Biology subjects

Feng, Q.

Publications and source records attributed to Feng, Q..

At least 19 recordsLinked to original sources

bioRxiv2026

NEIL2 regulates RNA polymerase II dynamics to suppress transcription replication conflicts in pancreatic cancer

Transcription replication conflicts (TRCs) arise from spatiotemporal interference between replication and transcription machinery and contribute to genome instability in cancer cells. In pancreatic ductal adenocarcinoma (PDAC) cells, oncogenic KRAS drives TRC formation, and base excision repair (BER) contributes to TRC resolution as an adaptive response. Here, we show that TRCs are enriched in pancreatic tumor sections from patients and are associated with malignant progression. We identify NEIL2, a bifunctional DNA glycosylase in the BER pathway, as a critical regulator of TRCs in PDAC cells. Mechanistically, NEIL2 loss causes aberrant RNA polymerase II (RNAPII) occupancy at transcription start sites and downstream of transcription end sites. Dysregulated RNAPII dynamics promote R-loop-dependent and -independent TRCs contributing to replication stress, DNA damage, and impaired cancer cell proliferation. Notably, the DNA-binding motif of NEIL2 necessary for canonical BER function is dispensable for TRC regulation. Together, these findings reveal an unrecognized role for NEIL2 in regulating RNAPII dynamics and mitigating TRCs in pancreatic cancer cells.

molecular biology↗

bioRxiv2026

Expandable DNA-origami rings as a nanomechanical platform for studying disordered nucleoporins

Phe-Gly-rich nucleoporins (FG-Nups) within the nuclear pore complex (NPC) form a diffusion barrier that controls the exchange of macromolecules between the nucleus and cytoplasm. The behaviors of these intrinsically disordered FG-Nups are fundamental to the NPC function but remain difficult to probe within the dynamic, native nuclear pore. To bridge this knowledge gap, here we build expandable DNA-origami rings with tunable elasticity and study FG-Nups site-specifically tethered in such mechanically responsive NPC mimics. The elastic deformation of DNA rings, measured by single-particle TEM, reveals the type (attraction or repulsion) and strength of FG-Nup interactions that shape the collective morphology of these unstructured proteins. Analyzing homotypic interactions of five FG-Nup species finds diverse FG-Nup behaviors that can be classified as repulsive/extended (Nsp1), moderately cohesive/extended (Nup62, Nup153, and Nup214), and strongly cohesive/compact (Nup98). Furthermore, we examine how FG-Nups' primary sequence, O-glycosylation, grafting density, and binding to nuclear transport receptors (NTRs) impact their biophysical state. For example, O-GlcNAcylation reduced FG-Nup cohesiveness, switching Nup98 from a collapsed state to more extended conformations. Our work thus elucidates spatially confined Nup-Nup and Nup-NTR interactions within an NPC-like nanopore, suggests a previously underappreciated role of FG-Nups in modulating NPC dilation, and establishes a generalizable method for studying multivalent interactions among disordered proteins.

biophysics↗

bioRxiv2026

Assessing the Reliability of LLM-Generated Phenotype-Genotype Associations Through External Validation

BackgroundPhenotype-genotype associations underpin precision medicine by enabling disease prevention, early diagnosis, risk stratification, therapeutic target discovery, and personalized treatment. However, the rapid growth of scientific evidence has made manual curation of these associations increasingly labor-intensive, time-consuming, and incomplete. Large Language Models (LLMs) offer a potential path to scalable genomic generation and synthesis of this knowledge, but their ability to accurately identify phenotype-genotype associations and the extent to which these outputs are supported by established genomic knowledge bases remain unclear. Materials and MethodsFour LLMs, Claude Sonnet 4.6, DeepSeek V4 Flash, Gemini 3 Flash Preview, and GPT-5.5, were benchmarked on six zero-shot task categories covering forward and reverse phenotype-gene and phenotype-SNP generation. A total of 4,196 associations were identified from curated inputs and evaluated through a multistage external verification pipeline comprising phenotype normalization, ontology mapping, genomic identifier validation against Ensembl, and evidence verification using both the GWAS Catalog and OMIM. Associations were assigned a fused evidence level of strong, moderate, weak, or none. ResultsOverall, 74.19% of generated associations were matched to at least one external genomic knowledge base; 9.15% received strong support and 54.46% moderate support. Phenotype-gene associations were more verifiable than phenotype-SNP associations (strong or moderate: 67.19% vs 54.06%). Among existing associations, Claude Sonnet 4.6 achieved the highest overall strong or moderate rate (69.2%), followed by GPT-5.5 (65.1%), DeepSeek V4 Flash (61.7%), and Gemini 3 Flash Preview (56.9%). ConclusionLLMs can support scalable generation of candidate phenotype-genotype associations. Performance varied substantially by relation type and was lower for SNP-level and rare disease associations, highlighting both the limitations of current genomic resources and the need for rigorous validation pipelines.

bioinformatics↗

bioRxiv2026

Nuclear Cx43 restrains microglial neurotoxicity during brain development

Microglia are essential for sculpting the developing brain, yet the molecular mechanisms that select beneficial overreactive phagocytosis remain incompletely understood. Connexin 43 (Cx43, encoded by GJA1 in humans) is best known as a gap junction and hemichannel protein, although its non-canonical, channel-independent functions are increasingly recognized. We found that Cx43 is highly expressed in microglia during the perinatal period in human and mouse, whereas proportion of full-length multimeric Cx43 unexpectedly localizes to the nucleoplasm. Deletion of microglial Cx43 in mice during development instigates a transient neurotoxic state with microgliosis, upregulated phagocytic and complement pathways, excessive neuronal apoptosis, translating into depressive-like and cognitive deficits in the adulthood. Notably, neither microglia-specific deletion of Cx43 in adulthood nor hemichannel blockade recapitulate these changes, indicating a channel-independent, developmental stage-specific neuroprotective mechanism. Nucleus-targeted Cx43 overexpression suppresses neurotoxic markers and neural apoptosis. Nuclear Cx43 interacts with transcriptional regulators to restrain proinflammatory gene programs, nuclear import of Cx43 is driven by neurogenic niche-derived bFGF, which triggers AKT-mediated phosphorylation of a C-terminal nucleus localization signal (NLS), 14-3-3 binding, and importin-dependent nucleus translocation. These findings reveal a developmentally restricted nuclear Cx43 function that restrains microglial neurotoxicity while promoting microglial physiological functions thus expanding connexin biology to transcriptional co-regulation and pointing to a potential avenue for therapeutic intervention.

neuroscience↗

bioRxiv2026

Identification of environmental factors and growth stages in the prediction of fibre yield and fibre quality traits in rain-grown cotton

ContextUnderstanding how and when environmental conditions influence overall crop performance is crucial for optimising the development of genotypes to a specific breeding target environment. We focused on economically important traits of Australian rain-grown cotton including fibre yield and quality traits, which have not been investigated comprehensively. The aim of the study was to identify relevant environmental factors, and the timing and extent of their impact on rain-grown cotton production. MethodsWe used a data driven approach to analyse the relationship between ten climate related environmental factors across various plant growth stages and eight fibre yield and quality traits, using a large-scale field dataset of 9,283 records collected over 23 years at 4 locations, with 53 unique year-location combinations. We applied eight complementary statistical models including stepwise, penalised and Bayesian linear regression, regression-tree based ensemble methods and deep learning frameworks to (1) select the most essential environmental covariates affecting rain-grown cotton production, and (2) evaluate the predictive performance of these models. ResultsThe environmental impacts on rain-grown cotton production were trait and growth-stage specific. Number of rainy days and solar radiation were identified as the most influential environmental factors for fibre yield traits, vapour pressure deficit at maximum daily temperature was the most influential factor for majority of fibre quality traits. However, each analysed trait was influenced by multiple environmental factors across multiple growth stages (rather than a single factor or a single growth stage). These influential covariates explained a wide range of variation in the traits, accounting for 5.8% to 68.2%. Using the best-fit random forest model, our findings revealed non-linear relationships between key environmental covariates and the traits. ConclusionsEnvironmental factors at different rain-grown cotton growth stages are key determinants for the performance of end-of-season fibre yield and fibre quality parameters. These findings highlight the need to account for environment conditions when developing cotton varieties optimised for rain-grown production systems. Potential strategies are proposed whereby these key environmental factors can be used to increase the rate of genetic gain in rain-grown cotton production systems. ImplicationsThe results of this study will be crucial for future genetic evaluations and analyses of genotype-by-environment interaction effects in rain-grown cotton, which must account for the influence of the environment on plant performance. Furthermore, these methods can be applied to other species to identify critical growth stages and environmental factors which most influence crop performance.

bioinformatics↗

bioRxiv2026

MilliMap: interactive closed-loop analysis for spatial omics

Spatial omics analysis requires iterative interplay between statistical computation and tissue-context interpretation, yet current workflows fragment these steps across disconnected environments. We present MilliMap, an interactive framework that unifies statistical analysis with spatial exploration. By closing the analysis-visualization loop, MilliMap empowers biologists to steer parameters, refine ROIs, and validate findings within a single environment. We demonstrate its utility by delineating complex neuroanatomy and identifying niche-restricted functional states in tumor microenvironments.

bioinformatics↗

bioRxiv2026

Hyperhomocysteinemia does not increase the risk of intracerebral hemorrhage in hypertensive mice

ObjectiveHyperhomocysteinemia (HHcy) affects approximately 75% of the population in China, and there is currently controversy regarding whether HHcy increases the risk of hemorrhagic stroke. This study aims to investigate the effects of high homocysteine (Hcy) levels on cerebral hemorrhage in hypertensive mice by administering homocysteine to them. MethodsMale C57BL/6 mice at 8 months of age were used in the experiment. The study was divided into two groups: the Hcy + AngII + L - NAME group and the AngII + L - NAME group. Magnetic resonance imaging (MRI) was performed when the mice exhibited signs of cerebral hemorrhage.After the hemorrhage, anesthesia was induced to euthanize the animals, and then the brain tissue was fixed. The total rearing period was 18 weeks. The relationship between homocysteine and stroke was described by plotting survival curves. The location and quantity of cerebral hemorrhage were determined through histopathological staining. ResultsThe serum Hcy concentration of mice fed with Hcy for 6 weeks increased to 23.07 mol/L, and the blood pressure ranged from 170 to 180 mmHg. The number of deaths due to cerebral hemorrhage was 10 in both the AngII + L - NAME + Hcy group and the AngII + L - NAME group. The p - value of the survival curves between the two groups was 0.162, indicating no statistically significant difference. ConclusionThe results demonstrated that elevated homocysteine levels did not influence the incidence of intracerebral hemorrhage in hypertensive mice. Hyperhomocysteinemia does not increase the risk of intracerebral hemorrhage in hypertensive mice

neuroscience↗

bioRxiv2026

BRD8 Disruption Unlocks Retrotransposon-Driven Tumor-Intrinsic Immunogenicity via Redistribution of Histone Acetylation in Liver Cancer

Overall response rate for immune checkpoint blockade (ICB) therapy remains limited in advanced hepatocellular carcinoma (HCC). Epigenetic perturbation has been shown to enhance tumor-intrinsic immunogenicity and thus reverse resistance to immunotherapy in multiple cancer types. Here, through domain-focused CRISPR/Cas9 genetic screens targeting chromatin regulators, we identified the bromodomain-containing protein 8 (BRD8) as a novel epigenetic factor that functions to suppress tumor-intrinsic immunity through BRD8/EP400 chromatin remodeling complex in HCC. Depletion of BRD8 potently induces anti-tumor immune responses and sensitizes tumors to ICB therapy in mouse tumor models. Mechanistically, BRD8 knockout leads to partial redistribution of H3K27ac to repetitive elements, activating double-stranded RNA (dsRNA) accumulation and subsequent type I interferon (IFN) response, leading to tumor rejection via remodeling the tumor microenvironment. The first-in-class selective chemical probe DN02 targeting the bromodomain of BRD8 also exhibits immunomodulatory and anti-tumor effects. In line with these findings, low BRD8 expression correlated with enriched interferon signatures, elevated immune cell infiltration, and prolonged survival in HCC patients. Together, this study reveals BRD8 as a selective epigenetic vulnerability for promoting tumor immunogenicity, and its bromodomain as a druggable target to overcome immunotherapy resistance in liver cancer patients. SignificanceThe induction of viral mimicry by epigenetic interference could trigger tumor-intrinsic immune response and enhance immunotherapy efficacy. Here, through domain-focused CRISPR/Cas9 screening, we identify BRD8 complex as a regulator involved in the suppression of repetitive elements by controlling H3K27ac distribution and propose BRD8 as a novel target to enhance anti-tumor immunity.

cancer biology↗

bioRxiv2025

Mechanistic Link Between Glyoxalase 1 Expression and Methylglyoxal-Induced Oncogenic Stress in Prostate Cancer

Prostate cancer (PCa) is the second leading cause of cancer-related death in American men, with African American/Black (AA/B) men experiencing higher incidence and mortality than European American (EA) men. Obesity, which disproportionately affects AA/B men, is linked to increased PCa mortality, potentially through metabolic dysregulation. We hypothesize that methylglyoxal (MG), a reactive byproduct of glucose, lipid, and protein metabolism that is elevated in obesity, contributes to PCa progression. MG forms covalent adducts on DNA, RNA, and protein. We found that MG-adducts are elevated in AA/B men with PCa compared to EA men with PCa, as well as men without PCa. AA/B men with PCa had a higher frequency of SNP rs1049346 in glyoxalase 1 (GLO1), the primary MG detoxification enzyme. PCa cell lines from EA (C4-2) and AA/B (MDA-PCa-2b) men showed differential rs1049346 status, with C4-2 cells heterozygous and MDA-PCa-2b cells homozygous for the variant. This was associated with altered GLO1 expression and activity, with MDA-PCa-2b cells exhibiting reduced GLO1 function and increased MG-adducts compared to C4-2 cells. MG altered DNA repair and RNA processing pathways and induced distinct metabolic shifts in MDA-PCa-2b compared to C4-2 cells, including increased glycolysis and reduced oxidative phosphorylation. Transcriptomic analysis revealed unique MG-induced stress responses including a tenfold higher induction of TXNIP in MDA-PCa-2b vs. C4-2 cells, a gene inversely linked to GLO1 expression and activity. These findings suggest that MG stress may contribute to PCa progression in AA/B men through metabolic reprogramming and impaired detoxification, offering insight into potential precision medicine applications. Statement of SignificancePatients with obesity and diabetes have an elevated risk of cancer mortality. Defining how metabolic alterations contribute to this link is critical to understanding disease progression and identifying strategies to improve outcomes.

cancer biology↗

bioRxiv2025

Androgen receptor contributes to radioresistance through DNA repair and autophagy in AR-positive prostate cancer cells

Androgen receptor (AR) is a critical therapeutic target in prostate cancer (PCa), and androgen blockade is known to act synergistically with radiation therapy. However, the mechanisms through which AR modulates radiation response are not yet fully understood. In this study, we aimed to investigate the role of AR in mediating radioresistance in PCa. AR-positive LNCaP and castration-resistant C4-2 cells exhibited significantly higher radioresistance than AR-negative cells, as determined by apoptosis and cell viability assays. Following irradiation, most LNCaP cells were arrested in the G1 phase, accompanied by rapid p53 activation and p21 induction. Consistently, AR silencing significantly increased radiosensitivity and reduced DNA-PKcs expression and phosphorylation, suggesting that AR enhances DNA repair, likely through non-homologous end joining (NHEJ). At the cellular level, irradiation markedly induced macroautophagy in LNCaP and C4-2 cells, as evidenced by increased LC3B-II accumulation and autophagic vacuole formation, and the upregulation of 11 autophagy-related genes was identified by whole-transcriptomic analysis. To assess their functional relevance, we performed siRNA-mediated knockdown of selected autophagy-related genes and assessed cell viability and Annexin V/PI staining. Notably, BECN1 and LC3 knockdown significantly enhanced radiosensitivity, with BECN1 knockdown showing an effect comparable to that observed with AR silencing. These results suggest that radiation-induced autophagy promotes the survival of AR-positive prostate cancer cells. Moreover, immunohistochemical analysis of ex vivo-irradiated, patient-derived PCa tissues from patients with newly diagnosed high-Gleason score prostate cancer undergoing prostatectomy further demonstrated that radiation-induced autophagy supports the survival of high-grade AR-positive tumor cells. Collectively, our findings reveal that AR promotes radioresistance in PCa by enhancing both DNA repair and autophagy. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/690226v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@3f713corg.highwire.dtl.DTLVardef@1233a11org.highwire.dtl.DTLVardef@1b94e5eorg.highwire.dtl.DTLVardef@c8338c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Plant cells at the organ surface use mechanical cues to activate a specific growth control programme

During morphogenesis of multicellular organs, cells acquire distinct identities that meet specific functional requirements. Epidermal identity is widely considered essential for plant morphogenesis due to the role of the epidermis in both restricting and promoting growth. In the root, epidermal cells are partially covered by a protective root cap, and partially positioned at the organ surface. Here, we propose that epidermal cells at the organ surface have unique requirements for growth control due to high mechanical tension, while covered epidermal cells are mechanically shielded by the root cap. We present in silico and in vivo evidence that plants use surface mechanical cues to activate a cell-type specific growth control programme involving the small GTPase RAB-A5c, allowing them to maintain directional growth at the organ surface. Positional mechanical cues may thus be used to control expression of a sub-population of epidermal genes, linking gene regulation to surface-specific functional requirements.

plant biology↗

bioRxiv2025

TopoLa: A Universal Framework to Enhance Cell Representations for Single-cell and Spatial Omics through Topology-encoded Latent Hyperbolic Geometry

Recent advances in cellular research demonstrate that scRNA-seq characterizes cellular heterogeneity, while spatial transcriptomics reveals the spatial distribution of gene expression. Cell representation is the fundamental issue in the two fields. Here, we propose Topology-encoded Latent Hyperbolic Geometry (TopoLa), a computational framework enhancing cell representations by capturing fine-grained intercellular topological relationships. The framework introduces a new metric, TopoLa distance (TLd), which quantifies the geometric distance between cells within latent hyperbolic space, capturing the networks topological structure more effectively. With this framework, the cell representation can be enhanced considerably by performing convolution on its neighboring cells. Performance evaluation across seven biological tasks, including scRNA-seq data clustering and spatial transcriptomics domain identification, shows that TopoLa significantly improves the performance of several state-of-the-art models. These results underscore the generalizability and robustness of TopoLa, establishing it as a valuable tool for advancing both biological discovery and computational methodologies.

bioinformatics↗

bioRxiv2025

OriGene: A Self-Evolving Virtual Disease Biologist Automating Therapeutic Target Discovery

Here, we present OriGene, a self-evolving multi-agent system that functions as a virtual disease biologist, systematically identifying original and mechanistically grounded therapeutic targets at scale. OriGenes architecture integrates over 600 specialized tools through a Model Context Protocol (MCP), enabling it to reason across diverse data modalities including genomics, protein networks, pharmacology, clinical records and literature evidence, to generate and prioritize target discovery hypotheses. We implemented a strategy combining a knowledge graph-based Tool RAG with an advanced agent selection mechanism to enable dynamic, context-aware tool deployment. Through a self-evolving framework, OriGene continuously integrates human and experimental feedback to iteratively refine its core thinking templates, tool composition, and analytical protocols, thereby enhancing both accuracy and adaptability over time. To comprehensively evaluate its performance, we established TRQA, an original benchmark comprising over 1,900 expert-level question-answer pairs spanning a wide range of diseases and target classes. OriGene consistently outperforms human experts, leading research agents, and state-of-the-art large language models in accuracy, recall, and robustness, particularly under conditions of data sparsity or noise. Critically, OriGene nominated previously underexplored therapeutic targets for liver (GPR160) and colorectal cancer (ARG2), which demonstrated significant anti-tumor activity in patient-derived organoid and tumor fragment models mirroring human clinical exposures. These findings demonstrate OriGenes potential as a scalable and adaptive platform for AI-driven discovery of mechanistically grounded therapeutic targets, offering a new paradigm to accelerate drug development.

bioinformatics↗

bioRxiv2025

FoldBench: An All-atom Benchmark for Biomolecular Structure Prediction

Accurate prediction of biomolecular complex structures is fundamental for understanding biological processes and rational therapeutic design. Recent advances in deep learning methods, particularly all-atom structure prediction models, have significantly expanded their capabilities to include diverse biomolecular entities, such as proteins, nucleic acids, ligands, and ions. However, comprehensive benchmarks covering multiple interaction types and molecular diversity remain scarce, limiting fair and rigorous assessment of model performance and generalizability. To address this gap, we introduce FoldBench, an extensive benchmark dataset consisting of 1,522 biological assemblies categorized into nine distinct prediction tasks. Our evaluations reveal critical performance dependencies, showing that ligand docking accuracy notably diminishes as ligand similarity to the training set decreases, a pattern similarly observed in protein-protein interaction modeling. Furthermore, antibody-antigen predictions remain particularly challenging, with current methods exhibiting failure rates exceeding 50%. Among evaluated models, AlphaFold 3 consistently demonstrates superior accuracy across the majority of tasks. In summary, our results highlight significant advancements yet reveal persistent limitations within the field, providing crucial insights and benchmarks to inform future model development and refinement.

bioinformatics↗

bioRxiv2025

Dual function of DOT1L suppresses tumor intrinsic immunogenicity in hepatocellular carcinoma

Immune checkpoint inhibitor (ICB) therapy for many cancers remains limited in patients overall response rate. Discovery and development of more effective combinatorial approaches is urgent. Here, through CRISPR/Cas9 genetic screens, we identify DOT1L as a versatile epigenetic factor that functions to suppress tumor-intrinsic immunity through a dual mechanism. Depletion of DOT1L induces the expression of transposable elements and subsequent type I interferon (IFN) response, and meanwhile lowers ZEB1 levels to further unleash the expression of immune-related genes. In turn, we demonstrate that DOT1L loss or treatment with the clinical stage inhibitor EPZ-5676 sensitizes tumors to ICB with increased immune infiltration in mice. More importantly, EPZ-5676 treatment alone is sufficient to enhance antitumor immunity in humanized mice. TCGA data analysis reveals an inverse correlation between DOT1L expression and IFN signatures across multiple cancer types. These findings provide a rationale for targeting DOT1L to improve tumor immunogenicity and overcome immunotherapy resistance. One Sentence SummaryCRISPR genetic screens identified DOT1L as a potential suppressor of tumor intrinsic immunogenicity

cell biology↗

bioRxiv2025

Haploinsufficiency of eNOS mitigates beneficial effects of maternal exercise on fetal heart development during pregestational diabetes

BackgroundPregestational diabetes (PGD) increases congenital heart defect (CHD) risk over five-fold. Maternal exercise enhances endothelial nitric oxide synthase (eNOS) activity, benefiting embryos, though its causal role remains unclear. This study investigated eNOSs role in maternal exercise-mediated protection of fetal heart development in a PGD mouse model. MethodsPGD was induced in eNOS+/- or wild-type (WT) female mice via streptozotocin before breeding with WT or eNOS+/- males. Pregnant females had access to a running wheel for voluntary exercise or remained sedentary. Fetuses were collected at embryonic day (E) 18.5 for genotyping and CHD assessment. E12.5 hearts were analyzed for proliferation, apoptosis, oxidative stress, and eNOS protein levels. ResultsMaternal exercise normalized litter size and mortality rates in offspring of diabetic eNOS+/- females but did not reduce CHD incidence in offspring of WT or eNOS+/- females with PGD. CHDs included septal defects, double outlet right ventricle, and valve defects. Exercise increased coronary artery density but not capillary density. Proliferation deficits at E12.5 were restored by exercise, yet oxidative stress remained elevated. Maternal exercise in eNOS+/- dams during PGD did not significantly change eNOS protein levels in both eNOS+/+ and eNOS+/- fetal hearts. Offspring genotype did not impact CHD incidence, cell proliferation, apoptosis or oxidative stress. ConclusionsMaternal exercise does not prevent CHDs in PGD offspring of eNOS+/- mice. Its ability to mitigate PGD-induced oxidative stress is eNOS-dependent and essential for improving heart morphology. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=178 SRC="FIGDIR/small/647329v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@4c9e4forg.highwire.dtl.DTLVardef@2d60fforg.highwire.dtl.DTLVardef@13b2d72org.highwire.dtl.DTLVardef@249a0c_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2025

Social evolution and absence of olfactory function in larval honey bees

Social evolution made larval honey bees dependent on adult colony members for feeding. We therefore predicted they have diminished olfactory capabilities, and based on organismal resource conservation theory, also have downregulated olfactory receptor (OR) gene expression. Behavioral assays demonstrated that larvae cannot find food via olfaction and expressed very low levels of Orco, an essential gene for OR function. By contrast, larvae showed higher expression of Ir25a, an essential gene for multiple forms of sensory perception including gustation. These results suggest larvae rely on taste for feeding. In addition, considering that adult bees use OR-based olfaction extensively, they demonstrate strong developmental regulation of the OR system. Comparative transcriptomics of social and non-social insects further highlight the role of social evolution in shaping this sensory trait.

evolutionary biology↗

bioRxiv2025

Root hair lifespan is antagonistically controlled by autophagy and programmed cell death

Root hairs are tubular tip-growing extensions of root epidermal cells that enhance root surface area for water and nutrient uptake. While mechanisms governing root hair fate, polarity, and tip growth are well understood, the regulation of root hair longevity remains largely unknown. Here, we show that root hair cells employ high levels of autophagy to promote their lifespan. Loss-of-function mutations in the autophagy regulators ATG2, ATG5, or ATG7 induce a premature, cell-autonomous cell death program. This cell death is activated via a gene regulatory network downstream of the NAC transcription factors ANAC046 and ANAC087. Our findings uncover an antagonistic relationship between autophagy and developmentally controlled cell death in root hair lifespan regulation, with potential implications for optimizing plant nutrient and water uptake in crop breeding. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=193 SRC="FIGDIR/small/643910v1_ufig1.gif" ALT="Figure 1"> View larger version (80K): org.highwire.dtl.DTLVardef@1bd570borg.highwire.dtl.DTLVardef@19db5eborg.highwire.dtl.DTLVardef@11279fborg.highwire.dtl.DTLVardef@661c7_HPS_FORMAT_FIGEXP M_FIG C_FIG

plant biology↗