Biology subjects

Zhao, M.

Publications and source records attributed to Zhao, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Fine-tuning an intracellular allosteric pocket programs GPCR signaling bias

Biased signaling of G protein-coupled receptors (GPCRs) offers a route for precise therapeutics with fewer adverse effects. Intracellular allosteric ligands can impose such bias, yet how subtle chemical changes within these pockets reshape receptor-transducer coupling and downstream signaling remains unclear. Here, we systematically fine-tuned the intracellular allosteric pocket of neurotensin receptor 1 (NTSR1) through chemical modification of the {beta}-arrestin-biased ligand SBI-553. Minor changes to the ligand scaffold altered transducer-coupling preferences, generating distinct profiles of G-protein and {beta}-arrestin signaling. Cryo-electron microscopy structures of NTSR1-{beta}-arrestin2 complexes bound to designed allosteric probes revealed ligand-dependent remodeling of the intracellular cavity that reshapes the receptor-effector interface. Alanine scanning identified transducer-sensitive residues within and beyond the immediate ligand-contact region. In mice, SBI-553 and N065 produced distinct physiological profiles, with N065 improving survival in a lethal endotoxemia model. Finally, phosphoproteomic profiling revealed partially overlapping but distinct downstream signaling profiles among the three modulators. Together, these findings establish the intracellular allosteric pocket as a tunable determinant of transducer coupling and show that closely related modulators can generate distinct signaling and physiological profiles.

pharmacology and toxicology↗

bioRxiv2026

Ancient genomes chronicle the history of adaptive evolution in East Asia

The transition from hunting and gathering to farming brought about novel selection pressures related to metabolism and immunity, but for East Asian populations the evolutionary genetic dynamics of these adaptations and their relationships to agriculture remain unclear. Using one of the largest datasets of ancient East Asian genomes (N=2236), we performed a genome-wide scan to identify selected variants and reconstructed their allele frequency changes over time and space. We tested for genetic association with farming using an environmental variable to represent historical farming intensity based on a large database of archaeobotanical sites (N=1220). Our analyses indicate selection began prior to the Neolithic for several well-established adaptive loci such as FADS1, FUT2, and OCA2. For rs1229984 at ADH1B, the strongest selection signal in our genome-wide scan, we observed variation in timing and strength of selection in East Eurasia and found evidence for a southern origin. Furthermore, ADH1B*48His was positively associated with wheat farming. Given these results, we propose a novel hypothesis about the fitness advantage of this variant. Our work underscores the heterogeneity in the strength and timing of selection across East Eurasia and provides a quantitative framework for testing agriculture's role as a selection pressure.

evolutionary biology↗

bioRxiv2026

LysM: a bacterial self-encoded peptidoglycan hydrolase as an antimicrobial and anti-biofilm agent for Gram-negative nosocomial pathogens

Agents with both anti-biofilm property and broad-spectrum antimicrobial activity are urgently needed, especially for drug-resistant nosocomial pathogens. Here, we report a bacterial genome-encoded glycoside hydrolase, named LysM, with lytic activity against multiple Gram-negative nosocomial pathogens and little toxicity to human cells. 3D structural modelling and site-directed mutagenesis indicates that LysM is a peptidoglycan-specific glycoside hydrolase. In combination with EDTA, exogenous LysM induces explosive bacterial cell lysis, exhibits potent bactericidal activity, and eliminates 24 h-old biofilms formed by Gram-negative ESKAPE group pathogens with the highest activity on three nosocomial pathogens, namely Pseudomonas aeruginosa, Acinetobacter baumannii, and Enterobacter cloacae, all of which contain LysM homologs in their genome. More strikingly, LysM supplied in growth media without EDTA, also inhibits the growth of several nosocomial pathogens. Single-cell tracking analysis reveals that LysM completely prevent biofilm formation of P. aeruginosa by reducing bacterial surface-adherence and extending the doubling time. A LysM-based cocktail consisting of LysM, EDTA, and matrix exopolysaccharide-degrading glycosidase PslG, shows potent anti-biofilm activity against P. aeruginosa, including drug-resistant clinical isolates, both in vitro and in human airway organoids (HAOs) biofilm infection model. In addition, LysM enhances the efficacy of many antibiotics from all major classes, including colistin, tobramycin, ciprofloxacin, and tetracycline. Our findings not only provide a clinical candidate for the treatment of nosocomial infections but also open a new path for antimicrobial discovery and anti-biofilm strategies, as homologues of LysM are present in the genomes of many bacteria and phages.

microbiology↗

bioRxiv2026

Differential Survival of Retinal Ganglion Cell Types Following Branch Retinal Vein Occlusion

Background. Branch retinal vein occlusion (BRVO) is a common cause of retinal ischemia, rapidly inducing neuronal death and often producing irreversible vison loss. Interventions such as thrombolysis restore perfusion but cannot recover neurons already lost, and most patients retain permanent visual deficits. Identifying which neuronal populations die, and how rapidly, may therefore reveal timing windows and targets for neuroprotective treatment. Aims. To determine the timing of pathology, we evaluated vascular changes and neuronal degeneration in a photocoagulation-induced mouse model of BRVO. To determine differences in retinal ganglion cells (RGC) type susceptibility, we tracked the survival of RGC subpopulations using immunofluorescence markers. Methods. BRVO was induced by retro-orbital injection of Rose Bengal and FITC dextran followed by targeted photocoagulation of a branch vein. Obstruction was confirmed by fluorescein angiography and vascular damage was viewed by optical coherence tomography angiography. Cell survival was quantified by immunostaining at 3, 7, and 14 days using RNA Binding Protein with Multiple Splicing (RBPMS, pan RGC). RGC subtype markers for intrinsically photosensitive RGCs (TBR2), RGCs (SPP1), ON OFF direction-selective RGCs (CART), and F RGCs (FOXP2) were used to examine differences in survival across RGC types. Results. Occlusion selectively disrupted the superficial and intermediate capillary plexus, sparing the deep plexuses. All examined neuronal populations were significantly depleted, but with markedly different magnitude and timing. RGCs and F RGCs were the most vulnerable subtypes, both approaching complete loss by one week, whereas intrinsically photosensitive RGCs were the most resistant. Conclusion. RGCs, typically resilient in glaucoma, trauma, and excitotoxicity, were markedly vulnerable in BRVO, indicating that RGC subtype susceptibility is insult-specific.

neuroscience↗

bioRxiv2026

High-throughput affinity profiling of antibodies against soluble and native membrane targets by digital flow cytometry

Binding affinity measurements are essential for optimizing and validating therapeutic and research antibodies, yet no high-throughput platform supports quantitative affinity measurements for both soluble and native membrane targets. Here we present a suite of digital flow cytometry (dFC) assays that determine equilibrium binding affinities by directly counting free and bound molecules in homogeneous mixtures without immobilization. The assays enable titration-free absolute KD measurements for fluorescent binding partners, affinity measurements for unlabeled antibodies against membrane receptors on cell-derived extracellular vesicles (EVs), and multiplexed assays for rapid ranking or screening of antibody variants. We demonstrate applications by quantifying the effects of degree-of-labeling on the affinity of antibody-dye conjugates, and of drug conjugation on therapeutic antibody binding to receptors on human cancer EVs. By combining single-molecule quantitation, adaptable assay designs, and high-throughput analysis, dFC provides a versatile platform for therapeutic antibody optimization and research antibody validation.

biophysics↗

bioRxiv2026

AMPK-dependent brain-wide norepinephrine release promotes recovery from metabolic coma in mice

Coma is a pathological brain state characterized by loss of consciousness. How the brain recovers from coma remains largely unknown. Using mouse models of metabolic coma, we identified an endogenous neuromodulatory pathway that actively promotes coma recovery. In mice subjected to hypoglycemic coma, hypoglycemia triggered AMPK-dependent excitation of nucleus tractus solitarius (NTS) neurons, which activated locus coeruleus (LC) norepinephrine neurons through a glutamatergic NTS-LC circuit. LC activation drives widespread norepinephrine release across cortical and subcortical regions, thereby promoting post-coma arousal. Notably, coma-associated brain-wide norepinephrine release was unconventional in both scale and duration, with a magnitude approximately 10-fold higher than physiological norepinephrine release during sleep-wake cycles. This neuromodulatory process also operated during hypercapnic coma. Vagus nerve stimulation accelerated coma recovery by engaging this endogenous anti-coma mechanism. Our findings uncover an AMPK-dependent brainstem circuit that actively restores arousal from metabolic coma, revealing a neural defense strategy against profound metabolic stress.

neuroscience↗

bioRxiv2026

Niche-dependent epistasis within the cancer genome shapes metastatic fitness

Epistasis, the genetic interaction between loci, directs non-additive genotype-to-phenotype outcomes. Within a multicellular organism, how the tissue niche (E) shapes gene-by-gene epistasis (GxG) and its phenotypic consequences remains poorly studied. Using tumor lung metastasis as an experimental model, we mapped GxGxE through combinatorial CRISPR perturbation coupled with depletion of defined host myeloid populations in mice. The metastatic niche first selects disseminated tumor cells on GxG epistatic fitness, then drives transcriptome convergence regardless of genotype. Removing anatomically distinct myeloid populations reshaped the metastatic epistasis landscape despite identical tumor genotypes. Gene-by-gene-by-environment epistasis therefore operates at the organismal level, with interaction magnitude and sign set by niche cells. Beyond metastasis, our data suggest that the tissue niche conditions how genetic interactions translate into divergent phenotypes.

genetics↗

bioRxiv2026

Seizures in a Dravet Syndrome mouse model inhibit the locus coeruleus but locally evoke supraphysiologic norepinephrine release

Locus coeruleus (LC) neurons are the primary source of norepinephrine / noradrenaline (NE) released to most brain structures, including seizure-prone neocortical and limbic regions. LC-NE networks regulate numerous physiological processes, including arousal, attention, and memory. Previous evidence suggests that LC-NE neurons may be involved in epilepsy and that their activation may have therapeutic effects on seizures, but the endogenous activity of the LC-NE network during seizures remains largely unclear. We combined electrocorticography recordings and in vivo imaging to measure somatic activity of LC-NE neurons as well as downstream NE release during hyperthermia-induced seizures in a well-characterized pre-clinical model of Dravet Syndrome. We found that population LC-NE somatic activity was inhibited during seizures, whereas downstream NE release was dramatically elevated. To reconcile these discordant findings, we established that activation of downstream regions is capable of locally evoking NE release, in part via activation of glutamate receptors, consistent with the Glutamate Amplifies Noradrenergic Effects (GANE) model. Finally, we confirmed that ictal NE release occurred across additional downstream brain regions, epilepsy models, and seizure induction methods. Thus, disruption of NE signaling is likely a widespread ictal signature, with implications for impaired consciousness during and after seizures.

neuroscience↗

bioRxiv2026

Chronic Alcohol Exposure Induces Persistent DNA Damage Response Signaling and Sensitizes Breast Epithelial Cells to PARP Inhibition

Chronic alcohol consumption is associated with increased breast cancer risk; however, the long-term effects of alcohol exposure on DNA damage response (DDR) signaling and therapeutic vulnerability in breast epithelial cells remain incompletely understood. In the present study, we established a chronic alcohol exposure model using immortalized human breast epithelial MCF-10A cells to investigate persistent alterations in DNA damage signaling and sensitivity to poly (ADP-ribose) polymerase (PARP) inhibition. MCF-10A cells that chronically exposed to 0.2% alcohol for 20 weeks and then withdrew alcohol treatment for 4 weeks still retained elevated {gamma}H2AX levels and sustained activation of ATM/ATR-associated DDR pathways. Chronic alcohol-exposed cells also exhibited increased sensitivity to the PARP inhibitors olaparib and veliparib, as demonstrated by reduced cell viability, decreased clonogenic survival, and enhanced apoptosis. Mechanistically, olaparib induced greater G2/M checkpoint activation and replication-associated DNA damage in chronic alcohol-exposed cells compared with control cells. In addition, chronic alcohol exposure increased PARP expression and enhanced activation of DDR signaling following PARP inhibition. These findings demonstrate that chronic alcohol exposure induces persistent DNA repair stress and sensitizes breast epithelial cells to PARP inhibition. Our study suggests that chronic alcohol-associated genomic stress may create potential vulnerability to PARP inhibition.

cell biology↗

bioRxiv2026

ALDH2 Knockout Induces Dysregulation of Arginine biosynthesis in SKBR-3 Breast Cancer Cells

Background/Objectives: Aldehyde dehydrogenase 2 (ALDH2), a mitochondrial enzyme, mitigates cellular stress by detoxifying reactive aldehydes produced during alcohol exposure and endogenous metabolic processes. ALDH2*2 polymorphism, which results in deficient catalytic activity, is prevalent in East Asian populations and is associated with an increased risk of cancer and other diseases. While the effects of ALDH2 deficiency on cellular stress responses are well documented, the specific metabolic dysregulations arising from this deficiency require further investigation. Methods; An ALDH2 knockout subline of SKBR-3 cells was established using CRISPR/Cas9 strategy. The metabolomic profiles of control (SKBR-3/C) and ALDH2 knockout (SKBR-3/ADKO) cells were evaluated via ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). Results: ALDH2 knockout in SKBR-3 cells resulted in increased cellular stress, evidenced by elevated levels of 8-OHdG, reactive oxygen species (ROS), and malondialdehyde (MDA). Metabolomic analysis of the paired cell lines assigned a total of 5,033 signals, of which 281 were significantly different (fold change [≥] 2, p-value <0.05) between the two groups. Pathway analysis with MetaboAnalyst identified significant metabolic pathways associated with ALDH2 deficiency, particularly those involving arginine biosynthesis, and arginine and proline metabolism. ALDH2 deficiency reprogramed arginine metabolism toward polyamine pathways while suppressing the urea cycle. Network analysis further revealed alterations in amino acid and lipid metabolism in ALDH2-deficient cells. Conclusions; This study provides a novel insight into the role of ALDH2 in cancer metabolism and may have broader implication for cancer biology.

cell biology↗

bioRxiv2026

Mechanistic Investigation of Reversible Hibernation-Driven Immune Suppression in Thirteen-Lined Ground Squirrels

Torpor in mammals imposes extreme energetic constraints, yet how it reshapes the immune system remains poorly understood. Here we combined single-cell RNA sequencing with quantitative image analysis of immune cell populations in splenic tissues to define immune remodeling during torpor in a natural hibernator, 13-lined ground squirrels. The torpid spleen showed a significant contraction of white pulp with a preferential reduction of B cell- and T cell-rich adaptive niches and relative preservation of innate myeloid populations. Across immune cell lineages, a conserved transcriptional program of metabolic downscaling emerged, marked by suppression of glycolysis, cell-cycle progression, RNA processing, and translation, together with reduced glucose transporter expression and induction of cold-shock RNA-binding proteins. Despite this pervasive metabolic quiescence, immune cells maintain lineage identity, with B cells undergoing numerical and transcriptional contraction linked to follicular remodeling and T cells adopting a quiescent, stress-resistant state without apoptotic enrichment. Innate cell populations remained numerically enriched but transcriptionally restrained, consistent with low-energy tissue surveillance rather than inflammatory activation. These findings identified torpor as a coordinated, multi-tiered state of reversible immune suppression, in which hierarchical metabolic and lineage-specific programs conserve energy while preserving essential immune infrastructure for rapid restoration. Our identified key molecules and pathways in immune suppression at the cellular and transcriptional levels have important implications for future development of targeted treatment for autoimmune diseases, cancers, and infectious diseases.

immunology↗

bioRxiv2026

OPA1-dependent mitochondrial remodeling coordinates TCR signaling and metabolic adaptation during iNKT cell differentiation

Invariant natural killer T (iNKT) cells require mitochondrial metabolism for terminal effector development. We found iNKT cells express elevated levels of proteins regulating mitochondrial membrane dynamics, and identified Opa1, but not Drp1, as selectively required for iNKT cell differentiation. OPA1 deficiency disrupted mitochondrial cristae organization, reduced mitochondrial membrane potential, increased mitochondrial mass, and altered calcium homeostasis in iNKT cells. Bulk and single-cell transcriptomic analyses revealed impaired TCR-responsive gene expression, activation of mitochondrial stress adaptation and integrated stress response, enhanced glycolysis, and retention of immature differentiation features. SCENITH analysis demonstrated increased glycolytic dependence; LDHA became required in Opa1-deficient iNKT cells while dispensable for normal iNKT development, indicating compensatory glycolytic adaptation. EGTA in thymic organ culture partially restored NKT1 marker expression in Opa1-deficient cells. Co-deletion of Drp1 improved mitochondrial morphology, TCR signaling, stress and metabolic adaptation, and partially rescued iNKT cell differentiation, demonstrating that balanced mitochondrial dynamics coordinate mitochondrial function and terminal effector development.

immunology↗

bioRxiv2026

Neural signatures of spontaneous transitions between internal and external thought

The human mind constantly shifts between internal representations and the external environment, yet the neural mechanisms underlying such spontaneous transitions remain underexplored. Here, we analyzed a think-aloud functional magnetic resonance imaging dataset, in which participants continuously verbalized their thoughts, to identify neural activity predicting transitions between internally and externally oriented thought. Internal-to-external transitions were preceded by increased activation in the salience/ventral attention network, with the strongest effect observed in the right temporoparietal junction. The spatial pattern of this pre-transition activation was positively associated with acetylcholine receptor density, suggesting a role for cholinergic signaling in cognitive reorientation. Pre-transition activation was itself preceded by a large-scale brain state proposed to serve as a flexible hub between functionally specialized states, indicating that spontaneous transitions are more likely when the brain occupies this intermediate configuration. Together, these findings suggest that multilevel neural mechanisms support flexible reorientation along the internal-external dimension of spontaneous cognition.

neuroscience↗

bioRxiv2026

Combining 3D-multispectral and hyperspectral imaging to identify environmental stress treatments imposed during plant growth

Non-invasive, high-throughput phenotyping tools are needed that can identify environmental effects on plant structure and function to diagnose factors responsible for reduced growth in commercial and non-commercial settings. In this study, we explored whether the integration of 3D-multispectral (3D) and 2D-hyperspectral imaging (HSI), aided by machine learning (ML), could be used to identify environmental stress treatments imposed during plant growth. Controlled environment-grown Nicotiana Benthamiana plants were subjected to a range of abiotic treatments - including different growth irradiances, heat treatment and drought stress - with the treatments resulting in differences in shoot height, biomass, leaf area and spectral reflectance. ML models were trained to identify these treatments using morphological and spectral traits measured at 27, 29, 31, and 34 days after sowing (DAS). A 3D-multispectral scanner was used to obtain information on plant height, biomass, and leaf area. A visible and near-infrared (VNIR) HSI camera provided detailed spectral information for deriving spectral indices including the Normalised Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI) and Normalized Difference Red Edge (NDRE). Manual measurements provided baseline comparative data. The 3D-multispectral scanner reliably estimated above-ground traits, with high correlations between manual and scanner-derived measurements. The ML models accurately differentiated among environmental stress treatments, with the fused 3D+HSI model achieving the best overall predictive performance across all evaluated metrics compared with models based on either imaging modality alone. Results demonstrated the effectiveness of combining 3D-multispectral and 2D-HSI data with ML analyses for non-destructive, high-throughput phenotyping. The integration of these techniques enabled non-destructive, high-throughput identification of environmental stress treatments imposed during plant growth.

plant biology↗

bioRxiv2026

Perturb-ME: Scalable mechanism discovery from phenotype-enriched genome-wide screens

Perturb-seq enables pooled genetic screens with rich single-cell profiling readouts, but genome-scale profiling remains costly and may not be associated with other established functional characteristics. Moreover, as screens grow in size and complexity, interpreting the resulting data comprehensively is challenging and slow. Here, we introduce Perturb-seq with Marker Enrichment (Perturb-ME), which combines genome-scale CRISPR screening, phenotype-based enrichment and multimodal single-cell profiling. Applied to MHC-I cell surface protein expression in melanoma, Perturb-ME profiled HLA-low and HLA-high cells with matched RNA, surface-protein and guide measurements. A regulatory model with 221 impactful regulators affecting 1,998 responsive genes recovered seven coherent co-functional regulatory modules governing nine gene programs, including the canonical IFN{gamma}-MHC-I axis regulating an antigen-presentation and interferon-response program. Agentic interpretation of the entire model with an AI co-scientist linked additional modules to trafficking, proteostasis and chromatin regulation. Perturb-ME, along with agentic interpretation, provide a scalable framework for comprehensive functional discovery from phenotype-enriched genetic screens.

cell biology↗

bioRxiv2026

The HES1-SOD1 Antagonism Shapes Senescence Heterogeneity and Impacts Metastatic Relapse of Circulating Tumor Cells

Circulating tumor cells (CTCs) encounter multiple challenges within the blood microenvironment, including oxidative stress, flow shear forces, and immune surveillance, often leading to anoikis. Recently, a transitional state of CTC senescence has been identified, contributing to metastatic inefficiency. However, the molecular mechanisms linking senescent CTCs to disease relapse remain to be defined. By integrating a genetic model of cortactin knockdown-induced CTC senescence with single-cell multi-omic analyses, we revealed two distinct senescent CTC subpopulations marked by HES1 expression levels. These HES1low and HES1high subpopulations exhibited differential evolutionary trajectory dynamics and unique molecular and metabolic signatures, which were significantly correlated with adverse clinical outcome across several patient cohorts. HES1low senescent CTCs displayed enhanced mitochondrial fitness, oxidative phosphorylation, and ROS-detoxifying capabilities, resulting in more efficient tumor regrowth with a pro-inflammatory and thrombotic phenotype when compared to the HES1high group. Mechanistically, HES1 directly bound to the Sod1 promoter and repressed its expression, leading to redox imbalance and mitochondrial dysfunction that were linked to weakened tumor regrowth capacity. Both senescent CTC subpopulations were broadly resistant to cytotoxic and targeted therapies, yet they showed elevated dependency on anti-apoptosis programs that make them susceptible to dual blockade by SOD1 inhibitor and the anti-senolytic drug ABT737 in vivo. Finally, in a prospective cohort of on-treatment melanoma patients, HES1 senescent CTCs were highly enriched in patients with progressive disease. Thus, the HES1-SOD1 antagonism shapes CTC senescence heterogeneity and contributes to differential tumor relapse, which can be therapeutically explored for eliminating residual metastatic disease.

cancer biology↗

bioRxiv2026

Interpretable Prediction of Phase Separation and Disease Variant Effects in Intrinsically Disordered Regions

Coding mutations within intrinsically disordered regions (IDRs) of proteins are increasingly implicated in human diseases yet remain poorly interpreted by conventional variant-effect predictors that rely on structural stability and conservation-based metrics. Quantifying disruption of IDR-mediated liquid-liquid phase separation (LLPS) offers a biophysically principled approach to interpreting the pathogenic impact of such variants. However, existing LLPS predictors suffer from training biases toward self-separating proteins, show limited performance on partner- dependent phase separation, and often lack interpretability for variant prioritization. We present an interpretable ensemble machine-learning framework that integrates protein language model embeddings of sequence and predicted structure to predict LLPS propensity and classify proteins as self-separating or partner-dependent. Our two-step classifiers outperform existing methods on independent benchmark datasets, with the largest gains for partner-dependent LLPS proteins. Beyond classification, our framework identifies critical phase-separating regions and quantifies mutation-induced perturbations in LLPS. Applied to disease-associated variant databases, we found that pathogenic mutations are enriched in predicted phase-separating regions and frequently perturb LLPS propensity scores, implicating mutation-induced LLPS dysregulation as a potential pathogenic mechanism for numerous diseases. Overall, our framework provides an accurate, interpretable approach for identifying phase-separating proteins and linking aberrant phase- separation behavior to disease pathogenesis.

bioinformatics↗

bioRxiv2026

Explainable AI identifies recombination and chromatin environment as key predictors of subgenome evolution in maize and Brassica

Polyploidy, or whole genome duplication, reshapes genomes through biased gene loss and regulatory rewiring, yet the drivers of biased fractionation among subgenomes remain unclear. Using maize and Brassica rapa as model allopolyploids, we compiled 60 genomic and epigenomic features in maize and 45 in B. rapa and constructed supervised machine-learning models to classify genes by subgenome identity. In both species, eXplainable Artificial Intelligence (XAI) approaches identified recombination rate as the most influential and highly interconnected feature despite nonsignificant mean differences between subgenome groups. Chromosome location, transposon density, and chromatin-associated features, including the proximity of accessible chromatin regions to genes and active histone marks such as H3K9ac and H3K27ac, consistently ranked among the top contributors to subgenome classification. XAI-derived co-variation and interaction networks further revealed recombination rate as the central node connecting significant features. Together, these results highlight recombination and chromatin environment as major predictors of subgenome divergence in polyploid genomes. TeaserRecombination and chromatin environment are key predictors of unequal gene loss and subgenome dominance after polyploidy.

plant biology↗