Biology subjects

Hu, Y.

Publications and source records attributed to Hu, Y..

At least 253 records · Page 14Linked to original sources

bioRxiv2024

CLCC1 Governs Bilayer Equilibration at the Endoplasmic Reticulum to Maintain Cellular and Systemic Lipid Homeostasis

The intricate orchestration of lipid production, storage, and mobilization is vital for cellular and systemic homeostasis1,2. Dysfunctional plasma lipid control represents the major risk factor for cardio-metabolic diseases, the leading cause of human mortality3,4. Within the cellular landscape, the endoplasmic reticulum (ER) is the central hub of lipid synthesis and secretion, particularly in metabolically active hepatocytes in the liver or enterocytes in the gut5,6. Initially assembled in the ER lumen, lipid-ferrying lipoproteins necessitate the cross-membrane transfer of both neutral and phospho-lipids onto the lumenal apolipoprotein B (APOB), in a poorly-defined process7-10. Here we show that trans-bilayer equilibration of phospholipids, regulated by the ER protein CLCC1, determines lipid partition across the ER membrane and consequently systemic lipid homeostasis. CLCC1 partners with the phospholipid scramblase TMEM41B11,12 to recognize imbalanced bilayers and promote lipid scrambling, thereby licensing lipoprotein biogenesis and the subsequent bulk lipid transport. Strikingly, loss of CLCC1 or TMEM41B leads to the emergence of giant lumenal lipid droplets enclosed by extensively imbalanced ER bilayers, and consequently drastically accelerated pathogenesis of metabolic-dysfunction-associated liver steatohepatitis (MASH). The above results establish phospholipid scrambling at the ER as the lynchpin to maintain a dynamic equilibrium. Considering the requirement of trans-bilayer phospholipid equilibration in numerous biological processes, ranging from catabolic autophagy to viral infection13-16, our study may enable further elucidation of a previously under-appreciated homeostatic control mechanism intrinsic to the ER function in lipid biogenesis and distribution.

cell biology↗

bioRxiv2024

Ephrin Forward Signaling Controls Interspecies Cell Competition in Pluripotent Stem Cells

In the animal kingdom, evolutionarily conserved mechanisms known as cell competition eliminate unfit cells during development. Interestingly, cell competition also leads to apoptosis of donor cells upon direct contact with host cells from a different species during interspecies chimera formation. The mechanisms underlying how host animal cells recognize and transmit cell death signals to adjacent xenogeneic human cells remain incompletely understood. In this study, we developed an interspecies cell contact reporter system to dissect the mechanisms underlying competitive interactions between mouse and human pluripotent stem cells (PSCs). Through single-cell RNA-seq analyses, we discovered that Ephrin A ligands in mouse cells play a crucial role in signaling cell death to adjacent human cells that express EPHA receptors during interspecies PSC co-culture. We also demonstrated that blocking the Ephrin A-EPHA receptor interaction pharmacologically, and inhibiting Ephrin forward signaling genetically in the mouse cells, enhances the survival of human PSCs and promotes chimera formation both in vitro and in vivo. Our findings elucidate key mechanisms of interspecies PSC competition during early embryogenesis and open new avenues for generating humanized tissues or organs in animals, potentially revolutionizing regenerative medicine.

cell biology↗

bioRxiv2024

Genome sequencing of 'Fuji' apple clonal varieties reveals evolutionary history and genetic mechanism of the spur-type morphology

Somatic variations arising during asexual reproduction can lead to the emergence of bud sports exhibiting advantageous traits, forming the basis for bud sport breeding in perennial plants. Here, we report a near-complete, fully phased genome assembly of Fuji apple, enabling comprehensive identification of somatic variants across 74 clonally propagated Fuji varieties. Phylogenetic analysis of Fuji sport varieties indicates that the emergence of spur-type and early maturation traits results from multiple independent formation events. A number of putative functional somatic variants are identified, including one spur-type specific deletion located in the promoter of the TCP transcription factor gene MdTCP11. DNA methylation level of the deletion-associated miniature inverted-repeat transposable element is lower in the spur-type varieties compared to the standard-type varieties, while the expression of MdTCP11 is significantly higher. Overexpression of MdTCP11 in apple decreases the plant height, highlighting its important role in the development of spur-type apple varieties. This study sheds light on the 80-year cloning history of Fuji and provides valuable candidate causative mutations for apple breeding.

plant biology↗

bioRxiv2024

Stable, chronic in-vivo recordings from a fully wireless subdural-contained 65,536-electrode brain-computer interface device

Minimally invasive, high-bandwidth brain-computer-interface (BCI) devices can revolutionize human applications. With orders-of-magnitude improvements in volumetric efficiency over other BCI technologies, we developed a 50-m-thick, mechanically flexible micro-electrocorticography (ECoG) BCI, integrating a 256x256 array of electrodes, signal processing, data telemetry, and wireless powering on a single complementary metal-oxide-semiconductor (CMOS) substrate containing 65,536 recording channels, from which we can simultaneously record a selectable subset of up to 1024 channels at a given time. Fully implanted below the dura, our chip is wirelessly powered, communicating bi-directionally with an external relay station outside the body. We demonstrated chronic, reliable recordings for up to two weeks in pigs and up to two months in behaving non-human primates from somatosensory, motor, and visual cortices, decoding brain signals at high spatiotemporal resolution.

neuroscience↗

bioRxiv2024

Neural Processing of Naturalistic Audiovisual Events in Space and Time

Our brain seamlessly integrates distinct sensory information to form a coherent percept. However, when real-world audiovisual events are perceived, the specific brain regions and timings for processing different levels of information remain less investigated. To address that, we curated naturalistic videos and recorded fMRI and EEG data when participants viewed videos with accompanying sounds. Our findings reveal early asymmetrical cross-modal interaction, with acoustic information represented in both early visual and auditory regions, while visual information only identified in visual cortices. The visual and auditory features were processed with similar onset but different temporal dynamics. High-level categorical and semantic information emerged in multi-modal association areas later in time, indicating late cross-modal integration and its distinct role in converging conceptual information. Comparing neural representations to a two-branch deep neural network model highlighted the necessity of early fusion to build a biologically plausible model of audiovisual perception. With EEG-fMRI fusion, we provided a spatiotemporally resolved account of neural activity during the processing of naturalistic audiovisual stimuli.

neuroscience↗

bioRxiv2024

Post-Transcriptional Modular Synthetic Receptors

Inspired by the power of transcriptional synthetic receptors and hoping to complement them to expand the toolbox for cell engineering, we establish LIDAR (Ligand-Induced Dimerization Activating RNA editing), a modular post-transcriptional synthetic receptor platform that harnesses RNA editing by ADAR. LIDAR is compatible with various receptor architectures in different cellular contexts, and enables the sensing of diverse ligands and the production of functional outputs. Furthermore, LIDAR can sense orthogonal signals in the same cell and produce synthetic spatial patterns, potentially enabling the programming of complex multicellular behaviors. Finally, LIDAR is compatible with compact encoding and can be delivered as synthetic mRNA. Thus, LIDAR expands the family of synthetic receptors, holding the promise to empower basic research and therapeutic applications.

synthetic biology↗

bioRxiv2024

Identification of high sugar diet-induced dysregulated metabolic pathways in muscle using tissue-specific metabolic models in Drosophila

Individual tissues perform highly specialized metabolic functions to maintain whole-body metabolic homeostasis. Although Drosophila serves as a powerful model for studying human metabolic diseases, modeling tissue-specific metabolism has been limited in this organism. To address this gap, we reconstruct 32 tissue-specific genome-scale metabolic models (GEMs) by integrating a curated Drosophila metabolic network with pseudo-bulk single-nuclei transcriptomics data, revealing distinct metabolic network structures and subsystem coverage across tissues. We validate enriched pathways identified through tissue-specific GEMs, particularly in muscle and fat body, using metabolomics and pathway analysis. Moreover, to demonstrate the utility in disease modeling, we apply muscle-GEM to investigate high sugar diet (HSD)-induced metabolic dysregulation. Constraint-based semi-quantitative flux and sensitivity analyses identify altered NAD(H)-dependent reactions and distributed control of glycolytic flux, including GAPDH. This prediction is further validated through in vivo 13C-glucose isotope tracing study. Notably, decreased glycolytic flux, including GAPDH, is linked to increased redox modifications. Finally, our pathway-level flux analyses identify dysregulation in fructose metabolism. Together, this work establishes a quantitative framework for tissue-specific metabolic modeling in Drosophila, demonstrating its utility for identifying dysregulated reactions and pathways in muscle in response to HSD.

systems biology↗

bioRxiv2024

Influences of single mutation and retinal binding on the THz absorption spectra of CRABP-II based rhodopsin mimics

The collective vibration of many biomolecules such as the skeleton vibration, dipole rotation and conformational bending falls in the terahertz (THz) frequency domain. Terahertz time-domain spectroscopy (THZ-TDS), which is very sensitive to the conformational changes, can be used to characterize the collective vibration of biomolecules. In this study, we investigated the low-frequency THz absorption spectra of two rhodopsin mimics using transmission THz-TDS. Using the normal model analysis (NMA), we successfully modelled the experimental terahertz absorption curve and attributed a unique collective motion pattern to each distinctive terahertz absorption frequency. By comparing the terahertz absorption spectra between without and with retinal, we show that the retinal binding can significantly alters the terahertz absorption spectra as well as the vibration modes. Furthermore, by comparing the terahertz absorption spectra between the two mutants, we observed that the single mutation can significantly change the influence of retinal binding on the terahertz absorption spectrum.

biophysics↗

bioRxiv2024

Combining transformer and 3DCNN models to achieve co-design of structures and sequences of antibodies in a diffusional manner

Antibody drugs are among the fastest growing therapeutic modalities in modern drug research and development. Due to the huge search space of antibody sequences, the traditional experimental screening method cannot fully meet the needs of antibody discover. More and more rational design methods have been proposed to improve the success rate of antibody drugs. In recent years, artificial intelligence methods have increasingly become an important means of rational design. We have proposed an algorithm for antibody design, called AlphaPanda (AlphaFold2 inspired Protein-specific antibody design in a diffusional manner). The algorithm mainly combines the transformer model, the 3DCNN model and the diffusion generative model, use the transformer model to capture the global information and uses the 3DCNN model to capture the local structural characteristics of the antibody-antigen complexes, and then uses the diffusion model to generate sequences and structures of antibodies. The 3DCNN model can capture pairwise interactions in antibody-antigen complex, as well as non-pairwise interactions in antibody-antigen complex, and it requires less training sample data, while avoiding the defects of the generation progress by the autoregressive model and by the self-consistent iterative model. Diffusion generative model can generate sequence and structure effectively and with high quality. By combining 3DCNN method and diffusion model method, we have achieved the integration of 3DCNN model to the protein design with flexible main chains. By utilizing the advantages of these aspects, a good performance has been achieved by the AlphaPanda algorithm. The algorithm we propose can not only be applied to antibody design, but also be more widely applied to various fields of other protein design. The source code can be get from github (https://github.com/YueHuLab/AlphaPanda).

bioinformatics↗

bioRxiv2024

Biochemical and structural insights into a 5' to 3' RNA ligase reveal a potential role in tRNA ligation

ATP-grasp superfamily enzymes contain a hand-like ATP-binding fold and catalyze a variety of reactions using a similar catalytic mechanism. More than 30 protein families are categorized in this superfamily, and they are involved in a plethora of cellular processes and human diseases. Here we identify C12orf29 as an atypical ATP-grasp enzyme that ligates RNA. Human C12orf29 and its homologs auto-adenylate on an active site Lys residue as part of a reaction intermediate that specifically ligates RNA halves containing a 5-phosphate and a 3-hydroxyl. C12orf29 binds tRNA in cells and can ligate tRNA within the anticodon loop in vitro. Genetic depletion of c12orf29 in female mice alters global tRNA levels in brain. Furthermore, crystal structures of a C12orf29 homolog from Yasminevirus bound to nucleotides reveal a minimal and atypical RNA ligase fold with a unique active site architecture that participates in catalysis. Collectively, our results identify C12orf29 as an RNA ligase and suggest its involvement in tRNA biology. Significance StatementATP-grasp enzymes share an atypical ATP-binding fold and catalyze a diverse set of reactions involved in many essential cellular processes. We identified C12orf29 as an atypical ATP-grasp enzyme. Our biochemical and structural characterizations reveal this enzyme to be a 5 to 3 RNA ligase, structurally and functionally similar to the phage T4 RNA ligase. C12orf29 can ligate tRNAs in vitro and C12orf29 knockout female mice have altered tRNA levels in brain. We also report structures of C12orf29, which have revealed critical insights into the mode of ATP binding and catalysis. Our work suggests that C12orf29 may be a new player in the regulation of tRNAs.

biochemistry↗

bioRxiv2024

Deciphering the Immune Subtypes and Signature Genes: A Novel Approach Towards Diagnosing and Prognosticating Severe Asthma through Interpretable Machine Learning.

Asthma, a pervasive pulmonary disorder, affects countless individuals globally. Characterized by chronic inflammation of the bronchial passages, its symptoms include cough, wheezing, dyspnea, and chest tightness. While many manage their symptoms through pharmaceutical interventions and self-care, a significant subset grapples with severe asthma, posing therapeutic challenges. This study delves into the intricate etiology of asthma, emphasizing the pivotal roles of immune cells such as T cells, eosinophils, and mast cells in its pathogenesis. The recent emergence of monoclonal antibodies, including Mepolizumab, Reslizumab, and Benralizumab, offers therapeutic promise, yet their efficacy varies due to the heterogeneous nature of asthma. Recognizing the potential of personalized medicine, this research underscores the need for a comprehensive understanding of asthmas immunological diversity. We employ ssGSEA and LASSO algorithms to identify differentially expressed immune cells and utilize machine learning techniques, including XGBoost and Random Forest, to predict severe asthma outcomes and identify key genes associated with immune cells. Using a murine asthma model and an online database, we aim to elucidate distinct immune-centric asthma subtypes. This study seeks to provide novel insights into the diagnosis and classification of severe asthma through a transcriptomic lens.

bioinformatics↗

bioRxiv2024

GPnotebook: A pan-cancer glycoproteomic database and toolkit for analysis of protein glycosylation changes associated with cancer phenotypes

Protein glycosylation plays a pivotal role in various biological processes, and the analysis of intact glycopeptides (IGPs) has emerged as a powerful approach for characterizing alterations in protein glycosylation associated with diseases. Despite the critical insights gained from IGP analysis, there is an evident scarcity of intact glycopeptide database and specialized tools for a comprehensive glycoproteomic examination. In response to this deficiency, we have developed a Python package, "GPnotebook," which consolidates the intact glycopeptides identified from different cancer types by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and includes analytical tools for an in-depth characterization of glycopeptides. GPnotebook facilitates an array of functions including statistical profiling, differential expression analysis, glycosylation subtype categorization, investigation of glycosylation-phosphorylation interplay, survival analysis, and glycosylation enzyme assessment. We have deployed GPnotebook in a study of Pancreatic Ductal Adenocarcinoma (PDAC), thereby validating its application and demonstrating its capabilities. Our findings suggest that IGPs hold significant promise as cancer-specific changes and subtype differentiation. Consequently, GPnotebook stands out as a valuable resource for cancer researchers delving into the nuances of protein glycosylation and its correlation with cancer phenotypes. HILIGHTSO_LISimplified and unified access to pan-cancer glycoproteomic database including 90,795 intact glycopeptides. C_LIO_LIDeveloped a glycoproteomic analysis toolkit for systematic glycoproteomic data analysis C_LIO_LIApplied the toolkit for identification of glycosylation changes associated with cancer phenotypes in pancreatic cancer. C_LI

bioinformatics↗

bioRxiv2024

Natural variation in salt-induced changes in root:shoot ratio reveals SR3G as a negative regulator of root suberization and salt resilience in Arabidopsis

Soil salinity is one of the major threats to agricultural productivity worldwide. Salt stress exposure alters root and shoot growth rates, thereby affecting overall plant performance. While past studies have extensively documented the effect of salt stress on root elongation and shoot development separately, here we take an innovative approach by examining the coordination of root and shoot growth under salt stress conditions. Utilizing a newly developed tool for quantifying the root:shoot ratio in agar-grown Arabidopsis seedlings, we found that salt stress results in a loss of coordination between root and shoot growth rates. We identify a specific gene cluster encoding domain-of-unknown-function 247 (DUF247), and characterize one of these genes as Salt Root:shoot Ratio Regulator Gene (SR3G). Further analysis elucidates the role of SR3G as a negative regulator of salt stress tolerance, revealing its function in regulating shoot growth, root suberization, and sodium accumulation. We further characterize that SR3G expression is modulated by WRKY75 transcription factor, known as a positive regulator of salt stress tolerance. Finally, we show that the salt stress sensitivity of wrky75 mutant is completely diminished when it is combined with sr3g mutation. Together, our results demonstrate that utilizing root:shoot ratio as an architectural feature leads to the discovery of new stress resilience gene. The studys innovative approach and findings not only contribute to our understanding of plant stress tolerance mechanisms but also open new avenues for genetic and agronomic strategies to enhance crop environmental resilience.

plant biology↗

bioRxiv2024

Leveraging cross-source heterogeneity to improve the performance of bulk gene expression deconvolution

We introduce CSsingle, a novel method that enhances the decomposition of bulk and spatial transcriptomic (ST) data by addressing key challenges in cellular heterogeneity. CSsingle applies cell size correction using ERCC spike-in controls, enabling it to account for variations in RNA content between cell types and achieve accurate bulk data deconvolution. In addition, it enables fine-scale analysis for ST data, advancing our understanding of tissue architecture and cellular interactions, particularly in complex microenvironments. We provide a unified tool for integrating bulk and ST with scRNA-seq data, advancing the study of complex biological systems and disease processes. The benchmark results demonstrate that CSsingle outperforms existing methods in accuracy and robustness. Validation using more than 700 normal and diseased samples from gastroesophageal tissue reveals the predominant presence of mosaic columnar cells (MCCs), which exhibit a gastric and intestinal mosaic phenotype in Barretts esophagus and esophageal adenocarcinoma (EAC), in contrast to their very low detectable levels in esophageal squamous cell carcinoma and normal gastroesophageal tissue. We revealed a dynamic relationship between MCCs and squamous cells during immune checkpoint inhibitors (ICI)-based treatment in EAC patients, suggesting MCC expression signatures as predictive and prognostic markers of immunochemotherapy outcomes. Our findings reveal the critical role of MCC in the treatment of EAC and its potential as a biomarker to predict outcomes of immunochemotherapy, providing insight into tumor epithelial plasticity to guide personalized immunotherapeutic strategies.

bioinformatics↗

bioRxiv2024

MGPfactXMBD: A Model-Based Factorization Method for scRNA Data Unveils Bifurcating Transcriptional Modules Underlying Cell Fate Determination

Manifold-learning is particularly useful to resolve the complex cellular state space from single-cell RNA sequences. While current manifold-learning methods provide insights into cell fate by inferring graph-based trajectory at cell level, challenges remain to retrieve interpretable biology underlying the diverse cellular states. Here, we described MGPfactXMBD, a model-based manifold-learning framework and capable to factorize complex development trajectories into independent bifurcation processes of gene sets, and thus enables trajectory inference based on relevant features. MGPfactXMBD offers more nuanced understanding of the biological processes underlying cellular trajectories with potential determinants. When bench-tested across 239 datasets, MGPfactXMBD showed advantages in major quantity-control metrics, such as branch division accuracy and trajectory topology, outperforming most established methods. In real datasets, MGPfactXMBD recovered the critical pathways and cell types in microglia development with experimentally valid regulons and markers. Furthermore, MGPfactXMBD discovered evolutionary trajectories of tumor-associated CD8+ T cells and yielded new subtypes of CD8+ T cells with gene expression signatures significantly predictive of the responses to immune checkpoint inhibitor in independent cohorts. In summary, MGPfactXMBD offers a manifold-learning framework in scRNA-seq data which enables feature selection for specific biological processes and contributing to advance our understanding of biological determination of cell fate.

bioinformatics↗

bioRxiv2024

A peptide targeting outer membrane protein A of Acinetobacter baumannii exhibits antibacterial activity by reducing bacterial pathogenicity

The World Health Organization has classified multidrug-resistant (MDR) Acinetobacter baumannii as a significant threat to human health, necessitating the urgent discovery of new antibacterial drugs to combat bacterial resistance. Outer membrane protein A of A. baumannii (AbOmpA) is an outer membrane-anchored {beta}-barrel-shaped pore protein that plays a critical role in bacterial adhesion, invasion, and biofilm formation. Therefore, AbOmpA is considered a key virulence factor of A. baumannii. Herein, we screened three phage display peptide libraries targeting AbOmpA and identified several peptides. Among them, P92 (amino acid sequence: QMGFMTSPKHSV) exhibited the highest binding affinity with AbOmpA, with a KD value of 7.84 nM. In vitro studies demonstrated that while P92 did not directly inhibit bacterial growth, it significantly reduced the invasion and adhesion capabilities of multiple clinical isolates of MDR A. baumannii and concentration-dependently inhibited biofilm formation by acting on OmpA. Furthermore, the polymerase chain reaction results confirmed a significant positive correlation between the antibacterial effect of P92 and OmpA expression levels. Encouragingly, P92 also displayed remarkable therapeutic efficacy against A. baumannii infection in various models, including an in vitro cell infection model, a mouse skin infection model, and a mouse sepsis model. These results highlight P92 as a novel and highly effective antimicrobial molecule specifically targeting the virulence factor AbOmpA. IMPORTANCEDifferent from the action mechanism of traditional antibiotics, antibacterial strategies aimed at targeting bacterial virulence factors can effectively reduce bacterial pathogenicity without compromising bacterial growth and reproduction, making it a crucial research direction in combating bacterial drug resistance. Despite the influence of various factors on the expression of bacterial virulence factors, specific and consistently expressed virulence factors in certain bacteria can still serve as viable targets for drug development. In this study, we focused on outer membrane protein A, a key virulence factor of A. baumannii, and successfully identified a highly specific antimicrobial peptide P92 through screening processes. Furthermore, our findings demonstrate its efficacy in various dynamic models for anti-infective therapy. These results validate that antibacterial agents targeting bacterial virulence factors possess relatively or absolutely narrow spectrum antimicrobial properties, enabling precise antibacterial action without inducing bacterial resistance.

microbiology↗

bioRxiv2024

Optineurin-facilitated axonal mitochondria delivery promotes neuroprotection and axon regeneration

Optineurin (OPTN) mutations are linked to amyotrophic lateral sclerosis (ALS) and normal tension glaucoma (NTG), but a relevant animal model is lacking, and the molecular mechanisms underlying neurodegeneration are unknown. We found that OPTN C-terminus truncation (OPTN{Delta}C) causes late-onset neurodegeneration of retinal ganglion cells (RGCs), optic nerve (ON), and spinal cord motor neurons, preceded by a striking decrease of axonal mitochondria. Surprisingly, we discover that OPTN directly interacts with both microtubules and the mitochondrial transport complex TRAK1/KIF5B, stabilizing them for proper anterograde axonal mitochondrial transport, in a C- terminus dependent manner. Encouragingly, overexpressing OPTN/TRAK1/KIF5B reverses not only OPTN truncation-induced, but also ocular hypertension-induced neurodegeneration, and promotes striking ON regeneration. Therefore, in addition to generating new animal models for NTG and ALS, our results establish OPTN as a novel facilitator of the microtubule-dependent mitochondrial transport necessary for adequate axonal mitochondria delivery, and its loss as the likely molecular mechanism of neurodegeneration.

neuroscience↗

bioRxiv2024

Growth patterns of caudal fin rays are informed by both external signals from the regenerating organ and remembered identity autonomous to the local tissue

Regenerating tissues must remember or interpret their spatial position, using this information to restore original size and patterning. The external skeleton of the zebrafish caudal fin is composed of 18 rays; after any portion of the fin is amputated, position-dependent regenerative growth restores each ray to its original length. We tested for transcriptional differences during regeneration of proximal versus distal tissues and identified 489 genes that differed in proximodistal expression. Thyroid hormone directs multiple aspects of ray patterning along the proximodistal axis, and we identified 364 transcripts showing a proximodistal expression pattern that was dependent on thyroid hormone context. To test what aspects of ray positional identity are directed by extrinsic cues versus remembered identity autonomous to the tissue itself, we transplanted distal portions of rays to proximal environments and evaluated regeneration within the new location. While neighboring proximal tissue showed robust expression of scpp7, a transcript with thyroid-regulated proximal enrichment, regenerating rays originating from transplanted distal tissue showed reduced (distal-like) expression during outgrowth. These distal-to-proximal transplants regenerated far beyond the length of the graft itself, indicating that cues from the proximal environment promoted additional growth. Nonetheless, these transplants initially regenerated at a much slower rate compared to controls, suggesting memory of distal identity was retained by the transplanted tissue. This early growth retardation caused rays that originated from transplants to become noticeably shorter than their native neighboring rays. While several aspects of fin ray morphology (bifurcation, segment length) were found to be determined by the environment, regeneration speed and ray length are remembered autonomously by tissues, persisting across multiple rounds of amputation and regeneration. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/586899v2_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@1760f4aorg.highwire.dtl.DTLVardef@1e5d990org.highwire.dtl.DTLVardef@12ea7f8org.highwire.dtl.DTLVardef@1596ab_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗