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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

Structural basis for catalytic and inhibitory divergence between archaeal and bacterial ammonia monooxygenases

Ammonia oxidation initiates nitrification and is closely linked to microbial N2O production. Ammonia monooxygenase (AMO) catalyzes the first and rate-limiting step of nitrification and is widespread across evolutionarily distinct ammonia-oxidizing archaea (AOA) and bacteria (AOB). The ocean is the largest biome for AOA and AOB, which have distinct ecological niches and markedly different sensitivities to nitrification inhibitors. However, the lack of archaeal AMO structures and inhibitor-bound AMO complexes has hindered mechanistic understanding of the architectural, catalytic, and inhibitory divergence between these two enzyme systems. Here, we report high-resolution cryo-electron microscopy (cryo-EM) structures of marine archaeal AMO captured in active and inactivated states within its native membrane environment, together with inhibitor-bound structures of estuarine bacterial AMO. Archaeal AMO forms an unexpected cup-shaped homotrimer composed of eight subunits per protomer and exhibits substantial architectural divergence from bacterial AMO. Integrated structural, biochemical, kinetic, and computational analyses reveal distinct periplasmic architectures, copper-center organization, and hydrophobic channels between archaeal and bacterial AMOs for ammonium acquisition, catalysis and inhibitor response. These findings provide a structural and mechanistic framework for understanding how archaeal and bacterial AMOs have diverged to distinct ammonia-oxidizing strategies and inhibitor susceptibilities across environmentally important ammonia oxidizers.

molecular biology↗

bioRxiv2026

The function of human PIF1 in G quadruplex formation and replication stress response at ALT telomeres

Cancers maintain their telomeres through two telomere maintenance mechanisms: 85-90% of cancers rely on telomerase (TEL+), while 10-15% of cancers adopt the Alternative Lengthening of Telomeres (ALT) pathway. The Break-Induced Replication (BIR) pathway plays a critical role in maintaining telomere length in the ALT+ cells. In both yeast and human, PIF1, a 5' to 3' helicase, is required for the robust activity of BIR. However, the extent of human PIF1 (hPIF1) involvement in the ALT pathway remains unknown. Here we showed that hPIF1 can be recruited to damaged telomeres in ALT+ cells. In addition, we demonstrated that inhibition of hPIF1 induced DNA damage and G quadruplex (G4) accumulation at ALT telomeres, leading to a moderate reduction of the mean telomere length. Most interestingly, we demonstrated that inhibition of hPIF1 also attenuates checkpoint activation, BLM recruitment, single-stranded DNA (ssDNA) formation, DNA damage, and G4s at telomeres in the FANCM deficient ALT+ cells. Finally, we showed that inactivation of hPIF1 affects the viability of both ALT+ and TEL+ cancers, suggesting that hPIF1 is a potential drug target for cancer therapy.

molecular biology↗

bioRxiv2026

TheCellVision.org repository: expansion with high-content cell imaging projects on eukaryotic intracellular organization and DUB biology

High-content cell imaging approaches enable the systematic characterization of cellular function through the acquisition of multimodal information from large cohorts of live single cells. Yet, due to their scale and complexity, data acquired via such approaches are often challenging to meaningfully share across laboratories and effectively use for independent studies. Since its inception, the main purpose of TheCellVision.org repository has been to fill this gap, providing the research community with access to large-scale, multimodal single-cell datasets, in a structured, intuitive, and user-friendly way. Here, we report on the third major update of TheCellVision.org, which involves the expansion of the repository with the addition of data from two single-cell phenomics projects; the Intracellular Organization Dynamics project, which quantitatively maps changes in the morphology of 21 major subcellular structures in live yeast cells elicited by the systematic inhibition of essential genes, and the DUB Biology project, which describes changes in the concentration and localization of the budding yeast proteome in mutants of key deubiquitination enzymes (DUBs). With these additions, the repository now hosts six complementary high-content imaging projects which collectively explore the dynamics of intracellular organization and the proteome during changes in cell state and in response to environmental and genetic perturbations.

cell biology↗

bioRxiv2026

An ecological model of masting reproduction matches empirical dynamics

Masting, characterized by highly variable, synchronized, and intermittent seed or fruit production, represents a common reproductive strategy among perennial plants and has profound ecological consequences. Resource provisioning and pollen limitation have long been viewed as central physiological mechanisms underlying this strategy, recent empirical evidence also highlights the role of weather cues in initiating and synchronizing reproductive effort. Drawing on mechanisms that drive periodicity in disease dynamics, this study proposes an alternative proximate mechanism for masting. We develop and analyze a stage-structured population growth model in which developmental delays create population-level cycles, and demographic stochasticity adds individual-level variation; together, yielding masting-like patterns. We compare the behaviour of this novel model with that of the widely used resource budget model and empirically observed patterns of masting in perennial plants. To quantify and compare model outputs and empirical observations, we employ three continuous metrics of masting that capture volatility, synchrony, and periodicity. Our study provides an alternative proximate mechanism for masting. Comparison of this novel mechanism and the established resource-budget model to empirical time-series reveals that both represent realistic yet distinct forms of masting reproduction. Together, these models provide a foundation for further exploration of the conditions under which this reproductive strategy can evolve. Beyond masting, our results highlight the general importance of life-history timing and demographic stochasticity in shaping population ecology.

ecology↗

bioRxiv2026

A reproducibility-audit framework for generalizable versus dataset-specific molecular transition boundaries in Alzheimer's disease

Molecular staging of Alzheimer's disease (AD) increasingly defines transition boundaries along single-cell pseudo-progression trajectories, yet whether such boundaries reproduce across brain regions, cohorts and molecular modalities is rarely tested. We present a permutation-controlled audit that combines nine boundary-detection algorithms with a fixed marker panel and four orthogonal reproducibility axes-algorithmic consensus, region, cohort and modality. On synthetic data with planted ground-truth boundaries the audit reaches 100% sensitivity and 94% specificity, rejecting four distinct artefact classes each by a different axis. Applied to the Seattle Alzheimer's Disease Brain Cell Atlas middle temporal gyrus, it localizes a transition that is robust across algorithms and recovered in most cell types but does not generalize: its leading marker is attenuated or absent in prefrontal cortex, entorhinal cortex and cerebrospinal fluid, and an apparent cross-region conservation of glial metabolic genes proves to be a global-expression offset rather than a shared program. The same audit nonetheless certifies an externally validated marker (astrocytic PTGDS) as reproducible across regions and modalities, showing that it separates generalizable anchors from dataset-specific ones rather than rejecting all signals. We provide this four-axis audit as a transferable, code-available standard to apply before a trajectory boundary is read as a biological stage, in AD and other progressive proteinopathies.

neuroscience↗

bioRxiv2026

From neuropeptide and receptor annotation to ligand-receptor pairing: a sequence- and structure-based framework for mapping the neuropeptide-receptor interactome in Gryllus bimaculatus

Neuropeptides and their G protein-coupled receptors (GPCRs) control much of insect physiology and behaviour, but in Gryllus bimaculatus, an emerging model and edible insect, receptor sequence similarity hinders the mapping of which peptide each GPCR activates. We re-annotated a chromosome-scale genome (BUSCO 95.3%, from 86.7% on insecta_odb12) with comprehensive curation of 48 neuropeptide precursor families (51 loci, including seven not previously identified) and 134 candidate GPCRs (66 rhodopsin-class, 68 secretin-class), providing a near complete neuropeptide-receptor interactome catalogue. We modelled all 15,946 peptide-receptor pairs with AlphaFold3 and Boltz-2 and scored each interface with pLDDT and ipSAE. Ranking these scores, and cross-checking the top candidate for each family against a receptor phylogeny of known ligand specificity, gave a confident, phylogenetically related receptor for 27 of 35 curated receptor groups. These matches confirm the structural scorings with existing deorphanization data and propose receptors for peptides with no prior functional evidence. The annotation, curated peptide and receptor sets, and ranked complexes are available through CricketBase (https://cricket.annotation.jp), a genome browser with a structure viewer of peptide-receptor complexes, providing a resource for G. bimaculatus endocrinology and a workflow to deorphanize GPCRs in other non-model insects.

bioinformatics↗

bioRxiv2026

The Gordian Knot Enhances Ubiquitin Binding in UCH-L1

UCH-L1 is a monomeric deubiquitinating enzyme whose native structure embeds a shallow $5_2$ knot located near the N-terminus, placing the knotted topology in direct proximity to both the substrate-binding pocket and the catalytic site. While our previous work established that N-terminal integrity is critical for catalytic activity, the energetic cost of unknotting and its structural consequences remained unquantified. Here, we combine steered molecular dynamics with an umbrella sampling scheme to generate topologically modified variants of UCH-L1 and, for the first time, reconstruct the free-energy profile of UCH-L1 unknotting. The potential of mean force reveals a steep energetic barrier to knot disruption, consistent with knotting being a late, rate-limiting folding step that is effectively locked in once the native structure is established. Long unbiased MD simulations of fully unknotted variants in both apo and holo states show that knot removal increases local flexibility at the N-terminus without inducing significant global structural destabilization. Binding energy calculations indicate that the unknotted variant binds to ubiquitin less tightly than the wild-type ($\sim$-62~vs~$\sim$-76~kcal/mol), suggesting that topological integrity contributes to substrate affinity. Together, these results show that the $5_2$ knot in UCH-L1 is not a passive structural feature but a functional element that fine-tunes folding kinetics and contributes to substrate binding efficiency.

biophysics↗

bioRxiv2026

Elucidating the functional domain architecture of ArCS1, a biomineralizing myosin chitin synthase: I. The role of lipids

In molluscs, chitin synthases are essential for biologically controlled biomineralization, with some variants possessing a myosin motor domain that may link polymer synthesis to the cytoskeleton. Experimentally, we established a reliable workflow for expressing ArCS1_E22TM in Dictyostelium discoideum and developed effective purification methods to reconstitute ArCS1_E22TM in nanodiscs using MSPs and specific lipid composition. MSP1D1deltaH5 proved optimal for nanodisc formation, yielding homogeneous, monodisperse discs (~8.2 nm). Lipids were refined to POPC:POPE:POPG (3:1:1) with 20% cholesterol, improving nanodisc quality and uniformity as observed by negative-stain EM. The full-length ArCS1 and its subdomains were modeled using AlphaFold3; the myosin motor, glycosyltransferase, and transmembrane regions are well-defined internally but loosely constrained relative to one another, suggesting flexible linking and conformational coupling. Modelling with Mg2+ and oleic acid as ligands and comparative analyses with bacterial cellulose synthase and yeast chitin synthase 1 provided insights into substrate binding and a potential mechanism for chitin polymerization and translocation. This research establishes a standard procedure for comprehensive structural analyses of recombinant molluscan chitin synthase in near-native or biomimetic membranes. This sets the stage for high-resolution cryo-electron microscopy to determine the first experimentally resolved structure of a molluscan chitin synthase and to provide insight into the enzyme's architecture and the regulatory mechanisms of biomineralization.

molecular biology↗

bioRxiv2026

Patterned alginate hydrogel spatially guides collagen fibrillogenesis, viscoelasticity and endothelial cell invasion

Angiogenesis following injury has been shown to be driven by fibrillar proteins of the extracellular matrix (ECM), such as collagen. However, the use of protein-based biomaterials presents some challenges, such as uncontrolled degradation and limited tuneability. We demonstrate how to create patterned interpenetrating networks (IPNs) based on covalently crosslinked alginate and physically crosslinked collagen that provide suitable mechanical properties to support migration of endothelial cells (ECs) in a spatially controlled manner. Low molecular weight alginate is functionalized with norbornene (N) or tetrazine (T), which enables two independent covalent crosslinking methods: UV-mediated and degradable crosslinks with matrix metalloproteinase (MMP) sensitive peptides (Deg) and slower spontaneous N:T non-degradable crosslinks (noDeg). Using photolithography, patterns in degradation, collagen fibrillogenesis, microarchitecture and matrix viscoelasticity are created. The potential of such 3D patterned alginate-collagen (Alg-Col) IPNs to spatially guide EC invasion and proliferation was tested in a microfluidics platform resembling an early healing setting. Only regions combining collagen fibrillogenesis, alginate degradability and viscoelasticity demonstrated EC cell invasion similar to the ones found in vivo following injury. The 3D patterned Alg-Col IPNs are compatible with microfluidics, offer an strategy to widen the applications of protein-based hydrogels and present a versatile platform for tissue engineering and disease modeling.

bioengineering↗

bioRxiv2026

An Information Geometry approach to model topological trajectories and Gene Expression Radius from UMAP geometry.

Understanding the relationship between gene expression dynamics and cellular identity remains a central challenge in single cell biology. Here, we introduce a novel computational and mathematical framework that integrates information geometry, fuzzy topology, and UMAP analysis to model gene expression landscapes derived from single cell RNA sequencing data. We formalize gene expression data as a fuzzy topological space, where interactions between expression points are governed by probabilistic distributions inspired by manifold learning approaches such as UMAP. Within this framework, we define an information geometric structure through a Fisher metric induced by these distributions, enabling the computation of geodesic trajectories that capture cellular differentiation processes. A key contribution of this work is the derivation of analytical conditions, expressed as expression radius formulas, that characterize local neighborhoods in gene expression space. These conditions allow for the identification of genes associated with stem cell states and predictions in transitional cell types in future work. Application of the proposed framework to single cell datasets reveals biologically meaningful gene sets enriched in key regulatory pathways and transcription factors, demonstrating the capacity of our approach to uncover latent structure in complex gene expression data. Our results suggest that integrating differential geometry with statistical learning theory offers a powerful paradigm for modeling genotype and phenotype relationships and cellular state transitions, with potential implications for precision medicine and systems biology.

bioinformatics↗

bioRxiv2026

Dissecting the TMEM132A-EGFR Dependency to Unlock Translational Therapeutic Opportunities for Pan-Solid Tumor

Solid tumors remain refractory to conventional treatments, yet cell surface proteins, by virtue of their extracellular accessibility and critical roles in tumor signaling, represent an attractive class of targets for precision-targeted therapy. Here, we report that TMEM132A is an essential and previously unrecognized pan-cancer target. TMEM132A interacts directly with EGFR and stabilizes its expression, thereby tethering EGFR at the plasma membrane and sustaining constitutive activation of lipid synthesis. Mechanistically, the TMEM132A-EGFR axis promotes lipogenesis by facilitating SREBP nuclear translocation, which in turn upregulates ACLY and ACSS2 expression to drive acetyl-CoA production and downstream lipid biosynthesis, ultimately disrupting lipid droplet homeostasis. To therapeutically target this axis, we developed a nanobody, LFNanoT132A#3, which effectively blocks the TMEM132A-EGFR interaction, abrogates downstream signaling activation, and potently inhibits proliferation across multiple solid tumor types. Notably, LFNanoT132A also exerts robust antitumor activity against H1975 xenografts, a model resistant to first- and second- generation EGFR inhibitors, underscoring its potential to overcome conventional drug resistance. Our findings establish TMEM132A#3 as a critical node in membrane-tethered oncogenic signaling and metabolic rewiring, and position LFNanoT132A#3 as a promising therapeutic candidate for precision cancer therapy.

cancer biology↗

bioRxiv2026

Predicting Cerebral Pericyte Contractility Across Experimental and Physiological Conditions: an in-silico framework

Pericytes (PCs) have recently emerged as critical regulators of cerebral blood flow (CBF) and represent a promising therapeutic target for various cerebrovascular pathologies. Given the complex array of biochemical and mechanical stimuli these cells integrate, a multiscale modeling framework is essential to quantify the impact of selective interventions on pericyte contractile machinery and blood flow restoration. Here, we introduce a computational framework to evaluate capillary pericyte responses across diverse experimental interventions and conditions (ex vivo and in vivo). To capture pharmacological modulation of the contractile apparatus, we developed a homogeneous intracellular model that incorporates key properties of robust control systems. In this framework, vascular tone generation depends strictly on intracellular calcium concentration (Ca2+), which emerges from a complex electrochemical equilibrium established by transmembrane ion (Na+, K+, Cl-) gradients, luminal mechanical forces, and external ligand concentrations. The resulting fraction of phosphorylated cross-bridges generates contractility, which is integrated into the strain energy function governing the constitutive behavior of the vascular wall. The model was successfully validated across four distinct experimental and pharmacological interventions (including pinacidil, high external K+, U46619, and nimodipine), demonstrating close agreement with observed ex vivo and in vivo vascular responses. By establishing a quantitative bridge between pericyte electrophysiology and microvascular mechanics, this framework provides a valuable foundation for evaluating targeted therapeutic strategies to alleviate tissue ischemia in stroke and vascular dementia.

systems biology↗

bioRxiv2026

A transcriptomic and spatial map of serotonin autoreceptor expression in Drosophila

Serotonin is an evolutionarily ancient neurotransmitter that modulates an array of behaviors such as mood, sleep, and appetite across species. Serotonin acts primarily by binding to serotonin receptors, which are expressed in post-synaptic neurons (heteroreceptors) and serotonergic neurons themselves (autoreceptors). Serotonin autoreceptors modulate serotonergic tone, the foundational principles of which have been excellently demonstrated in vertebrate and invertebrate models. However, many aspects of the mechanisms and contexts in which this modulation occurs are still unclear. Drosophila melanogaster is a powerful model organism that can provide unique insights into autoreceptor function by the ability to perform precise spatial and temporal genetic manipulation with structural and functional readouts / behaviors of serotonin systems. However, a systematic characterization of serotonin autoreceptor expression in Drosophila has not been conducted. Here we use single-cell sequencing and genetic labeling to show that all five serotonin receptors are expressed in serotonergic neurons and map their expression at both the larval and adult stages of development. This is the first evidence of 5-HT2A and 5-HT7 expression in serotonergic neurons in any organism. Moreover, the unique combinations of autoreceptor expression in specific neuronal clusters will aid in the development of novel hypotheses for autoreceptor function, and demonstrates the utility of Drosophila as a model organism to study the function of serotonin autoreceptors.

neuroscience↗

bioRxiv2026

Who rests with whom? Sex composition and group demography shape resting associations in free-ranging dogs

Free-ranging dogs frequently rest near conspecifics, but the demographic factors structuring their resting associations remain poorly understood. We quantified dyadic resting associations in 26 free-ranging dog groups in West Bengal, India, observed between 2019 and 2023. Association strength was estimated from scan based resting co-occurrences using the Half-Weight Index. We tested whether dyadic association strength varied with dyad sex composition, dyad life stage composition, group size, and group sex ratio using a generalised additive model for location, scale and shape that accounted for group identity and repeated occurrence of individuals across dyads. Male-male dyads had lower association strengths than female-female dyads, whereas mixed-sex dyads did not differ from female-female dyads. Association strength decreased with increasing group size but increased as the male-to-female ratio within the group increased, while life-stage composition had no detectable effect. Individual level network metrics, including strength, reach, clustering coefficient, affinity, and eigenvector centrality, did not vary with sex or season. Mixed-sex pairs were also frequently represented among the strongest dyadic associations within groups. These findings indicate that resting associations in free-ranging dogs vary with dyad sex composition and group demography. Further opportunity-controlled analyses are required to determine whether the prominence of mixed-sex dyads reflects preferential association rather than group composition alone.

animal behavior and cognition↗

bioRxiv2026

Low-Density Lipoprotein Modulates Plasma Fibrin Network Architecture and Impairs Fibrinolysis

Low-density lipoprotein (LDL) is a major atherogenic lipoprotein, yet its potential to directly modify the fibrin scaffold of blood clots is incompletely understood. Here, we investigated how LDL alters plasma fibrin network architecture and internal fibrinolysis across defined fibrinogen/thrombin conditions. Pooled normal human plasma was supplemented with LDL and clotted with controlled concentrations of fibrinogen and thrombin. Fibrin architecture was visualized by confocal microscopy and quantified by pore-size analysis; clot formation and lysis were monitored turbidimetrically in the presence of tissue plasminogen activator (tPA). Increasing LDL produced a pronounced reduction in fibrin-network pore size across the tested fibrinogen/thrombin conditions. The LDL dependence of pore diameter was well described by a power-law relationship, D_pore=(6.54 +/- 0.11)[LDL]^(-0.12 +/- 0.02) , (R^2 = 0.90), with a significant negative LDL exponent (p = 4 x 10^5). Increasing LDL also prolonged clot lysis time and altered turbidity kinetics. These findings extend epidemiologic and clinical associations between ApoB-containing lipoproteins and hypofibrinolytic clot phenotypes by demonstrating, in a controlled plasma system, that LDL itself can modify fibrin network architecture and fibrinolytic susceptibility. The results support a structure-function role for LDL within the fibrin biomaterial and motivate direct tests of LDL incorporation, protofibril packing, fibrinolytic-protein binding, and single-fiber mechanics.

biophysics↗

bioRxiv2026

DIFFERENTIAL PHOTOSYNTHETIC RESPONSES TO GLUFOSINATE AMMONIUM IN TWO GRASS WEEDS: Lolium multiflorum AND Echinochloa crus-galli.

Background: Weed control is one of the main challenges in agriculture today, particularly due to the increasing occurrence of herbicide-resistant populations. Among the most problematic species are Lolium multiflorum (L.) and Echinochloa crus-galli (L.) Beauv., for which glyphosate-resistant populations have been reported. In this context, glufosinate ammonium has emerged as an alternative for their control; however, its efficacy may vary depending on species and photosynthetic metabolism. Objective: The objective of this study was to evaluate the differential sensitivity of ryegrass (C3) and barnyardgrass (C4) to ammonium glufosinate by analyzing physiological responses associated with leaf senescence and photosystem II activity. Methods: Visual injury, chlorophyll fluorescence, and ammonium accumulation were assessed. Results: Results revealed a differential response between species. Barnyardgrass exhibited earlier symptom onset and a greater reduction in the quantum yield of photosystem II ({Phi}PSII), whereas ryegrass showed a slower senescence process. These differences indicate a higher sensitivity of barnyardgrass to glufosinate ammonium, possibly associated with its C4 photosynthetic metabolism. Conclusions: It is concluded that the effectiveness of glufosinate ammonium depends on the type of photosynthetic metabolism and on the ability of each species to cope with herbicide-induced oxidative stress. This information contributes to optimizing glufosinate ammonium use and to the development of management strategies aimed at delaying the evolution of herbicide resistance.

plant biology↗

bioRxiv2026

Using sequence-to-function models to interpret archaic hominin introgression

Understanding the functional impact of archaic hominin introgression remains challenging due to the poor representation of global introgression in publicly available genomics resources. Sequence-to-function models can predict the effects of any possible variant in the human genome and may fill this gap. Here, we used AlphaGenome to predict the effects of 144,139 introgressed SNPs segregating in present-day individuals of Papuan genetic ancestry. AlphaGenome's chromatin accessibility predictions recapitulate experimentally observed effects, but gene expression performs no better than chance. Predictions correlate more strongly with an independent reporter assay of single-variant activity than with the same variants' effects in live cells, indicating that AlphaGenome captures the regulatory potential of individual variants more reliably. Predictions carry tissue specificity, allowing us to predict specific tissues potentially impacted by introgressed haplotypes. We identify genes, including JAK1 and TAB2, that are associated with haplotypes that contain an excess of variants predicted by AlphaGenome to have large impacts on chromatin accessibility. Finally, we highlight the challenges and limitations associated with using sequence-to-function models for introgressed variant effect prediction, and show that while AlphaGenome's chromatin accessibility predictions can aid in prioritising candidate functional regions, expression predictions and the assignment of variants to target genes remain as open challenges.

genomics↗

bioRxiv2026

Dynamic microtubules drive yolk-cytoplasm segregation in the syncytial Drosophila embryo

Yolk-cytoplasm segregation is among the earliest spatial organization events in the developing embryo of many oviparous animals. The segregation process is intimately linked to early embryonic cleavage and pattern formation, and exhibits a wide range of spatial and temporal diversity. However, the underlying cytoskeletal mechanism remains largely unknown, except for a small number of species. Using quantitative live imaging, we investigated yolk segregation in the Drosophila embryo during the syncytial nuclear cycles 11-14. We find that the yolk vesicles move progressively inward in spatial and temporal coordination with the inward expanding microtubule networks that are nucleated from centrosomes positioned at the cortex, whereas cortical actin meshwork remains spatially restricted. Using the gnu RNAi embryo to decouple nuclear migration and division from cytoskeletal dynamics, we establish causality with targeted pharmacological disruption and find that microtubule dynamics is required for yolk segregation, while depolymerization of actin has no discernible effect. In support of a mechanism of growth-propelled passive displacement, microtubule plus end comets come in apparent contact with yolk vesicles, and injected, inert microbeads are displaced towards the embryo center presumably by the same pushing force. These findings identify microtubule polymerization as a predominant driver of yolk-cytoplasm segregation in Drosophila and suggest that diverse cytoskeletal mechanisms evolved to accomplish this crucial reorganization process

developmental biology↗