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PubMed2026

Maternal genetic variants associated with aneuploid conception: a narrative review.

BACKGROUND: Human aneuploid conception, a leading cause of infertility, pregnancy loss, and congenital disorders (e.g. Down's syndrome), arises from errors in chromosome segregation during oocyte meiosis or embryonic mitosis. While advanced maternal age is a well-established risk factor, significant inter-individual variation exists among younger women, suggesting a substantial role for maternal genetic determinants. OBJECTIVE AND RATIONALE: This review summarizes the identified maternal genetic variants associated with aneuploid conceptions and highlights directions for future research. SEARCH METHODS: We systematically searched PubMed, Embase, and the Cochrane Library (up to 12 January 2026), using key terms related to maternal genetics, genetic variants, aneuploidy, and pregnancy. Inclusion criteria were human studies, genetic confirmation of aneuploidy (in oocytes/embryos/products of conception/fetal cells), maternal variants (rare single-nucleotide variations, single-nucleotide polymorphisms, and small indels [≤50 bp]), and English-language publications. Exclusion criteria were non-human studies, structural/non-aneuploid numerical abnormalities, paternal factors, and conference abstracts. Extracted data items included study identifiers, population characteristics, variant details, detection methods, clinical phenotypes, type and origin of aneuploidy, pathogenicity or effect assessment, and gene inclusion in currently commercially available infertility next-generation sequencing (NGS) panels. Rare variants were classified per American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines, whereas common variants were evaluated based on effect estimates and functional validation. Study quality was appraised using a modified Newcastle-Ottawa Scale. Supplementary searches explored associations between the identified genes and a broader range of reproductive phenotypes. OUTCOMES: From 28 studies covering the broad clinical spectrum of aneuploid pregnancies (including embryo arrest, implantation failure, pregnancy loss, hydatidiform mole, and fetal aneuploidy), we identified maternal variants associated with aneuploid conceptions. These were functionally categorized into meiotic recombination, spindle dynamics, checkpoint enforcement, and the maternal-to-zygotic transition. Among them, variants in several genes are supported by higher-quality evidence, including likely pathogenic rare variants in KIF18A, ELL3, and CEP120, as well as common variants in PLK4 and CCDC66. Although some identified genes (HFM1, MCM9, MEI1, BUB1B, NLRP2, NLRP7, and TLE6) are included in commercial infertility NGS panels, their direct association with aneuploidy requires further validation. WIDER IMPLICATIONS: This review proposes that 'aneuploidy predisposition' constitutes a critical, mechanism-driven dimension for the genetic diagnosis of infertility, complementing phenotype-based frameworks. This approach would best serve women with unexplained infertility and a normal karyotype who have either a history of recurrent aneuploidy or heterogeneous reproductive phenotypes across different cycles. Adopting this perspective refines clinical genetic testing paradigms and underscores the need to prioritize artificial intelligence-enhanced clinico-genomic association studies and develop polygenic risk models integrated with clinical factors. PROSPERO REGISTRATION NUMBER: CRD42025636217.

Humans↗

PubMed2026

PDLIM4 promotes dephosphorylation of STAT transcription factors by recruiting PTP-BL and inhibits Th1, Th2, and Th17 cell differentiation.

STAT (signal transducers and activators of transcription) transcription factors are activated by tyrosine phosphorylation after cytokine stimulation and are critical for the differentiation of T-helper (Th) cells into particular Th lineage subsets. How STAT-mediated Th cell differentiation is negatively regulated, however, is not fully understood. Here, we report that PDLIM4 binds to STAT3, 4, and 6 and suppresses gene activation mediated by these STATs. PDLIM4 acts as an adaptor that recruits PTP-BL, a protein tyrosine phosphatase, through its LIM (abnormal cell lineage 11-islet 1-mechanosensory abnormal 3) domain, facilitating dephosphorylation of STAT proteins. PDLIM4-deficiency in CD4+ T cells resulted in augmented tyrosine phosphorylation of these STAT proteins and consequently enhanced Th1, Th2, and Th17 cell differentiation, suggesting that PDLIM4 regulates the differentiation of multiple lineages of Th cells by suppressing STAT signaling. We further found that a non-synonymous single-nucleotide polymorphism in PDLIM4, which causes the substitution of a glycine residue with a cysteine in the LIM domain, is associated with susceptibility to rheumatoid arthritis and Graves' disease, both of which are known to be Th17 cell-driven autoimmune diseases. Notably, PDLIM4 containing this amino acid substitution in the LIM domain showed reduced binding to PTP-BL and was therefore partially impaired in its ability to dephosphorylate STAT3 and suppress STAT3 signaling. Our findings define an essential role of PDLIM4 in negatively regulating STAT-mediated Th-cell differentiation and preventing the onset of human autoimmune diseases.

Animals↗

PubMed2026

First draft genome sequence of the emerging sexually transmitted dermatophyte Trichophyton mentagrophytes genotype VII.

Trichophyton mentagrophytes ITS-genotype VII (TMVII) is a globally emerging sexually transmitted dermatophyte causing severe skin infections characterised by painful, pustular lesions on the face, public area, genitalia, and trunk. To inform the prevention efforts, we present the first draft genomes of four TMVII isolates obtained from patients in the United Kingdom diagnosed between 2021 and 2025. We performed whole-genome sequencing and phylogenetic analysis based on single-nucleotide polymorphisms. We analysed the genetic relatedness of four TMVII isolates collected from UK patients, two had travel links to Spain and the Middle East. Two further isolates, including T. mentagrophytes ITS-genotype I/II obtained from a canine infection in the United Kingdom in 2025 and Trichophyton indotineae were sequenced for contextual analysis. We confirm that the TMVII strains studied here represent a highly clonal population, distinct from both zoophilic T. mentagrophytes genotype I/II and anthropophilic T. indotineae.

Humans↗

PubMed2026

Monitoring the fate of paternal mitochondria and their elimination in rice zygotes.

Mitochondria are preferentially transmitted from the maternal plant in most angiosperms, including rice, and paternal mitochondria are generally eliminated during microgametogenesis and/or in zygotes. The mechanism by which paternal mitochondria are eliminated progresses during plant reproductive processes. In the present study, we examined the distribution of paternal mitochondria in rice sperm cells and zygotes produced through the in vitro fertilization (IVF) of isolated rice gametes. Male gametes of rice possess mitochondria with nucleoids, suggesting the potential transfer of paternal mitochondria and their DNA into zygotes on fertilization and subsequent selective elimination of paternal mitochondria in the zygote. To intensively monitor the fate of rice paternal mitochondria in zygotes immediately after gamete fusion, time-lapse observations were conducted in paternal mitochondria labeled with GFP from rice zygotes produced using an IVF system. The results showed that the paternal mitochondria are progressively degraded during the early developmental stage at 1 to 3 h after fusion (HAF), leaving a small number of paternal mitochondria at 6 HAF. The remaining paternal mitochondria were considered to be degraded in later developmental-stage zygotes because paternal mitochondrial DNA-derived single-nucleotide polymorphisms were not detected in the sequencing reads of genomic DNA prepared from inter-subspecific hybrid rice. In addition, treatment with autophagy inhibitors stabilized the paternal mitochondria in zygotes. This suggests that the autophagy-dependent massive and selective elimination machinery for male mitochondria functions in rice zygotes immediately after gamete fusion and supports the strict maternal inheritance of mitochondria in rice.

Oryza↗

PubMed2026

Genomic Regions Associated with Resistance to Soybean Cyst Nematode (Heterodera glycines Ichinohe) Population HG Type 1.2.5.7 in Dry Beans (Phaseolus vulgaris L.).

North Dakota, the largest dry bean (Phaseolus vulgaris L.) producing state in the U.S., faces an emerging production threat caused by the soybean cyst nematode (SCN; Heterodera glycines Ichinohe, 1952). Host resistance is an effective management strategy, yet resistance to the virulent SCN population HG type 1.2.5.7 has not been genetically characterized in dry beans. In this study, 170 dry bean genotypes (113 breeding lines/cultivars and 57 germplasm accessions) were evaluated for response to HG type 1.2.5.7 under controlled conditions using female index (FI) as the resistance phenotype. FI values ranged from 4.1% to 78.1%, with one genotype (PI 313733) classified as resistant, 35 moderately resistant, 104 moderately susceptible, and 30 susceptible. Genome-wide association analysis using 2,044 single-nucleotide polymorphism (SNP) markers from the 3.8K Bean Panel chip and the BLINK model identified four significant marker-trait associations on chromosomes Pv02, Pv05, Pv07, and Pv11. Linkage disequilibrium-defined candidate intervals spanned 108 kb (Pv02), 1.50 Mb (Pv05), 798 kb (Pv07), and 1.45 Mb (Pv11), collectively containing 126 annotated genes: 20 on Pv02, 39 on Pv05, 35 on Pv07, and 32 on Pv11. The intervals contained putative genes annotated for signaling and transcriptional regulation, cell wall and carbohydrate metabolism, transport, and secondary metabolism. Together, these findings indicate that the response to HG type 1.2.5.7 in dry bean is quantitative and associated with multiple genomic regions. The identified intervals provide candidate targets for independent validation, fine mapping, functional analysis, and future marker development to support breeding for SCN resistance.

Disease Resistance↗

PubMed2026

Comparative Genome-Wide Association Studies of Metabolites and Grain-Related Traits in Common Wheat.

The metabolome is highly diverse and the closest layer to phenotype; therefore, it is commonly regarded as a bridge between the genome and phenome in plants. Here, we performed large-scale metabolome analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and 33 grain-related traits in a diverse panel of natural accessions and a recombinant inbred line (RIL) population. We identified a new network of 2286 associations between 947 metabolites and 33 grain-related traits. Systematic integration of metabolic genome-wide association study (mGWAS) and metabolic quantitative trait locus (mQTL) analyses identified 33 566 significant single-nucleotide polymorphisms (SNPs) and 3128 mQTL. Thirteen annotated metabolites co-localized within a physical interval on 7A. Integration of metabolite-based and phenotype-based GWAS and QTL revealed an overlapped region for gibberellin A4 (GA4) content and grain roundness on 4A. Phenotyping of an ethyl methanesulfonate (EMS)-induced mutant confirmed the role of TaSDR in regulating GA4 content and grain morphology. These findings provide novel insights into the metabolic pathways influencing key grain-related traits and advance our understanding of the complex molecular mechanisms regulating grain metabolites and phenotypes in wheat. The identified metabolic markers and candidate genes provide valuable targets for molecular breeding programs aimed at improving wheat yield and quality.

QTL↗

PubMed2026

Identification of OsCsLF6 Gene Responsible for Rice Seed Submergence Germination Through Genome-Wide Association Analysis.

Flooding stress is a primary environmental barrier that severely limits the widespread adoption of direct-seeded rice systems. Under submerged conditions, rapid coleoptile elongation serves as a vital morphological strategy that facilitates anaerobic germination and successful seedling establishment, yet its underlying molecular mechanisms remain poorly understood. Through a genome-wide association study, we identified a critical locus governing anaerobic coleoptile elongation, in which OsCsLF6, encoding a mixed-linkage glucan (MLG) synthase, was characterized as the causal gene. Genetic and biochemical analyses demonstrated that OsCsLF6 positively regulated coleoptile elongation by directly mediating MLG deposition into the primary cell wall. Mechanistically, we identified OsERF74, an AP2/ERF transcription factor, as an upstream master repressor that directly binds to a conserved core cis-element within the OsCsLF6 promoter. Under submergence, OsERF74 deficiency (oserf74 mutants) completely releases this transcriptional suppression, triggering a substantial upregulation of OsCsLF6 expression and subsequent hyper-accumulation of cell wall MLG. In contrast, constitutive overexpression of OsERF74 persistently blocks MLG biosynthesis. Crucially, a natural single-nucleotide polymorphism located within the OsERF74 binding element in the promoter defines two distinct haplotypes. The elite haplotype (Hap1) effectively disrupts OsERF74 binding affinity, which in turn attenuates transcriptional repression and sustains high OsCsLF6 expression, ultimately driving accelerated MLG synthesis and coleoptile elongation. Our findings establish a condition-specific OsERF74-OsCsLF6 regulatory module that serves as a central biochemical hub orchestrating cell wall remodelling during anaerobic germination. This module thus represents a promising molecular target and elite genetic resource for molecular breeding of flood-tolerant and direct-seeded rice varieties.

OsCsLF6↗

PubMed2026

Difficult-to-treat resistant Gram-negative bacteria and genomic resemblances between colonization and infection among patients in an intensive care unit of a tertiary care hospital in Bangladesh.

Colonization with difficult-to-treat-resistant Gram-negative bacteria (DTR-GNB) increases the risk of subsequent infections with limited treatment options. This study aimed to assess the burden of DTR-GNB colonization in ICU patients, explore its association with clinical outcomes, and examine genomic similarities. This secondary analysis included patients enrolled within 24 h of ICU admission between July 2023 and January 2024. Rectal swabs were collected at enrollment, on days 3, 7, and weekly during ICU stay to detect colonization. Bacterial isolates grown on selective chromogenic agar media were identified and tested for antimicrobial susceptibility using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) and automated broth microdilution, respectively. Blood, urine, and/or tracheal aspirate cultures were performed if clinically suspected sepsis. Whole-genome sequencing (WGS) was performed on paired colonization and infection isolates, and genomic relatedness was assessed using FastANI, core-genome single-nucleotide polymorphism (SNP) analysis, and phylogenetic reconstruction. Among 373 patients, 181 (48.5%) were colonized with DTR-GNB; 76 (20.4%) at enrollment, and 105 (53.0%) acquired during hospital stay. Among 52 (13.9%) patients evaluated for suspected infection, 30 (57.7%) had positive cultures, predominantly Acinetobacter baumannii (n = 15) and Klebsiella pneumoniae (n = 11) of DTR-phenotypes. Compared to non-colonized patients, patients colonized with DTR-GNB had higher risks of infections (risk ratio [RR]: 2.18, 95% CI: 1.27-3.76) and longer ICU stays (median 7 vs 2 days, P < 0.001). DTR-GNB-infected patients had a higher risk of death (RR: 1.57, 95% CI: 1.34-1.84) compared to patients without DTR-GNB infection. WGS revealed that 13 of 14 paired colonization-infection isolates were conspecific, with three pairs being highly clonal; whereas the remaining pairs showed greater genomic divergence, consistent with the SNP and phylogenetic analyses. While common, more than half acquired DTR-GNB colonization from the ICU. Its association with subsequent infection and prolonged ICU stays underscores the need for enhanced infection prevention and control measures to mitigate nosocomial transmission and improve patient outcomes.IMPORTANCEThis study underscores the growing threat posed by difficult-to-treat resistant Gram-negative bacteria (DTR-GNB) in intensive care units. Nearly half of critically ill patients were colonized, with a considerable proportion acquiring these multidrug-resistant organisms during their ICU stay. Colonization with these pathogens substantially increased the risk of subsequent infections, even by the same colonizing strain, prolonged ICU stays, and likely worsened clinical outcomes due to the unavailability of susceptible antibiotics. Alarmingly, more than 90% of patients infected with DTR-GNB expired in the hospital. These findings highlight the urgent need for robust infection prevention and control strategies to curb nosocomial transmission and mitigate the impact of DTR-GNB on vulnerable patient populations. Addressing this emerging resistance phenotype is critical to improving patient safety and reducing the burden on healthcare systems.

Humans↗

PubMed2026

Genetically Proxied Inhibition of Cholesterol-Lowering Drug Targets and Survival in HPV-Positive and Non-HPV-Driven Head and Neck Cancer: A Multicentre MR Study.

BACKGROUND: Cholesterol pathways may influence head and neck squamous cell carcinoma (HNSCC) progression, but evidence on prognosis is inconsistent. We used Mendelian randomization (MR) to test whether genetically proxied inhibition of major low-density lipoprotein cholesterol (LDL-C)-lowering drug targets and circulating lipid traits affects overall survival (OS) in HPV-positive and non-HPV-driven HNSCCs. METHODS: We proxied lifelong LDL-C lowering using 55 cis-acting single-nucleotide polymorphisms in HMGCR, NPC1L1, PCSK9, and LDL-receptor (LDLR) from the updated 2021 Global Lipids Genetics Consortium and instrumented circulating lipid traits. Two-sample MR estimated effects on OS in 4,869 multicentre HNSCC cases (1,291 HPV-positive; 3,578 non-HPV-driven) using minimally adjusted Cox models. Sensitivity analyses additionally adjusted for tumor stage and treatment, assessed collider bias using an external HNSCC incidence genome-wide association study, and examined between-center heterogeneity and colocalization. RESULTS: Using the updated Global Lipids Genetic Consortium 2021 instruments, genetically proxied HMGCR inhibition showed a directionally protective but nonsignificant association with OS in HPV-positive oropharyngeal HNSCC in the primary analysis [inverse variance weighted (IVW) HR = 0.19; 95% confidence interval (CI), 0.03-1.18; P = 0.08], with directionally concordant weighted median results. No corresponding protective association was observed for HMGCR in non-HPV-driven disease (IVW HR = 1.68; 95% CI, 0.78-3.63; P = 0.19). No clear evidence of association was observed for NPC1L1, PCSK9, LDLR, or circulating lipid traits in either HPV stratum. Colocalization did not support a shared causal variant. CONCLUSIONS: These analyses provide suggestive evidence that genetically proxied HMGCR inhibition may influence survival in HPV-positive oropharyngeal HNSCC. IMPACT: HMGCR-related pathways may be relevant to prognosis in HPV-positive oropharyngeal HNSCC, whereas clear survival effects of other cholesterol-lowering targets were not supported.

Humans↗

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

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

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

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

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

Strategies for mosaic variant calling in brain disorders.

The human brain is a genomic mosaic, where postzygotic mutations arising from embryogenesis to senescence drive diverse neurodevelopmental and neurodegenerative diseases. Because of numerous sequencing artifacts at ultralow variant allele frequencies (VAFs), detecting these variants remains a significant analytical challenge. This review focuses on single-nucleotide variants and small indels, summarizing current strategies for aligning sampling methods, including bulk, laser capture microdissection, and single-cell genomics, with the expected clonal architecture of the brain. It emphasizes that mosaic detection sensitivity is fundamentally constrained by sequencing depth, since even the most advanced algorithms cannot identify variants not physically represented in the sequencing library. The review further recommends the selection of variant calling algorithms based on validated VAF detection performance, matching tools like MuTect2 and MosaicForecast to their optimal performance ranges. Furthermore, we discuss how multitissue sampling, as emphasized by the SMaHT project, addresses the matched-control dilemma and supports accurate variant classification via cross-tissue VAF gradients. Integrating these established pipelines with multiomics modalities, including transcriptomic and epigenetic data, could advance the field toward a functional understanding of how the somatic genome impacts human brain health and disease.

Humans↗

PubMed2026

Identification and masking of artifactual and misleading within-host variants in deep-sequencing SARS-CoV-2 data.

Deep-sequencing data are increasingly used to study within-host viral diversity and to inform evolutionary inference. For SARS-CoV-2, analyses based on intra-host single-nucleotide variants (iSNVs) have been widely applied to quantify within-host diversity and infer transmission dynamics. However, these applications critically depend on the reliable identification of low-frequency variants, which remain vulnerable to systematic and technical artifacts. In this study, we show that recurrent artifactual iSNVs are common in large-scale SARS-CoV-2 sequencing data and can persist even under conservative minor allele frequency thresholds. Using data from the UK's Office for National Statistics COVID-19 Infection Survey, we demonstrate that such artifacts are predominantly sequencing center-specific rather than primer-specific. Each center exhibits a modest, distinct set of recurrent artifactual variants showing little overlap with sites routinely masked at the consensus level. To address this, we developed a systematic, dataset-aware framework that uses recurrence within sequencing datasets to identify small, noise-adapted sets of artifactual iSNVs to mask. Applying this framework reduces spurious sharing of low-frequency variants between samples and qualitatively alters downstream inferences, including estimates of within-host diversity and transmission bottleneck sizes. Although this study focused on SARS-CoV-2, it is likely that recurrent artifactual iSNVs will be problematic for other viruses as mass-sequencing becomes increasingly routine. Together, these findings highlight the importance of explicit, dataset-aware artifact control for robust inference from within-host variation, particularly as genomic studies increasingly seek to exploit sub-consensus diversity in rapidly evolving pathogens.

Humans↗