Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Synonymous Variants of Uncertain Silence.

ABSTRACT: Synonymous variants, traditionally regarded as silent mutations due to their lack of impact on protein sequence, structure and function, have been the subject of increasing scrutiny. This commentary explores the emerging evidence challenging the notion of synonymous variants as functionally inert. Analysis of the activity of 70 synonymous variants in the HIV Tat transcription factor revealed that 50% of the variants exhibited significant deviations from wild-type activity. Our analysis supports previous work and raises important questions about the broader impact of non-silent synonymous variants in human genes. Considering the potential functional implications, the authors propose classifying such variants as "synonymous variants of uncertain silence" (sVUS), highlighting the need for cautious interpretation and further investigations in clinical and genetic testing settings.

SUBMITTER: Giacoletto CJ

PROVIDER: S-EPMC10341574 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Synonymous Variants of Uncertain Silence.

Giacoletto Christopher J CJ Rotter Jerome I JI Grody Wayne W WW Schiller Martin R MR

International journal of molecular sciences 20230623 13

Synonymous variants, traditionally regarded as silent mutations due to their lack of impact on protein sequence, structure and function, have been the subject of increasing scrutiny. This commentary explores the emerging evidence challenging the notion of synonymous variants as functionally inert. Analysis of the activity of 70 synonymous variants in the HIV Tat transcription factor revealed that 50% of the variants exhibited significant deviations from wild-type activity. Our analysis supports ...[more]

PMID: 37445732

Similar Datasets

Broken silence: 22,841 predicted deleterious synonymous variants identified in the human exome through computational analysis.

Project description:Synonymous single nucleotide variants (sSNVs) do not alter the primary structure of a protein, thus it was previously accepted that they were neutral. Recently, several studies demonstrated their significance to a range of diseases. Still, variant prioritization strategies lack focus on sSNVs. Here, we identified 22,841 deleterious synonymous variants in 125,748 human exomes using two in silico predictors (SilVA and CADD). While 98.2% of synonymous variants are classified as neutral, 1.8% are predicted to be deleterious, yielding an average of 9.82 neutral and 0.18 deleterious sSNVs per exome. Further investigation of prediction features via Heterogeneous Ensemble Feature Selection revealed that impact on amino acid sequence and conservation carry the most weight for a deleterious prediction. Thirty nine detrimental sSNVs are not rare and are located on disease associated genes. Ten distinct putatively non-deleterious sSNVs are likely to be under positive selection in the North-Western European and East Asian populations. Taken together our analysis gives voice to the so-called silent mutations as we propose a robust framework for evaluating the deleteriousness of sSNVs in variant prioritization studies.

| S-EPMC10804382 | biostudies-literature

Decoding the effects of synonymous variants.

Project description:Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

| S-EPMC8682775 | biostudies-literature

Quantifying negative selection on synonymous variants.

Project description:Widespread adoption of DNA sequencing has resulted in large numbers of genetic variants, whose contribution to disease is not easily determined. Although many types of variation are known to disrupt cellular processes in predictable ways, for some categories of variants, the effects may not be directly detectable. A particular example is synonymous variants, that is, those single-nucleotide variants that create a codon substitution, such that the produced amino acid sequence is unaffected. Contrary to the original theory suggesting that synonymous variants are benign, there is a growing volume of research showing that, despite their "silent" mechanism of action, some synonymous variation may be deleterious. Here, we studied the extent of the negative selective pressure acting on different classes of synonymous variants by analyzing the relative enrichment of synonymous singleton variants in the human exomes provided by gnomAD. Using a modification of the mutability-adjusted proportion of singletons (MAPS) metric as a measure of purifying selection, we found that some classes of synonymous variants are subject to stronger negative selection than others. For instance, variants that reduce codon optimality undergo stronger selection than optimality-increasing variants. Besides, selection affects synonymous variants implicated in splice-site-loss or splice-site-gain events. To understand what drives this negative selection, we tested a number of predictors in the aim to explain the variability in the selection scores. Our findings provide insights into the effects of synonymous variants at the population level, highlighting the specifics of the role that these variants play in health and disease.

| S-EPMC10835449 | biostudies-literature

Inferring Potential Cancer Driving Synonymous Variants.

Project description:Synonymous single nucleotide variants (sSNVs) are often considered functionally silent, but a few cases of cancer-causing sSNVs have been reported. From available databases, we collected four categories of sSNVs: germline, somatic in normal tissues, somatic in cancerous tissues, and putative cancer drivers. We found that screening sSNVs for recurrence among patients, conservation of the affected genomic position, and synVep prediction (synVep is a machine learning-based sSNV effect predictor) recovers cancer driver variants (termed proposed drivers) and previously unknown putative cancer genes. Of the 2.9 million somatic sSNVs found in the COSMIC database, we identified 2111 proposed cancer driver sSNVs. Of these, 326 sSNVs could be further tagged for possible RNA splicing effects, RNA structural changes, and affected RBP motifs. This list of proposed cancer driver sSNVs provides computational guidance in prioritizing the experimental evaluation of synonymous mutations found in cancers. Furthermore, our list of novel potential cancer genes, galvanized by synonymous mutations, may highlight yet unexplored cancer mechanisms.

| S-EPMC9140830 | biostudies-literature

Saturation functional assays of MUTYH resolve clinical variants of uncertain significance

Project description:Variants of uncertain significance (VUS) limit the actionability of genetic testing. A prominent example is MUTYH, a base excision repair factor associated with polyposis and colorectal cancer, which has a pathogenic variant carrier rate approaching 1 in 50 individuals in some populations. To systematically interrogate variant function in MUTYH, we coupled deep mutational scanning with a DNA repair reporter containing its lesion substrate, 8OG:A. Our variant-to-function map covers >97% of all possible MUTYH point variants (n=10,941) and achieves 100% accuracy classifying pathogenicity of known clinical variants (n=247). Leveraging a large clinical registry, we observe significant associations with colorectal polyps and cancer, with more severely impaired missense variants conferring greater risk. We recapitulate known functional differences between pathogenic founder mutations and highlight sites of complete missense intolerance, including residues that intercalate DNA and coordinate essential Zn2+ or Fe-S clusters. This map provides a resource to resolve the 1,122 existing clinical missense VUS in MUTYH and demonstrates a scalable strategy to interrogate other clinically relevant DNA repair factors.

2025-03-01 | GSE290379 | GEO

Evaluation of Suspected Autosomal Alport Syndrome Synonymous Variants.

Project description:BackgroundAlport syndrome is an inherited disorder characterized by progressive renal disease, variable sensorineural hearing loss, and ocular abnormalities. Although many pathogenic variants in COL4A3 and COL4A4 have been identified in patients with autosomal Alport syndrome, synonymous mutations in these genes have rarely been identified.MethodsWe conducted in silico splicing analysis using Human Splicing Finder (HSF) and Alamut to predict splicing domain strength and disruption of the sites. Furthermore, we performed in vitro splicing assays using minigene constructs and mRNA analysis of patient samples to determine the pathogenicity of four synonymous variants detected in four patients with suspected autosomal dominant Alport syndrome (COL4A3 [c.693G>A (p.Val231=)] and COL4A4 [c.1353C>T (p.Gly451=), c.735G>A (p.Pro245=), and c.870G>A (p.Lys290=)]).ResultsBoth in vivo and in vitro splicing assays showed exon skipping in two out of the four synonymous variants identified (c.735G>A and c.870G>A in COL4A4). Prediction analysis of wild-type and mutated COL4A4 sequences using HSF and Alamut suggested these two variants may lead to the loss of binding sites for several splicing factors, e.g., in acceptor sites and exonic splicing enhancers. The other two variants did not induce aberrant splicing.ConclusionsThis study highlights the pitfalls of classifying the functional consequences of variants by a simple approach. Certain synonymous variants, although they do not alter the amino acid sequence of the encoded protein, can dramatically affect pre-mRNA splicing, as shown in two of our patients. Our findings indicate that transcript analysis should be carried out to evaluate synonymous variants detected in patients with autosomal dominant Alport syndrome.

| S-EPMC9034806 | biostudies-literature

In silico methods for predicting functional synonymous variants.

Project description:Single nucleotide variants (SNVs) contribute to human genomic diversity. Synonymous SNVs are previously considered to be "silent," but mounting evidence has revealed that these variants can cause RNA and protein changes and are implicated in over 85 human diseases and cancers. Recent improvements in computational platforms have led to the development of numerous machine-learning tools, which can be used to advance synonymous SNV research. In this review, we discuss tools that should be used to investigate synonymous variants. We provide supportive examples from seminal studies that demonstrate how these tools have driven new discoveries of functional synonymous SNVs.

| S-EPMC10204308 | biostudies-literature

Functional characterization of 84 PALB2 variants of uncertain significance.

Project description:PurposeInherited pathogenic variants in PALB2 are associated with increased risk of breast and pancreatic cancer. However, the functional and clinical relevance of many missense variants of uncertain significance (VUS) identified through clinical genetic testing is unclear. The ability of patient-derived germline missense VUS to disrupt PALB2 function was assessed to identify variants with potential clinical relevance.MethodsThe influence of 84 VUS on PALB2 function was evaluated using a cellular homology directed DNA repair (HDR) assay and VUS impacting activity were further characterized using secondary functional assays.ResultsFour (~5%) variants (p.L24S,c.71T>C; p.L35P,c.104T>C; pI944N,c.2831T>A; and p.L1070P,c.3209T>C) disrupted PALB2-mediated HDR activity. These variants conferred sensitivity to cisplatin and a poly(ADP-ribose) polymerase (PARP) inhibitor and reduced RAD51 foci formation in response to DNA damage. The p.L24S and p.L35P variants disrupted BRCA1-PALB2 protein complexes, p.I944N was associated with protein instability, and both p.I944N and p.L1070P mislocalized PALB2 to the cytoplasm.ConclusionThese findings show that the HDR assay is an effective method for screening the influence of inherited variants on PALB2 function, that four missense variants impact PALB2 function and may influence cancer risk and response to therapy, and suggest that few inherited PALB2 missense variants disrupt PALB2 function in DNA repair.

| S-EPMC7056643 | biostudies-literature

Synonymous variants associated with Alzheimer disease in multiplex families.

Project description:ObjectiveSynonymous variants can lead to disease; nevertheless, the majority of sequencing studies conducted in Alzheimer disease (AD) only assessed coding variation.MethodsTo detect synonymous variants modulating AD risk, we conducted a whole-genome sequencing study on 67 Caribbean Hispanic (CH) families multiply affected by AD. Identified disease-associated variants were further assessed in an independent cohort of CHs, expression quantitative trait locus (eQTL) data, brain autopsy data, and functional experiments.ResultsRare synonymous variants in 4 genes (CDH23, SLC9A3R1, RHBDD2, and ITIH2) segregated with AD status in multiplex families and had a significantly higher frequency in these families compared with reference populations of similar ancestry. In comparison to subjects without dementia, expression of CDH23 (β = 0.53, p = 0.006) and SLC9A3R1 (β = 0.50, p = 0.02) was increased, and expression of RHBDD2 (β = -0.70, p = 0.02) decreased in individuals with AD at death. In line with this finding, increased expression of CDH23 (β = 0.26 ± 0.08, p = 4.9E-4) and decreased expression of RHBDD2 (β = -0.60 ± 0.12, p = 5.5E-7) were related to brain amyloid load (p = 0.0025). SLC9A3R1 expression was associated with burden of TDP43 pathology (β = 0.58 ± 0.17, p = 5.9E-4). Using eQTL data, the CDH23 variant was in linkage disequilibrium with variants modulating CDH23 expression levels (top single nucleotide polymorphism: rs11000035, p = 4.85E-6, D' = 1.0). Using minigene splicing assays, the CDH23 and SLC9A3R1 variants affected splicing efficiency.ConclusionsThese findings suggest that CDH23, SLC9A3R1, RHBDD2, and possibly ITIH2, which are involved in synaptic function, the glutamatergic system, and innate immunity, contribute to AD etiology. In addition, this study supports the notion that synonymous variants contribute to AD risk and that comprehensive scrutinization of this type of genetic variation is warranted and critical.

| S-EPMC7323483 | biostudies-literature

A combined functional annotation score for non-synonymous variants.

Project description:AimsNext-generation sequencing has opened the possibility of large-scale sequence-based disease association studies. A major challenge in interpreting whole-exome data is predicting which of the discovered variants are deleterious or neutral. To address this question in silico, we have developed a score called Combined Annotation scoRing toOL (CAROL), which combines information from 2 bioinformatics tools: PolyPhen-2 and SIFT, in order to improve the prediction of the effect of non-synonymous coding variants.MethodsWe used a weighted Z method that combines the probabilistic scores of PolyPhen-2 and SIFT. We defined 2 dataset pairs to train and test CAROL using information from the dbSNP: 'HGMD-PUBLIC' and 1000 Genomes Project databases. The training pair comprises a total of 980 positive control (disease-causing) and 4,845 negative control (non-disease-causing) variants. The test pair consists of 1,959 positive and 9,691 negative controls.ResultsCAROL has higher predictive power and accuracy for the effect of non-synonymous variants than each individual annotation tool (PolyPhen-2 and SIFT) and benefits from higher coverage.ConclusionThe combination of annotation tools can help improve automated prediction of whole-genome/exome non-synonymous variant functional consequences.

| S-EPMC3390741 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data