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Results for “Single-nucleotide polymorphism”

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PubMed2026

Genetic regulation of AIF1 shapes immune and liver injury profiles in chronic alcohol use.

BACKGROUNDIn chronic alcohol consumers, immune cells may drive the progression from mild liver injury to more severe alcohol-associated liver disease (ALD), including alcohol-associated hepatitis (AAH) and cancer. Liver macrophages, both resident and infiltrating, express allograft inflammatory factor 1 (AIF1), which is upregulated during inflammation and enhances immune activation.METHODSUsing serum and urine samples from 868 individuals classified as having alcohol use disorder or not, based on DSM-IV/V criteria, along with serum and liver biopsy tissue from a second cohort of 27 patients diagnosed with AAH, we evaluated the impact of the AIF1 promoter single-nucleotide polymorphism (SNP) (rs3132451; C/C, C/G, G/G) on liver function markers and immune cell profiles.RESULTSAIF1 transcript levels were genotype dependent: C/C homozygotes expressed 5.2% of the levels observed in G/G individuals, while C/G heterozygotes expressed 46%. Unlike most SNPs associated with harmful effects, the G/G genotype is highly prevalent, present in about 70% of patients. Among chronic alcohol users, G/G individuals exhibited elevated markers of liver injury and a more than 3-fold increase in hepatic immune cells, including infiltrating AIF1+ macrophages and neutrophils. Despite similar durations of alcohol misuse, G/G individuals had higher Model for End-Stage Liver Disease scores compared with C/G individuals, indicating a significantly greater 90-day mortality risk. Notably, some immune abnormalities, such as elevated neutrophils, persisted in G/G males even after alcohol abstinence.CONCLUSIONThese findings suggest that functional genetic variation in AIF1 may contribute to the severity and persistence of ALD.TRIAL REGISTRATIONClinicalTrials.gov NCT02231840.FUNDINGResearch support was provided from the National Institute on Alcohol Abuse and Alcoholism of the NIH under grants 1ZIAAA000440-02 and R24AA025017.

Humans↗

PubMed2026

Development and optimization of T-ARMS PCR assays for detection of lethal haplotypes of TADA2A, UR1B, and PORL1B in pigs in Vietnam.

Marker-assisted selection has increasingly relied on single-nucleotide polymorphisms (SNPs) as robust genetic markers, particularly in livestock breeding programs. In pig farming, embryonic mortality significantly affects litter size, and SNPs in reference genes have been implicated as potential causal factors. We developed and optimized a tetra-primer amplification refractory mutation system (T-ARMS) PCR assay for rapid, cost-effective detection of SNPs in 3 candidate genes-TADA2A, PORL1B, URB1-that are associated with embryonic lethality and reproductive performance. Primer sets were designed based on known mutation sites and validated using synthetic gene constructs and porcine genomic DNA from pigs of Duroc and Landrace breeds. Optimization of annealing temperatures and primer concentration ratios yielded distinct and reproducible allele-specific amplicon patterns that were corroborated by PCR-RFLP and Sanger sequencing. Our T-ARMS PCR protocol, which requires minimal equipment and reduces processing time to <3 h, had high specificity and efficiency in differentiating wild-type, heterozygous, and homozygous mutant genotypes in 20 Duroc and 20 Landrace pigs. Our Tetra-ARMS PCR assay is a robust and economically viable tool for SNP genotyping in pig breeding programs, potentially contributing to the reduction of embryonic lethality and the improvement of overall reproductive outcomes.

Sus scrofa↗

PubMed2026

SNP genotyping in Pseudotsuga menziesii and Pinus radiata using targeted genotyping-by-sequencing (GBS): improved Bayesian SNP calling using a beta-binomial distribution and other optimized input parameters.

BACKGROUND: Single-nucleotide polymorphism markers (SNPs) have important applications in gene conservation, breeding, and fundamental genetics research. Our long-term goal is to develop routine approaches for SNP genotyping in forest trees. Ideally, these approaches would be inexpensive, able to accommodate a wide range of samples and SNPs, available through commercial providers, and produce high-quality SNP data. RESULTS: Using targeted genotyping-by-sequencing (GBS), we developed SNP assays for two highly heterozygous tree species, Douglas-fir (Pseudotsuga menziesii) and radiata pine (Pinus radiata). Using Douglas-fir haploid and diploid data, we optimized Bayesian SNP calling by testing four input parameters: (1) allele and genotype prior probabilities, (2) Rho, the beta-binomial dispersion parameter, (3) estimated read error (BayesReadError), and (4) the logPO cutoff used to filter low confidence SNP calls. logPO is the Bayesian posterior odds ratio for a called SNP. Compared to assuming a binomial distribution of read counts (Rho = 0), the beta-binomial distribution (Rho = 0.33) substantially reduced call error and heterozygote undercalling. Compared to the other Bayesian parameters, genotype priors had little effect on genotyping success. For Douglas-fir, we tested 5,360 SNP assays, and then studied the performance of the best 4,000. For radiata pine, we tested 6,000 SNP assays, and then studied the performance of the best 4,570. In Douglas-fir and radiata pine, our Bayesian approach resulted in median call rates of 95% to 98% for the top-ranked SNPs, with an estimated call error of 1.60% for known homozygous genotypes and 2.27% for known heterozygotes. In radiata pine, median and mean call rates were above 91% for GBS and SNP genotyping using an Axiom fixed genotyping array. Additionally, the median correspondence between the GBS and Axiom genotypes was about 98% overall (mean 96%). CONCLUSIONS: By optimizing Bayesian SNP calling, selecting the best 4-5 K SNPs, and excluding samples with low DNA amounts, we substantially reduced call error and heterozygote undercalling, resulting in SNP genotypes that were nearly identical to genotypes obtained using the Axiom array. Furthermore, genotyping performance should increase even further if our SNP rankings were used to develop less complex probe pools that target fewer SNPs.

Pinus↗

PubMed2026

Linking cortical structure and delirium in the elderly: insights from cohort study and shared genetic risk analysis.

BACKGROUND: This study aimed to assess the association between regional cortical changes measured via baseline magnetic resonance imaging (MRI) and the incidence of delirium. METHODS: Observational associations were assessed using a prospective cohort from the UK Biobank and an independent clinical cohort. The population-based study included participants aged 60 years or older who had undergone structural brain MRI since 2014. Regional cortical volume, mean thickness, and surface area were extracted based on the Desikan-Killiany cortical atlas. Delirium was defined using ICD-10 diagnostic codes. Additionally, preoperative brain MRI images from participants in another cohort were collected and automatically segmented using deep learning algorithms to obtain cortical measurements. Logistic analysis was performed to investigate the associations between cerebral cortical structure and delirium risk. Lastly, genome-wide association study data derived from the ENIGMA Consortium and FinnGen Biobank were utilized to conduct conditional/conjunctional false discovery rate (cond/conjFDR) analyses to identify shared genetic loci associated with cortical structures and delirium. RESULTS: This observational analysis included 31,890 participants from the UK Biobank and 152 participants from an independent cohort. In the UK Biobank cohort, decreased cortical thickness in the 17 regions was associated with a significantly increased risk of delirium. Similarly, a preoperative reduction in cortical volume in 7 regions was associated with an increased risk of delirium in the independent cohort. Besides, 100 single-nucleotide polymorphisms (SNPs) were identified as significantly associated with cortical structures when conditioned on delirium. Finally, colocalization analysis demonstrated that these pleiotropic risk loci modulated the expression of NT5C2, RGP1, CCDC25, TPM2, EEF1AKMT2, IQANK1 and LHPP in blood and brain tissues. CONCLUSION: Regional cortical atrophy is associated with an increased risk of delirium in the elderly. Brain MRI examinations may be beneficial for preoperative delirium risk assessment in elderly individuals undergoing elective surgery.

Humans↗

PubMed2026

Programmed cell death and risk of diabetic retinopathy: a Mendelian randomization study.

BACKGROUND: Programmed cell death (PCD) plays an important role in diabetic retinopathy (DR); however, the underlying genetic mechanisms remain unclear. We used Mendelian randomization (MR) to investigate the causal relationships between PCD-related genes and DR. This study aimed to investigate the effects of PCD on the risk of DR by conducting MR analysis. METHODS: Summary statistics from gene expression quantitative trait loci (eQTL) studies (31,684 Europeans) were analyzed. Genetic instrumental variables were selected using cis-eQTL single-nucleotide polymorphisms (SNPs; P < 5 × 10- 8). Summary data-based MR (SMR) was employed to assess causal associations between PCD-related genes and DR, with three additional MR methods used for sensitivity testing. Bayesian colocalization was used to examine the shared regulatory mechanisms between PCD QTLs and DR risk loci. RESULTS: Sensitivity and colocalization analyses revealed six genes that affected DR: cathepsin H (CTSH), NAD(P)H: quinone oxidoreductase 1 (NQO1), tribbles pseudokinase 3 (TRIB3), and phosphoglycerate mutase 5 (PGAM5), which increased DR risk, and iron-responsive element binding protein 2 (IREB2) and tumor necrosis factor (TNF), which exhibited protective effects. Multivariate MR confirmed significant causal effects for CTSH, IREB2, and PGAM5 (p < 0.050). Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis (including 10 STRING-derived genes) revealed that 13 genes were enriched in necroptosis, apoptosis, mitophagy, and TNF signaling pathways in DR. CONCLUSIONS: This MR study supports the causal involvement of PCD in DR and identifies candidate genes (CTSH, IREB2, PGAM5, NQO1, TRIB3, and TNF) for therapeutic targeting or biomarker development in DR prevention or diagnosis.

Humans↗

PubMed2026

Whole-Exome and Whole-Genome Sequencing of Candidate Pharmacogenomic and Schizophrenia-Related Genes in Sudanese Families with Schizophrenia.

BACKGROUND: Schizophrenia is considered a neuro-developmental disorder leading to disastrous lifelong disability of the patients and their families. There is a lack of data regarding pharmacogenomics of schizophrenia in Sudan. This study aimed to identify different genes affecting the treatment outcomes in Sudanese patients with schizophrenia. METHODS: A case-control study was conducted on seven families having more than one member diagnosed with schizophrenia. This was a small exploratory family-based sequencing study involving 18 affected individuals and 8 controls from seven families. Ethical clearance and informed consent were obtained. Demographic data were collected using a standardized data collection sheet. DNA was extracted from blood samples collected from patients and control groups. Then, whole-exome and genome sequencing were performed. Sixty-six genes associated with schizophrenia, treatment, and treatment resistance were selected from the variant calling file. Variants showing single-nucleotide polymorphisms (SNPs) were identified. These variants were then classified based on their impact on the protein-coding sequence into high- and moderate-impact. Moreover, indel mutations were also identified. RESULTS: Twelve variants of seven genes (COMT, FMO1, LPL, CYP2E1, ABCC1, GRM3, CYP2C9) were identified as genes with impact and potential association with schizophrenia (p-value=0.006632). Forty-three genes had a moderate impact, and they showed a potential association with schizophrenia (p-value=0.0004436). Two variants were indel mutations (CYP2D6, DTNBP1) and showed association with schizophrenia (p-value=0.004741). The p-values were generated from different databases. CONCLUSION: This exploratory family-based sequencing study identified several potentially relevant pharmacogenomic and schizophrenia-associated variants in Sudanese families, warranting validation in larger and ethnically diverse cohorts.

antipsychotics↗

PubMed2026

Genetic associations in sepsis and ARDS.

Critical illness syndromes, such as sepsis and acute respiratory distress syndrome (ARDS), are characterized by substantial clinical heterogeneity and remain major causes of morbidity and mortality worldwide. Increasing evidence suggests that genetic variation contributes to susceptibility, disease severity, and clinical outcomes in critically ill patients. However, the molecular mechanisms linking genetic predisposition to the pathophysiology of sepsis and ARDS remain incompletely understood. In this review, we evaluated genetic associations reported in sepsis and ARDS, including 13 genome-wide studies identifying 19 unique single-nucleotide polymorphisms (SNPs) across 17 distinct genomic loci, as well as 21 meta-analyses of candidate-gene studies identifying 21 SNPs across 16 genes. The identified variants were primarily associated with pathways involved in pathogen recognition, immune and inflammatory signaling, leukocyte recruitment, and endothelial dysfunction. Collectively, these findings support a polygenic basis for susceptibility to critical illness and highlight several biologically relevant pathways that may contribute to sepsis and ARDS pathogenesis. Improved understanding of the functional consequences of these variants may facilitate the identification of potential therapeutic targets and support the development of precision-guided approaches to critical care.

ARDS↗

PubMed2026

Genetic diversity, phylogenetic relationships, and marker development between Hydrangea serrata and H. macrophylla based on plastome and 45S nrDNA.

Ornamental hydrangeas (genus Hydrangea) are cultivated worldwide for their diverse flower colors and attractive morphology. Here, we assembled the complete plastid genome (plastome) and 45S nuclear ribosomal DNA (45S nrDNA) sequences of 22 individuals representing H. serrata, H. macrophylla, and related species (H. arborescens, H. paniculata, H. petiolaris, and H. hydrangeoides). The plastomes contained up to 2,344 single-nucleotide polymorphisms (SNPs) and 367 insertions/deletions (InDels) within the genus, whereas the assembled 45S nrDNA sequences showed 119 SNPs and 10 InDels. Phylogenetic analyses based on plastome and 45S nrDNA sequences clearly separated H. serrata and H. macrophylla from the other Hydrangea species. In the plastome-based tree, H. petiolaris was placed in the same clade as H. arborescens, whereas in the 45S nrDNA-based tree it showed a close relationship to H. hydrangeoides. The H. serrata and H. macrophylla samples were not always separated according to their species boundaries, as observed in samples Hse8-Hse12. Notably, one H. serrata sample (Hse8), collected from a wild mountainous region of Japan, exhibited a closer genetic relationship to H. macrophylla samples, indicating that cultivated hydrangeas may have originated from a specific wild lineage of H. serrata adapted to mountainous habitats. Using plastome-derived molecular markers, 66 Hydrangea samples were further classified into five groups, with Group II comprising both cultivated H. macrophylla and a subset of wild H. serrata samples, suggesting a close genetic affinity between this group and the ancestral gene pool of cultivated H. macrophylla. Based on these genomic resources, eight plastome-derived molecular markers were developed to differentiate cultivated hydrangeas from wild genotypes and to assess genetic diversity within H. serrata and H. macrophylla, providing practical tools for germplasm identification, breeding, and genetic resource management of Hydrangea species.

hydrangea↗

PubMed2026

Assessing the Association Between Age at First Sexual Intercourse and HIV Infection Risk Using A Two-sample Mendelian Randomization Framework.

This study applied a two-sample Mendelian randomization framework to investigate the potential association between age at first sexual intercourse (AFS) and the risk of Human Immunodeficiency Virus (HIV) infection. Summary-level Genome-Wide Association Study (GWAS) data from European populations were analyzed, including 214,547 individuals for AFS and 357 HIV cases with 218,435 controls from the FinnGen R5 dataset. Independent single-nucleotide polymorphisms significantly associated with AFS were selected as instrumental variables following linkage disequilibrium clumping and instrument-strength assessment. Causal estimates were evaluated using inverse-variance weighting (IVW), MR-Egger regression, weighted median, weighted mode, and simple mode. Cochran's Q test, MR-Egger intercept analysis, MR-PRESSO assessment, and leave-one-out sensitivity analyses were performed to evaluate heterogeneity, pleiotropy, and robustness. The IVW analysis suggested that genetically predicted later AFS was associated with reduced HIV infection risk (OR = 0.192, 95% CI = 0.062-0.592, P = 0.004), whereas earlier sexual debut corresponded to increased HIV susceptibility. Directionally consistent findings across multiple Mendelian randomization methods supported the stability of the observed association. However, the findings should be interpreted cautiously because the HIV outcome analysis relied on a single dataset with a limited number of HIV cases. These results support a potential association between earlier sexual debut and HIV susceptibility and demonstrate the utility of Mendelian randomization for investigating behavioral risk factors associated with infectious disease outcomes.

Humans↗

PubMed2025

Understanding recurrence in Mycobacterium avium complex pulmonary disease: genotypic strategies to support clinical decision-making.

Pulmonary disease caused by Mycobacterium avium complex (MAC-PD) is a chronic, recurrent disease, and its high recurrence rate after treatment makes clinical management difficult. Distinguishing whether recurrence is due to persistence of existing strains or reinfection with new strains is essential for establishing treatment strategies, preventing overuse of antimicrobials, and establishing infection control measures. According to reports, 54%-74% of MAC-PD recurrence is due to reinfection, which may be mainly related to environmental reservoirs such as household water supply. In this review, we present various clinical scenarios in which MAC-PD recurrence may occur and examine genotyping techniques as a strategy to distinguish and respond to them. From traditional methods such as IS1245-based restriction fragment length polymorphism, pulsed-field gel electrophoresis, and hsp65 and rpoB gene sequencing to high-resolution analysis techniques such as multilocus sequence testing and whole-genome sequencing, the latest molecular typing methods are comprehensively summarized. Integrating these genotype data into clinical settings, standardizing single-nucleotide polymorphism-based interpretation thresholds, and promoting the establishment of a global MAC strain database will make a substantial contribution to more accurately distinguishing the recurrence mechanisms of MAC-PD and establishing personalized treatment strategies.IMPORTANCEThe global burden of nontuberculous mycobacterial pulmonary disease (PD) is increasing, with Mycobacterium avium (MAC)-PD being the most prevalent and clinically challenging form. Its low treatment success rates, high frequency of recurrence, and persistent environmental exposure complicate both diagnosis and management. A critical clinical issue is determining whether recurrence represents true relapse, due to persistence of the original strain, or reinfection with a new strain, as this guides treatment and prevents overtreatment. Genotypic strategies capable of resolving strain-level differences can improve diagnostic accuracy, prevent misclassification, and ultimately support more informed treatment decisions. Therefore, integrating genotyping data into clinical workflows, standardizing single-nucleotide polymorphism thresholds, and establishing a global MAC strain database will not only support personalized treatment but also enhance the broader public health response to this disease.

Humans↗

PubMed2026

TET2 promotes monocyte inflammatory activation in asthma via ALKBH5-m6A regulation and PI3K signaling: evidence from m6A-SNP and single-cell analyses.

Asthma is a complex inflammatory airway disease with strong genetic determinants, yet the functional relevance of most asthma-associated non-coding variants remains unclear. Emerging evidence suggests that N6-methyladenosine (m6A) modification may serve as a critical epitranscriptomic link between genetic variation and immune regulation. In this study, we aimed to systematically identify functionally relevant m6A-regulated genes in asthma by integrating large-scale GWAS data, m6A-SNP annotations, and single-cell transcriptomic analyses, and to investigate their roles in monocyte-driven airway inflammation. We identified TET2 as a key m6A-regulated gene associated with both asthma and lung function, which was selectively upregulated in monocytes during asthma and accompanied by activation of inflammatory and PI3K signaling pathways. Mechanistic experiments further demonstrated that inflammatory stimulation induced ALKBH5 expression, reduced m6A modification of TET2 mRNA, and increased TET2 protein levels, thereby promoting PI3K/AKT signaling and pro-inflammatory cytokine production, whereas inhibition of TET2 or ALKBH5 attenuated these effects. Collectively, these findings demonstrate that ALKBH5-mediated m6A regulation of TET2 enhances PI3K/AKT signaling in monocytes, thereby promoting inflammatory responses in asthma. Our study establishes TET2 as a key m6A-regulated gene linking genetic susceptibility to monocyte-driven inflammation, and highlights the ALKBH5-m6A-TET2 axis as a potential therapeutic target for modulating aberrant immune responses in asthma.

Humans↗

PubMed2026

Influence of FAM13A gene polymorphism and serum matrix metalloproteinases 9 and 12 on the phenotypes of chronic obstructive pulmonary disease.

PURPOSE: FAM13A as a susceptibility gene for chronic obstructive pulmonary disease(COPD).Many studies verified that FAM13A involved epithelial‒mesenchymal transition (EMT) via the TGF-β1 pathway, some accompanied by an increase in MMP levels. The present study aimed to explore the disease susceptibility of the FAM13A gene, with clinical phenotypes, and investigate the relationships between FAM13A SNP loci and the serum levels of MMP-9 and MMP-12. PATIENTS AND METHODS: We recurited 497 patients with stable COPD patients and 303 healthy controls. Data on blood tests, pulmonary function, and HRCT imaging were collected. Serum MMP-9 and MMP-12 levels were measured by ELISA. Genomic DNA was extracted, and SNPs in the FAM13A gene were detected using targeted region genotyping chips. Logistic regression analysis was performed to assess the associations between SNP loci and COPD susceptibility. Differences in pulmonary function, haematological indicators, bronchial wall thickness, and emphysema parameters among different genotypes were evaluated. Multiple linear regression analysis was used to explore the relationship between genotypes and serum MMP-12 level. RESULTS: We screened a total of 476 SNPs and identified the rs2869947 polymorphism in the FAM13A gene as significantly associated with an increased risk of COPD,Stratified analyses further revealed that this association was particularly in males and individual with BMI ≥ 24.Serum levels of MMP-9 and MMP-12 were significantly higher in COPD patients compared with healthy controls. Genotype(AA vs.GG) showed no significant association with pulmonary function severity,bronchial wall indices,hematological marker,and serum MMP-9 levels in COPD patients(P > 0.05).Compared with GG genotype, AA genotype presented significantly higher LAA-950% and serum MMP-12 levels (P = 0.049 and P = 0.023). CONCLUSION: Our findings suggest that the FAM13A SNP rs2869947 may be associated with COPD susceptibility in the Han Chinese population. The FAM13A AA genotype increased serum MMP-12 levels and correlated with emphysema phenotype.

Humans↗

PubMed2026

Genetic Identification of Burned Human Remains: A Systematic Review.

Background/Objectives: DNA-based identification of degraded human remains represents a major challenge in forensic science, particularly in cases involving burned, fragmented, or commingled bodies. Advances in forensic genetics have expanded the analytical capabilities for such samples; however, the effectiveness of different approaches and their integration within Disaster Victim Identification (DVI) workflows remain heterogeneous. This systematic review aims to critically evaluate current evidence on DNA-based identification of degraded remains, focusing on methodological strategies, emerging genomic technologies, and DVI applications, while integrating laboratory evidence and operational forensic practice into a structured analytical framework. Methods: A systematic literature search was conducted in Scopus and Web of Science from database inception to 5 June 2026, following PRISMA 2020 guidelines. Eligible studies included original research addressing DNA analysis of degraded, thermally altered, or highly compromised human remains in forensic or DVI contexts. After a multistep screening process involving title/abstract and full-text evaluation, 37 studies were included. Data were extracted and organized into three thematic categories: (i) core DNA analysis, (ii) advanced molecular technologies, and (iii) DVI case applications. Results: The findings demonstrate that DNA recovery from degraded remains is influenced by thermal exposure, tissue type, and sampling strategy. Teeth and dense cortical bone consistently provide higher DNA yield. While autosomal STR profiling remains the primary analytical approach, its limitations in highly degraded samples are mitigated through the complementary use of mitochondrial DNA (mtDNA), Y-chromosome STRs (Y-STRs), and SNP markers, together with advanced sequencing technologies such as massively parallel sequencing (MPS). Emerging technologies, including rapid DNA systems and predictive models based on macroscopic indicators, significantly enhance efficiency and success rates. DVI studies report identification rates exceeding 90-95% when multidisciplinary and structured workflows are applied. The evidence further supports a flexible triage-based analytical strategy, in which marker selection is guided by tissue preservation and degradation level. Conclusions: DNA-based identification of degraded human remains has evolved into an adaptive, multi-level forensic process. Successful outcomes rely on the integration of optimized sampling, hierarchical genetic analysis, and coordinated DVI strategies. The findings support a triage-based framework that links tissue selection, degradation assessment, and analytical methodology to maximize identification success. Future developments should focus on predictive models, advanced genomic tools, and standardized workflows to further improve identification in challenging forensic scenarios.

Humans↗

PubMed2026

Polysomal Profiling Coupled to Allele-Specific Proteomics Reveals an EIF4H TranSNP Allele Possessing Higher mRNA Translation Potential.

To search for genetic sources of allele-specific mRNA translation, we leveraged heterozygous polymorphisms and variants present in the exome of HCT116 colorectal adenocarcinoma-derived cells, computing allelic fractions from both total and polysome-associated RNA from RNA-Seq data. Allelic imbalance in polysomal RNA led us to nominate 52 coding variants associated with allele-specific mRNA translation, of which 16 are nonsynonymous. To validate instances of allele-specific translation, a proteomics workflow was developed that combines label-free shotgun analysis, high-pH reversed-phase peptide fractionation, and targeted parallel reaction monitoring using isotope-labeled peptide standards. Using this approach, we provide proof-of-concept validation of the heterozygous G>A, R183H missense single-nucleotide variant rs1554710467 in the eukaryotic initiation factor 4H (EIF4H) gene. The variant is present in two EIF4H alternatively spliced variants, which showed equivalent translation efficiency in HCT116 cells but differ in abundance. The alternative peptide containing H183 was significantly more abundant than the corresponding reference peptide containing R183, consistent with the over-representation of the alternative allele in polysomal RNA in HCT116 cells. A dual-fluorescence ribosome-stalling assay confirmed the enhanced translation potential of the variant allele. The two EIF4H allelic proteins exhibited similar stability and subpolysomal localization. This study demonstrates the feasibility of using allele-specific proteomics at the endogenous protein levels by exploiting heterozygous coding variants. Overall, our approach extends the toolbox available to investigate allele-specific differences in mRNA translation potential, a relatively underexplored layer of gene expression regulation that could reveal interindividual differences in disease-relevant phenotypes.

Humans↗

PubMed2026

Genome-wide annotation of human multi-nucleotide variants reveals widespread functional differences from single nucleotide variants.

Multi-nucleotide variants (MNVs) represent a crucial yet underexplored category of genetic variation. Despite previous studies highlighting the prevalence and potential biological impact of MNVs in populations, comprehensive identification and detailed functional annotation of MNVs remain challenging. Here, we develop MNVAnno, a toolbox for rapid identification and annotation of complex MNVs, and utilize it to identify 3,984,258 MNVs from 700,134 human samples, expanding the human MNV list to 8,199,654. Our analysis reveals that MNVs can not only lead to distinct amino acid changes from their constituent single-nucleotide variants, but also significantly impact the function of non-coding regions. Furthermore, through genome-wide association studies, we identify some MNVs associated with multiple cancers, and establish the Human MNV Database to facilitate MNV research. Our study emphasizes the importance of MNV annotation, broadens the human MNV landscape, and opens avenues for exploring genetic variation in phenotypes and diseases.

Humans↗

PubMed2026

NCBoost v2: a classifier for non-coding single-nucleotide variants in Mendelian diseases.

MOTIVATION: The current diagnostic rate of rare diseases through whole-genome sequencing has stabilized at around 30% on average, highlighting the need for improved computational scores to identify pathogenic variants. In 2019, we developed NCBoost, a supervised-learning approach that mined a comprehensive set of sequence constraint features and proved particularly well suited to identifying high-effect pathogenic non-coding variants in genetic diseases. Since its first release, the substantial increase in the number of variants available for training, as well as the enhanced capacity to detect purifying selection signals from large-scale genome sequencing projects, motivated an update of NCBoost. RESULTS: We implemented NCBoost v2, a pathogenicity score for non-coding single-nucleotide variants, trained on the largest set of curated pathogenic variants in monogenic Mendelian diseases available to date. It leverages conservation features computed from recent large-scale genomic consortia such as Zoonomia and gnomAD, and incorporates recent splice-altering predictive scores. NCBoost v2 outperformed alternative state-of-the-art methods in a variety of scenarii, providing more consistent scores across non-coding genomic regions and fine-tuning the scoring of pathogenic splice-altering variants in Mendelian disease genes. AVAILABILITY AND IMPLEMENTATION: NCBoost v2 software is implemented in Python 3.10 and is freely available under the GNU General Public License Version 3 at https://doi.org/10.5281/zenodo.16029049 and https://github.com/RausellLab/NCBoost-2, together with precomputed scores for the human genome assembly GRCh38.

Polymorphism, Single Nucleotide↗

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

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↗