Biology subjects

Ye, Y.

Publications and source records attributed to Ye, Y..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

A novel type of gel-like proteasome condensate induced by toxic protein aggregates

Proteasomes reversibly form foci bodies in a liquid-liquid phase separation (LLPS)-dependent manner upon stress. We previously reported that internalized protein aggregates were targeted by proteasome-dense foci1, and proposed that such transient aggregate-associated droplets (TAADs) may facilitate aggregate removal2. Here we use quantitative imaging to show that TAADs represent a novel type of gel-like proteasome condensate. TAADs are irregular in shape and slow to disperse, sequestering proteasomes in agreement with our observation of confined diffusion3. We demonstrate that TAADs co-localize with cytosolic alpha-synuclein aggregates to facilitate their clearance. Inhibition of proteasome- or ubiquitination activity abolishes this aggregate clearance. We identify RAD23B necessary for TAAD formation, amid other co-localizing chaperones and (co-)proteins of the ubiquitin-proteasomes system. TAAD formation is associated with higher proteasomal substrate turnover whilst retaining overall catalytic efficiency, suggestive of altered degradation mechanisms upon aggregate engagement. Proteomics analysis reveals impact on key mitochondrial-associated processes even after TAAD-aggregate disengagement. Similar TAAD-aggregate co-localizations are found in iPSC-differentiated neurons and in disease-relevant samples, with no detection of compromised proteasome activity. Together, our results indicate a model where TAADs concentrate local proteasome activity, which facilitates aggregate clearance in healthy ageing cells. Potentially, should pathological aggregates persist, TAADs may remain engaged and conceivably sequester proteasomes from physiological activities, thus contributing to neurodegenerative disorders.

cell biology↗

bioRxiv2025

Identification and characterization of a novel exo-glycosidase activity of NGLY1 on ENGase-digested N-GlcNAc proteins in vitro

N-Glycanase 1 (NGLY1) is known for its activity to completely remove conjugated N-glycans from glycoproteins. Early studies illustrated that NGLY1 defects were associated with a rare disease named NGLY1-related congenital disorder of deglycosylation (NGLY1-CDDG). Although extensive research has been conducted over the past decade on the biological impact of NGLY1s endo-(N-)glycanase activity in cells and on disease, whether NGLY1 also exhibits an exo-(N-)glycanase activity remains open. In this study, an exo-(N-)glycanase activity of NGLY1 on the N-GlcNAc proteins was firstly reported and characterized in vitro. To distinguish for the conventional endo-(N-)glycanase activity and the newly reported exo-(N-)glycanase activity of NGLY1, the active sites of exo-NGLY1 were predicted and compared with those of endo-NGLY1. In addition, the correlation between NGLY1s exo-(N-)glycanase activity in vitro and NGLY1-CDDGs clinical characterization was investigated and discussed. The observation of NGLY1s novel exo-(N-)glycanase activity expanded the functional repertoire of NGLY1 beyond canonical endo-(N-)glycanase-mediated deglycosylation, and may provide a new framework to explain the clinical heterogeneity of NGLY1-CDDG.

biochemistry↗

bioRxiv2025

Neural mechanisms and effects of acute stress on athletess' unfair decision-making behavior

Acute stress may disrupt decision - making by affecting cognitive and emotional processing. The behavioral and neural mechanisms of this in athletes are unclear. This study explored how acute stress impacts athletes unfairness - related decision - making and its neural basis. Forty participants (20 university athletes and 20 non - athlete students) were randomly assigned to a stress group or a control group. Using functional near - infrared spectroscopy (fNIRS), the study monitored the prefrontal cortex (PFC) and temporoparietal junction (TPJ) blood oxygenation during an ultimatum game task after inducing acute stress via the Maastricht Acute Stress Test (MAST). Athletes under stress were more accepting of relatively unfair decisions than non - athletes. This was linked to lower activation in the frontal - eye areas (CH15), supramarginal gyrus (CH38), and somatosensory association cortex (CH67), and higher activation in the primary motor cortex (CH64) in athletes. The increase in acceptance efficiency correlated significantly with the reduced CH38 activation (Rho = - 0.425) and increased CH64 activation (Rho = 0.499). Long - term exercise likely enhances PFC - TPJ functional integration, helping athletes adopt adaptive strategies under acute stress. These findings offer insights for developing stress management and neuromodulation training programs for athletes.

neuroscience↗

bioRxiv2025

Inhibition of nonsense-mediated decay in TDP-43 deficient neurons reveals novel cryptic exons

TAR DNA-binding protein 43 kDa (TDP-43) is an essential splicing repressor whose loss of function underlies the pathophysiology of amyotrophic lateral sclerosis and frontotemporal dementia (ALS-FTD). Nuclear clearance of TDP-43 disrupts its function and leads to the inclusion of aberrant cryptic exons. These cryptic exons frequently introduce premature termination codons resulting in the degradation of affected transcripts through nonsense-mediated mRNA decay (NMD). Conventional RNA sequencing approaches thus may fail to detect cryptic exons that are efficiently degraded by NMD, precluding identification of potential therapeutic targets. We generated a comprehensive set of neuronal targets of TDP-43 in human iPSC-derived i3Neurons (i3N) by combining TDP-43 knockdown with inhibition of multiple factors essential for NMD, revealing novel cryptic targets. We then restored expression of selected NMD targets in TDP-43 deficient i3Ns and determined which genes improved neuronal viability. Our findings highlight the role of NMD in masking cryptic splicing events and identify novel potential therapeutic targets for TDP-43-related neurodegenerative disorders.

neuroscience↗

bioRxiv2025

Substrate properties and actin polymerization speed dictate universal modes of cell migration: gripping, slipping, and stick-slip

Understanding how cells sense mechanical cues and regulate migration is crucial in the development, fibrosis, and oncogenesis processes. However, a comprehensive physical picture of cell migration remains lacking, given the diverse environmental properties and cell physiologies. Here, we generalize the motor-clutch model to the whole-cell level and systematically investigate the effects of substrate stiffness, friction, and actin polymerization speed on cell migration. We unveil three distinct migration modes: gripping, slipping, and stick-slip. Notably, stiffness sensing occurs exclusively in the stick-slip mode, which requires a low substrate stiffness and a minimum actin polymerization speed as necessary conditions. Intriguingly, the optimal substrate stiffness that maximizes the migration speed is inversely proportional to the actin polymerization speed. Moreover, the maximal speed only depends on the nature of the clutch molecules, independent of substrate properties. We reveal the boundary criteria between the three migration modes and demonstrate that fast- and slow-migrating cells can coexist in an isogenic cell population without the need for biochemical feedback loops.

biophysics↗

bioRxiv2025

DCPS modulates TDP-43 mediated neurodegeneration through P-body regulation

The proteinopathy of the RNA-binding protein TDP-43, characterized by nuclear clearance and cytoplasmic inclusion, is a hallmark of multiple neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and Alzheimers disease (AD). Through CRISPR interference (CRISPRi) screening in human neurons, we identified the decapping enzyme scavenger (DCPS) as a novel genetic modifier of TDP-43 loss-of-function (LOF)-mediated neurotoxicity. Our findings reveal that TDP-43 LOF leads to aberrant mRNA degradation, via disrupting the properties and function of processing bodies (P-bodies). TDP-43 interacts with P-body component proteins, potentially influencing their dynamic equilibrium and assembly into ribonucleoprotein (RNP) granules. Reducing DCPS restores P-body integrity and RNA turnover, ultimately improving neuronal survival. Overall, this study highlights a novel role of TDP-43 in RNA processing through P-body regulation and identifies DCPS as a potential therapeutic target for TDP-43 proteinopathy-related neurodegenerative diseases.

neuroscience↗

bioRxiv2025

Single-cell transcriptomic integrated with machine learning reveals retinal cell-specific biomarkers in diabetic retinopathy

Diabetic retinopathy (DR) remains a principal cause of vision impairment worldwide, involved complex retinal cellular pathophysiology that remains incompletely understood. To elucidate cell-type-specific molecular signatures underlying DR, we generated a high-resolution single-cell transcriptomic atlas of 297,121 retinal cells from 20 Chinese donors, including non-diabetic controls (26.4%), diabetic without retinopathy (23.4%) and DR (50.2%). Following rigorous quality control, batch-effect correction, and clustering and annotation, 10 major retinal cell populations were delineated. Differential expression analyses across disease states within each cell type yielded candidate gene sets, which were further refined via a multi-stage machine-learning pipeline combining L1-regularized logistic regression and recursive feature elimination with cross-validation, alongside bootstrap stability selection. Resulting cell-type-specific classifiers achieved high accuracy (79-95%) and AUCs (0.85-0.99) in distinguishing DR disease states. Enrichment analyses implicated immune activation, oxidative stress, neurodegeneration and synaptic dysfunction pathways across multiple cell types in retina. Integrating 567 unique marker genes from all cell types, a general multilayer perceptron classifier achieved 95.31% overall accuracy on held-out test data, demonstrating the translational potential of these signatures for non-diabetic controls, diabetic without retinopathy and DR classification. This high-resolution atlas and the accompanying analytic framework provide a robust computational framework for biomarker discovery, mechanistic insight and targeted intervention strategies in diabetic retinal diseases.

bioinformatics↗

bioRxiv2025

Cell Type Specific Aging Transcriptional Signatures of Human Retina Through Integrated Machine Learning and Single-Cell Transcriptomics

PurposeTo characterize cell type specific transcriptional changes during human retinal aging and develop machine learning model for cellular age discrimination in a Chinese cohort. DesignCross-sectional, laboratory-based observational study. ParticipantsEighteen unfrozen retinas from 12 Chinese donors (9 young, 34-55y; 9 old, 68-92 y). MethodsSingle-cell RNA sequencing (10x, v3.1) generated 223612 cells, batch-corrected with scVI; age-related signatures were defined by intersecting single-cell and pseudo-bulk differentially expressed genes, then cell-type-specific panels were rank-ordered with L1-regularised logistic regression plus recursive feature elimination and interpreted through hallmark-pathway enrichment and transcription-factor regulon mapping. Main Outcome MeasuresAge-related cellular composition shifts; cell-type-specific differentially expressed genes; machine-learning classifier accuracy and feature rankings; transcription factor regulon activity changes. ResultsEleven major retinal cell populations were identified. Aging showed declining rod-to-cone ratios, reduced bipolar cell proportions among interneurons, and increased astrocyte abundance. Muller glial cells exhibited the most pronounced transcriptional changes, followed by bipolar cells and rods. Machine-learning classifiers achieved 80-96% accuracy across cell types (microglia 96%, horizontal cells 93%, bipolar cells 91%, cones 90%, rods 89%). Shared aging signatures included mitochondrial dysfunction and inflammatory activation. Cell specific vulnerabilities emerged: mitochondria-centric stress in rods/bipolar cells, proteostasis-retinoid metabolism in cones, and structural-RNA maintenance in horizontal cells. ConclusionsThis study provides the first machine learning derived, cell-type specific aging signatures for human retina in a Chinese cohort, revealing both conserved molecular hallmarks and distinctive cellular vulnerabilities that inform targeted therapeutic strategies for retinal aging.

bioinformatics↗

bioRxiv2025

SenolyticSynergy: An Attention-Based Network for Discovering Novel Senolytic Combinations via Human Aging Genomics

Senolytics, a category of drugs targeting aging processes, have garnered significant attention since their emergence in 2015. Unlike traditional drug development approaches that rely on randomized screening, research on aging-related pharmaceuticals has employed mechanism-based strategies, resulting in the discovery of the pioneering combination therapy of dasatinib (D) and quercetin (Q). Although preliminary studies with senolytic drug combinations have shown promising outcomes, the predictive capabilities of the research in this field remain limited by the extensive experimental data requirements. In this study, we employed differential gene expression analysis and machine learning techniques to investigate the combinatorial effects of senolytic drugs. We identified 1624 core aging-related genes and used this dataset to retrain a multimodal attention mechanism model, creating a specialized framework: SenolyticSynergy for predicting effective senolytic drug combinations. We then utilized 63 established senolytic compounds as starting points for combination testing, developing a comprehensive dataset of 1953 potential drug combinations for aging interventions. Following rigorous filtration, we identified 190 high-confidence drug combinations and predicted their synergistic scores. Among these combinations, ten demonstrated exceptionally high synergistic scores, exceeding 8. The combination of temsirolimus and nitazoxanide ranked first and may be the most promising candidate. The analysis of literature data and computational studies of molecular structures using 3D modeling validated the accuracy of these predictions. This framework paves the way for large-scale research into anti-aging drug combinations, advancing research capabilities in this field. GRAPH ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=176 HEIGHT=200 SRC="FIGDIR/small/655258v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@26aae1org.highwire.dtl.DTLVardef@9ca730org.highwire.dtl.DTLVardef@a471ddorg.highwire.dtl.DTLVardef@2f8b7a_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Genetically Programmable Adhesive Protein Hydrogels for Sealing Perforating Corneal Trauma

The cornea, situated at the forefront of the eyeball, is often subjected to varying degrees of mechanical laceration injuries due to various traumatic incidents. Timely and precise suturing of corneal wounds to prevent the leakage of intraocular contents is a significant clinical challenge. Although some studies have attempted to use hydrogels to accurately cover corneal injuries, most of these hydrogels are only suitable for adhering to focal stromal defects that do not involve the corneal stroma. Here, a fully protein-based hydrogel, based on SpyTag-SpyCatcher chemistry, was investigated for repairing corneal perforating injury models in rats and rabbits. The hydrogel formation relies on covalent bonding between SpyTag (A) and SpyCatcher (B) under physiologically mild conditions, eliminating requirements for organic solvents, elevated temperatures, or photoactivation Notably, integration of recombinant mussel foot protein 3 (Mfp3) endowed the hydrogels with exceptional water-resistant adhesiveness, while maintaining their original mechanical properties and biocompatibility. This study demonstrates the great potential of Mfp hydrogels in the timely and precise repair of corneal perforating injuries in complex physicochemical environments. TeaserBioinspired protein hydrogel rapidly seals corneal perforations, minimizing scarring and inflammation without sutures in animal models.

bioengineering↗

bioRxiv2025

Aromatic Microbial Metabolite Hippuric Acid Potentiates Pro-Inflammatory Responses in Macrophages through TLR-MyD88 Signaling and Lipid Remodeling

The gut microbiome generates a diverse array of metabolites that actively shape host immunity, yet the pro-inflammatory potential of microbial metabolites remains poorly understood. In this study, we identified hippuric acid, an aromatic gut microbe-derived metabolite, as a potent enhancer of pro-inflammatory responses using a murine bacterial infection model and a non-targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics. Administering hippuric acid intraperitoneally in murine models of Escherichia coli infection or LPS-induced inflammation significantly heightened pro-inflammatory responses and innate immune cell activation. In vitro, hippuric acid selectively potentiated M1-like macrophage polarization (LPS + IFN{gamma}) but had no effect on M2-like polarization (IL-4). Hippuric acid further enhanced responses to diverse MyD88-dependent TLR ligands, but not TRIF-dependent TLR3, implicating a possible mechanism of action via activation of TLR-MyD88 signaling. Genetic deletion of MyD88 abrogated the pro-inflammatory effects of hippuric acid both in vitro and in vivo, confirming its dependence on the MyD88 pathway. Transcriptomic and lipidomic analyses revealed that hippuric acid promoted cholesterol biosynthesis and lipid accumulation, linking microbial metabolism to lipid-driven immune activation. Notably, hippuric acid similarly enhanced pro-inflammatory responses in human macrophages, and its elevated levels correlated with increased sepsis mortality, highlighting its potential clinical relevance. These findings establish hippuric acid as a previously unrecognized microbial-derived inflammatory modulator, bridging gut microbial metabolism, lipid remodeling, and innate immune signaling, and offer new insights into its role in infection and inflammation.

immunology↗

bioRxiv2025

Universal Dual-Target CAR-γδT Cells Targeting B7-H3 and IL13Rα2 for Glioblastoma Therapy

Glioblastoma (GBM) represents the most prevalent and aggressive primary malignant neoplasm in the adult central nervous system, exhibiting marked infiltrative growth patterns, inevitable recurrence, and dismal therapeutic outcomes with current treatment modalities. While CAR-T cell immunotherapy has demonstrated remarkable success in hematological malignancies, its clinical translation for GBM has been hampered by several fundamental limitations. A key factor among these is tumor-intrinsic heterogeneity, which drives antigen escape and therapeutic resistance. Furthermore, although autologous CAR-T approaches dominate current clinical investigations, they encounter substantial barriers including manufacturing variability, scalability constraints, and practical limitations for widespread clinical deployment. In contrast, allogeneic "off-the-shelf" CAR-T therapy holds greater potential for the future applications. {gamma}{delta} T cells are a particularly compelling candidate for universal CAR therapy, offering several advantages including innate MHC-unrestricted target recognition obviating the need for HLA matching, polyfunctional cytotoxic mechanisms capable of addressing heterogeneous tumor populations, and intrinsic tropism for solid tumors. However, translational implementation has been constrained by their physiological rarity, ex vivo expansion difficulties, and genetic modification inefficiencies. To address these challenges, we adopted a dual-pronged targeting strategy focusing on B7-H3 and IL13R2 - two surface antigens demonstrating preferential overexpression across GBM subtypes while maintaining limited distribution in normal tissues. Using phage display platform and function-based nanobody screening we identified high-affinity binders against both targets. Subsequent optimization of {gamma}{delta} T cell expansion protocols and lentiviral transduction parameters enabled the development of a bispecific, allogeneic CAR-{gamma}{delta} T cell platform. Our in vitro studies revealed that dual-target CAR-{gamma}{delta}T cells sustained proliferative capacity under GMP-compatible culture conditions, exhibited potent and specific cytotoxicity against antigen-positive glioma cells, and critically, they showed superior elimination of target-heterogeneous tumors compared to monospecific CAR-T constructs. These results establish a robust preclinical foundation for clinical translation and highlight the therapeutic potential of combinatorial antigen targeting coupled with allogeneic {gamma}{delta} T cell engineering to overcome the persistent challenges in GBM immunotherapy.

immunology↗

bioRxiv2025

High-temporal-resolution point-of-care multiplex biomarker monitoring in small animals using microfluidic digital ELISA

Time-course monitoring of blood biomarkers with rapid turnaround has the potential to revolutionize the diagnosis, stratification of phenotypes, and therapeutic/prognostic approaches for various acute inflammatory diseases in both clinical and preclinical studies. Current approaches, however, are hampered by slow turnaround times and large sample volume requirements, limiting the exploration of disease mechanisms and therapeutic strategies. Here, we developed a microfluidic digital ELISA platform prototype, combining single-molecule counting with whole blood assay capability for the first time from small animal models. This platform is automated and enables repeated, rapid biomarker monitoring with just 3.5 {micro}L of whole blood collected from the tail. Our platform demonstrated high sensitivity and multiplexity, allowing real-time cytokine profiling within a 2-hour turnaround. Using a murine sepsis model, we achieved precise temporal monitoring of cytokine levels, demonstrating prognostic capability by correlating early-stage cytokine levels with a liver-injury biomarker. This microfluidic platform enables high temporal resolution and rapid monitoring of biomarker dynamics in a single mouse using freshly collected whole blood, significantly reducing the number of animals needed for preclinical studies. This technology has strong potential to transform ICU therapeutic strategies and preclinical research, enabling personalized treatment based on real-time biomarker profiles.

bioengineering↗

bioRxiv2025

Roles of the MO25 protein Pmo25 in contractile-ring stability and localization of the NDR kinase Sid2 during cytokinesis

Mouse protein-25 (MO25) family proteins are crucial in development and morphogenesis from plants to humans. The fission yeast MO25 protein Pmo25 is essential for cell polarity and division. However, how Pmo25 regulates cytokinesis remains largely unknown. Here we found that the actomyosin contractile ring and septum formation were defective during cytokinesis in pmo25 mutants. Pmo25 physically and genetically interacted with the myosin-II light chain Cdc4, which is essential for the contractile-ring assembly and function. Additionally, pmo25 mutations had synthetic genetic interactions with all other tested mutations in contractile-ring proteins. Moreover, Pmo25 colocalized with the NDR kinase Sid2 and participated in its recruitment to the division plane. Furthermore, Pmo25 directly bound the Munc13/UNC-13 protein Ync13 and modulated the secretion of glucanase Eng1 to the division site for daughter-cell separation. Our data provide insight into how Pmo25 regulates cytokinesis and suggest that the conserved MO25 proteins can link various steps of cytokinesis.

cell biology↗

bioRxiv2025

Deciphering Biosynthetic Gene Clusters with a Context-aware Protein Language Model

Microbial secondary metabolites, synthesized by biosynthetic gene clusters (BGCs), offer vast potential for biotechnological applications. Among BGC profiling techniques, computational detection methods face challenges, including time-consuming alignment and reliance on predefined profiles. To address these, we present BGC-Finder, an end-to-end pipeline utilizing protein language models for BGC detection and annotation from microbial genomes and metagenomes. This approach achieves remarkable increase in profiling speed of up to 100-fold, and employs genomic context-aware modeling to facilitate interpretable genetic essentiality assessment and large-scale BGC clustering. BGC-Finder outperformed traditional methods, successfully detecting 9.49% more biosynthetic-core genes and 27.70% more cytochrome P450s in 742 experimentally-validated BGCs. Notably, it retrieved 31 remote biosynthetic homologs from 210 polar marine metagenomes and identified 4,585 BGCs with 6,388 core genes from 256 fungal genomes. These findings highlight BGC-Finders capability to illuminate "microbial biosynthesis dark matter" (sequence-unrelated, function-similar biosynthetic enzymes) and expedite natural product discovery. HighlightsO_LIBGC-Finder is an accurate and ultrafast pipeline leveraging protein language models (pLMs) to predict and annotate biosynthetic gene clusters (BGCs) from microbial genomes and metagenomes. C_LIO_LIThe genomic context-aware model enables interpretable analysis: attention-driven identification of essential biosynthetic genes and embedding-guided BGC clustering. C_LIO_LIBGC-Finder sensitively retrieves remote homologous BGCs from both bacteria and fungi genomes, uncovering hidden microbial biosynthesis dark matter. C_LIO_LIWe discovered a non-ribosomal peptide synthetase (NRPS) family, which involved into function-specific BGCs in two evolutionarily distant fungi. C_LI

bioinformatics↗

bioRxiv2025

CellLoop: Identifying single-cell 3D genome chromatin loops

Single-cell 3D genome mapping offers insights into chromatin architecture, yet the inherent sparsity and high dimensionality of contact maps hinder reliable identification of chromatin loops at the single-cell level. Here, we present CellLoop, a single-cell chromatin loop detection algorithm based on a density-based center detection framework that integrates intra-cellular and neighboring inter-cellular contacts via a re-voting strategy. Applied to Dip-C data from the mouse brain, CellLoop demonstrates superior accuracy based on the genome spatial distance and compartment signals at the single-cell level. It reveals cell-specific chromatin loops linked to transcriptional regulation and improved cell state classification. In HiRES embryogenesis data, CellLoop refines cell subtype definitions by minimizing cell cycle effects. Integrating GAGE-seq with MERFISH in mouse cortex, CellLoop redefines spatial domain functions through chromatin loop dynamics. Together, CellLoop enables robust, scalable, and biologically meaningful single-cell chromatin loop detection.

bioinformatics↗

bioRxiv2025

Construction of Complete Telomere-to-Telomere Genome Assembly of the Rabbit Using Haploid Embryonic Stem Cells

The rabbit owns commercial importance in meat and fur production, and also has long served as a valuable animal model in biomedical research. Yet, the complete assembly of a high-quality rabbit reference genome has not been established. Here, we present a telomere-to-telomere (T2T) genome assembly of the New Zealand White (NZW) rabbit, the most complete and accurate rabbit genome to date. Using a haploid embryonic stem cells (haESCs) to overcame the challenges of homologous sequence interference and structural variation, we generate a genome with a contig N50 of 137.71 Mb, anchoring all chromosomes with only three gaps, through integrating long-read sequencing (PacBio HiFi, Oxford Nanopore), Hi-C, and Illumina data. Quality assessments reveal near-complete coverage of the BUSCO mammalian gene set, with 99.61% completeness. Notably, this complete assembly allowed for the first comprehensive annotation of the rabbit immunoglobulin loci and major histocompatibility complex region, which were previously unresolved in earlier genome versions. The NZW-T2T assembly based on haESCs not only provides a critical resource for advancing rabbit-based research, but also set a new benchmark for de novo genome assembly for other animals with complex genome.

genomics↗

bioRxiv2025

Convergent strigolactone perception via independent horizontal gene transfer of pre-adapted α/β-hydrolases

Strigolactones (SLs) are not only phytohormones that influence multiple aspects of plant growth and development, but also signaling molecules for interactions between plants and certain fungi or bacteria. In plants, the SL receptor is an /{beta}-hydrolase (ABH) encoded by the D14/KAI2 gene family, which is known to be derived from proteobacterial RsbQ through horizontal gene transfer (HGT). Here we show that the CpD14-like (CDL) gene family, which encodes another ABH exhibiting SL receptor functions in fungi, was acquired from actinobacteria via an independent HGT event. X-ray crystallographic experiments reveal that CDL and D14/KAI2/RsbQ (DKR) proteins have distinctive lid structures but maintain the same core /{beta} fold and catalytic triad. Biochemical assays further show that both actinobacterial CDL and proteobacterial RsbQ can recognize and hydrolyze SLs, suggesting that they are pre-adapted for SL perception. This work demonstrates that independent HGT of pre-adapted genes can trigger convergent evolution of key innovations and provides insights into how SLs are sensed by organisms across kingdoms.

evolutionary biology↗