Biology subjects

Li, T.

Publications and source records attributed to Li, T..

At least 91 records · Page 5Linked to original sources

bioRxiv2026

Vagal dopaminergic afferents link interoception to trigeminal pain modulation

The vagus nerve conveys interoceptive information, yet how specific vagal sensory afferents regulate pain remains unclear. Here, we tested whether vagus nerve stimulation (VNS) modulates temporomandibular disorder (TMD)-related pain. In a mouse model of TMD, auricular VNS (aVNS) attenuated temporomandibular joint (TMJ) pain behaviors and suppressed sensitization of trigeminal nociceptors. We identified a subset of vagal sensory afferents with dopaminergic features that was sufficient to mediate these effects, as selective activation of these afferents recapitulated the analgesic actions of aVNS. These findings highlight an underappreciated peripheral interoceptive pathway and provide a mechanistic framework for targeted neuromodulation in chronic craniofacial pain.

neuroscience↗

bioRxiv2026

ProteinSage: From implicit learning to explicit structural constraints for efficient protein language modeling

While protein language models typically rely on sequence-only pretraining objectives, this approach often fails to capture structural regularities and demands large datasets. To address this, we introduce ProteinSage, a pretraining framework that learns protein representations under explicit structural constraints. ProteinSage incorporates structural signals via structure-guided masking and a causal objective designed to model longrange dependencies. This structure-constrained pretraining equips ProteinSage with transferable representations using less data and computation, yet achieves competitive or superior performance across diverse structure-aware and general protein modeling benchmarks. To determine whether these gains stem from genuine structural generalization rather than task-specific fitting, we applied ProteinSage to a structure-driven protein discovery task, focusing on proteins with multi-pass transmembrane helical architectures such as distantly related microbial rhodopsins. The model successfully identified six previously unannotated microbial rhodopsin homologs. Together, our work establishes structure-constrained pretraining as an effective pathway toward data-efficient and structurally faithful protein representation learning.

bioinformatics↗

bioRxiv2026

DeSCENT: Deconvolutional Single-Cell RNA-seq Enhances Transcriptome-based Cancer Survival Analysis

MotivationAccurate cancer survival prediction requires modeling tumor heterogeneity across both population and cell levels. Most cancer survival analyses use tumor transcriptomes only, since cohorts are usually measured with bulk RNA-seq but are rarely recorded with single-cell RNA-seq. This prevents the direct use of cell-level transcriptomes in cancer survival analysis. ResultsTo bridge this gap, we propose using bulk RNA-seq deconvolution algorithms to reconstruct each subjects scRNA-seq profile from their bulk data. Then, by combining both scRNA-seq and bulk RNA-seq together with their survival labels (paired to bulk), we perform multimodal transcriptome-based survival analysis. We built this framework as DeSCENT and evaluated it with common survival models on eight TCGA cancer cohorts. Results showed notable and consistent improvements in C-index over bulk-only models or models using cellular information alone. AvailabilityOur code is available at GitHub: https://github.com/YonghaoZhao722/DeSCENT. Contactzpluo@swjtu.edu.cn; y.he@imperial.ac.uk Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2026

FishMamba-1: A Linear-Complexity Foundation Model for Deciphering Polyploid Cyprinid Genomes

The Cypriniformes order, comprising essential aquaculture species like carps and minnows, presents unique genomic challenges due to complex whole-genome duplication (WGD) events and extensive repetitive elements. Conventional annotation tools and Transformer-based foundation models often struggle to capture long-range dependencies in these expanded genomes due to quadratic computational complexity. Here, we introduce FishMamba-1, the first genomic foundation model tailored for the aquatic clade, built upon the selective state-space model (SSM) architecture. By leveraging Mamba-2s linear scaling efficiency, FishMamba-1 processes context windows of 32,768 base pairs (32k)--significantly surpassing the 4-6k limit of standard DNA Transformers--enabling the modeling of distal regulatory patterns on a single GPU. We curated Cypri-24, a comprehensive dataset comprising 28.8 Gb of high-quality genome assemblies from 24 representative species, to pre-train FishMamba-1 on 15 billion tokens. Subsequent fine-tuning for genome segmentation (FishSegmenter) demonstrates the models capability to annotate gene structures at single-nucleotide resolution with remarkable precision. Evaluation on a held-out test set reveals that FishMamba-1 achieves a precision of 64.6% in exon identification, effectively distinguishing coding regions from the vast non-coding background without relying on RNA-seq evidence. Furthermore, interpretability analysis confirms that the model captures biological syntax such as splice acceptor motifs. FishMamba-1 provides a scalable, open-source framework for decoding the complex genomes of non-model organisms, providing a scalable computational resource to support downstream applications in molecular breeding and ecological monitoring. The complete source code, pre-trained model weights, and datasets are freely available at https://github.com/lu1000001/FishMamba. Additionally, the FishMamba Hub, a web-based inference platform, is accessible at https://huggingface.co/spaces/lu1000001/FishMamba-Hub to facilitate real-time genomic segmentation for the aquatic research community. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/710409v1_ufig1.gif" ALT="Figure 1"> View larger version (71K): org.highwire.dtl.DTLVardef@f5ee02org.highwire.dtl.DTLVardef@1dcfd31org.highwire.dtl.DTLVardef@1729ef8org.highwire.dtl.DTLVardef@22e4f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

Exploring genetic, expression and regulatory patterns of parental alleles in Muscovy duck (Cairina moschata) using haplotype-resolved assemblies

BackgroundAlthough the biological mechanism for heterosis has been debated for a long time, heterosis is widely utilized to increase the global productivity of crops and livestock. Recently, the mechanism has been well characterized in crops and livestock with a male-heterogametic XY system due to genomic assembly advancements, especially the availability of haploid genomes. However, the biological mechanism for heterosis remains unclear in poultry possessing the female-heterogametic ZW system. ResultsHere, we assembled chromosome-level diploid and haploid genomes of the Muscovy duck. We developed an efficient and cost-effective method to assemble 12 variation graph-haploid Muscovy duck genomes from three full-sibling pairs with high quality using short-read Illumina sequences. We further characterized genetic, expression and regulatory patterns of parental alleles at multiple scales. We found that maternal haploid genomes generally had more open chromatin organization and higher accessibility, and higher levels of gene expression, while showing similar DNA methylation levels when compared to paternal haploid genomes. In contrast, the female paternal Z chromosome showed the most, and the male paternal Z chromosome presented more, relaxed chromatin organization and chromatin accessibility, and gene expression compared to the male maternal Z chromosome. Thus, the ZW system largely relies on compensation and balance to regulate gene expression on the sex Z chromosome. Moreover, we identified non-Mendelian regions covering 0.26% of the genome ([~]3.18 Mb). These regions contained lower gene density, GC content, and repeat sequence frequency, but were enriched for DNA motifs bound by transcription factors, likely leading to a compacted chromatin structure and lower chromatin accessibility. ConclusionsOur work here provides a comprehensive profile of parental alleles genetic, expression and regulatory patterns in the female-heterogametic ZW system, and might be useful for the utilization of heterosis in poultry.

genomics↗

bioRxiv2026

Wiz regulates clustered protocadherin genes by restricting CTCF/cohesin loop extrusion in a genomic-distance biased manner

Zinc finger (ZF) proteins (ZFPs) constitute the largest family of transcription factors in mammals; however, their regulatory mechanism remains largely elusive. Here we propose COP (C2H2-ZFP occupancy predictor), a deep learning framework that integrates DNA sequence information with protein primary and secondary features to systematically predict ZFP genomic enrichments. Applying COP to the mouse clustered protocadherin (cPcdh) gene locus, we identified dozens of C2H2-ZFPs potentially involved in CTCF-mediated gene regulation with Wiz having the highest number of 12 ZFs. We confirmed Wiz enrichments at all of the CBS (CTCF-binding site) elements across the Pcdh clusters by Myc-tagging the endogenous Wiz gene. Genetic experiments revealed significant increases of expression levels of the cPcdh genes upon Wiz deletion in both neuronal cells in vitro and in mouse brain in vivo. Finally, integrated ChIP-seq, RNA-seq, and 4C-seq analyses demonstrated that Wiz regulates CTCF/cohesin occupancy and long-range enhancer-promoter contacts in a genomic-distance biased manner. Together, these findings have interesting implications regarding molecular mechanism of C2H2-ZFPs in cPcdh gene regulation.

cell biology↗

bioRxiv2026

Genomic language models improve cross-species gene expression prediction and accurately capture regulatory variant effects in Brachypodium mutant lines

Predicting gene expression from cis-regulatory DNA sequences at the promoter and terminator regions is a central challenge in plant genomics. This capability is also a prerequisite for assessing the effects of regulatory mutations on gene expression. Here, we developed deep learning sequence-to-expression (S2E) models that leverage context-aware sequence embeddings from the PlantCaduceus genomic language model instead of one-hot encoding of sequences, to predict gene expression across 17 plant species. To further improve predictions, we integrated chromatin accessibility data as auxiliary regulatory features. First, we evaluated our models to predict gene expression on unseen gene families via cross-validation, demonstrating our models prediction accuracy across all species outperforms PhytoExpr, the current state-of-the-art (SOTA) S2E model in plants (Pearson R=0.82 vs. R=0.74). We then validated variant effect predictions using an experimental dataset across 796 Brachypodium mutant lines, specifically designed to test predictions at single-base resolution. Our models outperformed SOTA S2E models in predicting between-gene expression differences (regression coefficient {beta}=0.78 vs. {beta}=0.57). Remarkably, they also accurately predicted the effects of single-nucleotide mutations on within-gene expression, while SOTA S2E models showed only weak associations (regression coefficient {beta}=0.38 vs. {beta}=0.08). Our results demonstrated the value of context-aware DNA sequence embeddings for predicting regulatory variant effects in plants. They also reveal a persistent accuracy gap in S2E models when moving from between-gene to allelic variation, a challenge that needs to be addressed in future S2E studies.

bioinformatics↗

bioRxiv2026

Endocardial TIE1 synergizes with TIE2 to regulate the atrial internal muscular network assembly

Atrial cardiomyopathy is characterized by altered atrial structures, yet its underlying genetic basis remains inadequately explored. TIE1 mutations are reported in lymphedema patients, but whether they exhibit cardiac defects alongside lymphatic abnormalities remains unknown. Here, single-cell RNA sequencing showed high Tie1 and Tek expression in atrial endocardial cells. TIE1 deficiency severely disrupted atrial morphogenesis, with only minor ventricular defects. Bulk RNA-seq showed reduced transcripts for endothelial development and cardiac trabeculation in Tie1 mutants. Separate RNA-seq analysis of the atria and ventricles further confirmed these findings, revealing a more pronounced downregulation of trabecular genes, including Tek, in the atria upon Tie1 loss. Endothelial deletion of Tek impaired trabeculation, particularly in atria. Consistently, Tie1 loss combined with a single null Tek allele disrupted both atrial and ventricular trabeculation. Strikingly, atrial morphogenesis defects appeared within 48 hours of induced endothelial Tie1 loss coupled with Tek heterozygous deletion, implying a critical endocardial role in organizing the atrial muscular network. The synergy of TIE1 and TIE2 in remodeling atrial trabeculae was confirmed postnatally, whereas TIE1 insufficiency alone had no effect. Together, TIE1 is differentially required for atrial versus ventricular development, acting synergistically with TIE2 to regulate endocardial cell-coordinated assembly of atrial internal muscular network.

developmental biology↗

bioRxiv2026

Mitotic bookmarking by Prox1 preserves mammalian neuronal lineage identity memory via promoting timely H3K27me3 restoration

Mitosis poses a daunting challenge to transgenerational inheritance of cell identity memory. How neuronal lineage identity is faithfully transmitted across mitosis remains largely unexplored. Here we report that, in mouse hippocampus, the transcription factor Prox1 acts as a mitotic bookmark for safeguarding neuronal lineage identity across cell divisions. Prox1 exhibits mitotic retention in dentate gyrus (DG) neural stem cells and defines DG lineage identity by suppressing the alternative cornu ammonis (CA) identity. Mitotic bookmarking by Prox1 at key bivalent CA identity genes promotes timely and precise restoration of Polycomb repressive complex 2 (PRC2)-mediated H3K27me3 deposition to avoid ectopic expression of CA identity genes and lineage identity crisis. Remarkably, specific mitotic retention-deficient Prox1 conditional knock-in mice produce severe DG developmental defects. Thus, mitotic bookmarking imprints neuronal lineage identity in mouse hippocampus, which is likely to represent a fundamental principle underlying the preservation of lineage identity memory in mammalian brain development.

developmental biology↗

bioRxiv2026

Sampling Mismatch and Correction for Ptychographic Single-Particle Analysis

Ptychographic single-particle analysis (SPA) is a promising technique for high-resolution biological imaging but is still limited by sub-nanometer resolution. In this study, we identified and investigated a critical issue termed sampling mismatch in ptychography that is caused by inaccuracies in the scanning step size and the pixel size of convergent beam electron diffraction (CBED) images. This mismatch induces pixel-size deviations in the reconstructed micrographs and modulates information transfer through a mismatch-induced modulation function (MIMF), which is characterized by phase reversals at specific spatial frequencies of the micrographs. These phase reversals, which vary with the defocus, cause destructive interference when merging micrographs, fundamentally limiting the resolution of SPA. We proposed a correction strategy and demonstrated, on the T. Acidophilum 20S proteasome and apoferritin datasets, that correcting sampling parameters eliminates signal distortions and improves resolution for [~]1.5 [A]. These findings underscore the necessity for the precise control and calibration of the scanning system to achieve high-resolution ptychographic SPA.

biophysics↗

bioRxiv2026

A novel TaNF-YC10-TaNF-YB1-TabHLH95 module coordinates starch biosynthesis in wheat endosperm

Wheat grain weight and flour quality largely depend on starch biosynthesis, yet the mechanisms by which transcription factors coordinate this process remain poorly understood. In this study, using an integrative strategy that combines genome-wide association analysis with yeast two-hybrid library screening, we identify TaNF-YC10, a Nuclear Factor Y transcription factor, as a positive regulator of starch accumulation in the wheat endosperm. Loss of TaNF-YC10 reduces starch content and alters starch granule size distribution, whereas overexpression enhances starch accumulation and increases grain weight. TaNF-YC10 binds and activates core starch biosynthetic-related genes, including AGPL1, GBSS1, YUC11, and NF-YB7, and forms higher-order transcriptional complexes with TaNF-YB1 and TabHLH95 to coordinate multiple regulatory pathways. TaNF-YC10-A1-Hap2 is associated with higher starch content and thousand grain weight and has been selected during wheat breeding in China. Collectively, our findings establish TaNF-YC10 as a pivotal transcriptional hub in starch regulation and highlight its potential as a target for genetic improvement of grain yield in wheat.

plant biology↗

bioRxiv2026

Reproducible Tools and Enhanced Computational Workflows for Batch Effect Evaluation of High-Throughput Data Using BatchQC

Batch effect correction is a common and often necessary step in data analysis to reduce bias due to technical and experimental factors when combining multiple batches of data. The severity of the batch effects dictates the correction strategy; therefore, a careful assessment of each datasets batch effects is necessary. BatchQC is an R package that provides reproducible tools and visualizations for quantitatively and qualitatively addressing batch effects across a broad range of data types. BatchQC integrates with standardized Bioconductor data structures and features an object-oriented design, enabling the application of workflows that can freely evaluate and process data within and outside the package tools. Common batch evaluation methods, along with novel quantitative metrics, help determine the benefits of batch correction for each dataset and enable direct comparisons between methods. Here, we present BatchQC as the first comprehensive batch-correction R package, with independent tools, reproducible workflows, visualization, and novel statistics.

bioinformatics↗

bioRxiv2026

Antibody-Dependent Heterotypic Syncytia Drive COVID-19 Inflammation and Disease Progression

Severe COVID-19 is characterized by profound immune dysregulation and excessive inflammation. Aberrant myeloid responses drive hyperinflammation, yet the precise mechanisms remain elusive. Here, we demonstrate that certain spike antibodies promote the formation of heterotypic syncytia between monocytes/macrophages and virus-infected pneumocytes, leading to excessive inflammatory cytokine release. This antibody-dependent syncytium formation requires Fc{gamma}RI (CD64) and ADAM10, as well as the assembly of the six-helix bundle by the spike S2 subunit. Notably, these syncytia exhibit a stronger proinflammatory signature compared to virus-infected epithelial cells. In vivo, sub-neutralizing antibody concentrations amplified inflammation and exacerbated disease in SARS-CoV-2-infected mice without increasing viral burden. Furthermore, scRNA-seq of postmortem lung tissues from COVID-19 patients implicated the monocyte/macrophage-derived syncytia as a key cellular source of inflammatory cytokines. Together, these findings define a novel mechanism of antibody-dependent enhancement of inflammation that helps explain the hyperinflammatory responses in severe COVID-19 and suggest new therapeutic opportunities targeting this pathway.

immunology↗

bioRxiv2026

Generative AI Guided Design of High-Affinity T cell Receptors

Developing T cell receptors (TCRs) with sufficiently high affinity for tumor antigens (TAs) remains a fundamental challenge in TCR-T immunotherapy. Experimental methods such as affinity maturation and high-throughput screening have enabled the identification of TCRs with enhanced activity. However, their efficiency is often constrained by limited throughput, insufficient coverage, and the generally lower affinities of naturally occurring TCRs toward TAs. To address these challenges, we present TCRPPO2, an integrated AI-driven, in silico affinity maturation framework for peptide-specific TCR optimization. Using reinforcement learning, TCRPPO2 learns mutation policies that iteratively enhance the TCR binding affinity to the target peptide, derived from predictive models trained on carefully curated interaction data. The model is further augmented by a generative AI critic model that discourages implausible designs to ensure the biophysical validity. The designs are further screened by robust post-screening methods that leverage diverse functional annotations and physical prior knowledge. We applied TCRPPO2 to the clinically relevant MART-1 antigen and experimentally validated the designed candidates in Jurkat cell-based functional assays. Among the five engineered TCRs, all of which demonstrated positive cellular responses, three showed significantly increased activities relative to their templates and one showed substantial enhancement. These functional gains were consistent with more favorable interaction energy from structural and physical modeling. Together, our results support a generalizable paradigm for TCR engineering, in which learned mutation policies can efficiently navigate the peptide-specific binding landscape of TCRs and propose biologically enhanced candidates without explicit structural supervision, offering a practical route for early-stage computational TCR optimization for challenging tumor antigens.

immunology↗

bioRxiv2026

Multiplexed high-content imaging uncovers morphological diversity of lymphocyte activation and dysfunction

Single-cell transcriptomic and proteomic technologies enable molecular profiling of immune cells at scale but provide limited access to cellular phenotypes shaped by spatial organisation, organelle architecture and cytoskeletal remodelling. Here we present TGlow, a scalable high-content imaging platform optimized for systematic single-cell phenotyping of primary human lymphocytes. TGlow integrates cyclic immunofluorescence, deep z-stack confocal imaging, and open-source data processing pipelines, including both classical and self-supervised vision transformer-based feature extraction, to jointly quantify cellular morphology, organelle organization, and immune activation states. Applied across over 400,000 primary human T cells spanning CD4+ activation time courses, drug perturbations, CRISPR knockouts and CD8+ T-cell exhaustion, TGlow resolves distinct and reproducible phenotypic states. We uncover dose-dependent and mechanism-specific drug phenotypes, such as defective endoplasmic reticulum polarisation under mycophenolic acid and tofacitinib. We show that mitochondrial clustering reveals activation- and cell-cycle-linked remodelling programs, CRISPR perturbations map gene-specific phenotypes that reposition cells along activation trajectories, and we identify a previously unrecognised collapse of cytoskeletal architecture in exhausted CD8+ T cells. TGlow provides a scalable framework for high-dimensional phenotyping of lymphocyte states advancing functional genomics, perturbation screening and population-level immune profiling by resolving the morphological and functional heterogeneity of lymphocytes and enabling systematic linkage of genetic and pharmacological perturbations to cellular function.

immunology↗

bioRxiv2026

A selective Cullin 3 RING E3 ligase inhibitor attenuates hyperglycemia via dual insulin sensitizing and insulinotropic action

Hyperglycemia is a hallmark of type-2 diabetes and a key pathogenic driver of diabetic complications. Cullin RING E3 ligases (CRLs) are multi-subunit E3 ubiquitin ligases that mediate cellular protein turnover. The activity of CRLs requires cullin neddylation, a post-translational modification that can be pharmacologically targeted with therapeutic potentials. By using hyperinsulinemic-euglycemic clamp analysis, we discover that pan neddylation inhibitor exerts both insulin sensitization effect in liver and muscle and insulinotropic effect in pancreatic {beta} cells. This dual action is mediated by Cullin 3 (Cul3), a member of the 7 canonical cullin family proteins. DI-1859, a selective Cul3 neddylation inhibitor, effectively protects against hyperglycemia in obese mice. DI-1859 enhances insulin signaling by preventing Cul3-mediated insulin receptor substrate degradation in liver and muscle cells. DI-1859 increases insulin secretion in a glucagon-like peptide-1-independent manner in mice and directly potentiates glucose-stimulated insulin secretion in INS-1 832/13 {beta} cells and human islets. Mechanistic studies reveal that DI-1859 does not promote glycolytic flux or bioenergetics function but potentiates glucose-stimulated insulin secretion via mechanisms involving RhoA activation and cytoskeleton remodeling in {beta} cells. This study shows that a single agent targeting Cul3 neddylation simultaneously promotes insulin sensitization and insulin secretion to attenuate hyperglycemia in mice. Article Highlightsa. Pan cullin neddylation inhibitors exhibit potent hypoglycemic effect. b. The target organs and mechanisms underlying the hypoglycemia effect of cullin pan neddylation inhibitors are incompletely understood. c. We found that inhibition of Cul3 leads to a dual insulin sensitization and insulinotropic effect. d. Selective inhibition of Cul3 neddylation is a feasible approach to lower hyperglycemia.

physiology↗

bioRxiv2026

Pan-genome and multi-omics analyses reveal the genomic basis of symbiotic evolution in the mycoheterotrophic medicinal orchid Gastrodia elata

Mycoheterotrophy represents an extreme evolutionary strategy in which plants abandon photosynthesis and become obligately dependent on fungal partners for carbon and nutrients. Gastrodia elata, a medicinal orchid forming long-term symbioses with Armillaria and Mycena, provides a compelling system to investigate the genomic basis of obligate plant-fungus mutualism. Here, we generate a chromosome-level genome assembly (1.09 Gb) of a dark-red G. elata accession and construct a pan-genome from 12 Gastrodia accessions to dissect the evolutionary consequences of mycoheterotrophy. Phylogenomic analyses reveal pervasive hybridization across cultivated germplasm and demonstrate that tuber morphology more accurately reflects intraspecific relationships than stem color, challenging the traditional color-based taxonomy. Comparative genomic analyses reveal a pronounced degeneration of photosynthetic capacity. We detect no intact nuclear-encoded rbcS loci, which would preclude assembly of the Rubisco holoenzyme and thus canonical Calvin-Benson carbon fixation. Notably, a subset of photosynthesis-related genes is retained and transcriptionally active, suggesting their co-option into non-photosynthetic regulatory roles. Despite millions of years of intimate association with fungal partners, we detect no evidence of fungal-derived horizontal gene transfer based on a multi-step phylogenomic validation pipeline, indicating that G. elata-fungus mutualism is sustained through metabolic exchange rather than genetic integration. We further identify the Gastrodia antifungal protein (GAFP) gene family as a key molecular innovation underlying symbiotic homeostasis. The recently derived Class 1 GAFP lineage exhibits distinct domain architecture, tandem expansion, and elevated expression, consistent with enhanced regulation of fungal overgrowth. Finally, we delineate a specialized nutrient-acquisition framework adapted to obligate heterotrophy, in which fungal trehalose hydrolysis supplies hexose carbon via an expanded sugar transporter protein (STP) repertoire, while organic nitrogen is assimilated through amino acid and oligopeptide transporters coupled with urease-mediated conversion, compensating for the loss of nitrate uptake and reduction pathways. Together, these results establish a pan-genomic blueprint for symbiotic adaptation and reductive genome evolution in G. elata.

genomics↗

bioRxiv2026

Pre-myelinating oligodendrocyte ADGRG1 is required for axon ensheathment and CNS myelin formation

Myelin is essential for axonal health and rapid propagation of action potentials. In the central nervous system (CNS), myelination is initiated with axon ensheathment by pre-myelinating oligodendrocytes (preOLs), followed by iterative membrane wrapping and longitudinal extension along the axon. The molecular mechanisms that govern preOL development remain largely unknown. In this study, we identify the adhesion G protein-coupled receptor ADGRG1 (also called GPR56) as a key, evolutionarily conserved regulator of this process. We show that ADGRG1 is highly expressed in preOLs and that its conditional deletion in mouse preOLs leads to simplified preOL morphology and defective axon ensheathment, resulting in CNS hypomyelination. Live imaging in zebrafish demonstrated conserved function of Adgrg1 in axon ensheathment. Mechanistically, we show that ADGRG1 promotes preOL maturation by RhoA activation. Collectively, these findings reveal an ADGRG1-mediated RhoA signaling pathway that governs axon ensheathment and myelin formation.

neuroscience↗