Biology subjects

Yang, X.

Publications and source records attributed to Yang, X..

At least 145 records · Page 8Linked to original sources

bioRxiv2026

Funneliformis mosseae and Pseudomonas putida-symbiotic interaction promote drought resilience in Citrus reticulata

Climate change and increasing drought conditions significantly impedes citrus productivity in subtropical and tropical regions. This study explores the potential of combining arbuscular mycorrhizal fungi (AMF) Funneliformis mosseae and plant growth-promoting rhizobacteria (PGPR) Pseudomonas putida to mitigate drought resilience in Citrus reticulata (Red tangerine). AMF-mediated drought tolerance has been extensively documented; however, the collegial influence of PGPR and AMF on phytohormone signaling, photosynthetic efficiency, nutrient acquisition, and gene expression remains largely unexplored in citrus. We conducted a greenhouse experiment under both well water and drought stress conditions to assess the physiological and molecular responses to individual and co-inoculation with PGPR and AMF. Drought-stressed citrus plants, inoculated with AMF and PGPR, demonstrated significantly improved leaf water potential, stomatal conductance, carbon assimilation, and antioxidant defense. PGPR-AMF co-inoculation enhanced chlorophyll stability, osmotic adjustment, and nutrient uptake, while significantly reducing lipid peroxidation and ROS accumulation. The turquoise module emerged from transcriptomic and gene co-expression network analysis (WGCNA) as a potential key regulator of stress adaptation, revealed key regulatory transcription factors, e.g., CrMYB4, CrZFP8, CrSOS5, CrRGFR2, and CrQUA1, that were upregulated under combined inoculation, highlighting their potential role in stress adaptation. Our findings demonstrate that the synergistic PGPR-AMF interaction improves antioxidant enzyme activities and modulates gene expression to promote drought tolerance, providing new insights into the microbiomes role in plant resilience. These results offer a potential strategy to boost citrus growth and yield under water scarcity, with broad implications for agricultural resilience to climate change.

plant biology↗

bioRxiv2026

Sex-Specific Vulnerability to Radiofrequency Electromagnetic Radiation-Induced Reproductive and Neurological Impairment in Mice

Electromagnetic radiation (EMR) constitutes a pervasive environmental stressor, yet the sex-specific vulnerabilities to its biological effects remain inadequately characterized. This study investigated the differential impacts of 3.2 GHz pulsed EMR on reproductive and neurological functions in male and female mice following a four-week exposure regimen. We identified a pronounced sexual dimorphism in systemic and organ-specific responses. Male mice exhibited a primary vulnerability in the reproductive axis, manifesting as severe spermatogenic impairment, including depletion of the spermatogonial stem cell pool, disruption of sperm chromatin remodeling, and consequent declines in sperm quality and quantity. In contrast, exposed females showed preserved ovarian function but displayed marked neurobehavioral deficits, including increased anxiety- and depressive-like behaviors, and cognitive impairment, which were correlated with neurodegeneration in the hippocampus and prefrontal cortex. Proteomic analyses revealed distinct sex-specific biomarker profiles, with serum levels of Mdk, histone H1 variants (H1-1, H1-4, H1-5), Hp1bp3, Ncf2, and Rhoc strongly associated with male testicular dysfunction, while decreased levels of the synaptic motor protein KIF13A in serum and brain tissue were linked to female neurological impairment. Our findings delineate clear sex-divergent pathological pathways that target male spermatogenesis and female neurocognitive function and propose novel circulating protein biomarkers. This work provides a critical foundation for sex-aware risk assessment and the development of targeted preventive strategies against EMR-associated health risks.

pathology↗

bioRxiv2026

Towards building a World Model to simulate perturbation-induced cellular dynamics by AlphaCell

Predicting cellular responses to perturbations is crucial for therapeutic discovery, yet experimental screening is severely constrained by the combinatorial vastness of biological space. While computational simulations offer a scalable alternative, current models are limited by the incomplete latent representation----mainly relying on highly variable genes in feature representation; the poor genome-wide reconstruction fidelity; and the ungeneralizable dynamic laws across diverse contexts. Consequently, they fail to mechanistically transfer learned dynamics to unseen cellular contexts. To address these systemic flaws, we introduce AlphaCell, a generative Virtual Cell World Model that unifies genome-wise representation with continuous state transition modeling. AlphaCell achieves three synergistic innovations: (1) Latent Manifold Rectification, processing the full protein-coding transcriptome to construct a differentiable Virtual Cell Space, effectively filtering noise while preserving intrinsic cellular topology; (2) Biological Reality Reconstruction, utilizing a massive, knowledge-rich decoder to translate abstract latent states back into high-fidelity, genome-wide expression profiles; and (3) Universal State Transition, applying Optimal Transport Conditional Flow Matching to model perturbations as continuous, deterministic vector fields. By abstracting perturbation mechanisms into generalized dynamic laws, AlphaCell makes robust prediction of perturbation responses in a compositional generalization scenario and enables zero-shot prediction of cellular dynamics in entirely unseen cellular contexts, providing a foundational engine for cellular-context-generalizable perturbation prediction and perturbation-induced cellular dynamics simulation.

bioinformatics↗

bioRxiv2026

Rewiring of 3D Enhancer-Promoter Interactome Underlies Diabetic Endothelial Dysfunction

BackgroundDiabetic vascular complications are driven by endothelial dysfunction, yet the role of 3D genome organization in this process is unknown. We sought to define the alterations in chromatin architecture in diabetic endothelium and identify the key regulators involved. MethodsWe generated a high-resolution 3D epigenomic atlas of diabetic endothelial cells from mouse models and human subjects using H3K27ac HiChIP, complemented by ChIP-seq, ATAC-seq, and RNA-seq. A human cohort was used to assess protein expression in diabetic versus non-diabetic endothelial cells. To identify JUNB-interacting proteins, we performed rapid immunoprecipitation mass spectrometry of endogenous proteins (RIME), with protein-protein interaction validated by co-immunoprecipitation. Functional validation was performed using in vitro, ex vivo, and in vivo approaches, including endothelial-specific knockdown in a diabetic hindlimb ischemia model. ResultsMulti-omics profiling revealed extensive enhancer reprogramming in diabetic endothelium, with AP-1 binding motifs being consistently and selectively enriched in downregulated enhancers across three distinct diabetic models. Analysis of a human cohort confirmed significantly reduced JUNB protein levels in diabetic endothelial cells. We identified widespread disruption of JUNB-anchored enhancer-promoter interactions, which underlies transcriptional repression of key endothelial genes. RIME and co-immunoprecipitation established the E3 ubiquitin ligase RBBP6 as a direct JUNB interactor that promotes its polyubiquitination and proteasomal degradation in response to hyperglycemia. Human cohort analysis further showed reciprocal elevation of RBBP6 in diabetic endothelial cells. Either JUNB overexpression or RBBP6 knockdown restored enhancer-promoter connectivity, reactivated vasoprotective transcriptional programs, and rescued endothelial function. Critically, endothelial-specific knockdown of Rbbp6 in diabetic mice restored endothelium-dependent vasorelaxation and improved perfusion recovery after hindlimb ischemia, independent of systemic glucose levels. ConclusionsOur study unveils a novel mechanism whereby hyperglycemia induces enhancer reprogramming and disrupts endothelial 3D genome architecture through RBBP6-mediated degradation of JUNB. The RBBP6-JUNB axis is established as a crucial link between metabolic stress and epigenomic reprogramming in vascular disease, presenting a promising therapeutic target for diabetic vasculopathy.

genomics↗

bioRxiv2026

Therapeutic targeting inflammation linking periodontitis and atherosclerotic comorbidities using cell-free DNA-capturing nanomaterials

Periodontitis-associated systemic inflammation makes it a great challenge to explore therapeutic options applicable to periodontitis and atherosclerotic comorbidities. Here, we identify the crucial role of cell-free DNA (cfDNA) that underlies these comorbidities. Hypothesizing cfDNA as a therapeutic target, we engineer polyamidoamine dendrimer-functionalized nanomaterials to modulate such local-systemic inflammatory crosstalk. Periodontium-originated DNA can be systemically captured by cationic nanomaterials, and capturing cfDNA, whether locally or systemically, alleviates both periodontitis and atherosclerosis prior to severe atherosclerotic development in vivo. The transcriptomic and single-cell RNA sequencing analyses together reveal that cfDNA-capturing nanomaterials regulate inflammatory foam cell transformation in macrophages by modulating the expression of lipid-related foamy markers Spp1 and Fabp4. This study provides a proof of concept for cfDNA-driven periodontitis-atherosclerosis crosstalk, and offers a cfDNA-capturing nanoplatform for therapeutic intervention targeting periodontitis and atherosclerotic comorbidities in a holistic fashion.

immunology↗

bioRxiv2026

A long-read human pangenome initiative for comprehensive interpretation of nuclear-embedded mitochondrial DNA

Nuclear-embedded mitochondrial DNA segments (NUMT) preserve a record of ongoing mitochondrial-to-nuclear DNA transfer during evolution, with important implications for disease mechanisms and genome organization. Here, we developed a Pangenome Graph-based NUMT Detection (PG-NUMT) approach to improve NUMT detection sensitivity by 2.52-fold compared to short-read based approaches and comprehensively resolved seven concatenated mega-NUMTs with a maximum length of 127.7 kbp. We generated a high-resolution human NUMT map comprising 774 fixed, 280 polymorphic, and 123 pericentromeric NUMTs, alongside 74 superpopulation-stratified NUMTs. Both fixed and polymorphic NUMTs are hypermethylated and enriched within segmental duplications, whereas fixed NUMTs preferentially localize to intergenic regions and avoid transposable elements. Interestingly, NUMTs derived from the 3-end of the mtDNA D-loop are less frequently fixed in human genomes and exhibit potential cis-regulatory activity in the nuclear genome. These observations suggest that selective pressures shape the genomic features of fixed NUMTs. Seven NUMTs associated with gene expression or alternative splicing were further identified, suggesting potential modulatory functions of common NUMTs. Using 20 complete non-human primate genomes, we identified variable NUMT insertion rates across primate lineages (1.5-18.7 insertions per million years), with particularly high rates in the Pan lineage. Notably, we uncovered two NUMT-derived variable number tandem repeats (VNTRs), establishing NUMTs as a novel source of VNTRs. In summary, the integrated analysis enhances our understanding of NUMT genomic architecture, population dynamics, and evolutionary implications in human and non-human primates, establishing NUMTs as dynamic genomic components of biomedical relevance.

genomics↗

bioRxiv2026

Type 2 diabetes amplifies environmental Pb toxicity and intergenerational risk

Type 2 diabetes (T2D) and environmental lead (Pb) exposure intersect as prevalent global health challenges. Prior studies report elevated blood Pb in T2D, but the underlying mechanism and directionality remain unresolved. Here we show that T2D fundamentally alters Pb toxicokinetics, converting otherwise modest exposure into progressive organ injury and heritable risk. In a human cohort, elevated blood Pb in T2D specifically associated with impaired renal function rather than glycaemic control or adiposity. In db/db mice, diabetes increased oral Pb absorption through delayed gastrointestinal transit and epithelial barrier dysfunction, leading to enhanced systemic retention. With sustained exposure, renal Pb accumulation induced tubular stress that reduced effective clearance, creating a feed-forward loop in which diabetes promotes Pb retention and retained Pb accelerates kidney injury. Chronic Pb exposure exacerbated diabetic kidney injury without inducing hyperglycaemia, and short-course chelation attenuated renal stress markers. Beyond somatic toxicity, combined paternal T2D and Pb exposure programmed renal and neurobehavioral phenotypes across generations via sperm RNA. These findings redefine Pb from a passive environmental exposure to a context-dependent driver of disease, identify T2D as a vulnerability state that reshapes toxicant handling, and establish a mechanistic link between metabolic disease, environmental exposure and intergenerational risk. This work highlights the need for vulnerability-informed clinical management and environmental regulation in populations burdened by T2D.

genetics↗

bioRxiv2026

Targeting tRNA-Arg-TCT-4-1 suppresses cancer cell growth and tumorigenesis

tRNAs play a critical role in protein synthesis, influencing mRNA translation dynamics to shape proteomes. Emerging evidence links dysregulated tRNA activity to cancer progression, with tRNA-Arg-TCT identified as an oncogenic driver when ectopically overexpressed in non-malignant cells. The requirement of endogenous tRNA-Arg-TCT in cancer biology, however, remains untested. Moreover, considering that the tRNA-Arg-TCT family comprises six genes in humans, the importance of an individual tRNA isodecoder in cancer remains unknown. Here, we find elevated levels of tRNA-Arg-TCT-4-1 isodecoder are associated with poor patient prognosis across multiple cancer types. We demonstrate that, using different antisense RNA strategies, specific inhibition of tRNA-Arg-TCT-4-1 suppresses the growth of glioblastoma (GBM) and liposarcoma (LPS) cancer cells. Mechanistically, we find that tRNA-Arg-TCT-4-1 inhibition leads to a codon-biased remodeling of mRNA translation and the proteome, preferentially suppressing expression of growth-promoting genes and pathways encoded by mRNAs enriched in arginine AGA codons. Strikingly, intratumoral delivery of an antisense oligonucleotide (ASO) targeting tRNA-Arg-TCT-4-1 suppresses tumor growth and extends survival in mouse xenograft experiments performed using either a human LPS cell line or a patient-derived soft tissue sarcoma model. This study provides a foundation for targeting tRNA dysregulation as a novel therapeutic approach for cancer. One Sentence SummaryThis study identifies tRNA-Arg-TCT-4-1 as a new anti-cancer therapeutic target and demonstrates that an antisense oligonucleotide (ASO) targeting this tRNA effectively suppresses tumorigenesis and extends survival in mouse xenograft models.

cancer biology↗

bioRxiv2026

Evolutionary dynamics of insect odorant receptors reveal ecological tuning shaping olfactory perception

Insect olfaction is facilitated by a heterotetrameric odorant receptor-odorant receptor co-receptor (OR-Orco) complex, which is distinct from that of vertebrate ORs. However, extreme sequence divergence among insect ORs has hindered a unified understanding of their evolutionary history and ecological importance. In this study, we present a multiscale analysis of OR genes across 115 insect species. We overcome the limitations of traditional phylogenetic approaches by applying a protein similarity network-based strategy and introduce a "trunk-branch" framework to systematically describe the evolutionary trajectories of insect ORs across sequence, structural, and predicted olfactory potential levels. Although they possess different sequences and structural communities, all sampled insect orders contained ORs assigned to all six docking-derived functional communities. Notably, extant insect lineages with order-level origins spanning the end-Permian mass extinction (EPME) differed in docking-derived functional OR repertoires, and early-and late-diverging lineages differed in OR sequence-community diversity. The emergence of Orco represents a key evolutionary transition point, marking the shift from a homomeric to a heteromeric complex accompanied by specialization of the extracellular domain and binding pocket. Furthermore, we established robust associations between potential olfactory recognition breadth and ecological variables, including diet, circadian rhythm, and habitat. Our findings provide a class-level framework for investigating insect OR evolution and generate testable hypotheses about how receptor repertoire diversification may relate to ecological adaptation.

evolutionary biology↗

bioRxiv2026

Cigarette smoke induces colon cancer by regulating the gut microbiota and related metabolites

The causal relationship between smoking and colorectal cancer (CRC) remains unclear. In this study, a cigarette smoke-exposed mouse model demonstrated that smoking significantly increased CRC incidence by inducing gut microbiota dysbiosis and altering related metabolites. Smoke exposure reduced beneficial bacteria (e.g., Lactobacillus), increased harmful bacteria (e.g., Firmicutes and Clostridium), elevated metabolites such as histamine, and suppressed the tumor suppressor genes PARG, CPT2, and ALDH1A1, thereby promoting tumor development. Functional assays in CRC cell lines further confirmed that CPT2 knockdown enhanced malignant phenotypes, including proliferation, migration, and invasion. Clinical analysis showed that these genes were markedly downregulated in smoking-related CRC patients, with strong diagnostic value (AUC > 0.8). ConclusionSmoking promotes CRC by inducing gut microbiota dysbiosis, metabolic reprogramming, and suppression of tumor suppressor genes, particularly CPT2. These findings highlight the importance of smoking cessation in CRC prevention and provide potential biomarkers for early diagnosis and therapeutic intervention.

bioinformatics↗

bioRxiv2026

Large-scale quantum computing framework enhances drug discovery in multiple stages

Coherent Ising machines (CIMs) excel at solving large-scale combinational optimization problems (COPs), but their insufficient long-term stability has hindered their applications in compute-intensive tasks like computer-aided drug discovery (CADD). By improving fiber vibration isolation and temperature control system, we have implemented a 2000-node CIM named QBoson-CPQC-3Gen achieving stable solutions over one hour on large-scale COPs. Graph-based encoding schemes were further introduced to realize a CIM-based CADD workflow including allosteric site detection, protein-peptide docking and intermolecular similarity calculation. CIM-based methods demonstrated superior speed and accuracy than heuristic algorithms. Especially, QBoson-CPQC-3Gen identified 2 novel druggable sites and bioactive compounds for 6 targets, which were further validated in vitro, in-cell and by crystal structures. Our contributions established a quantum-computing framework for multi-stage drug discovery, representing a significant advancement in both quantum computing applications and pharmaceutical research.

bioinformatics↗

bioRxiv2026

Large language models unlock the ecology of species interactions

Species interactions shape population dynamics, geographic distributions, evolutionary trajectories, and responses to environmental change. Yet data on these interactions remain scarce across broad spatial, temporal, and taxonomic scales because they are difficult to collect in the field. One promising source of interaction data is citizen science platforms, which contain billions of biodiversity observations, often accompanied by unstructured text comments that may document interactions among organisms. Advances in large language models (LLMs) make it increasingly feasible to identify, extract, and categorize biotic interactions from these unstructured data at scale. Here, we present an LLM workflow that collects species interaction observations from multilingual citizen science comments. Using two case studies--bird-bird and plant-pollinator interactions--we show that LLMs can rapidly extract interaction types and participating species with high accuracy. These data can greatly expand the spatial, temporal, and taxonomic coverage and resolution of species interactions data, enable new tests of long-standing ecological questions, and improve our ability to track ecological changes. With appropriate validation, expert review, and attention to data privacy for both users and sensitive species, this approach opens new opportunities to characterize, forecast, and conserve biodiversity under global change.

ecology↗

bioRxiv2026

Astrocyte-induced internal state transitions reshape brainwide sensory, integrative, and motor computations

Animals rapidly adapt to changing circumstances by shifting how they perceive, integrate, and act. Such flexibility is often attributed to transitions between internal states that exert widespread influence across the brain. Yet the mechanisms that drive state transitions and how they reconfigure brainwide computation remain unclear. Larval zebrafish, when actions are rendered futile by decoupling visual flow feedback from swimming in virtual reality, enter a temporary passive, energy-preserving state. In this state, astrocyte calcium levels are elevated, and swim reinitiation requires greater accumulated visual motion. Using whole-brain, cellular-resolution activity imaging, we observed widespread circuit alterations underlying this disengaged state: neuronal visual responses weakened, visual motion integration over time became dramatically leakier, motor inhibition increased, and motor preparation slowed, together suppressing conversion of sensory evidence into action. Astrocyte calcium rose during futile swimming, tracked the emergence and resolution of these brainwide changes, and was both necessary and sufficient to drive them. Thus, astrocytes orchestrate internal states that profoundly reshape neural computations, most powerfully at intermediate integrative processing stages, to meet changing demands. HighlightsO_LIInternal state change alters brainwide neuronal processing at every stage of the sensorimotor transformation C_LIO_LIEffects are most powerful at integrative stages through stimulus memory collapse C_LIO_LIAs state resolves, amplification of sensory representations synergizes with reduced motor inhibition for action reinitiation C_LIO_LIAstrocyte activity drives these brainwide adaptive shifts in neuronal dynamics C_LI

neuroscience↗

bioRxiv2026

Optimizing actin turnover in cell-like conditions

A dynamic actin cytoskeleton, characterized by rapid filament turnover, is essential for driving intracellular transport and cellular movement. Despite extensive study, the contributions of many actin-binding proteins (ABPs) that regulate the different steps of the actin turnover cycle (filament assembly, disassembly and recycling into polymerizable actin monomers) remain ill-defined. Here, we introduce novel sensitive in vitro assays to quantitatively assess how ABPs catalyze actin turnover. By accurately measuring nucleotide exchange dynamics and ATP consumption, these assays enable robust characterization of ABP activity across broad concentration ranges. Using these methods and modeling of these reactions, we systematically examined the contributions of five conserved regulators, both individually and in combination, and identified conditions that maximize turnover efficiency. We also determined that increasing F-actin concentration to cellular levels affects ABP activity. Finally, we demonstrated that rapid actin turnover is preserved during encapsulation in cell-sized vesicles using the cDICE method. Together, these advances provide versatile tools and new insights into actin cytoskeletal dynamics under physiologically relevant conditions.

cell biology↗

bioRxiv2026

Molecular architecture of the tumor microenvironment caused by BRCA1 and BRCA2 somatic mutations in lung adenocarcinoma

ObjectivesHomologous recombination repair (HRR) deficiency is associated with improved immunotherapy responses in non-small cell lung cancer (NSCLC) patients. The HRR genes BRCA1/2 are key regulators of DNA repair, yet their impact on the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unclear. MethodsUsing single-cell sequencing and multi-omics data, we characterized BRCA1/2 mutation-associated transcriptional programs, immune cell composition, and functional alterations in T cells, investigating the molecular and immune architecture of BRCA-mutant LUAD patients. ResultsBRCA1/2 mutations were associated with increased genomic instability and poor prognosis in LUAD patients, but predicted better clinical outcomes following immune checkpoint blockade (ICB) treatment. BRCA1 mutations correlated with an upregulated type I IFN/IFN-{gamma} signature and CD8+ T cell activation. BRCA2 mutations were associated with alveolar/stress/inflammatory responses and enhanced MHC-II antigen presentation, linked to CD4+ T cell differentiation. Both alterations coincided with reduced CD28 co-stimulation and CTL activity, hinting of immune evasion. We identified two tissue-resident memory T cell (Trm) subsets as predictors of clinical outcomes and ICB response. BRCA1 mutations were associated with CD8+ Trm expansion, whereas BRCA2 mutations linked to tumor CD4+ Trm expansion and peripheral T/NK cell cytotoxicity. Furthermore, a cancer-promoting program activated by BRCA1 mutation was vulnerable to histone deacetylase inhibitors, which inhibited LUAD tumor growth. ConclusionsThis study provides a preliminary characterization of the BRCA-mutant TME in LUAD patients, revealing distinct transcriptional and immune patterns that highlight differences in BRCA1/2-associated molecular architecture and offer a framework for improving therapy efficacy in LUAD.

cancer biology↗

bioRxiv2026

F26BP enables control of glycolysis rate independent of energy state

Glycolysis is a conserved metabolic pathway that produces ATP and biosynthetic precursors. Multiple allosteric regulators control glycolytic enzymes in vitro. For example, phosphofructokinase (PFK) is allosterically regulated by fructose-2,6-bisphosphate (F26BP), ATP, ADP, AMP, citrate, acyl-CoA, and inorganic phosphate. It is not well understood which properties of homeostasis are enabled by each of these regulators, and whether they perform redundant or distinct functions. Using mathematical modeling and experiments with human cells lacking F26BP, we demonstrate that F26BP alters glycolytic rate independent of cellular ATP demand-a unique function not shared by other regulators. We also identified several downstream glycolytic intermediates as novel regulators of F26BP levels. Our findings clarify the role of F26BP as a unique regulator that controls the glycolytic rate independently of the cellular energy state in response to hormone and biosynthetic precursor levels. The F26BP regulatory circuit enables respiratory fuel selection and biosynthesis from glycolytic intermediates.

biochemistry↗

bioRxiv2026

An Integrated Single-Cell and Epigenomic Resource for Comparative Analysis of the Basal Ganglia

The basal ganglia regulate motor, cognitive, and affective behaviors, and their dysfunction underlies diverse neurological and psychiatric disorders. Comprehensive, accessible multi-omics resources are needed to understand the regulatory mechanisms governing basal ganglia cell types. Here we present an open, interactive web-based platform for exploring single-cell multi-omics datasets from basal ganglia, generated using 10X Multiome, snm3C-seq, and Paired-Tag technologies from the BICAN (NIH BRAIN Initiative Cell Atlas Network) consortium. The platform is available at https://basalganglia.epigenomes.net/ and enables integrated visualization of gene expression, chromatin accessibility, DNA methylation, histone modifications, and chromatin conformation across cell types and human, macaque, marmoset, and mouse species, with direct genome browser support and comparative epigenomic functionality. Representative analyses demonstrate cell-type-specific regulatory landscapes, conserved and species-specific regulatory elements, and links between epigenomic regulation and transcription. This resource provides a scalable, community-oriented foundation for advancing basal ganglia biology and interpreting regulatory mechanisms relevant to brain function and disease. HighlightsO_LIIntegrated single-cell epigenomic resource for basal ganglia C_LIO_LIInteractive genome browser enables multi-omics and cross-species exploration C_LIO_LIReveals cell-type-specific and species-specific regulatory landscapes C_LIO_LISupports community access to complex brain epigenomic datasets C_LI

genomics↗

bioRxiv2026

Exploring protein conformational ensembles using evolutionary conditional diffusion

Protein conformational ensembles encode the dynamic landscapes underlying biological function, regulation, and allostery. Accurately reconstructing such ensembles while balancing conformational distributions accuracy and physical plausibility remains a fundamental challenge in structural biology, particularly when dynamic data is scarce. Here, we propose DiffEnsemble, a diffusion-based framework designed for modeling protein conformational ensembles. DiffEnsemble learns latent dynamical representations from static protein structures in the Protein Data Bank, integrated with the structural profile derived from the AlphaFold Protein Structure Database as conditional guidance during the diffusion process. Benchmarking on 72 protein targets from the ATLAS molecular dynamics simulation dataset demonstrates that DiffEnsemble outperforms existing methods, including BioEmu and AlphaFLOW. Compared with AlphaFLOW, DiffEnsemble achieves improvements of 28.9% and 11.3% in Pearson correlation coefficients for ensemble pairwise root mean square deviation and root mean square fluctuation, respectively. Importantly, DiffEnsemble successfully captures the dominant motions for 42% of the targets. These results demonstrate that latent dynamical information embedded in static structural data can effectively support the modeling of protein conformational ensembles.

bioinformatics↗