Biology subjects

Fan, X.

Publications and source records attributed to Fan, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Combination of engineered cell type-specific promoters and a high-efficiency AAV capsid restores hearing in adult DFNB1 mice model with demonstrated safety in nonhuman primate

A major challenge in gene therapy for GJB2-related hearing loss (DFNB1)--the most common form of hereditary deafness--is achieving efficient and precise connexin 26 delivery. Herein, we engineered two cell type-specific promoters (GJB2-1 and WFS1-2274) and developed an AAV capsid, AAV-MAS012, with enhanced transduction efficiency in mature cochlear cells. Our AAV-mediated gene therapy systems restored hearing of low-to-mid-frequencies in newborn Gjb2 cKO mice to wild-type levels and maintained for 45 weeks. Additionally, our therapeutic systems restored low-to-mid-frequencies hearing function to wild-type levels in adult Gjb2 cKO mice. A humanized version of the therapy, AAV-MAS012-WFS1-2274-hGJB2, rescued hearing function in two distinct Gjb2-deficient mouse models, and demonstrated a favorable safety profile in nonhuman primates. This study represents the first successful hearing restoration in adult Gjb2-deficient mice. The significant therapeutic efficacy of the humanized gene therapy system shows great potential for clinical translation in DFNB1 patients.

genetics↗

bioRxiv2026

β-Amyloid and Glutathione Dysregulation Cooperatively Drive Lipid Peroxidation and Ferroptosis in Neuron-Like Cells

Alzheimers disease (AD) is a progressive neurodegenerative disorder characterized by {beta}-amyloid (A{beta}) accumulation and oxidative stress, with aging being its greatest risk factor. Age-related decline in antioxidant defenses, particularly glutathione (GSH), may increase neuronal vulnerability to A{beta}-mediated toxicity; however, the mechanisms linking redox dysregulation to neuronal death remain incompletely understood. In this study, we investigated how impaired GSH homeostasis influences neuronal susceptibility to A{beta}-associated injury. Human SH-SY5Y neuron-like cells were engineered to express either wild-type APP695 or the familial AD-associated APPSwe/Ind mutant, and intracellular GSH depletion was induced using both pharmacological and genetic approaches. GSH depletion markedly sensitized APPSwe/Ind-expressing cells to cell death, accompanied by increased plasma membrane lipid peroxidation, elevated malondialdehyde (MDA) and 4-hydroxynonenal (4-HNE) levels, and enhanced lactate dehydrogenase (LDH) release. This cell death was not prevented by the pan-caspase inhibitor Z-VAD-FMK but was effectively rescued by the ferroptosis inhibitors ferrostatin-1 (Fer-1) and liproxstatin-1 (Lip-1), indicating a ferroptotic mechanism. Similar ferroptotic responses were observed when A{beta} oligomers were combined with intracellular GSH depletion. Mechanistically, A{beta} and GSH depletion synergistically increased transferrin receptor-1 expression and intracellular iron levels while markedly suppressing glutathione peroxidase 4 (GPX4), a central regulator of ferroptosis. Importantly, inhibition of autophagy with bafilomycin A1 restored GPX4 expression and rescued cells from ferroptotic death, suggesting that autophagy-mediated GPX4 degradation contributes to this process. Collectively, our findings demonstrate that GSH dysregulation synergizes with A{beta} to induce lipid peroxidation and ferroptosis in neuron-like cells. These results identify impaired redox homeostasis as a critical driver of neuronal vulnerability in AD and suggest that preserving GSH levels or targeting ferroptotic pathways may offer promising therapeutic strategies for neurodegeneration.

neuroscience↗

bioRxiv2026

AI-Guided Structure-Aware Modeling and Thermal Proteomics Reveal Direct Demethylzeylasteral-ACLY Interaction

Target deconvolution of bioactive natural products (NPs) is frequently hampered by the inability of traditional thermal shift assays to distinguish direct ligand binding from indirect proteomic stabilization. Here, we developed an integrated target discovery framework combining MAPS-iTSA thermal proteomics with a structure-aware graph neural network (HoloGNN). This strategy identified ATP-citrate lyase (ACLY) as a high-confidence target of Demethylzeylasteral, a bioactive triterpenoid from Tripterygium wilfordii. Crucially, orthogonal biochemical assays, including surface plasmon resonance and limited proteolysis, validated its direct binding (KD = 9.86 M) and profound enzymatic inhibition (IC50 = 3.84 M). To establish the relevance of this interaction in the context of the source herb, thermal profiling of Tripterygium wilfordii extract together with ACLY-based affinity-ultrafiltration mass spectrometry supported ACLY engagement and identified Demethylzeylasteral as an ACLY-binding constituent. Given the established role of ACLY-mediated lipid metabolic reprogramming in psoriasis, we further evaluated the pharmacological significance of this interaction. Demethylzeylasteral suppressed keratinocyte proliferation, alleviated imiquimod-induced psoriasiform dermatitis, and reduced inflammatory cytokine expression in vivo. Single-cell RNA sequencing further revealed reversal of ACLY-SREBP-associated lipogenic reprogramming in keratinocytes. Collectively, these findings establish ACLY as a functionally relevant target of DEM and provide a robust AI-chemoproteomic paradigm for mechanism-guided NP drug discovery.

biochemistry↗

bioRxiv2026

Identification of the Phytophthora PAMP Pep-13 Receptor Using Diploid Potato Inbred Lines

Plants employ cell surface receptors to recognize pathogen-associated molecular patterns (PAMPs) and activate pattern-triggered immunity, a crucial defense mechanism against invading pathogens. Pep-13 is a PAMP derived from a class of conserved cell wall transglutaminases present in Phytophthora species, and its receptor PERU (Pep-13 receptor unit), was reported recently. In our parallel study, we observed distinct responses to Pep-13 between two diploid potato inbred lines: E4-63 recognizes Pep-13, whereas A6-10 does not. Genetic analysis demonstrated that Pep-13 recognition in E4-63 is controlled by a single genetic locus, tentatively designated TGER (Transglutaminase elicitor response). Through bulked segregant analysis sequencing, followed by complementation assays, we found that the TGERa gene in E4-63 is essential for Pep-13 recognition. Sequence alignment revealed that TGERa shares 99.91% amino acid sequence identity with PERU, indicating that TGERa and PERU are allelic variants of the same gene (PERU/TGERa). TGERb, a highly homologous gene of TGERa, was identified in the E4-63 genome; notably, TGERa, but not TGERb, can recognize Pep-13. We further demonstrated that TGERb exhibits defects in ligand binding. Additionally, we found that the TGERa allele in A6-10 is a weak allele with reduced expression levels, presumably resulting from a 3 kb DNA fragment insertion in its first intron. Heterologous introduction of TGERa into Nicotiana benthamiana and tomato significantly enhanced their resistance to Phytophthora infestans. Collectively, our findings confirm that PERU/TGERa functions as the Pep-13 receptor in potato and provide a valuable molecular target for improving Phytophthora resistance in plants.

plant biology↗

bioRxiv2026

gSV: a general structural variant detector using the third-generation sequencing data

Structural variants (SVs) are major contributors to genome diversity and disease susceptibility, particularly in cancer. Although third-generation sequencing technologies have substantially improved SV detection sensitivity, accurate detection of complex SVs remains challenging due to fragmented and heterogeneous alignment signals, as well as the dependence of many existing methods on predefined variant models. In this paper, we propose gSV, a general SV detector that integrates alignment-based and assembly-based approaches with the maximum exact match (MEM) strategy, with particular emphasis on resolving SVs with complex or atypical alignment signatures. Without predefined assumptions about SV types, gSV captures diverse variant signals, enabling the detection of SVs that are usually missed by conventional tools. Benchmarking using both simulated datasets and real long-read sequencing data demonstrates that gSV achieves improved sensitivity and overall detection performance compared with current state-of-the-art SV callers, particularly for simple and complex SV events with complex alignment patterns. Unique SV discoveries in four breast cancer cell lines, particularly in cancer-associated genes, demonstrate the potential biological relevance of gSV-enabled discoveries. Furthermore, analysis of a breast cancer cohort from the Chinese population highlights the utility of gSV for population-scale genomic studies. Collectively, gSV provides a unified framework for comprehensive SV discovery in both research and clinical genomics settings. O_TEXTBOXKey PointsO_LIExisting structural variant (SV) detection tools are limited in resolving SVs with complex alignment patterns due to their reliance on predefined variant models. C_LIO_LIgSV integrates alignment-based and assembly-based evidence using a maximum exact match (MEM) strategy, enabling capture of diverse and complex SV signals. C_LIO_LIBenchmarking on simulated and real long-read sequencing datasets demonstrates that gSV achieves competitive performance on canonical SV classes and improved sensitivity for complex SV patterns. C_LIO_LIApplication of gSV to breast cancer cell lines and a population-scale breast cancer cohort reveals previously unresolved SVs in cancer-associated genes, highlighting its utility in genomic and clinical studies. C_LI C_TEXTBOX

bioinformatics↗

bioRxiv2026

Single-cell profiling reveals pervasive heterogeneity in subcellular RNA localization

Subcellular RNA localization is a fundamental layer of gene regulation, yet its heterogeneity across individual cells remains poorly understood. Here, we introduce the RNA Localization Profiler (RLP), a proximity-based RNA-editing strategy that maps compartment-specific RNAs in living cells. Across the cytoplasm, endoplasmic reticulum (ER), and plasma membrane, RLP identifies robust and highly specific RNA localization programs linked to translation and membrane organization. Single-cell RLP (scRLP) reveals that individual cells harbor roughly 5,000-7,000 cytoplasmic RNAs, with <10% associated with the ER. These measurements uncover pervasive subcellular heterogeneity in RNA localization that is undetectable by bulk assays. Spatial RNA patterns define an orthogonal axis of cell-state identity that is independent of gene expression. For example, ZWINT mRNA relocalizes to the cytoplasm in a cell cycle-dependent manner. These findings establish heterogeneous levels of subcellular RNA localization as a variable dimension of intracellular organization and cell identity.

cell biology↗

bioRxiv2026

Genetic Compensation Restores Embryonic Viability in Fatty Acid Synthase Mutants

Fatty acid synthase (FASN) is a key rate-limited, dimeric multi-enzyme complex in the de novo lipogenesis pathway. Each FASN monomer contains seven catalytic domains, which coordinate the stepwise conversion of acetyl-CoA into fatty acids. While FASN has been extensively studied in cultured cells, particularly for its oncogenic role, its functions in the germline and early embryonic development remain elusive. A major challenge is that the FASN dysfunction typically causes embryonic lethality in animal models, which complicates detailed functional analysis and the identification of compensatory genetic interactors during development. To overcome this limitation and identify novel genetic suppressors of the FASN gene, we utilized a temperature-sensitive allele, fasn-1(g43ts) (A1424T), in the genetically tractable model Caenorhabditis elegans, to conduct unbiased forward genetic screens. We isolated 22 suppressor lines that significantly restored embryonic viability in the fasn-1(g43ts) mutant at the non-permissive temperature. Using a combination of MIP-MAP genomic mapping and a customized bioinformatic pipeline, we identified six missense mutations in the ptr-6 gene, which encodes a protein containing a patched domain associated with the Hedgehog signaling pathway. To validate this genetic suppression, we recreated one of the loss-of-function mutations, ptr-6 (W701*), in the fasn-1(g43ts) background using CRISPR/Cas9 gene editing. Notably, ptr-6(W701*) robustly rescued the embryonic lethality and permeability defects caused by fasn-1 loss-of-function. Taken together, our findings expand the genetic regulatory network of fatty acid synthase during early embryogenesis and highlight ptr-6 and Hedgehog signaling pathway as potential genetic modifiers of FASN-associated developmental and metabolic disorders.

genetics↗

bioRxiv2025

VEGF/ERK activation and PI3K inhibition together drive a vein-to-artery transition in an in vitro model of human angiogenesis

Artery endothelial cells (ECs) arise through different pathways, including differentiation from mesodermal cells (vasculogenesis) or from already established vein or capillary plexus ECs (angiogenesis), the latter being most common during embryonic development and regeneration. Understanding the vein-to-artery (v2a) transition could improve revascularization therapies, but progress is limited by a lack of human models. Here, we develop a human pluripotent stem cell (hPSC) differentiation protocol that models the v2a EC conversion. Comparing v2a and mesoderm-to-artery (m2a) transcriptomes with publicly available single cell RNA sequencing (scRNA-seq) data from human embryos showed they reflected angiogenesis- and vasculogenesis-derived artery ECs, respectively. This reductionist system revealed that VEGF activation alongside PI3K inhibition was sufficient for vein ECs to acquire arterial identity within 48 hours. We model a critical step in vascular development and define the minimal signals required for artery differentiation from veins, providing a framework to promote this conversion in revascularization or therapeutic contexts.

developmental biology↗

bioRxiv2025

Cross-species etiologically informed stratification enables T cell receptor-based diagnosis of Parkinson's Disease

BackgroundDeveloping peripheral blood-based diagnostic models for idiopathic Parkinsons disease (iPD), particularly those leveraging the T-cell receptor (TCR) repertoire, has long been considered infeasible because patient-derived TCRs appear to lack convergent sequence motifs. We reasoned that this apparent absence of shared TCR features likely reflects both insufficient sample sizes and unaccounted immune heterogeneity within the iPD population. MethodsWe reconstructed TCR repertoires from the two largest iPD cohorts currently available, anchoring them with three mechanistically distinct mouse models to stratify patients into model-anchored informed subtypes. Within these data-driven subtypes, we trained subtype-specific, multimodal multi-instance classifiers. ResultsWe demonstrated that iPD patients can be successfully stratified into model-anchored informed subtypes. Furthermore, the trained subtype-specific, multimodal multi-instance classifiers achieved an Area Under Curve (AUC) exceeding 0.8 for both subtypes. ConclusionsOur findings underscore the critical role of disease stratification in enabling TCR repertoire-based modeling in neurodegenerative diseases.

neuroscience↗

bioRxiv2025

Single-cell atlas reveals alveolar macrophage-specific Oncostatin-M drives pulmonary fibrosis via fibroblast activation in PCV2d infection

A hallmark of pulmonary fibrosis is the aberrant activation of lung fibroblasts into pathological fibroblasts that produce excessive extracellular matrix(1). Clarifying the cell-specific mechanisms by which viruses induce this process is crucial for developing effective strategies to intervene in disease progression. Here, we demonstrate that alveolar macrophage subsets specifically express tumor suppressor M (Osm) after infection by PCV2d infection and related intervention experiments in mice, combined with single-cell transcriptome sequencing (scRNA-seq). Through validation using histopathological analyses and an in vitro macrophage-fibroblast co-culture model, these alveolar macrophage-derived oncostatin M (Osm) were confirmed to specifically drive fibroblast activation. Vaccine intervention experiments further confirmed that targeted inhibition of oncostatin M (Osm) expression in alveolar macrophages significantly attenuated fibroblast activation and extracellular matrix deposition, thereby mitigating pulmonary fibrosis progression. Therefore, subgroup-specific secretion of oncostatin M (Osm) by alveolar macrophages represents a key driver mediating PCV2d infection-induced pulmonary fibrosis, and targeting this pathway offers a potential therapeutic strategy for viral-induced pulmonary fibrosis.

genomics↗

bioRxiv2025

RoBep: A Region-Oriented Deep Learning Model for B-Cell Epitope Prediction

MotivationAccurate in silico identification of B-cell epitope residues is crucial for antibody design and structure-guided vaccine development. Although recent protein language models and structure-aware methods can capture spatial information of tertiary structure when generating residue embeddings, most existing epitope predictors use these embeddings to perform classification for individual residues one by one, without enforcing spatial continuity for reported epitope residues. Such methods often result in biologically implausible predictions because B-cell epitope residues always cluster together on the antigen surface. ResultsWe present RoBep, a region-oriented B-cell epitope predictor that explicitly models the spatial clustering of epitope residues. RoBep introduces a novel region constraint mechanism and combines the advanced protein language model ESM-Cambrian with an equivariant graph neural network. Our method outperforms existing structure-based methods on the benchmark dataset, demonstrating improvements of 26%, 45%, 13%, and 43% in F1, MCC, AUPR, and AUROC0.1, respectively. In addition to residue-level predictions, RoBep can also provide antibody-antigen binding regions. Importantly, the predicted epitope residues are ensured to be spatially compact, enhancing biological plausibility and practical relevance for immunotherapeutic design. AvailabilityA user-friendly website for using RoBep is provided at https://huggingface.co/spaces/NielTT/RoBep. All datasets, source code used in this work, and implementation instructions of the website are publicly available at https://github.com/YitaoXU/RoBep.

bioinformatics↗

bioRxiv2025

Dissecting sequence determinants of DNA methylation and in silico perturbation

DNA methylation shapes cellular identity and genome function, yet the sequence logic that governs its establishment remains largely unresolved. Here we present MethylAI, a cross-species-pretrained and human-specialized deep learning framework that predicts single-CpG methylation states directly from genomic sequence with high fidelity. Through quantitative attribution, MethylAI uncovers intrinsic cis-regulatory principles embedded in DNA, revealing conserved transcription factor (TF) motifs whose influence extends beyond CpG composition. Activated motifs demarcate gene-body CpG islands, encode lineage-defining methylation states, and align with TF occupancy and diverse histone modifications, thereby linking sequence syntax to local chromatin regulation. CTCF perturbation experiments validated MethylAI-predicted methylation shifts at activated motifs, showing strong concordance with in silico perturbations. Mapping genetic variants onto methylation-linked active motifs further uncovered widespread connections to zinc-finger TF families, providing mechanistic insight into how noncoding variation contributes to human traits and diseases. By transforming DNA sequence into interpretable methylation grammar, MethylAI establishes a generalizable framework for decoding the regulatory architecture of the human epigenome.

genomics↗

bioRxiv2025

A human forebrain organoid model phenocopies dysregulated RNA and protein homeostasis in ALS/FTD-associated TDP-43 proteinopathies

TAR DNA-binding protein 43 (TDP-43) proteinopathy is a defining pathological feature of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), yet the downstream molecular events linking TDP-43 dysfunction to neurodegeneration remain incompletely understood. Here, we model TDP-43 proteinopathy by introducing the ALS/FTD-associated TARDBP K181E mutation into human induced pluripotent stem cells and differentiating them into three-dimensional forebrain organoids. Organoids carrying the K181E mutation exhibit spontaneous TDP-43 hyperphosphorylation, cytoplasmic p-TDP43 accumulation, RNA dysregulation, pro-inflammatory signaling, and activation of apoptotic pathways without TDP-43 overexpression or external stress. Single-cell transcriptomics and enhanced crosslinking immunoprecipitation reveal that the K181E mutation alters TDP-43 RNA-binding specificity, causing widespread RNA mis-splicing including cryptic exon inclusion. Among affected targets, we identify cryptic exon inclusion in the transcription factor PRDM2. PRDM2 cryptic exon-derived peptide immunoreactivity was detected in ALS spinal motor neurons and associated with p-TDP-43 pathology. These findings identify PRDM2 mis-splicing as a candidate downstream event linking TDP-43 dysfunction relevant to ALS and FTD. One sentence summaryHuman brain organoids reveal how mutant TDP-43 disrupts RNA processing and causes neuronal stress.

neuroscience↗

bioRxiv2025

Deep Learning Enables Automated Segmentation and Quantification of Ultrastructure from Transmission Electron Microscopy Images

Transmission electron microscopy (TEM) has become an essential technique for observing subcellular ultrastructure, and is widely used in both clinical diagnosis and biomedical research. However, analysis of TEM data remains extremely labor-intensive and often inconsistent across operators due to the lack of dedicated computational methods. Here, we present TEAMKidney, a deep learning framework for accurate and scalable measurement of ultrastructures in TEM images across species, magnifications, and instrument platforms. We collected 12,991 TEM images from patients with multiple kidney diseases and from different animal models. By combining a self-training-based semantic segmentation stage with a TEM-tailored panoptic segmentation model, we address two major challenges in TEM data analysis: the lack of accurately labeled training data and the difficulty of achieving high segmentation accuracy for complex ultrastructure. Application of TEAMKidney to both human and animal images successfully reveals disease-associated changes in two critical glomerular ultrastructures: the glomerular basement membrane and podocyte foot processes. In addition to significantly outperforming existing tools, TEAMKidney shows close agreement with pathological expert measurements used in clinical assessment protocols. By reducing dependence on manual tracing while preserving expert-level accuracy, TEAMKidney demonstrates that deep learning can substantially reduce the burden of image analysis in both clinical pathology and biomedical research settings.

bioinformatics↗

bioRxiv2025

Machine Vision Enabled Lateral Flow Immunoassay Using Functionalized Gold Nanoparticles for Point-of-Care Cardiac Biomarker Detection

Acute myocardial infarction (AMI) remains one of the most prevalent and fatal cardiovascular disease. Given the critical diagnostic significance of cardiac troponin I (cTnI) and myoglobin (Myo) in AMI, there is an urgent clinical demand for rapid and accurate detection methods to improve patient outcomes and reduce mortality. To meet this need, we developed a sensing platform that integrates functionalized gold nanoparticle-based lateral flow immunoassay (AuNPs-LFIA) with a machine vision model, enabling rapid quantitative detection of cTnI and Myo. By covalently conjugating antibodies to gold nanoparticles (AuNPs@Ab), we achieved greater probe specificity and stability. The integration of machine vision algorithms allowed quantitative readouts within 8 minutes, a 46.7% improvement of the detection time compared to conventional methods (15 minutes). The platform achieved limits of detection of 0.224 ng/mL for Myo and 0.071 ng/mL for cTnI, with excellent correlation to commercial kits (R2 > 0.99). Overall, these results demonstrate that machine vision-enhanced AuNPs-LFIA offers an efficient, sensitive and reliable strategy for point-of- care testing (POCT) in cardiovascular diagnostics, particularly in resource-limited settings.

bioengineering↗

bioRxiv2025

The neural basis of emotional generalization in empathy

The essence of empathy is generalization of emotion across persons. Here, we leverage recent theoretical advances in the neuroscience of generalization to help us understand empathy. We measured brain activity in human neurosurgical patients performing two tasks, one focused on identifying their own emotional response and one identifying emotional responses in others. We quantified the representational geometry of local field potential (LFP) high-gamma activity in four regions: the medial temporal lobe, anterior cingulate cortex, orbitofrontal cortex, and insula. We found encoding of both self- and other-emotions in all four regions, but codes for emotion and person are disentangled (that is, factorized) in the insula, but not the other regions. This factorized representation allows for cross-person generalization of emotion in a way that tangled (non-factorized) representations do not. Together, these results support the hypothesis that the insula uniquely contributes to social mirroring processes by which we understand emotions across individuals.

neuroscience↗

bioRxiv2025

Arhgef18 is a component of the outer limiting membrane required for retinal homeostasis

Biallelic ARHGEF18 mutations cause human adult-onset retinal degeneration. We now find that Arhgef18 associates with the retinal outer limiting membrane (OLM), an adherens junction between Muller glia and photoreceptors. Arhgef18 knockout in Muller glial cells led to OLM disruption and vision loss by P60. While mice developed morphologically normal retinas, retinal rosettes started to form by P8, and retinas then progressively degenerated with OLM disintegration, retinal thinning, and vascular leakage. ARHGEF18/p114RhoGEF depletion in Muller cells in culture confirmed disruption of junctional recruitment of OLM proteins. Depletion also induced activation of NF-{kappa}B and {beta}-catenin signalling, activation of the multifunctional kinase Tank-binding kinase 1 (TBK1) and reduced mitochondrial activity. TBK1 inhibition or directly supporting mitochondrial activity with nicotinamide attenuated NF-{kappa}B and {beta}-catenin signalling and rescued mitochondrial activity. Thus, Arhgef18 is essential for OLM maintenance, and its disruption leads to activation of mechanisms that are targetable for possible therapeutic approaches.

cell biology↗

bioRxiv2025

Genomic and Epigenetic Interplay Drives Adaptive Fusion via Reproduction Trade-Off

Investment in sexual reproduction has long been seen as a fitness cost for asexual proliferation, raising the question of how cells evolve to accommodate cyclical demands of sexual and asexual cycles. We addressed this question by evolving Schizosaccharomyces pombe lacking the critical fusion gene Prm1 through 18 cycles of alternating meiosis and mitosis. Initially, transcriptional tweaks offered a fragile means to fuse despite Prm1s absence. However, a telomeric 1% genome deletion that epigenetically silenced Clr5 ultimately locked in a latent, Prm1-independent fusion pathway involving the mating regulator Ste11 and the pheromone-MAPK scaffold Sms1. This adaptation, though efficient at restoring sexual reproduction, came at the cost of mitotic growth. By contrast, rationally constructing mutations in a "synthetic evolution" approach bypassed the trade-off, enabling simultaneous high fusion efficiency and near-wild-type proliferation. Our findings illustrate how epigenetic de-repression and genetic assimilation converge to create innovative solutions under cyclical selection pressures with trade-offs.

evolutionary biology↗