Our study aimed to determine the prevalence and clinical phenotypes of JAK2 pathogenic mutation carriers in the CNSR-III ischemic stroke (IS) cohort, and to develop a pre-test genetic screening model for identifying high-risk individuals. We performed retrospective characterization of JAK2 pathogenic variants using targeted sequencing data in the CNSR-III cohort. Clinical and laboratory characteristics of JAK2 V617F mutation carriers and non-carriers were tested in a logistic regression model to identify key features. V617F screening score was developed to predict positive JAK2 V617F test results. 46 cases (0.4%, 46/10428) harbored the JAK2 V617F-exclusive mutation. Mutation carriers manifested significantly inferior functional outcomes following stroke relative to non-carriers (adjusted OR 2.74[1.07, 6.49]). Significant predictors of mutation status comprised elevated platelet count (PLT, OR 1.02[1.02, 1.03]), increased hemoglobin concentrations (HGB, OR 1.06 [1.04, 1.08]), and a reduced burden of traditional stroke risk factors, such as history of hypertension (OR 0.24[0.11, 0.52]), smoking history (OR 0.08[0.02, 0.24]), and body mass index (BMI, OR 0.8[0.75, 0.97]). We constructed the JAK2 V617F screening score, which efficiently discriminated between carriers and non-carriers (area under the ROC curve, AUC 0.98), achieving sensitivity of 85%, specificity of 94%, and accuracy of 94% for a cut-off score of 3 points. Internal validation confirmed robust performance, with a consistent AUCof 0.98. Despite low prevalence (0.4%), JAK2 V617F mutation represents a clinically actionable stroke subtype with distinct pathophysiology. The prediction model offers a precision medicine approach, potentially reducing the need for comprehensive genetic testing.

GWAS have generally focused on common variants from genotyping arrays or rare protein-coding variants from exome sequencing. Here, we use whole-genome sequencing data to evaluate the contribution to and architecture of rare non-coding variants for three commonly studied anthropometric traits: height, BMI and waist-hip ratio adjusted for BMI. Analysing 447,461 individuals in the UK Biobank for discovery and 225,515 individuals in All of Us for replication, we identify 90 rare and low-frequency single variant associations, including two independent rare variants upstream of IGF2BP2 that substantially reduce waist-hip ratio adjusted for BMI, but have distinct effects on other adiposity traits. We further identify 135 coding variant aggregates. For example, UBR3 protein-truncating variants are associated with a 2.7 kg/m2 increase in BMI. We additionally identify 51 non-coding variant aggregate associations, including one in the 5'UTR of FGF18 associated with up to 6 cm effects on height. We show that 97% of rare variant associations occur near GWAS-identified loci, demonstrating convergence of rare and common variant associations. Finally, we show that ultra rare variants explain a small fraction of heritability compared to common variants for these traits, that heritability is largely shared across ancestries, and that it concentrates around common variant loci.

Sepsis is a life-threatening state of disseminated infection, and treatment requires knowledge of the organism responsible. The gold standard for sepsis diagnosis is blood culture, which requires days of growth. Next-generation sequencing has been proposed as an alternative; however, existing methods may lack sensitivity. In this work, we explore the idea of genomic quasi-G-primes, which are short DNA sequences specific to a single species within a group of relevant species. We first validated the genomic quasi-G-prime classification in controlled Staphylococcus aureus sequencing experiments, and then applied the same approach to blood-derived sequencing data from septic and healthy patients, where genomic quasi-G-prime profiles distinguished disease states. Our method is highly space-efficient, permitting fast classification on modest hardware and enabling it to outperform existing taxonomic classification approaches in this task.

The genus Dactylaria has long been recognized as polyphyletic. In this study, phylogenetic analyses based on LSU sequences indicate that Dactylaria is widely distributed across six different classes within Pezizomycotina . Further analyses using combined LSU, ITS, and RPB2 sequence data revealed that Funiliomyces biseptatus , ten previously described “ Dactylaria ” species, and our newly isolated strains form a distinct lineage (SH-aLRT/UFB/BPP = 99.9/94/0.99) within Amphisphaeriales , sister to Nothodactylariaceae . Interfamily genetic differences provide additional evidence for recognizing this lineage as an independent family-level clade. Accordingly, a new family, Funiliomycetaceae fam. nov ., is proposed to accommodate this lineage. The majority of species in this family are saprobes, endophytes, or epiphytes, occurring on a wide range of plant hosts across tropical to temperate regions. The sexual morph of Funiliomycetaceae is characterized by black, subglobose ascomata; cylindrical asci with an IKI-negative apical apparatus; and pale brown, torpedo-shaped, 2-septate ascospores bearing two hyaline mucilaginous appendages. The asexual morph is characterized by macronematous conidiophores and integrated, sympodial conidiogenous cells that exhibit remarkable diversity in denticle morphology, ranging from large cylindrical or geniculate forms to entirely absent, producing hyaline to pale smoky, septate conidia of variable dimensions. The diversity of Funiliomycetaceae is expanded here by the addition of one new species, Funiliomyces jiangxiensis sp. nov ., and the transfer of ten previously described species to Funiliomyces as new combinations ( F. acaciae comb. nov ., F. bisepatus comb. nov ., F. calliandrae comb. nov ., F. fragilis comb. nov ., F. hwasunensis comb. nov ., F. mavisleverae comb. nov ., F. monticola comb. nov ., F. retrophylli comb. nov ., F. sparsus comb. nov ., and F. zapatensis comb. nov .). Information on asexual morphology, lifestyle, host associations, and distribution of Funiliomyces species is provided to facilitate species identification.

The critical binding domain (CBD) is typically identified via tedious affinity screening of truncated and mutated sequences of an aptamer. We report here a wet-dry-wet experiment strategy, which enables the isolation of rapamycin-binding aptamers and the identification of the CBD at the same time without the need for affinity testing of numerous rationally designed sequences. In the first wet-experimental module, the pre-enriched library was obtained via 15 rounds of Capture-SELEX. In the dry-experimental module, the two key binding architectures, a three-stem-three-loop (3S3L) motif and a 3S3L-A motif (containing an additional adenosine in the second loop of 3S3L), were identified by comprehensively analyzing the high-throughput sequencing data using K-mer assembly, unsupervised learning (RBM), and mFold structure simulation. The structure-confined mixed secondary library designed based on the two structures exhibited high affinity, validating the importance of structure. In the second wet-experimental module, enriched library 2R6 was obtained after six rounds of second Capture-SELEX. A series of aptamers with nanomolar dissociation constants and high specificity were obtained, along with the identification of 11-nt CBD via analyzing the high-throughput sequencing result of 2R6. The decreased or completely lost binding affinity of the mutated sequences of seed aptamer 1R15-2 confirmed the CDB. A strand-displacement fluorescence sensor was constructed and capable of the detection of rapamycin spiked in 10% human serum with a nanomolar limit of detection. This study provides an efficient method for simultaneous aptamer isolation and CBD identification and can be applied to other targets.

Sedum sarmentosum Bunge is a perennial succulent plant of medicinal significance within the Crassulaceae family. To investigate its mitochondrial genome (mitogenome), structure, gene composition, and evolutionary implications, we assembled the complete mitogenome and plastid genome (ptgenome) of S. sarmentosum using high-fidelity sequencing data. The resulting mitogenome is a circular DNA molecule of 156,727 bp with a GC content of 45.30%, encoding 30 protein-coding genes (PCGs), eight tRNAs, and two rRNAs. Analyses identified 78 simple sequence repeats, two tandem repeats, and 30 dispersed repeats. A total of 617 potential RNA-editing sites were predicted, predominantly occurring at the second codon positions of mitochondrial PCGs. In addition, 18 mitochondrial plastid DNA transfer events were identified between the mitochondrial and chloroplast genomes, which included both tRNA and partial protein-coding gene segments. Moreover, the regional boundaries of chloroplasts of S. sarmentosum was identified, consisting of a large single-copy (LSC) region (81,798 bp), a small single-copy (SSC) region (16,671 bp), and two inverted repeat (IR) regions (25,778 bp each). Phylogenetic analyses based on mitogenomes of 26 species revealed that S. sarmentosum is closely related to members of the Rhodiola genus within Crassulaceae, providing new insights into evolutionary relationships among Saxifragales. Furthermore, codon usage bias, selection pressure analysis, and nucleotide diversity assessments uncovered lineage-specific patterns of molecular evolution, highlighting the balance between purifying and positive selection in shaping mitochondrial gene divergence. Altogether, this study contributes to our understanding of mitogenomic architecture, evolutionary adaptation, and phylogenetic placement of S. sarmentosum , and offers a valuable genomic resource for future studies in plant evolution, functional genomics, and molecular breeding.

The development of Bovine Respiratory Disease (BRD) in beef cattle is associated with stressful events, including auction and transport. In addition to the effects of commingling on pathogen exposure, stress also impacts immune function and has classically been associated with an immunosuppressed state. Much of the research on cattle immunity in stress has focused on peripheral blood immune functionality rather than mucosal immune responses. To characterize immunity at the primary site of pathogen colonization in BRD, we evaluated stress responses in lung cells from beef stocker cattle to understand mucosal immune changes. Stocker calves were sampled via bronchoalveolar lavage fluid (BALF) collection within 24 hours of auction and transport to a new facility (Stressed, n = 12), or allowed to acclimate for 2 months at the new facility before sampling (Acclimated, n = 7). Lavage cellular RNA was extracted and sequenced for bulk RNA-seq gene expression. Differential gene expression analysis of RNA sequencing data demonstrated a profound upregulation of inflammatory genes in Stressed calves compared to Acclimated calves, including expression of CXCL8, CSF3R, IL1B, and CCL22. Top pathway upregulation in Stressed calves involved neutrophil migration and chemotaxis, and cytokine signaling. To predict cellular population proportions from the data, CIBERSORTx was used to deconvolute bulk RNA-seq gene counts. This analysis showed that Stressed calves had significantly increased BALF neutrophils compared to Acclimated calves (p = 0.003). Neutrophilic infiltration occurred in the absence of pathogen colonization of the lungs in most calves, as demonstrated by a multi-pathogen respiratory qPCR screen. As such, the stress induced an inflammatory response in lungs not explained by pathogen exposure. This study provides strong evidence that shipping stress in beef stocker calves can trigger increased inflammatory pulmonary mucosal immune responses, which has important implications for the pathogenesis of BRD.

Deep 'bulk' T-cell receptor (TCR) sequencing is a comprehensive approach to gauge the TCR repertoire in clinical specimens to address spatio-temporal differences in TCR compositions. Clonal T-cell expansion in the course of anti-cancer directed cellular immune responses can be antigen-driven, either by commonly shared or mutant tumor-associated antigens (TAAs), by viral targets, or reflect 'bystander activation' of T-cell clones. Different analytic tools and platforms are available to describe the molecular texture of the TCR composition. We report here on an open-access platform 'TCRcloud' that enables to address the unmet need to visualize TCR diversity in cellular immune response, e.g. to checkpoint blockade therapies, termed 'clonal replacement'. We took advantage of a publicly available dataset that linked TCR composition analysis with clinically relevant responses to immune checkpoint inhibitor (ICI) treatment and visualized the TCR changes using the TCRcloud platform described in this report. In order to test 'real world data', we visualized TCRs and B-cell receptors (BCRs) in blood and matching tumor tissue from 3 patients with pancreatic cancer. TCRcloud, is a computational tool to screen the 'TCR data warehouse' for biologically and clinically relevant patterns, i.e. the CDR3 length, number of unique CDR3 transcripts, TCR convergence, different indices gauging the TCR composition in biological samples, i.e. the D50 Index, Gini Coefficient, Shannon Index, Gini-Simpson Index, Chao1 index, as well as the changes in amino acid usage at each position of the TCR and BCR CDR3. TCRcloud is a free open-source software distributed under the MIT license and available from https://github.com/eriicdesousa/TCRcloud or via the Python Package Index (PyPI). TCRcloud is compatible with both TCR and BCR molecular datasets if these fulfill Adaptive Immune Receptor Repertoire (AIRR) community standards. The analysis of a public TCR database allowed us to select a subject to demonstrate detailed molecular changes in the CDR3 TCR datasets which have been associated with relevant clinical responses in patients with basal cell cancer or squamous cell carcinoma receiving checkpoint inhibitor treatment (Yost et al. 10.1038/s41591-019-0522-3). Analysis of real world immune receptor sequencing data obtained from tissue from patients with cancer allowed us to demonstrate the different dynamics in the TCR and BCR in blood and corresponding tumor from of 3 patients with pancreatic cancer. TCRcloud enables to i) intuitively visualize molecular TCR compositions, ii) combine different TCR repertoire measurements within a single radar plot to capture biologically relevant TCR indices in a single image iii) visualize the usage of the V-genes and iv) visualize the frequency of amino acids in the CDR3. This easy to use tool enables to intuitively visualize changes in bulk TCR and BCR compositions in association with immunotherapies in a spatio-temporal fashion.

Sequence data indicate that a new virus, bee xinmovirus 1, is present in both honey bee (Apis mellifera) and mining bee (Andrena spp.) samples from Israel. The near-complete genome is approximately 13,130 nucleotides long and most similar to viruses of the family Xinmoviridae (S. Sharpe and S. Paraskevopoulou, J Gen Virol 104:001906, 2023, https://doi.org/10.1099/jgv.0.001906).

Background Glucose-6-phosphate dehydrogenase (G6PD) deficiency is traditionally recognized as a risk factor for drug- or infection-induced hemolytic anemia. Emerging evidence implicates potential roles of G6PD in neurodevelopment, yet its association with rare neurological disorders remains underexplored in population-based genetic studies, especially within the Chinese population. Methods We conducted a retrospective case-control study utilizing whole-exome sequencing (WES) data from a Chinese cohort. Six most prevalent pathogenic G6PD variants in China were screended in children with rare neurological disorders (n = 211) and in controls without neurological involvement (n = 202). Genotype and carrier frequency comparisons were performed. Stratified analyses were performed based on diagnostic certainty and the presence of de novo mutations. Multivariable logistic regression was employed to calculate sex-adjusted odds ratios (ORs) to control for potential sex-related confounding. Results After adjusting for sex, the overall carrier rate of pathogenic G6PD variants was significantly higher in patients with neurological disorders than in controls (adjusted OR = 2.44, 95% CI: 1.18–5.06, p = 0.014). Further comparisons across specific groups revealed distinct patterns: affected male patients had a higher carrier rate than their own unaffected fathers (OR = 2.30, 95% CI: 1.08–4.91, p = 0.043), and mothers of case patients showed a higher carrier rate than mothers of controls (OR = 2.03, 95% CI: 1.09–3.78, p = 0.030). The variants NM_001042351.3: c.1376G>T (G6PD Canton) and NM_001042351.3:c.1388G>A (G6PD Kaiping) were the most prevalent across all groups. Conclusion This population-based genetic analysis provides preliminary evidence that G6PD deficiency may be a underrecognized genetic risk factor for rare neurological disorders in Chinese children. The findings suggest a potential maternal genetic contribution and indicate that the phenotypic spectrum of G6PD deficiency may extend beyond hematological manifestations to include neurodevelopmental vulnerability. Important limitations include the lack of functional validation and the use of a clinical control group. Further prospective studies incorporating G6PD enzyme activity assessment and functional investigations are warranted to elucidate the underlying mechanisms.

Previous studies have demonstrated that the USP14 inhibitor IU1 and USP14/UCHL5 inhibitor b-AP15 can extend the survival period of TP53-deficient mice with spontaneous osteosarcoma (OS). However, the underlying molecular mechanisms remain to be fully elucidated. The transmembrane protein TMEM158 has been identified as a key regulator in the progression of various cancers. Nevertheless, its functional role in OS remains largely unknown. In this study, we conducted comprehensive bioinformatics analyses-including cluster analysis, differential expression analysis, and functional enrichment analysis-on clinical OS databases to assess the correlation between TMEM158 expression and the proteasome-associated USP14 and UCHL5. Primary tumor cells (TP53-deficient OS cells), SAOS-2 and U-2OS cells were treated with IU1 or b-AP15, respectively. The expression levels of TMEM158 were quantified using qPCR. Subsequently, TMEM158 was knocked down in three cell lines, and subsequent changes in cellular activity and TGF-β signaling were evaluated. Concurrently, single-cell RNA sequencing data were analyzed to identify cell types exhibiting high TMEM158 expression and to explore their associated intercellular communication patterns. Both IU1 and b-AP15 significantly prolonged the survival of TP53-deficient OS mice and exhibited enhanced cytotoxic effects on TP53-deficient OS cells. These compounds selectively suppressed TMEM158 expression in TP53-deficient primary OS and SAOS-2 cells. Bioinformatics analysis revealed that TMEM158 is positively correlated with USP14 and UCHL5 expression and serves as an independent prognostic marker for poor clinical outcomes in OS patients. Experimental validation showed that TMEM158 knockdown significantly reduced the viability of TP53-deficient primary OS and SAOS-2 cells, and inhibited TGF-β pathway activation. Osteoblastic OS cells displayed concurrent suppression of the P53 pathway and activation of the TGF-β pathway, with a strong covariant relationship between TMEM158 and activity of TGF-β pathway. Meanwhile, there may be intercellular TGF-β signaling communication between osteoblastic OS cells with high expression levels of TMEM158 and macrophages. Our findings demonstrated that the TMEM158-TGF-β pathway plays a central role in mediating the heightened sensitivity of TP53-deficient OS to USP14 inhibition. Targeting this pathway may represent a promising therapeutic strategy for precision treatment of osteosarcoma.

Reliable detection of Host-Microbe Signatures in cancer using PRISM.

Lactylation, a recently identified post-translational modification mediated by lactate, plays a critical role in regulating metabolic and immune processes in tumors. However, its function in neuroblastoma, particularly its association with tumor progression and immune modulation, remains unclear. We conducted immunohistochemical analyses on neuroblastoma tissue samples to evaluate lactylation levels and their clinical relevance. Single-cell RNA sequencing data and the AUCell algorithm were utilized to identify lactylation-related genes (LRGs) and map their expression within the tumor microenvironment. A seven-gene LRGs-based prognostic model was constructed using Cox regression and Least absolute shrinkage and selection operator (LASSO) analysis and validated in independent datasets. Bioinformatics analyses were performed to assess the associations between LRGs and clinical characteristics, biological pathways, immune infiltration, and therapeutic response. Functional assays further investigated the role of KLHL32, a key gene identified in the model. Our study revealed significantly elevated lactylation levels in neuroblastoma tumor tissues, which were associated with advanced disease stages and poor prognoses. We identified 407 LRGs and developed a seven-gene prognostic model that effectively stratified patients by risk, showing robust predictive performance in both internal and external validations. High-risk patients exhibited increased activation of tumor-promoting pathways, including glycolysis and PI3K/AKT signaling, alongside reduced immune cell infiltration, indicative of an immunosuppressive tumor microenvironment. Among the LRGs, KLHL32 emerged as a key tumor suppressor, inhibiting neuroblastoma cell proliferation, migration, and invasion, while enhancing NK cell-mediated cytotoxicity and anti-GD2 immunotherapies response. KLHL32 overexpression suppressed lactate production by downregulating the PI3K/AKT pathway, reducing protein lactylation levels, and promoting anti-tumor immunity. Our findings establish lactylation as a critical determinant of neuroblastoma progression and prognosis. The seven-gene lactylation-related prognostic model provides a novel tool for patient stratification and therapeutic decision-making. Additionally, KLHL32 represents a promising target for enhancing immunotherapy efficacy by modulating metabolic and immune pathways, offering new opportunities for precision treatment in high-risk neuroblastoma patients.

The Nujiang River, an important international river and one of the six major water systems in Yunnan Province, China, is characterized by numerous tributaries, complex topography, and abundant natural resources. During an investigation of lignicolous freshwater fungi in this river, three Neomyrmecridium taxa were isolated from submerged wood samples. Based on morphological characteristics and phylogenetic analyses of combined ITS and LSU sequence data, we introduce a novel species, Neomyrmecridium nujiangense. Additionally, two known species were identified as N. aquaticum and N. fusiforme. This study provides detailed morphological illustrations and phylogenetic trees of both the new and known taxa. Our findings enhance the understanding of freshwater fungal diversity in the Nujiang River and highlight the essential role of integrating morphological and molecular data in fungal taxonomy, particularly for groups exhibiting high phenotypic plasticity.

Improving feed efficiency in cattle is increasingly important for both environmental and economic reasons. Although feed efficiency traits are under considerable genetic control, with an average moderate heritability estimate of 0.33, genetic evaluations are limited by the difficulties in measuring feed intake and the lack of records from most commercial herds. Most genetic evaluations rely on small numbers of records from research farms, resulting in under-represented genetic variation and pronounced sampling errors in heritability estimates. To enhance the discovery of genetic mechanisms underlying feed efficiency and to address measurement limitations and the under-representation of genetic variation, we used joint phenotypic and genotypic measurements from two distinct herds for GWAS and in-depth genomic analysis. By applying this approach, our exploratory analysis discovered fourteen significant markers with effects on residual feed intake (RFI) ranging from -1.41 to 1.44 kg/day. Quantitative trait loci (QTLs) enrichment analysis specifically pointed to traits that contributed to RFI, including dry matter intake (DMI), body weight (BW), and protein yield. Gene enrichment analysis, which was largely biased by a local cluster of vomeronasal receptor genes within a single ~ 500 kb region on BTA18, suggested three sets of genes of interest: a vomeronasal pheromone receptor cluster (VN1R1 and four additional response to pheromone genes on BTA18), genes linked to social and behavioral responses (EPC2 on BTA2; SYN3 on BTA5), and fat metabolism-related genes (KIF5C on BTA2; SV2B on BTA21). Of these candidate genes, likely functional amino acid (AA) variations were observed in the VN1R1 putative protein (314 AA) after screening a sample of 27 Israeli Holstein genomes. These functional variations included two truncation mutations that could encode 89 and 239 AA polypeptides. Consistent with these findings, whole-genome sequence data analysis of RFI-characterized Irish bulls identified a significant association between the 89 AA truncation and high RFI, further validating our results and indicating that although such variation was common, the presence of an intact VN1R1 receptor was associated with a beneficial effect on feed efficiency. Moreover, the 89 AA truncation was observed in diverse cattle breeds, including American, Israeli, Irish, and New Zealand Holstein. These findings are compatible with feed efficiency, a complex trait governed by neural (behavioral) and metabolic components. Further characterization of these factors would allow genetic selection to reduce feed costs and environmental footprints.

The cultivated apple (Malus × domestica Borkh.) is the most economically important crop in Poland, the largest producer of apple fruits in Europe. During the growing season of 2024, typical symptoms of branch cankers and scaling-off of the bark were observed on the 24-year-old and over 60-year-old apple trees in the historical garden located in Nieborów, Lodzkie voivodeship. Fungi with greyish mycelium were repeatedly isolated from the interior of symptomatic branches. Based on cultural and morphological characteristics and DNA sequence data comparisons for ITS rDNA and translation elongation factor 1-alpha (EF1-α) regions, the causing fungus was identified as Diplodia bulgarica. Pathogenicity tests were performed on apple trees cv. 'Najdared', by inoculating them with mycelial plugs. All examined strains caused necrotic lesions on the leader, leading to the death of the whole tree, confirming the pathogenicity of the studied fungal isolates toward the apple tree.

Tuberculosis (TB) remains a global health challenge, exacerbated by the emergence of drug-resistant Mycobacterium tuberculosis strains. Most methods for drug susceptibility testing (DST) are culture-dependent and time consuming, possibly delaying optimal TB-treatment. This study aimed to develop an extensive targeted next-generation sequencing (tNGS) approach for rapid genotypic DST directly from clinical samples. We designed a tNGS panel comprising 30 amplicons targeting 19 genomic regions associated with resistance to 20 antibiotics. This method was applied to 71 smear-positive (0–3+) pulmonary TB clinical samples collected at the Portuguese National Reference Laboratory. DNA was extracted and amplified using multiplex PCRs, followed by sequencing on Oxford Nanopore Technologies MinION platform. Sequencing data were analysed using TB-Profiler and the tNGS results compared to phenotypic DST and whole genome sequencing (WGS) data from corresponding isolates. The tNGS demonstrated high concordance with both phenotypic and WGS-based DST across different sample types and smear positivity levels. For first-line drugs, tNGS showed 88% categorical agreement (CA) with pDST, increasing to 97% when excluding undetermined results. Compared to WGS across all analysed antibiotics, tNGS achieved 92% CA, increasing to >99% when excluding undetermined results. Validation of the tNGS panel showed 90% (1,895/2,076) of amplicons reaching >10x coverage at all analysed positions and 43 (61%) samples with all complete amplicons above this threshold. Non-specific amplification of contaminant bacterial DNA was minimal, with most mapped off-target reads being of human origin. This method enables comprehensive resistance prediction directly from clinical samples and signifies an important development in TB diagnostics and resistance monitoring.

Genome-wide association studies (GWAS) have identified dozens of genetic loci linked with metabolic dysfunction-associated steatotic liver disease (MASLD). To identify liver-expressed genes that may represent therapeutic candidates for MASLD, we conducted a new GWAS meta-analysis including 16,532 cases and 1,240,188 controls. We also generated RNA sequencing data of liver samples and genome-wide genotyping of 504 individuals of the Quebec Obesity Biobank. Using Mendelian randomization (MR) and genetic colocalization, we confirm the implication of genes previously linked with MASLD and identified novel ones including AKNA (AT-hook transcription factor), EPHA2 (EPH receptor A2), CHEK2 (encoding Checkpoint kinase 2) and PCCB (Propionyl-CoA carboxylase subunit beta). More specifically, we found a strong and positive effect of the long non-coding RNA TRIB1AL on MASLD. The lead genetic variant was not linked with expression levels of the nearby protein-coding gene TRIB1 (Tribbles Pseudokinase 1). In participants of the UK Biobank with whole exome sequencing data available, rare loss-of-function variants in TRIB1 were not associated with liver fat accumulation or plasma triglyceride levels, suggesting that the long non-coding RNA TRIB1AL may carry cardiometabolic effects independently of TRIB1. Targeted- and phenome-wide MR also identified lower liver-expressed TRIB1AL as being associated with reduced liver fat accumulation, lower plasma lipoprotein-lipid levels and decreased atherosclerotic cardiovascular disease risk. These results open the door to liver-targeted therapeutics silencing of the non-coding genome for the prevention and treatment of MASLD and cardiometabolic diseases.

As a protandrous hermaphrodite with natural male-to-female sex change, maroon clownfish (Premnas biaculeatus) serves as an ideal model organism for investigating sequential hermaphroditism. However, genomic resources for this interesting species remain scarce, thereby limiting in-depth research on its unique biological traits. In this study, we generated the first telomere-to-telomere (T2T) gap-free genome assembly of maroon clownfish by integrating multi-platform sequencing data, including MGI short reads, PacBio HiFi long reads, ONT ultra-long reads, and Hi-C sequencing data. The final haplotypic genome spans 884.39 Mb, with all sequences successfully anchored onto 24 chromosomes. This assembly is highly contiguous, with a contig N50 of 37.98 Mb. Comprehensive genomic characterization revealed the precise localization of telomeric repeats and centromeric region within each chromosome. Independent quality assessments, such as QV of 71.01, CRAQ score of 98.98%, and BUSCO completeness of 99.98%, confirmed good assembly accuracy. Additionally, alignment of ONT ultra-long and PacBio HiFi reads to the assembly yielded a high mapping rate exceeding 99%, further validating a good assembly integrity. Repetitive elements constituted 33.51% (296.37 Mb) of the assembled genome, and a total of 24,556 protein-coding genes were annotated. This high-quality T2T genome assembly will not only provide a valuable genetic resource to advance related research in comparative genomics, population genetics, molecular breeding, and functional genomics of maroon clownfish, but also lay a solid foundation for resolving molecular mechanisms underlying its protandrous reproductive strategy.

Morbid obesity is a complex, multifactorial disorder characterized by metabolic and inflammatory dysregulation. The aim of this study was to observe changes in obese patients adhering to a personalized nutrition plan based on multi-omic data. This study included 14 adult patients with a body mass index (BMI) > 40 kg/m2 who were consecutively recruited from those presenting to our outpatient clinic and who met the inclusion criteria. Clinical, biochemical, hormonal, and glycomic parameters were assessed, along with whole-genome sequencing (WGS) that included a focused analysis of obesity-associated genes and an extended analysis encompassing genes related to cardiometabolic disorders, hereditary cancer risk, and nutrigenetic profiles. Patients were stratified into nutrigenetic clusters using a patented unsupervised machine learning platform (German Patent Office, No. DE 20 2025 101 197 U1), which was employed to generate personalized nutrigenetic dietary recommendations for patients with morbid obesity to follow over a six-month period. At baseline, participants exhibited elevated glucose, insulin, homeostatic model assessment for insulin resistance (HOMA-IR), triglycerides, and C-reactive protein (CRP) levels, consistent with insulin resistance and chronic low-grade inflammation. The majority of participants harbored risk alleles within the fat mass and obesity-associated gene (FTO) and the interleukin-6 gene (IL-6), together with multiple additional significant variants identified across more than 40 genes implicated in metabolic regulation and nutritional status. Using an AI-driven clustering model, these genetic polymorphisms delineated a uniform cluster of patients with morbid obesity. The mean GlycanAge index (56 ± 12.45 years) substantially exceeded chronological age (32 ± 9.62 years), indicating accelerated biological aging. Following a six-month personalized nutrigenetic dietary intervention, significant reductions were observed in both BMI (from 52.09 ± 7.41 to 34.6 ± 9.06 kg/m2, p < 0.01) and GlycanAge index (from 56 ± 12.45 to 48 ± 14.83 years, p < 0.01). Morbid obesity is characterized by a pro-inflammatory and metabolically adverse molecular signature reflected in accelerated glycomic aging. Personalized nutrigenetic dietary interventions, derived from AI-driven analysis of whole-genome sequencing (WGS) data, effectively reduced both BMI and biological age markers, supporting integrative multi-omics and machine learning approaches as promising tools in precision-based obesity management.