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Construction of circRNA-miRNA-mRNA regulatory networks in the intestine of turbot (Scophthalmus maximus) following Vibrio anguillarum infection.

Circular RNAs (circRNAs) play pivotal roles in post-transcriptional regulation by acting as molecular sponges for microRNAs (miRNAs) within the competitive endogenous RNA (ceRNA) network. However, the regulatory mechanisms in teleost immune responses remain poorly understood. In this study, circRNA-miRNA-mRNA networks were investigated in turbot (Scophthalmus maximus) following Vibrio anguillarum infection to elucidate host-pathogen interactions. Through high-throughput sequencing of intestinal tissues, a total of 50 differentially expressed circRNAs (DE-circRNAs) (18 at 2 hpi, 16 at 12 hpi, 16 at 48 hpi), 212 DE-miRNAs (11 at 2 hpi, 70 at 12 hpi, 15 at 48 hpi), and 1774 DE-mRNAs were identified. Functional enrichment analyses (GO/KEGG) revealed significant associations with immune pathways, including the MAPK signaling pathway and gap junction. An integrated circRNA-miRNA-mRNA regulatory network was constructed, highlighting key interactions including novel_circ_0002573/DE-miR-27a-3p/FGB and novel_circ_0002423/novel_347/GNE, which may regulate inflammatory and antibacterial responses. The expression patterns of selected circRNAs, miRNAs and mRNAs were validated using qRT-PCR, confirming the reliability of the sequencing results. Importantly, fibrinogen beta chain (FGB) and CXCR4/CXCL12 signaling were identified as critical immune modulators. These findings provide insights of the ceRNA regulatory networks involved in teleost intestinal immunity and provide potential molecular targets for selective breeding of disease resistance in this species.

Animals

Genome-wide identification and expression profiling of CSP and OBP genes in Stictocephala bisonia reveals candidate genes potentially associated with insecticide response.

Stictocephala bisonia is an important invasive agricultural pest. Due to the frequent application of insecticides in its habitat, this species is under intense selection pressure. Chemosensory proteins (CSPs) and odorant-binding proteins (OBPs) are known to play key roles in insecticide resistance, but their specific functions in S. bisonia remain unclear. In this study, we identified a total of 22 SbisCSPs and 16 SbisOBPs based on the S. bisonia genome. To screen for candidate genes potentially linked to insecticide resistance, we adopted a multi-criteria screening strategy that integrated phylogenetic analysis, molecular docking with three insecticides, and tissue-specific expression profiling. Phylogenetic analysis identified several SbisCSPs and SbisOBPs clustering with genes known to be involved in insecticide resistance, serving as an initial evolutionary filter. Molecular docking results indicated that λ-Cyhalothrin exhibited the strong predicted binding affinity with most of SbisCSPs and SbisOBPs. Subsequent qPCR validation of seven prioritized candidates revealed distinct expression patterns: SbisCSP22 was highly expressed in adults and demonstrated strong binding affinity to all three insecticides tested, suggesting a potential role in mediating multi-insecticide response. Conversely, SbisCSP17 was significantly upregulated in larvae, clustered with genes known to mediate imidacloprid resistance, and exhibited strong binding affinity to imidacloprid. Given its larval-specific expression and the soil-dwelling behavior of larvae, we hypothesize that SbisCSP17 is a key candidate gene for larvae coping with soil-treated insecticides.

Animals

Multi-omics integrative analysis provides insight into potential molecular responses to sustained high water flow in common carp (Cyprinus carpio) cultured in recirculating aquaculture.

To investigate the potential molecular responses by which water flow intensity affects the growth of common carp (Cyprinus carpio) in a recirculating aquaculture system (RAS), a control group (CG, actual water velocity 0.3&#xa0;cm/s) and three sustained flow treatment groups were established, including a low-flow group (LF, 1 body length per second, bl/s), a medium-flow group (MF, 2 bl/s), and a high-flow group (HF, 3 bl/s). After 12&#xa0;weeks of culture in the RAS, growth performance was compared among groups under different flow intensities. The best-performing group and the control group were then selected for the determination of intestinal digestive enzyme activities, as well as transcriptomic and whole-genome bisulfite sequencing analyses of muscle tissue. The results showed that the specific growth rate and feed intake of the HF group were significantly higher than those of the other groups (P&#xa0;<&#xa0;0.05), whereas no significant difference in feed conversion ratio was observed among groups. Compared with the CG group, lipase activity was significantly higher in the HF group (P&#xa0;<&#xa0;0.05), while &#x3b1;-amylase and trypsin activities showed increasing trends without significant differences. RNA-seq identified a total of 273 differentially expressed genes, including 72 upregulated genes and 201 downregulated genes in the HF group relative to the CG group. These genes were mainly enriched in glycolysis, pyruvate metabolism, ATP metabolism, the pentose phosphate pathway, the insulin signaling pathway, the PPAR signaling pathway, and the adipocytokine signaling pathway, indicating that sustained high water flow induced a muscle transcriptional response characterized by remodeling of energy metabolism and substrate utilization. Whole-genome bisulfite sequencing analysis showed that DNA methylation in common carp muscle occurred predominantly in the CpG context. Differentially methylated regions between the HF and CG groups were mainly distributed in transcription-related regulatory regions, including promoters, CpG islands, and CpG island shores. In promoter regions, the number of hypermethylated regions in the HF group relative to the CG group was markedly higher than that of hypomethylated regions. Integrated analysis further identified two candidate genes showing both promoter differential methylation and differential expression, namely LOC109094644 and bcorl1, suggesting that adaptation to high water flow may involve IGF-related growth regulation and remodeling of upstream transcriptional programs. The qPCR results were consistent with the transcriptomic data. Taken together, within the tested range, a sustained water flow of 3 bl/s was more conducive to the growth of common carp in the RAS, which may be associated with enhanced lipid digestion and utilization, remodeling of the muscle energy metabolic network, changes in promoter methylation, and the coordinated regulation of key candidate genes. This study provides a theoretical basis for clarifying the exercise adaptation mechanism of common carp in recirculating aquaculture and for optimizing flow velocity parameters.

Animals

Mineral-driven molecular signatures of energy metabolism underpin sperm motility in buffalo.

The success of spermatogenesis depends on the interplay of various biomolecules that ultimately determine sperm quality. In this study, RNA-seq analysis of frozen-thawed buffalo sperm (n&#x202f;=&#x202f;8) revealed the presence of 263 mineral-associated genes (>1 FPKM) in high (n&#x202f;=&#x202f;4) and 181 in low motile (n&#x202f;=&#x202f;4) sperm groups. Among these, 177 mineral-associated genes were commonly expressed between them, and the majority were upregulated (>1 fold), LOC102391588 (ncRNA; 37-fold), ZNF699 (26.5-fold), MYZAP (13-fold), etc., in the high motile group. The expression of selected mineral-associated genes was validated. The top enriched functions in commonly expressed genes were regulation of transcription by RNA polymerase II (FDR: 4.7&#x202f;&#xd7; 10&#x207b;2; ZNF331, ZNF692, ZNF180, etc.), followed by spermatogenesis (FDR: 2.9&#x202f;&#xd7; 10&#x207b;2; CALR3, ADAM18, ADAM29, etc.), proton transmembrane transport (FDR: 4.0&#x202f;&#xd7; 10&#x207b;2; ATP6V0E1, ATP1A4, ATP6V1B2, etc.) and flagellated sperm motility (FDR: 2.3&#x202f;&#xd7; 10&#x207b;1; CATSPERD, EFCAB6, CABS1, etc.). Additionally, the chromatin remodeling pathway (FDR: 3&#x202f;&#xd7; 10&#x207b;2; PTP4A1, PPM1A, DUSP1, etc.) emerged as the most significant and may suggest that these minerals influence genome packaging and sperm functionality. Mineral-associated genes were predominantly associated with zinc (49%), followed by calcium (20%), phosphorus (10%), iron (5%), sodium (2%), potassium (2%), copper (1%) and other trace elements (11%). Although the current study uses frozen-thawed sperm, the findings indicate that mineral-associated genes are crucial for promoting membrane stability, energy production, motility and chromatin integrity, which may contribute to the superior fertilizing ability of sperm.

Animals

Amino acid reprogramming and biofilm-specific tricarboxylate transporters in PET-degrading Piscinibacter sakaiensis.

Plastic-degrading bacteria predominantly colonize polymer surfaces as biofilms, yet it remains unclear whether the biofilm phenotype contributes to metabolism beyond retaining extracellular enzymes. Here, we combine population-level RNA-sequencing across three conditions-biofilm cells on polyethylene terephthalate (PET), planktonic cells incubated with PET, and planktonic cells on maltose-with single-cell Raman spectroscopy to characterize the PET response of Piscinibacter sakaiensis (formerly Ideonella sakaiensis). This integrated approach reveals two metabolically distinct response layers. A carbon-source-driven response shared by all PET-exposed cells is dominated by a broad amino acid reprogramming, led by upregulation of branched-chain amino acid transport genes, enhanced serine biosynthesis, and reduced chemotaxis. A biofilm-specific layer selectively induces tripartite tricarboxylate transporter genes from three distinct genomic loci. This transcriptional feature is accompanied by a single-cell phenotype consistent with a protein-rich and saturated membrane. These results suggest that biofilm formation is not limited to enzyme retention but is associated with selective activation of transport systems, consistent with a putative role in capturing PET-derived intermediates at the polymer interface. This two-layer model separates general metabolic adaptation to PET from biofilm-specific functions and provides a framework for understanding how surface-associated bacterial physiology contributes to plastic degradation.IMPORTANCEPolyethylene terephthalate (PET) degradation in natural and engineered environments is largely mediated by surface-attached microbial communities, yet the physiological role of biofilm state during plastic degradation remains poorly understood. Using the model PET degrader Piscinibacter sakaiensis, we show that biofilm-associated cells are not simply retained near the polymer surface but exhibit a distinct metabolic program characterized by selective induction of tripartite tricarboxylate transporters. In contrast, extensive amino acid reprogramming occurs in both biofilm and planktonic PET-exposed cells, indicating that it is driven by carbon source rather than surface attachment. These findings reveal that PET degradation involves two separable physiological layers: a general metabolic response to PET-derived carbon shared across cell phenotypes, and a biofilm-specific transport response potentially linked to substrate capture at the plastic interface. This work advances our understanding of how microbial physiology is organized during plastic biodegradation and identifies transport processes as previously unrecognized components of PET-degrading biofilms.

PET biodegradation

SGLF-Net:Staged Global-to-Local Cross-Scale Fusion Network for Colonoscopic Polyp Segmentation.

Polyp segmentation in colonoscopy images plays a pivotal role in computer-aided medical diagnosis and the early prevention of colorectal cancer. However, existing methods often suffer from performance degradation when confronted with extreme polyp scale variation and polyp boundary ambiguity. To address these challenges, we propose the Staged Global-to-Local Cross-Scale Fusion Network (SGLF-Net), which adopts a novel staged global-to-local learning paradigm to progressively refine segmentation from coarse global semantics to fine-grained local details. Specifically, the Global Semantic Perception Stage integrates a Swin Transformer Encoder and a Dynamic Attentive Decoder (DAD) to construct comprehensive multi-scale contextual representations. The Local Detail Refinement Stage employs an Edge-aware Dynamic Attentive Decoder (E-DAD) to enhance structural fidelity and boundary precision through explicit edge-guided supervision. Furthermore, we introduce the Cross Spatial-Scale Feature Aggregation and Reconstitution (CSSAR) module, equipped with hybrid attention mechanisms, to facilitate efficient semantic structural interaction between the two cascaded stages. Extensive experiments on five public benchmark datasets demonstrate that SGLF-Net consistently outperforms state-of-the-art methods in both segmentation accuracy and boundary preservation.

Journal Article

Systematic evaluation of one-dimensional-to-two-dimensional near-infrared spectroscopy transformations with deep learning for quantifying coconut sap adulteration.

Near-infrared (NIR) spectroscopy have limitations when combined with deep learning (DL) algorithms because they rely on low-dimensional datasets. Therefore, we investigated the potential of transforming one-dimensional (1D) NIR spectra into two-dimensional (2D) spectrograms using synchronous and asynchronous techniques and the continuous wavelet transform (CWT) and their effectiveness by integrating with DL for detecting adulteration in coconut sap. NIR spectra (12,500-4000&#xa0;cm-1) were collected from binary mixtures (0%-100%;w/w). The performance of all DL (convolutional neural networks-CNN, AlexNet and ResNet) models was compared with that of partial least squares (PLS). The models were ranked in the mentioned order based on their performances: 2D-CWT&#xa0;>&#xa0;2D-asynchronous > 2D-synchronous > 1D/2D-PLS. The important features of the best model can be explained and visualized using gradient-weighted-class-activation-mapping. The findings highlight that the 1D-to-2D NIR data transformation combined with DL is a highly robust approach because it addresses the feature representation gap in NIR data and effectively captures the spatial-spectral correlations.

Spectroscopy, Near-Infrared

Morphology-Encoded Colorimetric Hydrogen Sensing Using Embedded Reactive Pd Absorbers in Fabry-Perot Cavities.

Chemical reactions offer a powerful strategy for generating visible optical responses through localized changes in absorption, dielectric environment, and interfacial wetting. A palladium (Pd)-embedded Fabry-Perot cavity is introduced as a reaction-active optical platform in which structural color is governed by intracavity absorption coupled with reaction-induced dielectric perturbation. Positioning Pd within the dielectric spacer creates a spatially controllable reactive absorber whose vertical location relative to the standing-wave field dictates wavelength-selective absorption within the cavity. The morphology of the embedded Pd layer provides an additional design parameter by modulating both optical loss and interfacial wetting. Under hydrogen exposure in the presence of oxygen, catalytic water formation at the Pd/polymer interface generates localized dielectric heterogeneity and interfacial water droplets, thereby perturbing the optical path length and amplifying the visible response. As a result, the cavity exhibits pronounced, morphology-dependent color transitions that are inaccessible through dielectric-layer engineering or Pd/PdH refractive-index changes alone, enabling direct visual hydrogen sensing under ambient light, as well as flexible optical devices capable of large-area patterning. These findings establish a design framework for reaction-active optical cavities that translate localized chemistry into a colorimetric hydrogen sensing mechanism.

Fabry&#x2013;Perot resonator

Mitochondrial translocation of DNMT3L suppresses oxidative phosphorylation and restrains megakaryopoiesis.

DNMT3L, a catalytically inactive member of the DNA methyltransferase family, is identified here as a negative regulator of megakaryopoiesis. In K562 cells undergoing PMA-induced megakaryocytic differentiation, DNMT3L protein levels declined progressively, and shRNA-mediated depletion enhanced differentiation, whereas overexpression attenuated it. Consistent with these findings, Dnmt3l-knockout mice exhibited elevated peripheral blood platelet counts and expanded bone marrow megakaryocytes. Mechanistically, megakaryocytic differentiation triggered rapid mitochondrial translocation of DNMT3L within 6&#xa0;h; mitochondrial DNMT3L suppressed oxidative phosphorylation (OXPHOS) capacity and ATP production and downregulated mitochondrial-encoded genes spanning Complex I, III, IV, and ATP synthase, without altering mitochondrial DNA copy number. This metabolic suppression was mediated through compartment-specific remodeling of DNMT3L-containing protein complexes: upon differentiation, DNMT3L selectively dissociated from DNMT1 and DNMT3B in mitochondria, relieving the repressive constraint on OXPHOS, whereas in the nucleus DNMT3L remained associated with DNMT3A, which concomitantly accumulated during differentiation. These findings reveal a previously unrecognized mechanism by which a catalytically inactive epigenetic co-regulator spatially redistributes to coordinate mitochondrial metabolic output with nuclear epigenetic control, thereby facilitating terminal megakaryocytic maturation.

Animals

Beyond species trees: pervasive gene flow limits phylogenomic resolution in the diversification of Juniperus from the Qinghai-Tibet Plateau.

Understanding how lineages diversify despite persistent ancestral polymorphism and recurrent gene flow remains a central challenge in evolutionary biology. Juniperus distributed across the Qinghai-Tibet Plateau provide an ideal system for addressing this question because repeated geological uplift and climatic oscillations have likely promoted cycles of lineage divergence, range shifts, and secondary contact. Here, we combined approximately 1.08 million genome-wide SNPs from 164 individuals representing thirteen Juniperus lineages with phylogenomic datasets comprising 3,381 nuclear single-copy genes and nearly complete plastomes. We detected extensive phylogenomic discordance and cytonuclear incongruence across genomic datasets. Topology weighting, coalescent simulations, quartet-based tests, and analyses of gene flow and reticulation collectively support the interpretation that these patterns were shaped by the combined effects of prolonged incomplete lineage sorting and gene flow during lineage diversification. Ecological niche analyses further provide a spatial and climatic context in which environmentally similar lineages may have had greater opportunities for secondary contact during historical range shifts. Collectively, our results reveal that the evolutionary history of Qinghai-Tibet Plateau Juniperus is characterized by reticulate diversification rather than strictly bifurcating evolution, and demonstrate how genome-wide discordance can provide biological insights into the evolutionary processes underlying lineage diversification.

Gene Flow

Wounds that echo: community perceptions of the socio-structural determinants of community violence in post-apartheid South Africa in the context of COVID-19.

The COVID-19 pandemic and its associated public health measures significantly altered the social, economic, and psychological landscape of communities worldwide. In South Africa, the post-COVID-19 period has been marked by a notable surge in homicide rates and interpersonal and community violence. Using a combined structural and social disorganisation framework, this qualitative study critically explores community members' perceptions of the socio-structural factors contributing to community violence, in the context of COVID-19. Utilising data from in-depth interviews and focus group discussions, this study examines the lived experiences of residents in a marginalised high-risk South African community, unpacking the interplay between structural inequities, social disintegration, and community violence. Community violence emerged not as periodic or individual, but as structurally generated, geographically concentrated, and socially normalised. The findings demonstrate that community violence is perceived as being embedded in cycles of survival, where long-standing systemic inequality, economic precarity, spatial disadvantage, and institutional neglect and inequity generate contexts in which community violence becomes normalised and self-reinforcing. The study findings advocate for interventions that not only address immediate catalysts of violence but also the deeper historical and structural determinants of violence in the post-pandemic era, while ensuring preparedness for effective violence prevention during future pandemics.

Humans

Epigenetic Gene Networks Governing Immune State Transitions Across the Lifespan.

Immune function across development, tissue repair, aging, and disease depends not only on signaling pathways but also on epigenetic architectures that determine whether coordinated transcriptional programs can be accessed and resolved. Increasing evidence indicates that epigenetic gene networks regulate the accessibility and reversibility of semi-stable immune states, shaping plastic, homeostatic, reparative, and degenerative configurations. We propose the concept of epigenetic transition windows, defined as temporally and contextually restricted intervals during which epigenetic constraints are relaxed, permitting coordinated and reversible transitions between immune states. During development, these windows are broad and support immune tolerance and adaptive plasticity. In adulthood they become spatially and temporally restricted, preserving stability while enabling conditional adaptation. With aging, they progressively narrow, contributing to chronic inflammation, impaired repair, and increased vulnerability to neurodegeneration. Conversely, pathological persistence of regulatory permissiveness may underlie immune evasion and sustained plasticity in cancer. We outline operational genomic readouts for quantifying transition windows, including chromatin accessibility variance, enhancer switching dynamics, reversibility metrics, and cross-cell coordination indices, and derive experimentally testable predictions that distinguish this model from pathway-centric or damage-centric explanations. By reframing immune dysfunction as a failure of regulated state transition rather than excessive signaling alone, this framework integrates inflammaging, trained immunity, immune resolution failure, and tumor immune escape within a unified regulatory architecture and provides a systems-level perspective on immune adaptability across the lifespan.

Epigenesis, Genetic

The mighty microproteins: from versatile cellular regulators to precision medicine therapeutics.

Microproteins, are tiny proteins encoded by small open reading frame (sORF), translation of these non-canonical open reading frames (ncORFs) has been implicated in diverse biological processes and diseases. This review summarizes recent developments in the discovery, biogenesis, and functional characterization of microproteins, and their involvement in various disease, with special focus on their roles in cancer, cardiovascular, metabolic, neurodegenerative and immune-related disorders. We emphasize the regulation of key cellular pathways by microproteins, including mitochondrial homeostasis, apoptosis, metabolic reprogramming, and immune signaling, all of which affect disease initiation and progression. Emerging evidence also supports their potential as disease biomarkers and therapeutic candidates for precision medicine. Finally, the review critically discusses the current challenges including discrepancies in microprotein annotation, the limitations of ribosome profiling and proteogenomic approaches, the gap between computationally predicted and experimentally validated microproteins, and the need for rigorous orthogonal validation by means of CRISPR-based genome editing, ribosome release assays, mutational analysis, high-resolution mass spectrometry, and functional studies. Finally, we review recent development of AI-assisted ORF prediction, single-cell translatomics, spatial proteomics, and integrated multi-omics as emerging technologies reshaping. Microprotein discovery and functional annotation. Finally, we discuss the translational potential of microproteins and highlight the remaining challenges to clinical application, including peptide stability, pharmacokinetics, tissue-specific delivery, immunogenicity, and the need for rigorous preclinical and clinical validation. Together, this review provides an updated and critical overview of the rapidly evolving microprotein field and highlights future research priorities for translating these molecules into clinically useful biomarkers and precision therapeutics.

Microproteins

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metabolism axis in this comorbidity remains unclear. We explored its underlying mechanisms and evaluated the therapeutic potential of gentiopicroside. METHODS: Integrated multi-omics analyses combining transcriptomics, single-cell RNA sequencing, Mendelian randomization, machine learning, molecular docking, and in vitro functional assays were performed to identify shared molecular pathways and therapeutic targets across PCOS, hypertension, NAFLD, and T2DM. RESULTS: SLC11A2 was consistently dysregulated in PCOS transcriptomic datasets, and associated with iron metabolism, inflammatory response and oxidative stress pathways. Genetic analyses validated RAS-related regulation in hypertension susceptibility and revealed shared genetic architecture between PCOS and cardiometabolic traits. Network and single-cell analyses characterized SLC11A2-associated molecular patterns in disease-relevant cell types; machine learning identified disease-classifying molecular signatures. Gentiopicroside alleviated inflammatory and oxidative stress phenotypes, including reduced IL-6 expression and reactive oxygen species accumulation. CONCLUSION: This study defines an RAS-SLC11A2 molecular framework linking iron metabolism dysregulation to PCOS-related cardiometabolic risk, elucidating the mechanisms connecting ovarian dysfunction, inflammation, oxidative stress and hypertension, and supports gentiopicroside as a promising therapeutic candidate.

Humans

Effects of strength and balance training on the structure of the aging brain.

BACKGROUND: While it is established that motor training induces structural changes in the brains of young adults, structural adaptations in aging brains are less studied. METHODS: This randomized controlled study investigated the impact of long-term strength and balance training on the structural plasticity in 60 elderly adults (64 - 82 years old, 70.6 &#xb1; 4.7) using multi-modal neuroimaging. We compared the effects of three months of strength training to balance training of the same duration and to a passive control group. Voxel-based morphometry (VBM) and tract-based spatial statistics (TBSS) were used to assess grey matter (GM) and white matter (WM) plasticity. White matter tract integrity (WMTI) modelling was employed to explore the microstructural underpinnings of white matter alterations. RESULTS: We found that strength training was associated with changes in diffusion metrics consistent with white matter microstructural remodeling, specifically increased extra-axonal axial diffusivity in the bilateral inferior fronto-occipital and longitudinal fasciculi. Additionally, both balance and strength training mitigated reductions in axonal water fraction in the splenium of the corpus callosum and the right posterior corona radiata observed in the control group. CONCLUSION: These results underscore the potential relevance of strength and balance training to induce beneficial neural plasticity by counteracting aging-related demyelination in the corpus callosum and highlight the specific role of strength training in facilitating white matter reorganization in key transmission fiber pathways.

Humans

Parent-of-origin effects on allelic expression bias in interspecific poplar hybrids.

In hybrid plants, phenotypic outcomes are governed by interactions between the two parental genomes. However, the mechanisms underlying the interplay of divergent regulatory networks from these genomes remain poorly understood. In this study, we compared gene-level and allele-specific expression patterns, as well as differentially enriched pathways between F&#x2081; and complex backcross (CBC) lines derived from a natural interspecific hybrid population of Populus fremontii (Pf) and P. angustifolia (Pa). Metabolic differences between Pf and Pa which exhibit low and high levels respectively of phenylpropanoid-derived condensed tannins were leveraged. Using individualized transcriptome references, differential expression and clustering analyses revealed CBC-biased and F&#x2081;-biased expression for genes involved in phenylpropanoid metabolism and photosynthesis, respectively. Biased expression of these genes at the allele level was also observed in F1. At the whole-transcriptome level, Pa-biased genes predominated in F&#x2081; hybrids, and Pa alleles displayed more conserved expression patterns than Pf alleles across examined samples. Further analyses indicated that allelic expression bias was significantly associated with parental origin, which could be driven by sequence variations in cis-regulatory elements and differences in CpG island length. Our findings demonstrate strong parent-of-origin effects on divergent regulatory networks governing gene expression in poplar hybrids and provide clues for strategic parental selection tailored to specific metabolic pathways of interest.

cis-regulation

Revealing the Shared Genetic Architecture of Metabolic Dysfunction-Associated Steatotic Liver Disease-Related Traits Through Genomic Structural Equation Modeling.

Although individual traits related to metabolic dysfunction-associated steatotic liver disease (MASLD) have been investigated through large-scale genome-wide association studies (GWASs), the shared genetic susceptibility across these traits remains unclear. We therefore conducted a multivariate GWAS of key MASLD-related traits to elucidate their common genetic architecture. We applied genomic structural equation modeling to model a latent genetic factor (MASLD-F) underlying genetically correlated MASLD-related traits, leveraging their GWAS-derived genetic correlations. We then performed functional annotations, including fine-mapping, transcriptome-wide association study, and cell- and tissue-type-specific enrichment analyses, and conducted Mendelian randomization analyses to identify modifiable risk factors. Our multivariate MASLD-F GWAS identified 50 independent variants across 48 genomic loci. Transcriptomic imputation identified several MASLD-F-associated genes, including ARNTL, NPC1, BTBD10, VDAC2, TSKU, SFMBT1, and ABHD17C. We observed significant enrichment of MASLD-F-related genetic signals predominantly in brain tissues, pancreatic islets, and the adrenal gland. Additionally, six modifiable risk factors and four modifiable protective factors for MASLD-F were identified. These findings reveal a complex shared genetic architecture underlying MASLD components, thereby expanding our understanding of disease pathogenesis and providing novel insights for precision medicine and public health interventions.

Humans

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation