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 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 Low Diversity of Human Variation Despite Mostly Mild Functional Impact of De Novo Variants

2021 ◽  
Vol 8 ◽  
Author(s):  
Yannick Mahlich ◽  
Maximillian Miller ◽  
Zishuo Zeng ◽  
Yana Bromberg
Keyword(s):  
Amino Acid ◽  
Protein Function ◽  
Environmental Changes ◽  
Rare Variants ◽  
De Novo ◽  
Function Optimization ◽  
Reference Sequence ◽  
Single Amino Acid ◽  
Human Variation ◽  
Functional Effect

Non-synonymous Single Nucleotide Variants (nsSNVs), resulting in single amino acid variants (SAVs), are important drivers of evolutionary adaptation across the tree of life. Humans carry on average over 10,000 SAVs per individual genome, many of which likely have little to no impact on the function of the protein they affect. Experimental evidence for protein function changes as a result of SAVs remain sparse – a situation that can be somewhat alleviated by predicting their impact using computational methods. Here, we used SNAP to examine both observed and in silico generated human variation in a set of 1,265 proteins that are consistently found across a number of diverse species. The number of SAVs that are predicted to have any functional effect on these proteins is smaller than expected, suggesting sequence/function optimization over evolutionary timescales. Additionally, we find that only a few of the yet-unobserved SAVs could drastically change the function of these proteins, while nearly a quarter would have only a mild functional effect. We observed that variants common in the human population localized to less conserved protein positions and carried mild to moderate functional effects more frequently than rare variants. As expected, rare variants carried severe effects more frequently than common variants. In line with current assumptions, we demonstrated that the change of the human reference sequence amino acid to the reference of another species (a cross-species variant) is unlikely to significantly impact protein function. However, we also observed that many cross-species variants may be weakly non-neutral for the purposes of quick adaptation to environmental changes, but may not be identified as such by current state-of-the-art methodology.

scholarly journals MotSASi: Functional Short Linear Motifs (SLiMs) prediction based on genomic single nucleotide variants and structural data

2021 ◽  
Author(s):  
Mariano Martin ◽  
Carlos Pablo Modenutti ◽  
Juan Pablo Nicola ◽  
Marcelo Adrian Marti
Keyword(s):  
Protein Function ◽  
Complex Structure ◽  
False Positives ◽  
Single Amino Acid ◽  
Cell Physiology ◽  
Sequence Information ◽  
Sequence Variant ◽  
Single Nucleotide Variants ◽  
Short Linear Motifs ◽  
Linear Motifs

Short linear motifs (SLiMs) are key to cell physiology mediating reversible protein-protein interactions. Precise identification of SLiMs remains a challenge, being the main drawback of most bioinformatic prediction tools their low specificity (high number of false positives). An important, usually overlooked, aspect is the relation between SLiMs mutations and disease. The presence of variants in each residue position can be used to assess the relevance of the corresponding residue(s) for protein function, and its (in)tolerance to change. In the present work, we combined sequence variant information and structural analysis of the energetic impact of single amino acid substitution (SAS) in SLiM-Receptor complex structure, and showed that it significantly improves prediction of true functional SLiMs. Our strategy is based on building a SAS tolerance matrix that shows, for each position, whether one of the possible 19 SAS is tolerated or not. Herein we present the MotSASi strategy and analyze in detail 4 SLiMs involved in intracellular protein trafficking. Our results show that inclusion of variant and sequence information significantly improves both prediction of true SLiMs and rejection of false positives, while also allowing better classification of variants inside SLiMs, a results with a direct impact in clinical genomics.

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.

Variant discovery using next-generation sequencing and its future role in pharmacogenetics

2020 ◽  
Vol 21 (7) ◽  
pp. 471-486
Author(s):  
Laura E Russell ◽  
Ute I Schwarz
Keyword(s):  
Next Generation Sequencing ◽  
Protein Function ◽  
Large Scale ◽  
Clinical Care ◽  
Next Generation ◽  
Clinical Implementation ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Variant Discovery ◽  
Generation Sequencing

Next-generation sequencing (NGS) has enabled the discovery of a multitude of novel and mostly rare variants in pharmacogenes that may alter a patient’s therapeutic response to drugs. In addition to single nucleotide variants, structural variation affecting the number of copies of whole genes or parts of genes can be detected. While current guidelines concerning clinical implementation mostly act upon well-documented, common single nucleotide variants to guide dosing or drug selection, in silico and large-scale functional assessment of rare variant effects on protein function are at the forefront of pharmacogenetic research to facilitate their clinical integration. Here, we discuss the role of NGS in variant discovery, paving the way for more comprehensive genotype-guided pharmacotherapy that can translate to improved clinical care.

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.

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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