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 ◽  
...  

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.

2013 ◽  
Vol 44 (21) ◽  
Author(s):  
Sushant Kumar ◽  
Declan Clarke ◽  
Mark Gerstein

Abstract Population-scale sequencing is increasingly uncovering large numbers of rare single-nucleotide variants (SNVs) in coding regions of the genome. The rarity of these variants makes it challenging to evaluate their deleteriousness with conventional phenotype–genotype associations. Protein structures provide a way of addressing this challenge. Previous efforts have focused on globally quantifying the impact of SNVs on protein stability. However, local perturbations may severely impact protein functionality without strongly disrupting global stability (e.g. in relation to catalysis or allostery). Here, we describe a workflow in which localized frustration, quantifying unfavorable local interactions, is employed as a metric to investigate such effects. Using this workflow on the Protein Databank, we find that frustration produces many immediately intuitive results: for instance, disease-related SNVs create stronger changes in localized frustration than non-disease related variants, and rare SNVs tend to disrupt local interactions to a larger extent than common variants. Less obviously, we observe that somatic SNVs associated with oncogenes and tumor suppressor genes (TSGs) induce very different changes in frustration. In particular, those associated with TSGs change the frustration more in the core than the surface (by introducing loss-of-function events), whereas those associated with oncogenes manifest the opposite pattern, creating gain-of-function events.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Sebastian Carrasco Pro ◽  
Katia Bulekova ◽  
Brian Gregor ◽  
Adam Labadorf ◽  
Juan Ignacio Fuxman Bass

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.


Author(s):  
Jacqueline Neubauer ◽  
Shouyu Wang ◽  
Giancarlo Russo ◽  
Cordula Haas

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.


2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii32-ii32
Author(s):  
Charlotte Eaton ◽  
Paola Bisignano ◽  
David Raleigh

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.


Genes ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 1076
Author(s):  
Victor Jaravine ◽  
James Balmford ◽  
Patrick Metzger ◽  
Melanie Boerries ◽  
Harald Binder ◽  
...  

A novel approach is developed to address the challenge of annotating with phenotypic effects those exome variants for which relevant empirical data are lacking or minimal. The predictive annotation method is implemented as a stacked ensemble of supervised base-learners, including distributed random forest and gradient boosting machines. Ensemble models were trained and cross-validated on evidence-based categorical variant effect annotations from the ClinVar database, and were applied to 84 million non-synonymous single nucleotide variants (SNVs). The consensus model combined 39 functional mutation impacts, cross-species conservation score, and gene indispensability score. The indispensability score, accounting for differences in variant pathogenicities including in essential and mutation-tolerant genes, considerably improved the predictions. The consensus combination is consistent with as many input scores as possible while minimizing false predictions. The input scores are ranked based on their ability to predict effects. The score rankings and categorical phenotypic variant effect predictions are aimed for direct use in clinical and biological applications to prioritize human exome variants and mutations.


2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Hai Lin ◽  
Katherine A. Hargreaves ◽  
Rudong Li ◽  
Jill L. Reiter ◽  
Yue Wang ◽  
...  

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.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3422-3422
Author(s):  
Melinda M Dean ◽  
Katrina Kildey ◽  
Thu V Tran ◽  
Kelly Rooks ◽  
Shoma Baidya ◽  
...  

Abstract Introduction During routine storage packed red blood cells (PRBC) undergo biochemical and biophysical changes collectively referred to as the “RBC storage lesion”. Donor-to-donor variability in the severity of the storage lesion has been reported. The extent to which donor-associated differences in blood component storage affect blood product quality and post-transfusion outcome remains unknown. Murine models with single nucleotide variants (SNV) in gene encoding spectrin-1β were used to investigate the impact of mutations on the RBC storage lesion. Methods Two murine lineages with N-ethyl-N-nitrosourea (ENU) generated single SNV in Spnb1, encoding spectrin-1β (Table 1), were selected from the Australian Phenomics Facility library (http://databases.apf.edu.au/mutations). Using genetic selection, homozygous (HOM), heterozygous (HET) and unaffected (WT) mice from each strain were generated (C57BL/6 background strain). Murine blood was leucoreduced, prepared in SAGM (0.4 HCT) and stored at 4°C for time course assessment of RBC characteristics. At day (D), D2, D7, D14 and D21 of storage, RBC integrity and evidence of storage-related changes were investigated using RBC osmotic fragility and flow cytometric analysis of CD44, CD47, TER119 and phosphatidylserine (PS). Data were generated from analysis of blood from Spnb1 (pedigree spectrin-1β a) homozygous (HOM, n=3), heterozygous (HET, n=3) and unaffected (WT, n=2 ); Spnb1 (pedigree spectrin-1β b) HOM (n=4), HET( n=4); C57BL/6 (n=4). The Mann-Whitney Test and ANOVA were utilised for statistical analyses (95% CI). Results At D2 of storage SNV in Spnb1 did not alter RBC characteristics, with all mice studied demonstrating a similar resistance to osmotic lysis and levels of CD44, CD47, TER119 and PS. By D7 of storage, clear pedigree-related differences in RBC characteristics were evident. At D7, RBC from spectrin-1β(a) HOM mice had significantly increased osmotic fragility and exposure of PS as well as significantly reduced CD44 and TER119 expression compared to unaffected siblings and background strain. Of note, these changes were not evident in the spectrin-1β(b) HOM mice at D7. For both strains at D7, heterozygous SNV did not exhibit altered storage parameters. By D14 both HOM and HET spectrin-1β(a) mice demonstrated a phenotype consistent with an exacerbated RBC storage lesion, characterised by significantly increased osmotic fragility and exposure of PS, and reduced CD44 and CD47 compared to background strain. At D14 there was also evidence of exacerbation of the storage lesion in stored RBC from HOM spectrin-1β(b) mice (significantly increased PS), though this was not to the extent observed in the spectrin-1β(a) mice. By D21 all murine RBC were substantially degraded under these storage conditions. Conclusions SNV in Spnb1,encoding RBC structural protein spectrin-1β, resulted in both early onset and exacerbation of the RBC storage lesion. Further, the degree of storage lesion and the point at which RBC degradation was observed was not only dependent on the homozygous or heterozygous status, but the mutation itself. These data demonstrate that minor genetic variation in genes encoding important RBC proteins contribute to donor related differences in PRBC storage. Disclosures: No relevant conflicts of interest to declare.


2020 ◽  
Vol 48 (W1) ◽  
pp. W287-W291
Author(s):  
Milad Miladi ◽  
Martin Raden ◽  
Sven Diederichs ◽  
Rolf Backofen

Abstract RNA molecules fold into complex structures as a result of intramolecular interactions between their nucleotides. The function of many non-coding RNAs and some cis-regulatory elements of messenger RNAs highly depends on their fold. Single-nucleotide variants (SNVs) and other types of mutations can disrupt the native function of an RNA element by altering its base pairing pattern. Identifying the effect of a mutation on an RNA’s structure is, therefore, a crucial step in evaluating the impact of mutations on the post-transcriptional regulation and function of RNAs within the cell. Even though a single nucleotide variation can have striking impacts on the structure formation, interpreting and comparing the impact usually needs expertise and meticulous efforts. Here, we present MutaRNA, a web server for visualization and interpretation of mutation-induced changes on the RNA structure in an intuitive and integrative fashion. To this end, probabilities of base pairing and position-wise unpaired probabilities of wildtype and mutated RNA sequences are computed and compared. Differential heatmap-like dot plot representations in combination with circular plots and arc diagrams help to identify local structure abberations, which are otherwise hidden in standard outputs. Eventually, MutaRNA provides a comprehensive and comparative overview of the mutation-induced changes in base pairing potentials and accessibility. The MutaRNA web server is freely available at http://rna.informatik.uni-freiburg.de/MutaRNA.


2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Robert Fragoza ◽  
Jishnu Das ◽  
Shayne D. Wierbowski ◽  
Jin Liang ◽  
Tina N. Tran ◽  
...  

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.


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