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RegSNPs-splicing: a tool for prioritizing synonymous single-nucleotide substitution.

ABSTRACT: While synonymous single-nucleotide variants (sSNVs) have largely been unstudied, since they do not alter protein sequence, mounting evidence suggests that they may affect RNA conformation, splicing, and the stability of nascent-mRNAs to promote various diseases. Accurately prioritizing deleterious sSNVs from a pool of neutral ones can significantly improve our ability of selecting functional genetic variants identified from various genome-sequencing projects, and, therefore, advance our understanding of disease etiology. In this study, we develop a computational algorithm to prioritize sSNVs based on their impact on mRNA splicing and protein function. In addition to genomic features that potentially affect splicing regulation, our proposed algorithm also includes dozens structural features that characterize the functions of alternatively spliced exons on protein function. Our systematical evaluation on thousands of sSNVs suggests that several structural features, including intrinsic disorder protein scores, solvent accessible surface areas, protein secondary structures, and known and predicted protein family domains, show significant differences between disease-causing and neutral sSNVs. Our result suggests that the protein structure features offer an added dimension of information while distinguishing disease-causing and neutral synonymous variants. The inclusion of structural features increases the predictive accuracy for functional sSNV prioritization.

SUBMITTER: Zhang X

PROVIDER: S-EPMC5602096 | biostudies-literature |

REPOSITORIES: biostudies-literature

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The synonymous nucleotide substitution RHD 1056C>G alters mRNA splicing associated with serologically weak D phenotype.

Project description:BACKGROUND:D antigen is one of the most clinically significant blood group antigens. Variation of the RHD gene can cause weak D or partial D phenotypes. While most variations are missense substitutions with amino acid changes, those without are called "silent" or "synonymous" substitutions. Synonymous substitutions often have little effect on the protein, not altering the phenotype. However, effect on splicing can affect end-product protein. We report a new synonymous variation, RHD 1056C>G, that resulted in weak D phenotype, and predicted its effect with various in silico methods. METHODS:Serologic testing of the D antigen with full sequencing of the RHD gene was done. Human Splice Finder was used to predict the effect of this variation, and validation of this method was done with all known RHD variations reported in the literature. RESULTS:RHD 1056C>G was predicted to cause the formation of an exonic splicing silencer (ESS) site. The creation of new ESS site potentially inhibits the splicing event, resulting alteration of splicing. This is similar to remodeling of splice acceptor or donor site, as this kind of deep exonic variation could affect the D antigen's quality or quantity. This is in concordance with serologic results, which showed only delayed weak agglutination to anti-D reagents. CONCLUSIONS:The analytic methods we applied showed good correlation with the actual phenotype, along with concordant results when analyzing other known variants reported in the literature. We conclude that RHD 1056C>G results in serologic weak D phenotype.

| S-EPMC6817278 | biostudies-literature

Syntool: A Novel Region-Based Intolerance Score to Single Nucleotide Substitution for Synonymous Mutations Predictions Based on 123,136 Individuals.

Project description:Synonymous mutation is the single nucleotide change that does not cause an amino acid change but can affect the rate and efficiency of translation. So recent increase in our knowledge has revealed a substantial contribution of synonymous mutations to human disease risk and other complex traits. Nevertheless, there are still rarely synonymous mutation prediction methods.Nonsynonymous and synonymous coding SNPs show similar likelihood and effect size of human disease association. Here we defined synonymous and missense variation as single nucleotide substitution variation. And then we evaluated the intolerance of genic transcripts to single nucleotide substitution variation based on gnomAD 123136 individuals. After regressing all variations on common variations, we defined residuals of regression model as every genomics region intolerance scores.We constructed a total of 24799 nonoverlapped region-based intolerance score by their intolerance to single nucleotide substitution variation (Syntool). The results show that Syntool score can discriminate synonymous disease causing mutations in Human Gene Mutation Database (HGMD Professional) and ClinVar database much better than others. Taken together, this study provides a novel prediction system for synonymous mutations, called Syntool, which could be helpful in identifying candidate synonymous disease causing mutations.

| S-EPMC5546077 | biostudies-other

Genomewide pattern of synonymous nucleotide substitution in two complete genomes of Mycobacterium tuberculosis.

Project description:Comparison of the pattern of synonymous nucleotide substitution between two complete genomes of Mycobacterium tuberculosis at 3298 putatively orthologous loci showed a mean percent difference per synonymous site of 0.000328 0.000022. Although 80.5% of loci showed no synonymous or nonsynonymous nucleotide differences, the level of polymorphism observed at other loci was greater than suggested by previous studies of a small number of loci. This level of nucleotide difference leads to the conservative estimate that the common ancestor of these two genotypes occurred approximately 35000 ago, which is twice as high as some recent estimates of the time of origin of this species. Our results suggest that a large number of loci should be examined for an accurate assessment of the level of nucleotide diversity in natural populations of pathogenic microorganisms.

| S-EPMC2738538 | biostudies-literature

regSNPs: a strategy for prioritizing regulatory single nucleotide substitutions.

Project description:MotivationOne of the fundamental questions in genetics study is to identify functional DNA variants that are responsible to a disease or phenotype of interest. Results from large-scale genetics studies, such as genome-wide association studies (GWAS), and the availability of high-throughput sequencing technologies provide opportunities in identifying causal variants. Despite the technical advances, informatics methodologies need to be developed to prioritize thousands of variants for potential causative effects.ResultsWe present regSNPs, an informatics strategy that integrates several established bioinformatics tools, for prioritizing regulatory SNPs, i.e. the SNPs in the promoter regions that potentially affect phenotype through changing transcription of downstream genes. Comparing to existing tools, regSNPs has two distinct features. It considers degenerative features of binding motifs by calculating the differences on the binding affinity caused by the candidate variants and integrates potential phenotypic effects of various transcription factors. When tested by using the disease-causing variants documented in the Human Gene Mutation Database, regSNPs showed mixed performance on various diseases. regSNPs predicted three SNPs that can potentially affect bone density in a region detected in an earlier linkage study. Potential effects of one of the variants were validated using luciferase reporter assay.

| S-EPMC3389767 | biostudies-literature

Ranking non-synonymous single nucleotide polymorphisms based on disease concepts.

Project description:As the number of non-synonymous single nucleotide polymorphisms (nsSNPs) identified through whole-exome/whole-genome sequencing programs increases, researchers and clinicians are becoming increasingly reliant upon computational prediction algorithms designed to prioritize potential functional variants for further study. A large proportion of existing prediction algorithms are 'disease agnostic' but are nevertheless quite capable of predicting when a mutation is likely to be deleterious. However, most clinical and research applications of these algorithms relate to specific diseases and would therefore benefit from an approach that discriminates between functional variants specifically related to that disease from those which are not. In a whole-exome/whole-genome sequencing context, such an approach could substantially reduce the number of false positive candidate mutations. Here, we test this postulate by incorporating a disease-specific weighting scheme into the Functional Analysis through Hidden Markov Models (FATHMM) algorithm. When compared to traditional prediction algorithms, we observed an overall reduction in the number of false positives identified using a disease-specific approach to functional prediction across 17 distinct disease concepts/categories. Our results illustrate the potential benefits of making disease-specific predictions when prioritizing candidate variants in relation to specific diseases. A web-based implementation of our algorithm is available at http://fathmm.biocompute.org.uk.

| S-EPMC4083756 | biostudies-literature

Evaluation of non-synonymous NPPA single nucleotide polymorphisms in atrial fibrillation.

Project description:Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is an important cause of morbidity and mortality. A genetic mutation in the NPPA gene, which encodes the atrial natriuretic peptide, has been identified as the putative causative factor in a family with an autosomal dominant pattern of inheritance for AF. Two common single nucleotide polymorphisms (SNPs) in NPPA, rs5063 and rs5065, result in amino acid changes of the primary peptide and have been previously implicated in conditions associated with AF, including stroke and hypertension. Recently, the rs5063 SNP has been reported to confer an increased risk of AF development in a Chinese population. We sought to examine the associations of both rs5063 and rs5065 with AF in two separate North American cohorts of European ancestry.Patients with early-onset AF, along with healthy controls, were recruited at the University of Ottawa Heart Institute (UOHI) and the Massachusetts General Hospital (MGH). Study participants were genotyped for rs5063 and rs5065 using a combination of restriction fragment length polymorphism analysis and DNA microarrays. The study genotyped a total of 620 AF cases and 2446 healthy controls. The UOHI arm of the study identified an odds ratio (OR) of 0.72 [95% confidence interval (CI): 0.42-1.24] for rs5063, whereas an OR of 1.33 (95% CI: 0.80-2.21) was observed in the MGH arm. The combined OR approximated unity (OR 0.99; 95% CI: 0.54-1.80). Analysis of rs5065 revealed an OR of 1.12 (95% CI: 0.84-1.48) in UOHI, 1.08 (95% CI 0.80-1.45) in MGH, and 1.10 (95% CI 0.90-1.35) when combined.Common non-synonymous genetic variants within NPPA in these two large North American cohorts of European ancestry are not associated with the development of AF.

| S-EPMC2910603 | biostudies-literature

Deleterious mis-splicing of STK11 caused by a novel single-nucleotide substitution in the 3' polypyrimidine tract of intron five.

Project description:BackgroundPathogenic variants in STK11, also designated as LKB1, cause Peutz-Jeghers syndrome, which is a rare autosomal dominant disorder characterized by mucocutaneous pigmentation changes, polyposis, and a high risk of cancer.MethodsA male meeting the clinical diagnostic criteria for Peutz-Jeghers syndrome underwent next-generation sequencing. To validate the predicted splicing impact of a detected STK11 variant, we performed RNA-Seq on mRNA extracted from patient-derived Epstein-Barr virus-transformed lymphocytes treated with cycloheximide to inhibit nonsense-mediated decay ex vivo.ResultsBlood testing identified a novel single-nucleotide substitution, NM_000455.4:c.735-10C>A, at the end of the 3' polypyrimidine tract of intron five in STK11. RNA-Seq confirmed a predicted eight base pair insertion in the mRNA transcript. Following inhibition of nonsense-mediated decay, the out-of-frame insertion was detected in 50% of all RNA-Seq reads. This confirmed a strong, deleterious splicing impact of the variant.ConclusionWe characterized a novel likely pathogenic germline variant in intron five of STK11 associated with Peutz-Jeghers syndrome. The study highlights RNA-Seq as a useful supplement in hereditary cancer predisposition testing.

| S-EPMC7507455 | biostudies-literature

Predicting Amino Acid Substitution Probabilities Using Single Nucleotide Polymorphisms.

Project description:Fast genome sequencing offers invaluable opportunities for building updated and improved models of protein sequence evolution. We here show that Single Nucleotide Polymorphisms (SNPs) can be used to build a model capable of predicting the probability of substitution between amino acids in variants of the same protein in different species. The model is based on a substitution matrix inferred from the frequency of codon interchanges observed in a suitably selected subset of human SNPs, and predicts the substitution probabilities observed in alignments between Homo sapiens and related species at 85-100% of sequence identity better than any other approach we are aware of. The model gradually loses its predictive power at lower sequence identity. Our results suggest that SNPs can be employed, together with multiple sequence alignment data, to model protein sequence evolution. The SNP-based substitution matrix developed in this work can be exploited to better align protein sequences of related organisms, to refine the estimate of the evolutionary distance between protein variants from related species in phylogenetic trees and, in perspective, might become a useful tool for population analysis.

| S-EPMC5629329 | biostudies-literature

Reclassification of a TMC1 synonymous substitution as a variant disrupting splicing regulatory elements associated with recessive hearing loss.

Project description:Alterations of the transmembrane channel-like 1 gene (TMC1) are involved in autosomal recessive and dominant nonsyndromic hearing loss (NSHL). To date, up to 117 causal variants including substitutions, insertions and splice variants have been reported in families from different populations. In a patient suffering from severe prelingual NSHL, we identified, in the homozygous state, the previously considered likely benign synonymous c.627C>T; p.(Leu209=) substitution. We used in silico tools predicting variant-induced alterations of splicing regulatory elements (SREs) and pinpointed this transition as a candidate splice-altering variation. Functional splicing analysis, using a minigene assay, confirmed that the variant altered a critical regulatory sequence which is essential for the exon 11 inclusion in the TMC1 transcripts. This result was reinforced by the analysis of orthologous TMC1 mammalian sequences for which the deleterious effect on the mRNA processing of a native thymidine was always counteracted by the presence of a stronger donor splice site or additional enhancer motifs. This study demonstrates, for the first time, the pathogenicity of the c.627C>T alteration leading to its reclassification as a causal variant impacting SREs and highlights the major importance of exhaustive studies to accurately evaluate the pathogenicity of a variant, regardless of the variation type.

| S-EPMC8738754 | biostudies-literature

Genetic association analyses of non-synonymous single nucleotide polymorphisms in diabetic nephropathy.

Project description:Aims/hypothesisDiabetic nephropathy, characterised by persistent proteinuria, hypertension and progressive kidney failure, affects a subset of susceptible individuals with diabetes. It is also a leading cause of end-stage renal disease (ESRD). Non-synonymous (ns) single nucleotide polymorphisms (SNPs) have been reported to contribute to genetic susceptibility in both monogenic disorders and common complex diseases. The objective of this study was to investigate whether nsSNPs are involved in susceptibility to diabetic nephropathy using a case-control design.MethodsWhite type 1 diabetic patients with (cases) and without (controls) nephropathy from eight centres in the UK and Ireland were genotyped for a selected subset of nsSNPs using Illumina's GoldenGate BeadArray assay. A chi (2) test for trend, stratified by centre, was used to assess differences in genotype distribution between cases and controls. Genomic control was used to adjust for possible inflation of test statistics, and the False Discovery Rate method was used to account for multiple testing.ResultsWe assessed 1,111 nsSNPs for association with diabetic nephropathy in 1,711 individuals with type 1 diabetes (894 cases, 817 controls). A number of SNPs demonstrated a significant difference in genotype distribution between groups before but not after correction for multiple testing. Furthermore, neither subgroup analysis (diabetic nephropathy with ESRD or diabetic nephropathy without ESRD) nor stratification by duration of diabetes revealed any significant differences between groups.Conclusions/interpretationThe nsSNPs investigated in this study do not appear to contribute significantly to the development of diabetic nephropathy in patients with type 1 diabetes.

| S-EPMC2687720 | biostudies-literature

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