-information on the actual effect on the protein function. Moreover, many of these algorithms are able to predict an effect that no necessarily translates directly into pathogenicity. VarQ Web Server is an online tool that given an UniProt id automatically analyzes known and user provided SAS for their effect on protein activity, folding, aggregation and protein interactions among others. VarQ assessment was performed over a set of previously manually curated variants, showing its ability to correctly predict the phenotypic outcome and its underlying cause. This resource is available online at http://varq.qb.fcen.uba.ar/.Contact: [email protected] Information & Tutorials may be found in the webpage of the tool.

scholarly journals Initial Insights Into the Genetic Epidemiology of SARS-CoV-2 Isolates From Kerala Suggest Local Spread From Limited Introductions

2021 ◽  
Vol 12 ◽  
Author(s):  
Chandni Radhakrishnan ◽  
Mohit Kumar Divakar ◽  
Abhinav Jain ◽  
Prasanth Viswanathan ◽  
Rahul C. Bhoyar ◽  
...  
Keyword(s):  
Genetic Epidemiology ◽  
Binding Sites ◽  
Haplotype Analysis ◽  
Rt Pcr ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Functional Variants ◽  
Local Spread ◽  
Novel Variants ◽  
The World

Coronavirus disease 2019 (COVID-19) rapidly spread from a city in China to almost every country in the world, affecting millions of individuals. The rapid increase in the COVID-19 cases in the state of Kerala in India has necessitated the understanding of SARS-CoV-2 genetic epidemiology. We sequenced 200 samples from patients in Kerala using COVIDSeq protocol amplicon-based sequencing. The analysis identified 166 high-quality single-nucleotide variants encompassing four novel variants and 89 new variants in the Indian isolated SARS-CoV-2. Phylogenetic and haplotype analysis revealed that the virus was dominated by three distinct introductions followed by local spread suggesting recent outbreaks and that it belongs to the A2a clade. Further analysis of the functional variants revealed that two variants in the S gene associated with increased infectivity and five variants mapped in primer binding sites affect the efficacy of RT-PCR. To the best of our knowledge, this is the first and most comprehensive report of SARS-CoV-2 genetic epidemiology from Kerala.

scholarly journals SVEP1 IS IMPORTANT FOR MORPHOGENESIS OF LYMPHATIC SYSTEM: POSSIBLE IMPLICATIONS IN LYMPHEDEMA

Lymphology ◽  
2021 ◽  
Vol 54 (1) ◽  
Author(s):  
S. Michelini ◽  
B. Amato ◽  
M. Ricci ◽  
R. Serrani ◽  
D. Veselenyiova ◽  
...  
Keyword(s):  
Candidate Gene ◽  
Protein Interactions ◽  
Lymphatic System ◽  
Review Of The Literature ◽  
Single Nucleotide Variants ◽  
Lymphatic Malformations ◽  
Single Nucleotide ◽  
Three Samples ◽  
Knockout Animals ◽  
Mosaic Protein

SVEP1, also known as Polydom, is a large extracellular mosaic protein with functions in protein interactions and adhesion. Since Svep1 knockout animals show severe edema and lymphatic system malformations, the aim of this study is to evaluate the presence of SVEP1 variants in patients with lymphedema. We analyzed DNA from 246 lymphedema patients for variants in known lymphedema genes, 235 of whom tested negative and underwent a second testing for new candidate genes, including SVEP1, as reported here. We found three samples with rare heterozygous missense single-nucleotide variants in the SVEP1 gene. In one family, healthy members were found to carry the same variants and reported some subclinical edema. Based on our findings and a review of the literature, we propose SVEP1 as a candidate gene that should be sequenced in patients with lymphatic malformations, with or without lymphedema, in order to investigate and add evidence on its possible involvement in the development of lymphedema.

scholarly journals Extensive disruption of protein interactions by genetic variants across the allele frequency spectrum in human populations

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Robert Fragoza ◽  
Jishnu Das ◽  
Shayne D. Wierbowski ◽  
Jin Liang ◽  
Tina N. Tran ◽  
...  
Keyword(s):  
Allele Frequency ◽  
Protein Interactions ◽  
Human Populations ◽  
Protein Protein Interactions ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Allele Frequency Spectrum ◽  
Disease Mutations ◽  
Coding Variants ◽  
The Impact

Abstract Each human genome carries tens of thousands of coding variants. The extent to which this variation is functional and the mechanisms by which they exert their influence remains largely unexplored. To address this gap, we leverage the ExAC database of 60,706 human exomes to investigate experimentally the impact of 2009 missense single nucleotide variants (SNVs) across 2185 protein-protein interactions, generating interaction profiles for 4797 SNV-interaction pairs, of which 421 SNVs segregate at > 1% allele frequency in human populations. We find that interaction-disruptive SNVs are prevalent at both rare and common allele frequencies. Furthermore, these results suggest that 10.5% of missense variants carried per individual are disruptive, a higher proportion than previously reported; this indicates that each individual’s genetic makeup may be significantly more complex than expected. Finally, we demonstrate that candidate disease-associated mutations can be identified through shared interaction perturbations between variants of interest and known disease mutations.

scholarly journals Evolution and Functional Impact of Rare Coding Variation from Deep Sequencing of Human Exomes

Science ◽  
2012 ◽  
Vol 337 (6090) ◽  
pp. 64-69 ◽  
Author(s):  
Jacob A. Tennessen ◽  
Abigail W. Bigham ◽  
Timothy D. O’Connor ◽  
Wenqing Fu ◽  
Eimear E. Kenny ◽  
...  
Keyword(s):  
Protein Function ◽  
Complex Traits ◽  
Rare Variants ◽  
Purifying Selection ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Protein Coding ◽  
Protein Coding Genes ◽  
Functional Variants ◽  
A Minor

As a first step toward understanding how rare variants contribute to risk for complex diseases, we sequenced 15,585 human protein-coding genes to an average median depth of 111× in 2440 individuals of European (n = 1351) and African (n = 1088) ancestry. We identified over 500,000 single-nucleotide variants (SNVs), the majority of which were rare (86% with a minor allele frequency less than 0.5%), previously unknown (82%), and population-specific (82%). On average, 2.3% of the 13,595 SNVs each person carried were predicted to affect protein function of ~313 genes per genome, and ~95.7% of SNVs predicted to be functionally important were rare. This excess of rare functional variants is due to the combined effects of explosive, recent accelerated population growth and weak purifying selection. Furthermore, we show that large sample sizes will be required to associate rare variants with complex traits.

scholarly journals Single-Nucleotide Polymorphisms Sequencing Identifies Candidate Functional Variants at Prostate Cancer Risk Loci

Genes ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 547 ◽  
Author(s):  
Peng Zhang ◽  
Lori S. Tillmans ◽  
Stephen N. Thibodeau ◽  
Liang Wang
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Single Nucleotide Polymorphisms ◽  
Protein Binding ◽  
Prostate Cancer Risk ◽  
Sequencing Analysis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Functional Variants ◽  
Dependent Protein

Genome-wide association studies have identified over 150 risk loci that increase prostate cancer risk. However, few causal variants and their regulatory mechanisms have been characterized. In this study, we utilized our previously developed single-nucleotide polymorphisms sequencing (SNPs-seq) technology to test allele-dependent protein binding at 903 SNP sites covering 28 genomic regions. All selected SNPs have shown significant cis-association with at least one nearby gene. After preparing nuclear extract using LNCaP cell line, we first mixed the extract with dsDNA oligo pool for protein–DNA binding incubation. We then performed sequencing analysis on protein-bound oligos. SNPs-seq analysis showed protein-binding differences (>1.5-fold) between reference and variant alleles in 380 (42%) of 903 SNPs with androgen treatment and 403 (45%) of 903 SNPs without treatment. From these significant SNPs, we performed a database search and further narrowed down to 74 promising SNPs. To validate this initial finding, we performed electrophoretic mobility shift assay in two SNPs (rs12246440 and rs7077275) at CTBP2 locus and one SNP (rs113082846) at NCOA4 locus. This analysis showed that all three SNPs demonstrated allele-dependent protein-binding differences that were consistent with the SNPs-seq. Finally, clinical association analysis of the two candidate genes showed that CTBP2 was upregulated, while NCOA4 was downregulated in prostate cancer (p < 0.02). Lower expression of CTBP2 was associated with poor recurrence-free survival in prostate cancer. Utilizing our experimental data along with bioinformatic tools provides a strategy for identifying candidate functional elements at prostate cancer susceptibility loci to help guide subsequent laboratory studies.

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 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.

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