Satellite DNAs (satDNAs) are repetitive sequences that play important roles in chromosomal architecture, genome evolution, and regulation. Here, we present a comprehensive characterization of Tenebrio molitor satellitome, integrating cytogenetic mapping, in silico genome annotation, divergence profiling, screening of extrachromosomal circular DNA (eccDNA), transcription analysis across developmental stages, and phylogenetic and age analyses. SatDNAs exhibited diverse chromosomal organizations, ranging from widespread to chromosome-restricted distributions. Discrepancies between assembly-based and physical mapping highlight limitations of individual approaches and underscore the importance of their integration. Divergence landscape analyses revealed different homogenization efficiencies and turnover rates, reflecting distinct evolutionary trajectories among individual satDNAs. Phylogenetic reconstruction revealed distinct patterns which include clear species-specific clustering of monomers, mixed interspecific clustering, and dispersed topologies. Comparative analyses across insect orders enabled age estimation, identifying both ancient (≥380 MYA) and lineage-specific satDNAs, apparently restricted to T. molitor. We designed and applied an approach that enables the simultaneous detection of multiple satDNAs within the eccDNA fraction which confirmed the presence of six satDNAs in eccDNA. RNA-seq analyses revealed coordinated, stage-specific transcription of all satDNAs, with elevated expression in late male pupae and early male adults. Together, these results reveal a highly dynamic, heterogeneous, and functionally relevant satDNA landscape in T. molitor and demonstrate the importance of integrative approaches for understanding molecular mechanisms and trajectories of satDNA evolution.
The Neotropical family Serrasalmidae (pacus and piranhas) exhibits remarkable karyotype conservation, yet cytogenetic data remain limited for several genera, particularly Myloplus. Here we present the first integrative cytogenomic characterization of Myloplus tiete, an endemic and near-threatened species from the upper Paraná River basin, combining classical cytogenetics with satellitome analysis. Karyotyping of 12 specimens collected from Rio Grande, Frutal-MG, Brazil, revealed a consistent diploid number of 2n = 58 chromosomes with karyotype formula 16m + 20sm + 22a, while C-banding identified heterochromatic blocks predominantly in pericentromeric and subtelomeric regions. Genome sequencing and iterative satDNA mining identified 32 satellite DNA families, with repeat lengths ranging from 24 to 2,265 bp and a predominance of AT-rich sequences. Comparative analysis with the Colossomatinae species Colossoma macropomum and Piaractus mesopotamicus revealed 12 conserved satDNAs across ~ 40 million years of divergence, with moderate consensus turnover rates. FISH mapping of the ten most abundant satDNAs revealed diverse chromosomal distributions, including pericentromeric, subtelomeric, and dispersed patterns, highlighting the diverse genomic integration of conserved repeats. These findings provide evidence for long-term evolutionary conservation of both karyotype architecture and satDNA repertoires across Serrasalmidae subfamilies and suggest that structural or functional constraints may contribute to shaping the evolution of repetitive DNA in this ecologically and aquaculturally important fish group.
Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition characterized by persistent difficulties in social communication together with restricted, repetitive patterns of behaviour and sensory-processing differences. Growing evidence suggests that ASD is shaped by complex interactions among genetic susceptibility, epigenetic regulation, immune signalling, maternal and early-life exposures and gut microbiome-related pathways. However, many of these associations remain biologically plausible rather than definitively causal, particularly when findings from experimental models are considered alongside human clinical data. This narrative review examines recent advances across these interconnected domains, with particular emphasis on maternal immune activation, prenatal nutrition, gut microbial imbalance, epigenetic and molecular mechanisms, emerging therapeutic directions and developing biomarker platforms. We also discuss current diagnostic limitations and evaluate the potential of salivary microRNAs, perinatal metabolic and epigenetic markers, oxidative stress-related measures and microbiome-based profiles as early and biologically informative indicators of ASD risk. Special attention is given to the need for biologically informed stratification, although current subgrouping frameworks remain preliminary and not yet sufficiently validated for routine clinical use. Likewise, candidate biomarkers remain investigational and require stronger evidence for reproducibility, external validation, longitudinal performance and clinically meaningful sensitivity and specificity before they can be considered for screening or precision-guided care. Emerging therapeutic strategies targeting immune, epigenetic and microbiome-related pathways are also reviewed, but most remain preclinical or early-stage and face substantial translational barriers. The convergence of epigenomics, microbiome research and early diagnostic science may help advance a more personalized medicine framework for ASD, provided that future studies improve cross-cohort reproducibility, clarify brain relevance of peripheral signals and develop practical multiomics models that can support clinically meaningful integration.
Salt stress is a primary abiotic constraint on global rice productivity. To establish a robust genomic framework for breeding, we performed a genome-wide meta-QTL (MQTL) analysis integrating QTL data from both the seedling and reproductive stages. A high-density consensus map was constructed, and initial QTLs from independent studies were curated and filtered for redundancy. Confidence intervals were refined via meta-analysis to define stable MQTL regions. From 926 original QTLs at the seedling stage, 87 seedling MQTLs (SeMQTLs) were identified. Notably, SeMQTL1-5, which encompasses the major locus Saltol, and three additional high-confidence SeMQTLs (CI < 1 cM, physical interval ≤ 1 Mb, average PVE > 17%) were associated with ion homeostasis under salt stress. At the reproductive stage, 43 reproductive MQTLs (ReMQTLs) were consolidated from 241 QTLs, with PVE values ranging from 4.84% to 46.36%. Subsequent analysis nominated MQTLSIH1-2 (the most stable region) and MQTLSIH1-5 (containing SKC1) as key candidates for seedling tolerance, while MQTLPF11-1 (PVE > 28%) was prioritized for reproductive-stage breeding. A total of 39 MQTLs co-localized with SNP-based selection hotspots. Within these regions, we developed 21 InDel markers, of which 18 were validated as effective allele-specific markers for discriminating salt tolerance. This work delivers the first consolidated set of high-confidence, MQTL-derived InDel markers for salt tolerance in rice, providing a valuable resource for marker-assisted selection and the pyramiding of resilience loci into elite genetic backgrounds.
Tumor-associated high endothelial venules (TA-HEVs) mediate lymphocyte trafficking into tumors and modulate the tumor microenvironment, with reported effects on clinical outcomes. However, reports have described discordant associations across cancers and microenvironmental contexts. Studies on state-specific, pan-cancer analyses of TA-HEV function remain limited. We integrated publicly available single-cell RNA sequencing datasets from 11 cancer types. Functional features of TA-HEVs were inferred by pathway enrichment and single-cell gene-set scoring for pathway gene sets. State-specific programs were applied to The Cancer Genome Atlas dataset to assess their clinical impact. We constructed a comprehensive atlas of tumor-associated endothelial cells and identified TA-HEV subclusters. Five TA-HEV subclusters were grouped into two functional states: inflammatory and stress-metabolic. The inflammatory TA-HEVs were enriched for innate immune stimulation, cytokine/chemokine signaling, and MHC class II antigen presentation, whereas the stress-metabolic TA-HEVs were characterized by the unfolded protein response, heat shock pathways, oxidative phosphorylation, and ATP biosynthesis. Across cancers, the stress-metabolic TA-HEV state was generally associated with worse prognosis, while the inflammatory TA-HEV state showed context-dependent associations. Together, these findings define TA-HEVs as a heterogeneous endothelial population comprising distinct functional states with divergent clinical associations, providing a pan-cancer framework for interpreting TA-HEV signals in tumor biology.
Selenoproteins represent a structurally and functionally distinct class of proteins that contribute to cellular antioxidant defense and a wide range of other essential biological processes in specific organisms. They contain the 21st amino acid selenocysteine (Sec) in their active sites, which is encoded by an in-frame UGA stop codon through a translational reprogramming mechanism. Due to the dual functionality of the UGA codon, selenoprotein genes are frequently misidentified and misannotated in genomic databases, especially in bacteria where selenoproteins exhibit greater complexity and diversity compared to their eukaryotic counterparts. Thus, a comprehensive resource is urgently required to enable accurate identification of selenoprotein genes across diverse bacterial genomes. We have developed BSepDB, a specialized database dedicated to systematic curation of bacterial selenoprotein genes and proteins, providing an exhaustive resource for the research community. The current version (BSepDB v. 1.0) encompasses over 57,000 selenoprotein entries derived from 16,621 bacterial species, representing the largest and most taxonomically diverse repository of bacterial selenoproteins to date. To facilitate intuitive data exploration, BSepDB offers multiple user-friendly interfaces, such as interactive browsing and search tools, an integrated BLAST search function, and options for bulk data download. Additionally, the curated entries in BSepDB are cross-referenced with established genomic databases (e.g., GenBank and RefSeq) to improve the accuracy of selenoprotein annotations in large-scale genomic projects. BSepDB serves as a valuable resource for researchers investigating selenium utilization and the functional diversity of selenoproteins in bacteria. The database is freely available at https://bsepdb.metalbioinfolab.net.
Soil salinization and phytopathogen infection threaten global crop productivity. Plant growth-promoting rhizobacteria that alleviate abiotic stress while suppressing disease offer a sustainable solution. We aimed to identify a strain with robust salt tolerance, broad-spectrum antagonism, and effective root colonization. A novel halotolerant bacterium isolated from plant rhizosphere at an artificial lakeside was evaluated for plant growth-promoting and biocontrol capacities through phenotypic assays. High-quality whole genome sequencing and bioinformatic analysis were used for functional annotation. The results showed that Strain 105, identified as Bacillus halotolerans, exhibited exceptional tolerance to NaCl concentrations up to 14% (w/v). Under 200 mmol/L NaCl stress, inoculation significantly enhanced wheat seedling growth, increasing root length by 20% and plant height by 18% compared to controls. Strain 105 displayed strong in vitro antagonistic activity against four phytopathogenic fungi that infect crops during the growing period, three postharvest phytopathogenic fungi, and three pathogenic bacteria. Genomic analysis revealed a 4.2-Mb chromosome encoding four key functional modules: (i) osmoprotective systems for glycine betaine and proline metabolism; (ii) an indole-3-pyruvate pathway for indole-3-acetic acid biosynthesis; (iii) multiple secondary metabolite biosynthetic gene clusters (e.g., iturin, fengycin, bacillibactin, and bacilysin); and (iv) a complete set of genes for chemotaxis, biofilm formation, and root adhesion. In conclusion, the multifunctionality of B. halotolerans Strain 105 arises from the synergistic interplay of genetic modules, enabling it to thrive in saline conditions while promoting plant growth and suppressing diverse pathogens. Strain 105 is a promising candidate for developing next-generation microbial inoculants for sustainable agriculture in saline-alkali soils.
Thyroblastoma is a rare and highly aggressive embryonal thyroid malignancy typically associated with DICER1 alterations. However, DICER1-wildtype cases remain poorly characterized at the molecular level. We report a case of aggressive thyroblastoma in a 62-year-old male, negative for canonical DICER1 RNase IIIb mutations. Comprehensive genomic profiling was performed using Oxford Nanopore long-read sequencing, followed by integrative bioinformatic and pathway-level analyses. Molecular analysis revealed an alternative oncogenic signature characterized by an EIF1AX p.Lys3_Lys5dup duplication, TERT alterations (promoter C228T and coding p.C42R), and an AGK-BRAF fusion predicted to drive constitutive MAPK/ERK signaling. Functional enrichment analyses highlighted dysregulation of translational initiation, telomere maintenance, and mitogenic pathways, alongside potential immune-escape mechanisms linked to DUX4 activation. Clinically, the tumor exhibited a triphasic morphology, extensive locoregional infiltration, pulmonary metastases, and only transient response to chemotherapy. These findings expand the molecular spectrum of thyroblastoma beyond the canonical DICER1-driven paradigm and suggest that DICER1-wildtype cases may represent a distinct biological subgroup. The identification of alterations affecting TERT and MAPK pathways highlights potential therapeutic vulnerabilities and supports the clinical value of comprehensive genomic profiling in ultra-rare thyroid malignancies.
Urbanisation is a pervasive form of anthropogenic environmental change and a driver of contemporary evolution. Yet, it remains unclear how demographic processes and environmentally associated genomic variation shape genomic patterns in cities and whether these responses depend on species-specific ecological traits. Here, we addressed this gap using whole-genome sequencing of two related, diet-specialised solitary bees (Andrena florea and Andrena vaga) that differ in dispersal-related traits, rarity and host-plant distribution, sampled along an urban intensity gradient. By integrating population and landscape genomic analyses, we quantified genetic diversity, demographic history, population structure and genotype-environment associations. Neutral genomic patterns differed strongly between species: A. florea showed lower genetic diversity, higher differentiation and a recent population decline, whereas A. vaga maintained higher diversity, connectivity and demographic stability. Genetic diversity was associated with species-specific landscape features (edge density in A. florea and semi-natural habitat in A. vaga), rather than with urban intensity per se. Despite weak population structure, genotype-environment association analyses identified loci associated with urban intensity, and haplotype-based scans detected genomic regions showing patterns consistent with positive selection. Functional annotation and cross-species comparisons revealed partial convergence in candidate genes and functional pathways. Together, these results show that genomic responses to urbanisation cannot be explained by urban intensity alone, but instead emerge from the interaction between gene flow, genetic drift and selection, mediated by species-specific ecological traits. This leads to divergent demographic trajectories but partly convergent genomic responses across species.
Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici, is a globally prevalent, wind-borne fungal disease and remains one of the most destructive threats to wheat production. By combining BSA-seq and QTL mapping using the wheat 120K SNP array, we identified two genomic regions associated with stripe rust resistance. Among them, a QTL on the short arm of chromosome 3A, QYr.cib-3AS, was consistently detected across environments, explaining 20.10%-25.21% of the phenotypic variance and showing LOD of 2.57-3.58. QYr.cib-3AS was delimited to an interval flanked by dCAPS-78 and dCAPS-83. Additive-effect analysis showed that RILs pyramiding QYr.cib-3AS with YrT14 increased stripe rust resistance by 77.20% relative to RILs lacking both QYr.cib-3AS and YrT14, indicating that the pyramiding strategy had a significant impact on stripe rust resistance and underscoring its importance for high-yielding cultivars with durable resistance. The candidate interval exhibited high collinearity. Among the 48 high-confidence genes annotated in this region, an integrated analysis of transcriptome data, functional annotation, and sequence variation suggested that TraesCS3A03G0118200 and TraesCS3A03G0119800 are key candidate genes underlying QYr.cib-3AS. Collectively, these findings provide a foundation for marker-assisted breeding and future cloning and functional characterization of stripe rust resistance genes, which may help accelerate the development of elite stripe rust-resistant wheat cultivars, thereby improving wheat resistance to this destructive pathogen.
Polyploidy results in genome redundancy and drives ecological diversification in freshwater fishes, yet the genomic architecture and adaptive significance of recent polyploidization in high-altitude ecosystems remain poorly understood. Herein, after determining genome size and karyotype, we tackle the long-standing challenge of resolving highly similar homologous chromosomes in autopolyploid vertebrates. By integrating long-read sequencing, Hi-C scaffolding, and haplotype-specific phasing, we assemble a haplotype-resolved genome of the autotetraploid Schizothorax nukiangensis, comprising 100 chromosomes grouped into 25 homologous sets, with a genome size of 3.59 Gb in one cell. Evidence consistently support its autotetraploid origin, with a lineage-specific polyploidization event dated to ~0.68 Ma. Comparative genomics reveals substantial expansions of gene families in innate immunity, redox regulation, and transposon activity, suggesting genome remodeling might have contributed to adaptation in hypoxic, pathogen-rich, and fast-flowing mountain rivers. Population genomics across three elevational zones reveal subtle yet significant structure and identify candidate genes under selection related to skeletal development, immune defense, and ciliary function, consistent with adaptation to the torrents or rapids in fast-moving rivers characteristic of steep mountain ranges. Transcriptomic profiling further shows altitude-associated upregulation of genes related to immune responses and oxidative stress mitigation, which is consistent with other reported schizothoracines, highlighting convergent molecular strategies for altitude adaptation. Collectively, these demonstrate that recent autotetraploidization, coupled with gene family innovation and homeolog-specific expression divergence, has facilitated the ecological success of Schizothorax nukiangensis in extreme environments of the Salween River. This work provides important insights into the genomic imprints underlying adaptation in high-altitude freshwater vertebrates. 多倍化造成基因组冗余，并推动了淡水鱼类生态多样性的形成与扩展。然而，高海拔生态系统中近期多倍化的裂腹鱼类基因组结构及其适应性意义仍知之甚少。本研究确定了四倍体怒江裂腹鱼（ Schizothorax nukiangensis）基因组大小和染色体数目，组装了四倍体怒江裂腹鱼的单倍型基因组，组装总基因组大小为3.59 Gb，挂载到了100条染色体，分为25个同源染色体组。kmer评估、共线性分析以及系统发育树等多个证据一致支持怒江裂腹鱼的同源多倍化起源，并推断其谱系特异性多倍化事件发生在约0.68百万年前。在此基础上，第一，我们比较基因组学揭示了先天免疫、氧化还原调控和转座子活性相关基因家族在怒江裂腹鱼中显著扩张，表明基因组重塑可能促进了怒江裂腹鱼在恶劣的生态环境中适应。第二，群体基因组学分析揭示了怒江裂腹鱼三个海拔群体的细微群体结构，并鉴定出高海拔群体与骨骼发育、免疫防御和纤毛功能相关的环境适应候选基因，这与怒江裂腹对湍急河流的适应相一致。第三，转录组分析进一步显示，与免疫反应和氧化应激缓解相关的基因表达随海拔升高而上调，这与其他已报道的裂腹鱼一致，凸显了趋同的分子策略在海拔适应中的应用。综上所述，本研究组装了怒江裂腹鱼的单倍型基因组，揭示了其近期同源多倍化事件，在此基础上，发现因同源多倍化基因家族的扩张和同源基因特异性表达分化可能促进了怒江裂腹鱼对高原急溪等极端生态环境的适应。本研究为高海拔急溪和气候多变的淡水鱼类适应性基因组特征研究提供了重要见解。.
Plant-associated microbiomes are central to crop productivity, nutrient efficiency, and stress resilience, yet conventional microbiome manipulation strategies, largely based on microbial inoculation and agronomic management, often suffer from inconsistent field performance and limited persistence. Although several recent reviews have discussed CRISPR-mediated plant-microbe engineering and synthetic microbial community (SynCom) design separately, few reviews integrate genome editing, ecological stability of microbiomes, and climate-resilient agricultural applications within a unified conceptual framework. Recent advances in molecular biotechnology are transforming this landscape by enabling precision engineering of plant-microbe interactions at genetic, metabolic, and community levels. In particular, synthetic biology tools including CRISPR/Cas genome editing, RNA interference, and synthetic microbial communities (SynComs), now allow targeted modification of plant traits governing microbial recruitment, microbial pathways underpinning nutrient cycling and stress tolerance, and community-level functional complementarity. This review integrates molecular genetics, microbial ecology, and systems-level microbiome design to frame the plant and its microbiome as an engineerable holobiont. We integrate insights from genome editing in plants and microbes, omics-guided SynCom design, climate-resilience mechanisms, and emerging AI-assisted decision frameworks, including machine learning and ecological modeling approaches used to analyze multi-omics datasets, and predict plant-microbiome interactions across experimental and field-based studies. Importantly, we critically assess limitations related to ecological stability, trait trade-offs, biosafety, and regulatory challenges that constrain large-scale deployment. By bridging genome-enabled microbiome manipulation with ecological design principles, this review proposes an integrative framework for climate-smart microbiome engineering and identifies key research priorities required to transition from empirical inoculation toward predictive, sustainable, and socially responsible agricultural biotechnology.
The recognition of FOXP3 as the master regulator of regulatory T cells (Tregs) established the genetic and functional basis for peripheral immune tolerance. Contemporary advances in single-cell genomics and epigenetic mapping have further refined this landscape, revealing distinct, tissue-adapted Treg subsets and identifying the Treg-specific demethylated region (TSDR) as the critical molecular marker for durable lineage stability. The transition toward personalized Treg medicine has become feasible through an integrated pipeline that maps individual cellular signatures and employs precision engineering. Transitioning to personalized Treg medicine requires an integrated pipeline combining antigen-specific CAR-Treg design, CRISPR-mediated epigenetic stabilization, and metabolic reprogramming. However, durable success hinges on navigating biological and translational hurdles, including lineage plasticity, receptor-driven exhaustion, and manufacturing bottlenecks. By integrating real-time TSDR monitoring and inducible safety switches like iCasp9, this framework translates mechanistic insights into context-matched, precision interventions. This roadmap provides a definitive strategy for restoring immune balance in autoimmunity and transplantation while addressing the complex constraints of modern living-cell therapies.
Triple-negative breast cancer (TNBC) is a highly aggressive subtype lacking effective targeted therapies. Increasing evidence highlights metabolic reprogramming as a hallmark of tumor progression and immune evasion. However, in this context, the specific metabolic-immune mechanisms underlying TNBC remain unclear. We performed an integrative multi-omics analysis combining bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics across TNBC and non-TNBC samples from TCGA, GEO, and 10X Genomics. Eighty-five KEGG metabolic pathways were profiled to identify TNBC-specific alterations. Machine learning models (Random Forest, XGBoost) were used to prioritize key metabolic genes. Immune infiltration was evaluated using CIBERSORT, ssGSEA, and ESTIMATE algorithms. Validation was conducted through immunohistochemistry (IHC) on 100 clinical samples from The First Affiliated Hospital of Anhui University Chinese Medicine. The Lacto/Neolacto glycosphingolipid metabolism pathway was markedly activated in TNBC compared to adjacent and non-TNBC tissues, correlating with worse prognosis. Machine learning identified ST3GAL4 as the core enzyme within this pathway. High ST3GAL4 expression was associated with increased infiltration of regulatory T cells (Tregs) and M2 macrophages, reduced CD8+ T-cell activity, and enhanced epithelial-mesenchymal transition. Spatial transcriptomics confirmed localized enrichment of immunosuppressive cells in ST3GAL4-high regions. IHC validation demonstrated that ST3GAL4 overexpression in TNBC tissues predicts poor clinical outcomes. ST3GAL4-driven glycosphingolipid metabolism promotes tumor immune evasion and aggressiveness in TNBC. This metabolic-immune coupling axis represents a potential therapeutic target, offering mechanistic rationale for combining metabolic and immune checkpoint blockade strategies.
Rice seed storage proteins (SSPs) are major determinants of grain nutritional quality, serving as primary sources of dietary protein, energy, and essential nutrients. However, limited understanding of their diversity, evolution, and regulation constrains efforts to improve grain quality. This study aimed to perform a comprehensive genome-wide characterization of SSPs in rice. A combined homology- and domain-based approach was employed to identify SSP-encoding genes in the rice genome. These proteins were further analysed through phylogenetic reconstruction, domain and motif characterization, promoter cis-element analysis, expression profiling across seed developmental stages, and three-dimensional structural modelling. A total of 65 SSP genes were identified, including 19 previously uncharacterized members. Phylogenetic and domain analyses revealed evolutionary relationships between albumins and prolamins, and between globulins and glutelins. Tandem clustering of albumins, glutelins, and prolamins suggested gene duplication as a major driver of SSP family expansion. Expression profiling indicated that albumins, globulins, and glutelins were transcriptionally active from the S2 stage, whereas prolamins were predominantly expressed from the S3 stage onwards. Promoter analysis identified several seed-specific cis-regulatory elements, including CAATBOX1, EBOXBNNAPA, and DOFCOREZM. Structural modelling showed that albumins and prolamins are primarily composed of α-helices, while globulins and glutelins are enriched in β-strands and coils. This integrative analysis provides comprehensive insights into the classification, evolution, regulatory mechanisms, and structural features of rice SSPs. The findings establish a valuable resource for future functional studies and offer a foundation for strategies aimed at improving grain nutritional quality.
Metabolic reprogramming and the formation of an immunosuppressive tumor microenvironment(TME) are hallmarks of osteosarcoma (OS). However, the metabolic characteristics of OS and its associated immune microenvironment remain largely unknown. The single-cell data were processed for dimensionality reduction and cell-type annotation by using the Seurat package. Pseudotime analysis and metabolic difference prediction were performed using the SCPA algorithm to predict the metabolic profiles of immune cells. Through integrative analyses using BeyondCell and scMetabolism, three distinct cancer cell subpopulations were identified. Metabolic flux potential and intercellular metabolic communication within each subpopulation were subsequently quantified using METAFlux and Mebocost. Spatial colocalization analysis and intercellular communication prediction were conducted using SpaCET and CellChat. Furthermore, qRT-PCR and survival analyses were performed on our cohort of OS patients. Monocytes emerged as the predominant immune cell population within OS tissues, displaying pronounced metabolic reprogramming marked by significant upregulation of glycolysis and tryptophan metabolism. Additionally, three cancer cell subpopulations with distinct chemosensitivity profiles were identified; Subpopulation 2, characterized by high expression of CCNA2, UBE2C, and CENPF, demonstrated significantly reduced sensitivity to methotrexate, doxorubicin, cisplatin, ifosfamide, and etoposide. Moreover, both cancer cells and monocytes function as key metabolic regulators, with glutamine serving as a critical metabolic mediator. Monocytes were predominantly localized in proximity to tumor cells and exhibited activation of signaling pathways such as SPP1 and ICAM. SLC7A7 expression was significantly downregulated in OS tissues, and its expression level was correlated with patient prognosis. Furthermore, monocytes exhibiting SLC7A7 downregulation may display aberrant recruitment patterns and functional deficits, potentially playing a pivotal role in supplying glutamine to OS cells and fostering an immunosuppressive TME. This study provides a preliminary characterization of the metabolic landscape of OS and its associated immune microenvironment. Targeting SLC7A7-deficient monocytes may represent promising strategies for enhancing the efficacy of immunotherapy in OS.
Non-coding DNA, long considered "junk", is now recognized as a central regulator of genome architecture. Highly repetitive satellite DNA sequences shape heterochromatin and are essential for chromosome stability, segregation, and gene regulation. Pericentromeric heterochromatic variants, or chromosomal heteromorphisms (CHs), have emerged as modulators of human fertility, potentially affecting gametogenesis and early embryonic development. Despite their ubiquity, the functional and clinical significance of CHs remains largely enigmatic. Molecular reference genomes fail to fully capture these repetitive domains, and cytogenetic assessment has shown critical inconsistencies due to the lack of standardized evaluation criteria. To address this gap, we proposed a comparison-based scoring system to reliably identify and characterize CHs. By applying this framework to 300 individuals with idiopathic reproductive disorders and 155 fertile controls, we observed a significantly higher CH frequency in the infertile cohort (2.4-fold increase; p < 0.001). Chromosome 9 variants were the most prevalent (5.3%; p = 0.036), with 1qh+ and 16qh+ as the most common type-specific variants. Cases of recurrent pregnancy loss exhibited the highest CH burden. These results support a significant association between CHs and adverse reproductive outcomes, suggesting that heterochromatic variants may act as predisposing factors for infertility. Importantly, the proposed scoring system addresses critical cytogenetic inconsistencies and provides a comprehensive, reproducible framework that will enhance cross-study comparability and enable future investigations into the structural, functional, evolutionary, and clinical relevance of satellite DNA-enriched heterochromatic regions.
Enhancers play an important role in transcriptional regulation by modulating gene expression from distal genomic locations. Although single-cell ATAC and RNA sequencing (scATAC/RNA-seq) data have been leveraged to infer enhancer-gene links, establishing regulatory links between enhancers and their target genes remains a challenge due to the absence of chromatin conformation information. Here, we present SCEG-HiC, a machine learning method based on weighted graphical lasso, which decodes enhancer-gene links from single-cell multi-omics data by integrating bulk average Hi-C as prior knowledge. SCEG-HiC supports both paired scATAC/RNA-seq and scATAC-only inputs, improving prediction accuracy while retaining context-specific correlations and enabling the discovery of biologically relevant links. Comprehensive evaluation across 10 human and mouse single-cell multi-omics datasets shows that SCEG-HiC outperforms existing single-cell models. Application of SCEG-HiC to COVID-19 datasets illustrates its capacity to more reliably reconstruct gene regulatory networks underlying disease severity, and elucidate functional associations between noncoding variants and their putative target genes. SCEG-HiC is freely available as an open-source and user-friendly R package, facilitating broad applications in regulatory genomics research.
C-reactive protein (CRP) is a marker of inflammation associated with autoimmune, cardiovascular, and neuropsychiatric disorders. However, it remains unclear whether CRP causally affects these traits or if observed associations result from reverse causation or confounding. Mendelian randomization (MR) uses genetic variants as instrumental variables to estimate causal effects and avoid the biases present in observational studies. Prior MR studies have suggested causal effects of CRP on several traits, including low-density lipoprotein (LDL) cholesterol, schizophrenia (SCZ), and knee osteoarthritis (OA). However, MR may produce biased results if traits that confound the exposure and outcome are heritable, resulting in horizontal pleiotropy. This is a major concern for studies of CRP, because CRP levels may increase in response to inflammation caused by a wide range of heritable conditions. Multivariable Mendelian randomization (MVMR) can be used to eliminate bias from heritable confounding when genome-wide association study (GWAS) summary data are available for confounders. In this study, we used MVMR to estimate the causal effects of CRP on 16 outcomes with prior evidence of a causal or associational link to CRP. We used a novel computational pipeline to identify a broad set of potential heritable confounders between CRP and each outcome trait from studies in the Medical Research Council Integrative Epidemiology Unit (MRC-IEU) OpenGWAS database. We compared MVMR results with computationally selected confounders to univariable MR results and MVMR adjusting only for body mass index. Univariable MR suggests evidence of potential causal effects of CRP on coronary artery disease, high-density lipoprotein (HDL) cholesterol, LDL cholesterol, triglycerides, type 2 diabetes, glycated hemoglobin (HbA1c), rheumatoid arthritis (RA), SCZ and OA at the nominal P < .05 significance level. However, after adjusting for computationally selected heritable confounders, only effects on HDL cholesterol (negative), HbA1c (positive), RA (risk increasing), and SCZ (risk decreasing) remain nominally significant. Using confounder-adjusted MVMR additionally reveals evidence of a protective effect of CRP on bipolar disorder not observed in the univariable analysis. These results suggest that univariable MR analyses of CRP may be biased by high levels of heritable confounding, though CRP may indeed play a causal role in development of some diseases, potentially mediated by its role in innate immunity. These results also highlight the potential for automatic confounder selection to improve the robustness of MR analyses.
The large-scale production of poultry manure poses significant environmental safety challenges, and Black Soldier Fly (BSF) has emerged as a potential resource utilization solution. However, the toxicological effects of doxycycline (DOX) contamination in poultry feces on methane (CH4) and nitrous oxide (N2O) emission potential throughout the BSF manure recycling process remains unclear, especially from a phage-microbe interaction perspective. This study investigates the roles of bacterial and phage-related functional genes associated with CH4 and N2O metabolism in the "chicken manure-organic fertilizer" and "chicken manure-BSF-chicken" pathways. The results reveal that DOX in poultry manure causes toxicological perturbations of the microbial community, significantly elevating the levels of key functional genes (mcrA/pmoA and (nirS+nirK)/nosZ) linked to GHG emission potential. These DOX-induced elevated gene levels persisted in BSF-derived organic fertilizer and in the feces of laying hens fed BSF reared on contaminated manure. However, 24-hour starvation pretreatment combined with 8-hour drying at 65 °C can effectively alleviate the negative toxicological effects induced by DOX, and the emission potentials of CH₄ and N₂O in the feces of laying hens fed BSF treated in this way were reduced by 91.1% and 82.4%, respectively. Importantly, phage-mediated horizontal gene transfer (HGT) plays a significant regulatory role in these gene changes, further amplifying the DOX-induced GHG emission risk. This study highlights the potential of BSF pretreatment to reduce the environmental risk of antibiotic-contaminated poultry manure while addressing climate concerns from an environmental toxicology perspective. It also provides a scalable toxicological risk mitigation strategy to reduce greenhouse gas emission potential in poultry farming systems, which is of great significance for the environmental safety of intensive poultry production.