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Results for “SNV”

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At least 19 recordsLinked to original sources

PubMed1979

DNA of noninfectious and infectious integrated spleen necrosis virus (SNV) is colinear with unintegrated SNV DNA and not grossly abnormal.

The cleavage sites of eight restriction endonucleases in linear spleen necrosis virus (SNV) DNA were mapped, and the map was oriented with respect to viral RNA. With the aid of this map, several structural features of the viral DNA were elucidated: unintegrated linear SNV DNA is terminally redundant; the majority of SNV DNA molecules integrated in chicken DNA, which were previously shown to be present in many sites in cellular DNA, are colinear with unintegrated viral DNA; no tandem integration of proviral molecules is detectable; and the majority of integrated SNV DNA molecules, including integrated SNV DNA molecules previously shown to be noninfectious, do not have an altered restriction enzyme digestion pattern.

Animals↗

PubMed2026

Visual Detection and Stratification of Pathogenic mtDNA SNV Heteroplasmy by Balancing FnCas12a Signal Output and Allelic Discrimination.

Assessment of pathogenic mitochondrial DNA (mtDNA) single-nucleotide variant (SNV) heteroplasmy is important for molecular diagnostics, yet rapid visual profiling remains analytically challenging because an assay must combine single-nucleotide allelic discrimination, mutant-fraction-associated readout, and suitable target access. Herein, we report VISTA (visual identification and stratification of targeted mtDNA alleles), a broad-PAM FnCas12a assay that rebalances trans-cleavage signal output and mutant-wild-type discrimination for visual mtDNA SNV heteroplasmy analysis. VISTA uses unmodified FnCas12a with relaxed TTN PAM recognition and integrates crRNA spacer-length engineering with PEG8000/acBSA reaction tuning to improve the practical signal-discrimination balance without nuclease engineering. At the m.3243A>G model locus, spacer truncation enhanced mutant-wild-type discrimination, while molecular-dynamics simulations identified spacer-dependent differences between matched and mismatched complexes at the crRNA-DNA interface. The optimized assay resolved defined synthetic m.3243A>G heteroplasmy gradients by fluorescence imaging and was further adapted to lateral-flow detection. In locus-specific analyses of a deidentified collection of 74 peripheral-blood samples, fluorescence and lateral-flow readouts achieved ROC AUC values above 0.9 for mutant-allele classification after target-region amplification. Fluorescence supported heteroplasmy-associated profiling, whereas lateral flow provided a visual, semiquantitative readout for relative ranking based on the T/C ratio rather than absolute heteroplasmy measurement. VISTA therefore provides an accessible dual-readout analytical strategy for visual detection and heteroplasmy-associated profiling by tuning the FnCas12a signal output and allelic discrimination.

DNA, Mitochondrial↗

PubMed2026

High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV.

Accurate detection of mutations within bacterial species is critical for fundamental studies of microbial evolution, reconstruction of transmission events, and identification of antimicrobial resistance mutations. Although many tools have been developed to identify single-nucleotide variants (SNVs) from whole-genome sequencing, they often suffer from high false-positive rates owing to the complexity of bacterial genomes and the need for different filtering cutoffs across sample types and sequencing depths. As data sets increase in size, the manual filtering required for high accuracy presents a significant obstacle. Here, we present AccuSNV, a novel deep learning-based tool for high-precision and automated bacterial SNV calling. Unlike traditional methods that process one sample at a time, AccuSNV leverages a convolutional neural network (CNN) that integrates alignment information across multiple samples, enhancing precision through learned across-sample patterns. We evaluate AccuSNV against seven popular SNV-calling tools using simulated data from six bacterial species with varied sequencing depths, numbers of isolates, mutations, and divergence levels. To further validate its real-world utility, we test AccuSNV on multiple curated bacterial data sets containing reported SNVs. In both simulated and real-world scenarios, AccuSNV consistently achieves the best performance. Moreover, AccuSNV provides comprehensive user-friendly downstream analysis modules and outputs, including mutation annotation information, phylogenetic inference, d N/d S calculations, and optional manual filtering. Together with the automated deep learning-based calling, these features make AccuSNV broadly accessible to users with different levels of computational expertise.

Deep Learning↗

PubMed2026

Development of a novel SNV-based genotyping method for Prototheca bovis.

We developed a novel single nucleotide variant (SNV)-based genotyping method for Prototheca bovis based on mitochondrial and plastid genome polymorphisms. Sequencing of five PCR amplicons targeting six informative SNVs discriminated field isolates with a Simpson's D value of 0.927, providing a simple and robust epidemiological typing method.

Journal Article↗

PubMed2025

G4SNVHunter: An R/Bioconductor Package for Evaluating SNV-Induced Disruption of G-Quadruplex Structures Leveraging the G4Hunter Algorithm.

G-quadruplexes (G4s) are nucleic acid secondary structures with important regulatory functions. Single-nucleotide variants (SNVs), one of the most common forms of genetic variation, can potentially impact the formation of G4 structures if they occur within G4 regions. However, there is currently a lack of software tools specifically designed to assess such effects. Here, we present an R/Bioconductor package named G4SNVHunter, which enables rapid detection of variants that may disrupt G4 structures. This tool, based on the core principles of the G4Hunter algorithm, can provide precise quantitative assessment of the propensity for G4 formation within genomic sequences. Specialized experimental methods can then be designed based on the results provided by G4SNVHunter to further verify the specific functions of the affected G4 structures, facilitating deeper insights into the biological impacts of genetic variants from the perspective of G4 structures. To showcase the functionality of the G4SNVHunter package, we analyzed the Neandertal and Denisovan archaic introgressed variants detected by the Sprime software, and identified approximately 5,800 variants located within G4 regions, among which around 230 may impair G4 structure formation propensity. The source code for the G4SNVHunter package has been publicly released under the MIT license at https://github.com/rongxinzh/G4SNVHunter and https://bioconductor.org/packages/devel/bioc/html/G4SNVHunter.html.

G-Quadruplexes↗

PubMed1975

Purification and properties of spleen necrosis virus DNA polymerase.

DNA polymerase was purified to apparent electrophoretic homogeneity from virions of spleen necrosis virus (SNV). (SNV is a member of the reticuloendotheliosis group of avian ribodeoxyviruses). The SNV DNA polymerase appears to consist of a single polypeptide with a molecular weight of 68,000. The SNV DNA polymerase has a preference for Mn2+ for DNA synthesis with an RNA template and Mg2+ for DNA synthesis with a deoxyribohomopolymer template. At the optimum concentrations of divalent cation, the relative rates of DNA synthesis by SNV DNA polymerase with different template.primers were similar to the relative rates of DNA synthesis by an avian leukosis virus DNA polymerase, with the exception of a lower relative rate of DNA synthesis by SNV DNA polymerase with SNV RNA. However, in contrast to DNA synthesized by the avian leukosis virus DNA polymerase with a SNV RNA template, DNA synthesized by SNV DNA polymerase with an SNV RNA template did not hybridize to the SNV RNA. SNV DNA polymerase has RNase H activity which is antigenically distinct from the RNase H activity of avian leukosis-sarcoma virus DNA polymerase.

Animals↗

PubMed1978

Sites of integration of reticuloendotheliosis virus DNA in chicken DNA.

The pattern of integration of spleen necrosis virus (SNV) DNA in DNA from a large population of SNV-infected chicken cells was studied by nucleic acid hybridization with iodinated viral RNA by the blotting technique of Southern. SNV DNA was found to be integrated at multiple sites in acutely infected chicken cells. Concomitant with the transition from acute to chronic infection, a shift in the pattern of integration was observed. The majority of integrated SNV DNA found in acutely infected cells was absent from chronically infected cells. This result is consistent with the hypothesis that the cell death that occurs after infection of avian cells with reticuloendotheliosis viruses is a consequence of the multiple integrations of the provirus. Viral DNA was also integrated at multiple sites in chronically infected cells. However, infectious viral DNA molecules in chronically infected cells migrated in a uniform manner in agarose gel electrophoresis after EcoRI digestion (which does not cut viral DNA), indicating that not all integrated SNV copies are equally infectious.

Acute Disease↗

PubMed1977

Formation of reticuloendotheliosis virus pseudotypes of Rous sarcoma virus.

Superinfection of chicken embryo fibroblasts transformed by the defective Bryan strain of Rous sarcoma virus (BH-RSV) with two different reticuloendotheliosis viruses (REVs), REV strain T (REV-T) or spleen necrosis virus (SNV), resulted in the production of infectious sarcoma virus pseudotypes. These pseudotypes were neutralized by antiserum prepared against SNV and were unable to infect chicken cells preinfected with either REV-T or SNV. These results suggest that defective BH-RSV is able to use the glycoprotein from REV to form infectious pseudotypes. On the other hand, neither REV-T nor SNV was able to supply a functional reverse transcriptase to the polymerase-negative mutant BH-RSValpha, nor was REV-T or SNV able to complement the defect in the internal protein gene of the temperature-sensitive avian sarcoma virus mutant NY45.

Animals↗

PubMed1992

Spleen necrosis virus, an avian immunosuppressive retrovirus, shares a receptor with the type D simian retroviruses.

The reticuloendotheliosis viruses (REV) are a family of highly related retroviruses isolated from gallinaceous birds. On the basis of sequence comparison and overall genome organization, these viruses are more similar to the mammalian type C retroviruses than to the avian sarcoma/leukemia viruses. The envelope of a member of the REV family, spleen necrosis virus (SNV), is about 50% identical in amino acid sequence to the envelope of the type D simian retroviruses. Although SNV does not productively infect primate or murine cells, the receptor for SNV is present on a variety of human and murine cells. Moreover, interference assays show that the receptor for SNV is the same as the receptor for the type D simian retroviruses. We propose that adaptation of a mammalian type C virus to an avian host provided the REV progenitor.

Amino Acid Sequence↗

PubMed1992

Multiple sequence elements are involved in RNA 3' end formation in spleen necrosis virus.

The function of the poly(A) signal in spleen necrosis virus (SNV) is dependent upon the distance between the cap site and the poly(A) site, while the function of the SV40 late poly(A) signal is independent of the distance. Deletions in the SNV poly(A) sequence do not alter the distance-dependent function. SNV/SV40 chimeric poly(A) signals show intermediate behavior between the SNV and SV40 poly(A) signals. These results indicate that multiple sequence elements are involved in the functions of either the SNV or SV40 poly(A) signals. This intermediate behavior is also observed with poly(A) signals from the mouse alpha-globin and herpes simplex virus thymidine kinase genes.

Base Sequence↗

PubMed2025

TSC angiofibroma and ungual fibroma have different mutation signatures, with recurrent mutations in KMT2C.

PURPOSE: Tuberous sclerosis complex (TSC) is an autosomal dominant tumor suppressor syndrome characterized by tumors affecting multiple tissues, including skin, due to inactivating TSC1/TSC2 variants. Genome-wide profiling of somatic mutations in a unique collection of angiofibroma (FAF) and ungual fibroma (UF) TSC skin tumors was performed. METHODS: Genome sequencing was performed on 9 samples, comprising 4 FAF and 5 UF, along with 6 matched normal samples from 6 individuals with TSC. RESULTS: TSC-FAF and TSC-UF skin tumors have different mutation signatures, with a predominance of UV-related single-nucleotide variant (SNV; SBS7a and SBS7b) and dinucleotide variant (DNV; DBS1) signatures in FAF, and aging-related SNV (SBS1 and SBS5) signatures in UF. We also identified a novel DNV signature for TSC-UF, with frequent TG>CA and TT>GG substitutions. Furthermore, 3 inactivating somatic mutations in KMT2C were observed in 2 of 4 TSC-FAF and 5 mutations in other cancer genes. CONCLUSION: The distinct SNV mutation signatures seen in TSC-FAF and UF indicate that they develop through distinct pathogenic mechanisms, UV-induced mutagenesis in FAF, and aging-related mutagenesis in UF. The mechanism of the novel DNV signature in UFs merits further investigation. Our observation on the occurrence of KMT2C mutations suggests that KMT2C inactivation contributes to the pathogenesis of TSC-FAF.

Humans↗

PubMed1979

Pheasant virus DNA polymerase is related to avian leukosis virus DNA polymerase at the active site.

The DNA polymerase from Amherst pheasant virus (APV), a member of the pheasant virus species of retroviruses, was compared to the DNA polymerases of avian leukosis viruses (ALV) and a reticuloendotheliosis virus (spleen necrosis virus (SNV)). Immunoglobulin inhibition tests and competition immunoassays showed that APV and ALV DNA polymerases are closely related at their active sites. The determinants common to their active sites are not shared by SNV DNA polymerase. Bu using a species-specific radioimmunoassay, it was shown that both APV and SNV DNA polymerases are grossly different from ALV DNA polymerase. The specificity of the relationship of the active sites of APV and ALV DNA polymerases was confirmed by a heterologous radioimmunoassay. Our data indicate that pheasant viruses are evolutionarily linked to ALV.

Avian Leukosis Virus↗

PubMed2026

Molecular residual disease assessment in colorectal and bladder cancer by somatic structural variant analysis of cell-free DNA whole-genome sequencing data.

BACKGROUND: Whole-genome sequencing (WGS)-based methods for circulating tumor DNA (ctDNA) detection typically rely on tumor-informed identification of somatic single nucleotide variants (SNVs). Somatic structural variants (SVs) are another type of cancer-specific genomic alteration, which owing to their larger genomic footprint and unique breakpoint junctions, are easier to distinguish from sequencing noise than SNVs. They are, however, rarely used for ctDNA detection because of (1) artifacts from WGS procedures that SV callers may falsely interpret as genuine SVs. This makes it difficult to establish high-confidence SV catalogos from short-read tumor WGS and can cause false-positive ctDNA detections. (2) Lack of robust strategies to quantify SV-supporting reads in plasma WGS. To address these barriers and enable integration of SV biomarkers into WGS-based ctDNA detection, we present a bioinformatic framework for algorithmic curation of somatic SV calls from fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tumors, coupled with a novel approach for sensitive, accurate mapping and quantification of SV breakpoint-supporting reads in plasma WGS. METHODS: Tumor, normal and plasma WGS data from 144 patients with stage III colorectal cancer was used to establish the bioinformatic framework. This included ~30x WGS data from 1564 serially collected plasma samples. The framework was validated using tumor/normal/plasma WGS data from 32 patients with muscle-invasive bladder cancer. SV-based ctDNA detection was benchmarked against previously published SNV-based ctDNA results for the same samples. RESULTS: After curation of SV calls and quantification in plasma WGS, our SV-based approach enabled robust ctDNA detection with overall specificity exceeding 99% in plasma samples. Furthermore, we observed strong concordance (Pearson’s r > 0.93, p < 2.2 × 10− 16) between ctDNA-positive samples identified by our SV-based method and previous SNV-based analyses, validating the reliability of our approach. Finally, we demonstrated application of the method in an independent bladder cancer cohort, highlighting its generalizability and potential clinical use. CONCLUSIONS: We provide a bioinformatic framework that establishes somatic SVs as ultra-specific biomarkers for WGS-based, tumor-informed ctDNA detection. The approach delivers specific detection even when the SV catalogos are established from FFPE samples. The SV framework can stand alone or enhance SNV-based analysis pipelines.

Humans↗

PubMed2026

Cross-kingdom genomic variation in chicken gut microbiomes: insights from China's diverse local breeds.

BACKGROUND: The gut microbiome possesses substantial genetic diversity that supports microbial adaptation, but the genomic variation patterns across its prokaryotic and viral populations remain incompletely characterized. RESULTS: Through integrated metagenomic and metatranscriptomic analysis of ten indigenous chicken breeds from China, we recovered 1527 representative prokaryotic MAGs, 37,555 representative DNA viral contigs, and 1867 representative RNA viral contigs (primarily comprising Bacillota/Bacteroidota, Uroviricota, and Lenarviricota/Pisuviricota, respectively). By integrating complementary short-read and long-read metagenomics with metatranscriptomics, we identified structural variants (SVs) and single-nucleotide variants (SNVs) in these cross-kingdom genomes. Positive SV-SNV density correlations occurred consistently across all microbial groups, indicating coordinated mutational processes. DNA viruses exhibited the highest variant prevalence (86.9% SNVs, 47.7% SVs), with temperate phages accumulating significantly more variants than virulent phages. Functionally, prokaryotic variants accumulated in carbohydrate metabolism and amino acid metabolism, while viral variants demonstrated broad metabolic hijacking. Horizontal gene transfer (HGT) was characterized by a strong virus-associated signature (69.40% of 536 events) and marked by an asymmetric pattern, with phage-to-bacteria (P-to-B) flow alone constituting 37.50% of all events. Random forest analysis revealed a strong bidirectional predictive relationship between SV and SNV densities across prokaryotic, DNA viral, and RNA viral populations, suggesting coupled genomic instability. Niche breadth emerged as a major driver of SNVs across kingdoms and was positively correlated with variant density. In prokaryotes, HGT events significantly shaped variant patterns. For viruses, genomic GC content was an important factor and consistently showed a negative correlation with SNV density in both DNA and RNA viruses. CONCLUSIONS: These findings demonstrate that coordinated mutational processes and kingdom-specific intrinsic factors drive genomic variation, with viruses serving as key genetic exchange vectors in chicken gut ecosystems. Video Abstract.

Animals↗

PubMed1992

Effect of electric charged molecules on Sindbis virus hemagglutination and hemolysis.

The role of electrostatic interactions in the attachment and fusion at acidic pH of Sindbis virus (SNV) with goose erythrocytes was studied, investigating the effect of several anionic and cationic polyelectrolytes on SNV hemagglutination and hemolysis. In order to establish the target of active drugs, the compounds were incubated either with the virus particles or with the erythrocytes. Dextran sulfate was the only compound able to inhibit the attachment of SNV to the erythrocytes. Fusion of virus with red cells was reduced dose-dependently by the polyanions dextran sulfate, mucin and polygalacturonic acid. On the contrary two polycations, polylysine and polybrene, enhanced viral hemolytic activity. However the effect of polyions is not exclusively related to the electric charge since ineffective molecules were found in both classes of compounds.

Animals↗

PubMed2026

Somatic likelihood tiering: an interpretable post-calling triage protocol for tumor-only whole-exome variant review.

Tumor-only whole-exome sequencing (WES) is used when matched normal tissue is unavailable, but one sample can produce thousands of variants. Somatic likelihood tiering (SLT) is an interpretable post-calling protocol that ranks Mutect2 calls into four review-priority tiers using population-frequency, germline-quality, cancer-knowledge, PureCN posterior, and clonal-hematopoiesis evidence. Layer 2 distinguishes common, rare-callable, and unevaluable gnomAD states; missing or unmatchable gnomAD evidence is not positive rarity evidence. On the SEQC2 HCC1395 benchmark, the callability-aware SLT-A row contained 101 calls, 78 truth variants, 77.2% PPV (95% Wilson confidence interval 68.1%-84.3%), and a Number Needed to Review (NNR) of 1.29 (1.19-1.47). The conservative SLT-C catchment retained 352 of 455 truth variants (77.4%, 73.3%-81.0%) and all tiers together retained 430 of 455 truth variants. SNV performance is the primary calibration frame: SLT-C retained 341 of 439 SNV truth variants, whereas indel results were exploratory because only 16 truth indels were available. Clinical cohorts are reported as recall and concordance versus partially dependent matched-normal Mutect2 references, not independent clinical sensitivity. Patient-level bootstrap intervals were principal: HdM-BLCA-1 SLT-A recall was 18.2% (14.0%-23.5%), and LUAD-TW SLT-A recall was 49.1% (26.6%-63.3%) among 32 evaluable patients. The HdM-BLCA-1 median SLT-A queue remained 1277 variants per patient, so SLT reduces first-pass candidate counts but does not measure review time or eliminate FFPE candidate-count burden. SLT provides an auditable tumor-only WES review queue, not a substitute for matched-normal sequencing, independent orthogonal validation, or definitive somatic classification.

Humans↗

PubMed2026

scSNViz: visualization and analysis of cell-specific expressed SNVs.

MOTIVATION: Accurately characterizing expressed genetic variation at the single-cell level is essential for understanding transcriptional heterogeneity, allelic regulation, and mutational dynamics within complex tissues. However, few tools enable comprehensive visualization and quantitative analysis of expressed variants across individual cells. RESULTS: scSNViz is an R package for the exploration, quantification, and visualization of expressed single-nucleotide variants (SNVs) from cell-barcoded single-cell RNA sequencing (scRNA-seq) data. The software supports estimation of variant allele fractions, clustering of SNV expression profiles, and 2D and 3D visualization of individual SNVs or user-defined SNV groups. Beyond visualization, scSNViz facilitates investigation of cell-, cluster-, or lineage-specific variant expression patterns, as well as allelic dynamics including imprinting, random allele inactivation, and transcriptional bursting. It interoperates seamlessly with established single-cell frameworks-Seurat for clustering, Slingshot for trajectory inference, scType for cell-type annotation, and CopyKat for copy-number profiling-enabling integrative multi-omic analyses of expressed variation. AVAILABILITY AND IMPLEMENTATION: scSNViz is implemented in R and freely available at https://github.com/HorvathLab/scSNViz (DOI: 10.5281/zenodo.17307516). The package includes comprehensive documentation and example workflows designed for users with limited bioinformatics experience.

Software↗

PubMed2026

GUANinE v1.1 reveals complementarity of supervised and genomic language models.

There has been much debate about the benefits of supervised versus unsupervised learning on genomes. Determining which is better in what contexts requires developing comprehensive benchmarks spanning functional and evolutionary tasks. Importantly, such benchmarks need large sample sizes to enable well-powered ranking of models. Having developed and applied such a benchmark here (GUANinE v1.1), we conclusively demonstrate each paradigm offers key advantages and outperforms on certain tasks. In accordance with training, supervised sequence-to-function models exhibit strong performance when annotating functional states characterized by chromatin accessibility or histone marks, while self-supervised language models outperform on evolutionary conservation. Our hundreds of new evaluations in this v1.1 expansion provide evidence for a tradeoff between input context size and model parameter count for a fixed compute budget, which we depict with new metrics such as kiloparameters/base pair. We also construct two new large-scale variant interpretation tasks in v1.1: cadd-snv measuring deleteriousness, and clinvar-snv measuring clinical pathogenicity. We find that conservation scores, and by extension, genomic language models, predict deleteriousness well, but successfully translating deleteriousness predictions to pathogenicity remains challenging. GUANinE v1.1 newly evaluates dozens of pretrained genomic models, and we conclude that moderate-context hybrid or post-trained language models may define the next era of machine learning in genomics.

Genomics↗