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 Comprehensive variant effect predictions of single nucleotide variants in model organisms

2018 ◽  
Author(s):  
Omar Wagih ◽  
Bede Busby ◽  
Marco Galardini ◽  
Danish Memon ◽  
Athanasios Typas ◽  
...  
Keyword(s):  
Amino Acid ◽  
Protein Complex ◽  
Model Organisms ◽  
Single Nucleotide Variants ◽  
Cellular Mechanisms ◽  
Single Nucleotide ◽  
Post Translational Modifications ◽  
Variant Effect ◽  
Coding Variants ◽  
The Impact

AbstractThe effect of single nucleotide variants (SNVs) in coding and non-coding regions is of great interest in genetics. Although many computational methods aim to elucidate the effects of SNVs on cellular mechanisms, it is not straightforward to comprehensively cover different molecular effects. To address this we compiled and benchmarked sequence and structure-based variant effect predictors and we analyzed the impact of nearly all possible amino acid and nucleotide variants in the reference genomes of H. sapiens, S. cerevisiae and E. coli. Studied mechanisms include protein stability, interaction interfaces, post-translational modifications and transcription factor binding sites. We apply this resource to the study of natural and disease coding variants. We also show how variant effects can be aggregated to generate protein complex burden scores that uncover protein complex to phenotype associations based on a set of newly generated growth profiles of 93 sequenced S. cerevisiae strains in 43 conditions. This resource is available through mutfunc, a tool by which users can query precomputed predictions by providing amino acid or nucleotide-level variants.

scholarly journals The Protein Interactome of Glycolysis in Escherichia coli

Proteomes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 16
Author(s):  
Shomeek Chowdhury ◽  
Stephen Hepper ◽  
Mudassir K. Lodi ◽  
Milton H. Saier ◽  
Peter Uetz
Keyword(s):  
Escherichia Coli ◽  
Protein Interactions ◽  
Allosteric Regulation ◽  
Glycolytic Enzymes ◽  
Protein Protein Interactions ◽  
Post Translational Modification ◽  
Interacting Protein ◽  
E Coli ◽  
Protein Interactome ◽  
The Impact

Glycolysis is regulated by numerous mechanisms including allosteric regulation, post-translational modification or protein-protein interactions (PPI). While glycolytic enzymes have been found to interact with hundreds of proteins, the impact of only some of these PPIs on glycolysis is well understood. Here we investigate which of these interactions may affect glycolysis in E. coli and possibly across numerous other bacteria, based on the stoichiometry of interacting protein pairs (from proteomic studies) and their conservation across bacteria. We present a list of 339 protein-protein interactions involving glycolytic enzymes but predict that ~70% of glycolytic interactors are not present in adequate amounts to have a significant impact on glycolysis. Finally, we identify a conserved but uncharacterized subset of interactions that are likely to affect glycolysis and deserve further study.

scholarly journals Prediction of genome-wide effects of single nucleotide variants on transcription factor binding

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Sebastian Carrasco Pro ◽  
Katia Bulekova ◽  
Brian Gregor ◽  
Adam Labadorf ◽  
Juan Ignacio Fuxman Bass
Keyword(s):  
Binding Sites ◽  
Cancer Type ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Regulatory Regions ◽  
Genome Wide ◽  
Transcriptional Regulatory ◽  
Gene Regulatory ◽  
The Impact ◽  
The Relationship

Abstract Single nucleotide variants (SNVs) located in transcriptional regulatory regions can result in gene expression changes that lead to adaptive or detrimental phenotypic outcomes. Here, we predict gain or loss of binding sites for 741 transcription factors (TFs) across the human genome. We calculated ‘gainability’ and ‘disruptability’ scores for each TF that represent the likelihood of binding sites being created or disrupted, respectively. We found that functional cis-eQTL SNVs are more likely to alter TF binding sites than rare SNVs in the human population. In addition, we show that cancer somatic mutations have different effects on TF binding sites from different TF families on a cancer-type basis. Finally, we discuss the relationship between these results and cancer mutational signatures. Altogether, we provide a blueprint to study the impact of SNVs derived from genetic variation or disease association on TF binding to gene regulatory regions.

scholarly journals Re-evaluation of single nucleotide variants and identification of structural variants in a cohort of 45 sudden unexplained death cases

2021 ◽  
Author(s):  
Jacqueline Neubauer ◽  
Shouyu Wang ◽  
Giancarlo Russo ◽  
Cordula Haas
Keyword(s):  
Sudden Death ◽  
Cardiac Diseases ◽  
Structural Variants ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Sudden Unexplained Death ◽  
Unexplained Death ◽  
Pathogenic Variants ◽  
The Impact ◽  
Death Cases

AbstractSudden unexplained death (SUD) takes up a considerable part in overall sudden death cases, especially in adolescents and young adults. During the past decade, many channelopathy- and cardiomyopathy-associated single nucleotide variants (SNVs) have been identified in SUD studies by means of postmortem molecular autopsy, yet the number of cases that remain inconclusive is still high. Recent studies had suggested that structural variants (SVs) might play an important role in SUD, but there is no consensus on the impact of SVs on inherited cardiac diseases. In this study, we searched for potentially pathogenic SVs in 244 genes associated with cardiac diseases. Whole-exome sequencing and appropriate data analysis were performed in 45 SUD cases. Re-analysis of the exome data according to the current ACMG guidelines identified 14 pathogenic or likely pathogenic variants in 10 (22.2%) out of the 45 SUD cases, whereof 2 (4.4%) individuals had variants with likely functional effects in the channelopathy-associated genes SCN5A and TRDN and 1 (2.2%) individual in the cardiomyopathy-associated gene DTNA. In addition, 18 structural variants (SVs) were identified in 15 out of the 45 individuals. Two SVs with likely functional impairment were found in the coding regions of PDSS2 and TRPM4 in 2 SUD cases (4.4%). Both were identified as heterozygous deletions, which were confirmed by multiplex ligation-dependent probe amplification. In conclusion, our findings support that SVs could contribute to the pathology of the sudden death event in some of the cases and therefore should be investigated on a routine basis in suspected SUD cases.

Swim-exercised mice show a decreased level of protein O-GlcNAcylation and expression of O-GlcNAc transferase in heart

2011 ◽  
Vol 111 (1) ◽  
pp. 157-162 ◽  
Author(s):  
Darrell D. Belke
Keyword(s):  
Protein Interactions ◽  
Contractile Function ◽  
Cell Physiology ◽  
Protein Protein Interactions ◽  
Training Exercise ◽  
General Protein ◽  
Exercise Induced ◽  
Glcnac Transferase ◽  
The Impact ◽  
Physiological Hypertrophy

Swim-training exercise in mice leads to cardiac remodeling associated with an improvement in contractile function. Protein O-linked N-acetylglucosamine ( O-GlcNAcylation) is a posttranslational modification of serine and threonine residues capable of altering protein-protein interactions affecting gene transcription, cell signaling pathways, and general cell physiology. Increased levels of protein O-GlcNAcylation in the heart have been associated with pathological conditions such as diabetes, ischemia, and hypertrophic heart failure. In contrast, the impact of physiological exercise on protein O-GlcNAcylation in the heart is currently unknown. Swim-training exercise in mice was associated with the development of a physiological hypertrophy characterized by an improvement in contractile function relative to sedentary mice. General protein O-GlcNAcylation was significantly decreased in swim-exercised mice. This effect was mirrored in the level of O-GlcNAcylation of individual proteins such as SP1. The decrease in protein O-GlcNAcylation was associated with a decrease in the expression of O-GlcNAc transferase (OGT) and glutamine-fructose amidotransferase (GFAT) 2 mRNA. O-GlcNAcase (OGA) activity was actually lower in swim-trained than sedentary hearts, suggesting that it did not contribute to the decreased protein O-GlcNAcylation. Thus it appears that exercise-induced physiological hypertrophy is associated with a decrease in protein O-GlcNAcylation, which could potentially contribute to changes in gene expression and other physiological changes associated with exercise.

scholarly journals CSIG-22. CANCER-ASSOCIATED MISSENSE SINGLE NUCLEOTIDE VARIANTS REGULATE THE STABILITY AND SUBCELLULAR LOCALIZATION OF NF2/MERLIN

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii32-ii32
Author(s):  
Charlotte Eaton ◽  
Paola Bisignano ◽  
David Raleigh
Keyword(s):  
Tumor Suppressor ◽  
Subcellular Localization ◽  
Function Analysis ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Ferm Domain ◽  
Binding Partners ◽  
Subcellular Compartments ◽  
The Stability ◽  
The Impact

Abstract BACKGROUND Alterations in the NF2 tumor suppressor gene lead to meningiomas and schwannomas, but the tumor suppressor functions of the NF2 gene product, Merlin, are incompletely understood. To address this problem, we performed a structure-function analysis of Merlin by expressing cancer-associated missense single-nucleotide variants (mSNVs) in primary cancer cells for biochemical and cell biology experiments. METHODS All NF2 mSNVs were assembled from cBioPortal and COSMIC, and modelled on the FERM, a-helical, and C-terminal domains of Merlin (PDB 4ZRJ) using comparative structure prediction on the Robetta server and visually inspected using Pymol. mSNV hotspots were defined from sliding windows with at least 10 mutations within 5 residues in either direction. mSNVs from hotspots in meningiomas, schwannomas, or both, were selected for in vitro mechanistic analyses using immunofluorescence and immunoblotting of whole cell, plasma membrane, cytoskeletal, cytoplasmic, nuclear, and chromatin subcellular fractions from M10G meningioma cells and HEI-193 schwannoma cells. RESULTS We identified the following cancer-associated hotspot mSNVs in NF2, which were over-expressed for mechanistic studies: L46R, S156N, W191R, A211D, V219M, R418C and R462K. Endogenous Merlin was detected in all subcellular compartments, but was enriched in the nucleus. L46R and A211D mapped to hydrophobic pockets in the FERM domain, destabilized Merlin, and excluded Merlin from all subcellular compartments except the cytoskeleton. S156N, W191R and V219M also mapped to the FERM domain, but did not affect Merlin stability, and V219M attenuated chromatin localization, suggesting this motif may be involved in binding events that regulate subcellular localization. R418C and R463K mapped to the a-helical domain, but only R418C destabilized Merlin. CONCLUSION Our results suggest that cancer-associated mSNVs inactive the tumor suppressor functions of NF2 by altering the stability, subcellular localization, or binding partners of Merlin. Further work is required to identify and understand the impact of binding partners and subcellular localization on Merlin function.

scholarly journals RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Hai Lin ◽  
Katherine A. Hargreaves ◽  
Rudong Li ◽  
Jill L. Reiter ◽  
Yue Wang ◽  
...  
Keyword(s):  
Rna Splicing ◽  
Evolutionary Conservation ◽  
Random Forest Classifier ◽  
Training Data ◽  
Reporter Assay ◽  
Single Nucleotide Variants ◽  
Excellent Performance ◽  
Computational Framework ◽  
Single Nucleotide ◽  
The Impact

AbstractSingle nucleotide variants (SNVs) in intronic regions have yet to be systematically investigated for their disease-causing potential. Using known pathogenic and neutral intronic SNVs (iSNVs) as training data, we develop the RegSNPs-intron algorithm based on a random forest classifier that integrates RNA splicing, protein structure, and evolutionary conservation features. RegSNPs-intron showed excellent performance in evaluating the pathogenic impacts of iSNVs. Using a high-throughput functional reporter assay called ASSET-seq (ASsay for Splicing using ExonTrap and sequencing), we evaluate the impact of RegSNPs-intron predictions on splicing outcome. Together, RegSNPs-intron and ASSET-seq enable effective prioritization of iSNVs for disease pathogenesis.

scholarly journals Fido-SNP: the first webserver for scoring the impact of single nucleotide variants in the dog genome

2019 ◽  
Vol 47 (W1) ◽  
pp. W136-W141 ◽  
Author(s):  
Emidio Capriotti ◽  
Ludovica Montanucci ◽  
Giuseppe Profiti ◽  
Ivan Rossi ◽  
Diana Giannuzzi ◽  
...  
Keyword(s):  
Matthews Correlation Coefficient ◽  
Genomic Variation ◽  
Gradient Boosting ◽  
Binary Classifier ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Coding Regions ◽  
Variation Data ◽  
Boosting Algorithm ◽  
The Impact

Abstract As the amount of genomic variation data increases, tools that are able to score the functional impact of single nucleotide variants become more and more necessary. While there are several prediction servers available for interpreting the effects of variants in the human genome, only few have been developed for other species, and none were specifically designed for species of veterinary interest such as the dog. Here, we present Fido-SNP the first predictor able to discriminate between Pathogenic and Benign single-nucleotide variants in the dog genome. Fido-SNP is a binary classifier based on the Gradient Boosting algorithm. It is able to classify and score the impact of variants in both coding and non-coding regions based on sequence features within seconds. When validated on a previously unseen set of annotated variants from the OMIA database, Fido-SNP reaches 88% overall accuracy, 0.77 Matthews correlation coefficient and 0.91 Area Under the ROC Curve.

scholarly journals The evolution of gene duplicates in angiosperms and the impact of protein-protein interactions and the mechanism of duplication

2019 ◽  
Author(s):  
Jonas Defoort ◽  
Yves Van de Peer ◽  
Lorenzo Carretero-Paulet
Keyword(s):  
Protein Interactions ◽  
Specific Property ◽  
Small Scale ◽  
Biological Interactions ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Functional Dynamics ◽  
Dosage Balance ◽  
Gene Duplicates ◽  
The Impact

Abstract Gene duplicates, generated either through whole genome duplication (WGD) or small-scale duplication (SSD), are prominent in angiosperms and are believed to play an important role in adaptation and in generating evolutionary novelty. Previous studies reported contrasting evolutionary and functional dynamics of duplicate genes depending on the mechanism of origin, a behaviour that is hypothesized to stem from constraints to maintain the relative dosage balance between the genes concerned and their interaction context. However, the mechanisms ultimately influencing loss and retention of gene duplicates over evolutionary time are not yet fully elucidated. Here, by using a robust classification of gene duplicates in Arabidopsis thaliana, Solanum lycopersicum and Zea mays, large RNAseq expression compendia and an extensive protein-protein interaction (PPI) network from Arabidopsis, we investigated the impact of PPIs on the differential evolutionary and functional fate of WGD and SSD duplicates. In all three species, retained WGD duplicates show stronger constraints to diverge at the sequence and expression level than SSD ones, a pattern that is also observed for shared PPI partners between Arabidopsis duplicates. PPIs are preferentially distributed among WGD duplicates and specific functional categories. Furthermore, duplicates with PPIs tend to be under stronger constraints to evolve than their counterparts without PPIs regardless of their mechanism of origin. Our results support dosage balance constraint as a specific property of genes involved in biological interactions, including physical PPIs, and suggest that additional factors may be differently influencing the evolution of genes following duplication, depending on the species, time and mechanism of origin.

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