Biology subjects

Zhu, Q.

Publications and source records attributed to Zhu, Q..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

An Integrated Single-Cell and Epigenomic Resource for Comparative Analysis of the Basal Ganglia

The basal ganglia regulate motor, cognitive, and affective behaviors, and their dysfunction underlies diverse neurological and psychiatric disorders. Comprehensive, accessible multi-omics resources are needed to understand the regulatory mechanisms governing basal ganglia cell types. Here we present an open, interactive web-based platform for exploring single-cell multi-omics datasets from basal ganglia, generated using 10X Multiome, snm3C-seq, and Paired-Tag technologies from the BICAN (NIH BRAIN Initiative Cell Atlas Network) consortium. The platform is available at https://basalganglia.epigenomes.net/ and enables integrated visualization of gene expression, chromatin accessibility, DNA methylation, histone modifications, and chromatin conformation across cell types and human, macaque, marmoset, and mouse species, with direct genome browser support and comparative epigenomic functionality. Representative analyses demonstrate cell-type-specific regulatory landscapes, conserved and species-specific regulatory elements, and links between epigenomic regulation and transcription. This resource provides a scalable, community-oriented foundation for advancing basal ganglia biology and interpreting regulatory mechanisms relevant to brain function and disease. HighlightsO_LIIntegrated single-cell epigenomic resource for basal ganglia C_LIO_LIInteractive genome browser enables multi-omics and cross-species exploration C_LIO_LIReveals cell-type-specific and species-specific regulatory landscapes C_LIO_LISupports community access to complex brain epigenomic datasets C_LI

genomics↗

bioRxiv2026

A Single-Cell and Spatial 3D Multi-omic Atlas of Developing Human Basal Ganglia and Inhibitory Neurons

The human basal ganglia (BG), subcortical nuclei fundamental to motor regulation and cognitive modulation, is constructed from neurons produced during gestation in the adjacent ganglionic eminences (GEs). GEs are transient structures in the ventral prenatal brain that also generate GABAergic inhibitory neurons which migrate to destinations in the BG, cortex and other destinations. This study aims to elucidate the epigenomic and 3D-genomic dynamics involved in the specification and maturation of GEs and GE-derived neurons, using single-nucleus methyl-3C sequencing (snm3C-seq), highly-multiplexed spatial transcriptomics, and chromatin+RNA single-molecule imaging. Our multi-modal data support a heterogeneous temporal progression across GE subregions, with the lateral GE (LGE) showing declining neurogenic activity in mid-gestation and caudal GE (CGE) exhibiting ongoing developmental progression through infancy. We identified regulatory programs that specify subtypes of BG principal cells, medium spiny neurons (MSN), via synchronized maturation of the 3D-epigenome. In infant brains, we found a transient short-range enriched (SE) chromatin conformation during the transition between oligodendrocyte progenitors (OPCs) and oligodendrocytes (ODCs), and a temporary shift toward Long-range Enriched (LE) chromatin conformation in projection neurons, extending previous works showing the differentiation of neurons and glial cells is associated with permanent SE and LE conformation, respectively. Lastly, we found that gene regulatory regions active in MSNs were enriched in loci associated with genetic risk for neuropsychiatric disease. Our study delineates the highly complex, lineage-specific 3D genomic dynamics in ventral progenitors and basal ganglia populations of the perinatal human brain. HighlightsO_LIJoint 3D genome and DNA methylome analysis of ventral brain progenitor zones C_LIO_LIHeterogeneous developmental progressions of the ganglionic eminences C_LIO_LIDistinct development dynamics and regulatory landscape of MSNs and interneurons C_LIO_LITransient remodeling of the 3D-genome in neurons and oligodendrocyte progenitors C_LI

genomics↗

bioRxiv2026

Efficient and scalable Python implementation of ANCOM-BC for omics differential abundance testing

ANCOM-BC (Analysis of Compositions of Microbiomes with Bias Correction) is a critical algorithm for differential abundance analysis. Designed for handling compositional data, it features the ability to estimate the unknown sampling fractions and correct the bias induced by their differences. While the original R package is robust for standard dataset sizes, the increasing magnitude of modern multi-omics studies presents computational challenges, often resulting in runtime bottleneck for high-dimensional data. Here, we present a native Python implementation of ANCOM-BC in the scikit-bio package that significantly accelerates the workflow, enabling its application to large-scale datasets. By leveraging the vectorization with NumPy and numerical optimization in SciPy, we enhanced the efficiency without compromising the statistical accuracy of the method. The benchmarking results revealed a dramatic increase in performance in both simulated and real datasets. We demonstrated that our Python implementation generates test results that match the original R package, while achieving a 100-fold acceleration in runtime and an 87% reduction in memory consumption. This new implementation allows for the analysis of datasets that are significantly larger than previously possible, and enables applications to alternative omics data types and complex statistical models that vary greatly by the number of samples, features, and covariates.

bioinformatics↗

bioRxiv2026

Impacts of mutation accumulation and order on tumor initiation revealed by engineered murine colorectal cancer organoids

Tumorigenesis typically follows a multi-hit trajectory, driven by accumulating oncogenic mutations. Colorectal cancer (CRC) has long served as a paradigmatic model of multi-hit tumorigenesis, characterized by adenoma-carcinoma transition accompanied by acquisition of specific oncogene and tumor suppressor mutations. However, how the temporal order of early mutations influences CRC initiation remains poorly understood. To address this, we established a CRC tumorigenesis model using murine intestinal organoids. By introducing defined combinations of key CRC driver mutations (Kras, Apc, and Trp53) in distinct orders, we systematically investigated how the order of mutation accumulation affects tumor initiation. Our results reveal that the mutation accumulation confers growth advantages in both in vitro and in vivo models. Strikingly, mutation order also influenced the tumorigenic properties of the organoids. Whereas organoids with Trp53 loss before or after Apc loss similarly affected organoid phenotypes in vitro or tumorigenicity in immunodeficient mice, organoids with Trp53 loss preceding Apc inactivation exhibited reduced tumor-forming potential in immunocompetent mice, likely due to their distinct immunological features. Collectively, our study reveals a critical role of ordered mutation accumulation in CRC initiation, an insight that may hold clinical relevance.

cancer biology↗

bioRxiv2026

Glucose is a ligand-like trigger for secretion of postprandial GLP-1

Glucagon-like peptide 1 (GLP-1) is secreted from the intestinal L cells in a glucose-dependent manner. However, the mechanism underlying how glucose stimulates the secretion remains unclear. Here, we found that glucose at postprandial concentrations near the Km of GK for glucose ([~]10 mM), as well as nonmetabolizable glucose analogs, triggers GLP-1 secretion by intestinal L cells through directly binding to glucokinase (GK), without increasing intracellular ATP levels. We also show that in postprandially high glucose, glucose-bound GK interacts and inhibits KATP, as assessed by immunoprecipitation and FRET-FLIM analyses, as well as patch clamping. In addition, we have utilized GK mutants identified in diabetics, demonstrating that those mutants defective in binding to glucose impair GLP-1 secretion in however high glucose, whereas mutants constitutively bound to glucose with defects in catalysis, promote GLP-1 secretion even in low glucose. Furthermore, the KATP mutant unable to bind to GK blocks GLP-1 secretion in high glucose. We have also provided evidence showing that sodium-glucose cotransporter 1 (SGLT1) plays an important role in the basal secretion of GLP-1, but not in high glucose. We have thus revealed that glucose the molecule itself and GK act as a ligand and the receptor, respectively, to induce GLP-1 secretion in response to high glucose, providing new therapeutic avenues targeting metabolic diseases.

biochemistry↗

bioRxiv2025

CancerSTFormer enables multi-scale analysis of spot-resolution spatial transcriptomes and dissects the gene and immune regulatory responses of targeted therapies

The growing number of spot-resolution sequencing based spatial transcriptomic (ST) datasets provides an unprecedented opportunity to study multicellular spatial niches driving cancer transitions. However studying niche-level behavior of tumors remains challenging as it requires a multi-scale approach to modeling the spatial niches and the ability to predict possible effects of genetic perturbations on spatial niches. We propose CancerSTFormer, consisting of a pair of spatially aware transcriptomic foundation models to accommodate niche modeling at different length scales. These models, at the 50{micro}m-Local and 250{micro}m-Extended scales, possess unique capabilities to recover ligand-target gene relationships, niche-specific differentially expressed genes, and organ-specific metastasis associated genes in diverse cancer applications. CancerSTFormer can also reveal the regulatory effects of immune-checkpoint blockade therapies, and other targeted therapies, on patients tumors through perturbation analysis, and accurately recapitulated perturbation responses from a spatial Perturb-map experiment. By reusing existing spot-resolution ST studies at scale, this tool transforms the vast spot-resolution ST data into a resource for understanding how gene perturbation impact spatial niches in cancer, while also providing ST-driven, gene-based refinement of treatment-resistance and sensitivity signatures derived from existing bulk transcriptomic studies, enhancing signature interpretation.

bioinformatics↗

bioRxiv2025

A K27-linked Ubiquitin Checkpoint Controls NOTCH Homeostasis

Cell surface receptors such as NOTCH1 must be tightly regulated to ensure developmental fidelity and prevent pathological activation. Although the proteolytic steps culminating in nuclear NOTCH1 signaling are established, how cells prevent excessive or uncontrolled activation has remained unresolved. Here we identify the autophagy-related protein UVRAG as a negative regulator of NOTCH1. Upon receptor activation, UVRAG, acting independently of autophagy, recruits and activates the E3-ligase ITCH to catalyze K27-linked ubiquitination of membrane-tethered NOTCH1, thereby licensing ESCRT-dependent lysosomal degradation. Disruption of the UVRAG-ITCH-ESCRT axis stabilizes activated NOTCH1 intermediates and amplifies oncogenic signaling. In T-cell leukemia models driven by constitutive NOTCH1 activity, restoring UVRAG expression reinstates receptor turnover, suppresses disease progression, and improves therapeutic response. These findings define a ubiquitin-directed safeguard circuit that enforces NOTCH1 signaling homeostasis and reveals a tunable axis for intervention in NOTCH1-driven cancers.

molecular biology↗

bioRxiv2025

Immunotherapy with Pro-regenerative Macrophages from Embryonic Stem Cells Ameliorate Osteoarthritis via TNFAIP3-Mediated Chondroprotection

Immune cell-based therapies for osteoarthritis (OA) remains underexplored. Macrophages coordinate tissue repair, yet their functional heterogeneity and therapeutic applicability, particularly for designed stem cell-derived populations with tailored reparative properties are not fully delineated. Inspired by embryonic skeletal development as a paradigm of scarless regeneration, we identified a pro-regenerative macrophage population through a single-cell RNA atlas of developing skeletal tissues. We subsequently established a mechanically dynamic induction approach to efficiently generate pro-regenerative macrophages from human embryonic stem cells (hESCs), mimicking this developmental phenotype. In vitro, these macrophages mitigate cartilage degradation in OA explants and suppress pro-inflammatory, catabolic signaling in chondrocytes. Injection into murine OA joints robustly attenuates disease progression, reduces extracellular matrix breakdown, and resolves synovial inflammation, representing the first demonstration of immune cell-based therapy for OA. Mechanistically, these macrophages orchestrate chondroprotection not through broad immunosuppression, but by activating a TNFAIP3-dependent signaling hub that restrains inflammatory and catabolic responses in chondrocytes. This TNFAIP3 activation precisely reversed the OA-associated gene signature, suppressing catabolic mediators while enhancing reparative factors, thereby restoring the anabolic-catabolic balance. Our findings uncover a developmental blueprint for engineering pro-regenerative macrophages from stem cells and establish a pioneering targeted immune cell therapy that engages an intrinsic chondroprotective program, offering a transformative and translationally relevant strategy for OA treatment.

immunology↗

bioRxiv2025

Multiscale Spatial Transcriptomic Atlas of Human Basal Ganglia Cell-Type and Cellular Community Organization

We generated a multi-region, subcellular-resolution spatial transcriptomic atlas of the human basal ganglia by integrating MERFISH+ and Stereo-seq across four neurotypical donors. These datasets profiled [~]7 million cells spanning the caudate, putamen, nucleus accumbens, and globus pallidus, resolving 60 transcriptionally distinct cell types. We show region-selective, molecular and spatial diversification of medium-spiny-neuron cell types and multiple non-neuronal populations with distinct molecular identities and spatial localizations. Subcellular RNA localization captures somatic size and projection-inferred signatures that reflect direct and indirect pathway topology. Cellular community analyses reveal the enrichment of sub-clusters of astrocytes and oligodendrocytes at striosome-matrix borders, while primate-expanded interneurons are confined to matrix territories. Cross-species mapping uncovers orthologous striosome-matrix organization and conserved dorsolateral-ventromedial gene expression gradients. This atlas provides a foundational molecular and spatial framework for studying human basal ganglia architecture, offering a multi-centimeter scale resource that links cell types, spatial architecture, and subcellular transcript topography across multiple nuclei. HighlightsO_LIOur multi-centimeter scale spatial taxonomy identifies the precise locations of 60 neuronal and glial cell types of human basal ganglia. C_LIO_LIMERFISH+ and Stereo-seq platforms map consistent spatial modules that align with classical neuroanatomical nuclei. C_LIO_LID1D2 hybrid MSNs and primate-expanded interneurons show regional and domain specific organization C_LIO_LISubcellular RNA localization reports soma morphology and projection-inferred signatures. C_LI

neuroscience↗

bioRxiv2025

MERFISH+, a large-scale, multi-omics spatial technology resolves the molecular holograms of the 3D human developing heart

Hybridization-based spatial transcriptomics technologies have advanced our ability to map cellular and subcellular organization in complex tissues. However, existing methods remain constrained in gene coverage, multimodal compatibility, and scalability. Here, we present MERFISH+, an enhanced version of Multiplexed Error-Robust Fluorescence in Situ Hybridization (MERFISH), which integrates chemical probe anchoring in protective hydrogels with high-throughput microfluidics and microscopy. This optimized design supports robust and repeated hybridization cycles across an entire centimeter-scale tissue sample. MERFISH+ allowed to simultaneously quantify over 1,800 genes and resolve the 3D organization of chromatin loci and their associated epigenomic marks in developing human hearts. Using a generative integration framework for spatial multimodal data (Spateo-VI), we harmonized these MERFISH+ transcriptomic and chromatin data to reconstruct a 3D spatially-resolved multi-omic atlas of the developing human heart at subcellular resolution capturing 3.1 million cells across 34 distinct populations. This 3D atlas provides a holistic view of an entire organ enabling the characterization of 3D cellular neighborhoods and transcriptional gradients of substructures such as the descending arteries. Thus, MERFISH+ offers a robust, large-format platform for spatial multi-omics that enables high resolution mapping of gene expression at subcellular resolution and the characterization of cellular organization within 3D organs. One Sentence SummaryMERFISH+ is an spatial multi-omics platform that integrates hydrogel-based probe anchoring, automated high-throughput microfluidics, and large-format multimodal data production to enable comprehensive, subcellular resolution mapping of gene expression and chromatin organization across millions of cells within complex developing human organs. HighlightsO_LIMERFISH+ expands MERFISH capabilities to measure >1,800 genes and at whole-organ 3D imaging scale C_LIO_LICombines chemical probe anchoring with high-throughput volumetric microscopy and microfluidics C_LIO_LIGenerates a 3D molecular atlas of a developing human heart with > 3.1 million cells at subcellular resolution C_LIO_LIIntroduces Spateo-VI, a novel generative framework integrating 3D multimodal datasets C_LI

genomics↗

bioRxiv2025

ANUBI: A Platform for Affinity Optimization of Proteins and Peptides in Drug Design

The increasing availability of computational power is opening unprecedented opportunities in computational biology and drug design. Computer simulations based on physical models can now reproduce or replace critical biophysical experiments such as binding affinity evaluations in the drug screening process. Here we present ANUBI (ANUBI Nexus for Understanding Binding Interactions), a software package that automates sequence space exploration and binding free energy calculations to optimize protein or peptide drug candidates for improved target binding. Starting from a user-provided molecular model of the drug-target interaction, ANUBI systematically evaluates point mutations in selected regions using Monte Carlo methodology, retaining favorable mutations based on calculated binding affinity differences. We demonstrate that this approach efficiently samples sequence space, generating dozens of optimized variants in timeframes comparable to experimental approaches at substantially reduced cost. As proof of concept, we applied ANUBI to an antibody-antigen complex and a peptide-protein interaction, identifying variants with significantly improved predicted binding energy (approximately 20 kcal/mol, calculated using the MMPBSA method), within 20 days of computation on a single GPU. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/683353v2_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@17fa242org.highwire.dtl.DTLVardef@75cf1dorg.highwire.dtl.DTLVardef@70888aorg.highwire.dtl.DTLVardef@14412d_HPS_FORMAT_FIGEXP M_FIG TOC GRAPHIC C_FIG

biophysics↗

bioRxiv2025

IGP receptors act as redox sensors to mediate broad-spectrum disease resistance induced by cellooligomers

Cys-oxidation is a well-established post-translational regulator of intracellular protein function, yet its role in extracellular receptor-mediated signaling remains poorly understood. Here, we investigate the LRR-Malectin receptor-like kinase IGP1, a key receptor for plant cell wall damage-associated molecular patterns (DAMPs). We demonstrate that IGP1 directly recognizes cellooligomers with a degree of polymerization [≥] 3 via a conserved binding groove in its LRR domain, not the malectin domain as anticipated. Strikingly, a pair of cysteines within the malectin domain functions as a redox sensor, undergoing hydrogen peroxide-induced oxidation that sterically reduces ligand binding affinity and attenuates immune signaling. Phylogenetic analyses reveal that IGP originated after the terrestrialization of plants, and is an evolutionarily conserved redox sensor in land plants. Functional studies in Arabidopsis (Arabidopsis thaliana), wheat (Triticum aestivum), and soybean (Glycine max) confirm that the IGP-cellooligomer module confers broad-spectrum disease resistance. Our work uncovers a unique mechanism where ligand perception and redox sensing are integrated into a single receptor to regulate DAMP-triggered immunity.

plant biology↗

bioRxiv2025

Convergent utilization of APN receptor by hedgehog merbecoviruses

Dipeptidyl peptidase-4 (DPP4) and angiotensin-converting enzyme 2 (ACE2) are well-established receptors for merbecoviruses, yet the receptor usage of merbecoviruses of European and Asian hedgehogs (EriCoVs) remains unknown. Here, by testing hedgehog orthologs of known coronavirus receptors, we identify hedgehog aminopeptidase N (APN) as a functional receptor for EriCoVs. Analysis of 94 APN orthologs indicates that EriCoVs have a limited host range, primarily utilizing hedgehog APN and, to a lesser extent, APN from certain felids, shaped by specific determinants at the virus-receptor interface. Cryo-EM reveals an APN-binding mode distinct from those used by alpha- and deltacoronaviruses. Functional assays indicate that hedgehog transmembrane serine protease 2 (TMPRSS2) enhances spike activation and promotes pseudovirus entry. Neutralizing antibodies targeting RBD and APN were developed and could effectively block EriCoV pseudovirus entry and propagation. These findings reveal an unexpected convergent evolution of APN utilization among merbecovirus, establishing a foundation for risk assessment and countermeasure development. Graphic abstractConvergent utilization of hedgehog APN by EriCoVs O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/676546v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@1ea334aorg.highwire.dtl.DTLVardef@cd53bforg.highwire.dtl.DTLVardef@352102org.highwire.dtl.DTLVardef@a1eed_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2025

Iterative delivery of mRNA by MEFI

Conventional therapeutic mRNA delivery systems are inherently single-use, limiting expression potency, duration, and penetration across biological barriers. To address this, we engineered the mRNA Exporting and Ferrying Implement (MEFI), a platform that enables iterative cell-to-cell transfer of cargo mRNA, allowing a single mRNA molecule to be utilized multiple times across various cells. MEFI encodes a fusion protein that assembles virus-like particles (VLPs) and encapsulates both itself and cargo mRNA into these VLPs, orchestrating reproduction of VLPs from targeted cells and continuous intercellular spreading. MEFI significantly amplified cargo protein expression in the transfected cell populations ([~]20-fold) and in organs ([~]500-fold in lung) from mice administered systemically. Notably, through intramuscular injection of naked plasmids, MEFI promoted robust ([~]20-fold) and durable ([~]2-month) cargo expression, interorgan mRNA transfer, and successful crossing of the blood-brain barrier. Moreover, modified MEFI demonstrated cell-type-specific targeting, mediating the elimination of antigen-expressing cells. Collectively, MEFI establishes a modular platform for enhancing mRNA delivery, leveraging the concept of iterative delivery of mRNA. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/667827v2_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@14522c2org.highwire.dtl.DTLVardef@1ecfa7dorg.highwire.dtl.DTLVardef@1314347org.highwire.dtl.DTLVardef@1380cc7_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

MTARC1 Regulates Lipid Droplet Degradation via Phospholipid Remodeling in Metabolic Fatty Liver Disease

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a spectrum of liver disease, including simple fatty liver, hepatic steatosis, fibrosis, cirrhosis, and hepatocellular carcinoma, with limited treatment options. MTARC1 p.A165T variant is associated with reduced risk of MASLD. We previously showed that this variant promotes MTARC1 protein degradation, suggesting MTARC1 inactivation may represent a potential therapeutic strategy. Here, we report that global or liver specific Mtarc1 knockout markedly suppresses diet-induced hepatic TG accumulation, liver injury, inflammation, and fibrosis in a manner dependently on lipolysis and lipophagy. MTARC1 inactivation post-transcriptionally upregulates PEMT and CEPT1 expression, consequently elevating GPL levels, including PC, PE, and lyso-PE, three major GPLs of hepatic LDs. Furthermore, we observed that MTARC1-deficient hepatocytes exhibited smaller but more numerous LDs compared to controls, under comparable cellular TG levels during lipolysis/lipophagy inhibition. Importantly, inhibition of CEPT1 or PEMT could attenuated the hepatoprotective effect of MTARC1 deficiency. Mechanistically, subcellular GPL remodeling induced by MTARC1 deficiency reduce LD size while increase their surface-to-volume ratio, which in turn promote TG degradation through lipolysis and lipophagy. Collectively, our findings identify MTARC1-GPL biosynthesis-LD degradation axis as a key regulator of fatty liver disease and highlight MTARC1 inhibition as a promising therapeutic strategy for MASLD.

cell biology↗

bioRxiv2025

The open-source Masala software suite: Facilitating rapid methods development for synthetic heteropolymer design

Although canonical protein design has benefited from machine learning methods trained on databases of protein sequences and structures, synthetic heteropolymer design still relies heavily on physics-based methods. The Rosetta software, which provides diverse physics-based methods for designing sequences, exploring conformations, docking molecules, and performing analysis, has proven invaluable to this field. Nevertheless, Rosettas aging architecture, monolithic structure, non-open source code, and steep development learning curve are beginning to hinder new methods development. Here, we introduce the Masala software suite, a free, open-source set of C++ libraries intended to extend Rosetta and other software, and ultimately to be a successor to Rosetta. Masala is structured for modern computing hardware, and its build system automates the creation of application programming interface (API) layers, permitting Masalas use as an extension library for existing software, including Rosetta. Masala features modular architecture in which it is easy for novice developers to add new plugin modules, which can be independently compiled and loaded at runtime, extending functionality of software linking Masala without source code alteration. Here, we describe implementation of Masala modules that accelerate protein and synthetic peptide design. We describe the implementation of Masala real-valued local optimizers and cost function network optimizers that can be used as drop-in replacements for Rosettas minimizer and packer when designing heteropolymers. We explore design-centric guidance terms for promoting desirable features, such as hydrogen bond networks, or discouraging undesirable features, such as unsatisfied buried hydrogen bond donors and acceptors, which we have re-implemented far more efficiently in Masala, providing up to two orders of magnitude of speedup in benchmarks. Finally, we discuss development goals for future versions of Masala.

biochemistry↗

bioRxiv2025

Lf2 is a knotted homeobox regulator that modulates leaflet number in soybean

Variation in leaf complexity modulates light capture and is a target for crop enhancement. Soybean typically has compound leaves with three leaflets each, but a spontaneous mutation, designated lf2, possesses seven leaflets, offering a means to dissect the molecular mechanisms specifying leaflet number and assess its potential for soybean improvement. However, the developmental and genetic bases of the lf2 mutation remain unknown. Here, we characterize the seven-leaflet phenotype and identify the mutation responsible for the phenotypic changes. Microscopic examination of leaf emergence sites revealed that the seven-leaflet phenotype arises in a two-step process: five leaflets form initially followed by secondary leaflet initiation at the margins of the central leaflet. Genetic mapping delineated lf2 to a [~]2.5 Mb region at the start of chromosome 11. Fortuitously, integration of pedigree analysis with comparative analysis of genomic sequences from the region pinpointed a 2-bp deletion in the coding sequence of a gene, which is homologous to the Arabidopsis KNAT7 encoding a KNOTTED1-LIKE HOMEOBOX 2 transcription factor, as the sole candidate for Lf2. The deletion is predicted to result in disruption of the putative DNA-binding homeodomain. Expression of the wild-type allele of the candidate gene in the seven-leaflet lf2 mutant restored the three-leaflet phenotype, while disruption of the wild-type allele through CRISPR-Cas9 editing induced extra leaflet formation. This study advances our understanding of leaflet formation in legumes and provides a template for utilizing compound leaf architecture to optimize photosynthetic efficiency and yield in soybean.

plant biology↗

bioRxiv2025

PB-scope: Contrastive learning of dynamic processing body formation reveals undefined mechanisms of approved compounds

Membraneless organelles (MLOs) formed by liquid-liquid phase separation contribute to intracellular compartmentalization of specific biological functions. The dynamic regulation of MLOs is critical for RNA metabolism, stress response, and signal transduction. While the number and size of MLOs serve as valuable indicators of cellular states, leveraging their spatial distribution and diverse quantitative characteristics to infer cellular conditions has posed significant challenges. Here, we present processing body (PB)-scope: an unsupervised deep learning-based framework designed for imaging-based phenotypic screening of PB, one representative MLO. The model was trained on a substantial dataset comprising over 400,000 single-cell confocal microscopy images from a colon cancer cell line treated with 280 compounds. PB-scope enabled precise drug classification based on their effects on PB characteristics, including number and size. This artificial intelligence framework offers insights previously obscured by the dynamic and subtle nature of PBs. Notably, PB-scope identified drugs with a shared function in the JAK signaling pathway, a previously unrecognized regulator of PB dynamics. PB-scope holds the potential for adapting to the study of other MLOs, offering broad applicability in this emerging field of cell biology.

cell biology↗