Biology subjects

Song, Q.

Publications and source records attributed to Song, Q..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Multi-omics analysis reveals genetic regulatory mechanismsof muscle traits in wild and domesticated Bactrian camels

Bactrian camels, large domesticated animals adapted to extreme environments, have evolved under natural and artificial selection to suit their living conditions and meet human needs. In arid and semi-arid regions, they provide valuable resources through economically important traits such as meat, milk, and wool production, contributing significantly to both economy and ecology. However, research on gene function, adaptive evolution, and molecular mechanisms underlying complex traits in Bactrian camels remains limited, constraining the full utilization of their breeding potential and conservation efforts.To address this gap, we performed whole-genome resequencing (WGS) on 35 domesticated Bactrian camels from the Chinese Sunite local population and integrated this data with publicly available WGS data from 112 Asian Bactrian camels. Our comprehensive analysis revealed significant genetic differences and genomic features between wild and domesticated Bactrian camels. We further integrated 27 epigenomic (ATAC-seq) and transcriptomic (RNA-seq) datasets from eight biologically important tissues of four Bactrian camels, along with skeletal muscle scRNA-seq and scATAC data. This allowed us to identify tissue-specific genes, regulatory elements, and genes under positive selection.Our integrated analysis identified target genes and their upstream regulatory elements, including potential regulatory transcription factors, with a focus on positively selected regions in Bactrian camel muscle tissue. We constructed regulatory pathways from key SNPs to regulatory elements to genes, and for the first time, identified regulatory elements in major tissues of the Bactrian camel genome. Our results also summarized the single-cell transcriptional landscape of Bactrian camel skeletal muscle, revealing cellular heterogeneity and genetic expression patterns across two developmental stages.This comprehensive regulatory element map provides a valuable resource for genetic and genomic studies in Bactrian camels. It reveals key regulatory networks, important genes, and regulatory elements influencing muscle development, as well as potentially significant functional variants affecting meat production traits. These findings will provide crucial data support for future genetic improvement and breeding efforts in Bactrian camels.

genetics↗

bioRxiv2025

GatorST: A Versatile Contrastive Meta-Learning Framework for Spatial Transcriptomic Data Analysis

IntroductionRecent advances in spatial transcriptomics (ST) technologies have revolutionized our understanding of cellular functions by providing gene expression profiles with rich spatial context. Effectively learning spatial representations is crucial for downstream analyses and requires robust integration of spatial information with transcriptomic data. While existing methods have shown promise, they often fail to adequately capture both local (neighbor-level) and global (tissue-wide) spatial contexts. Moreover, they tend to rely heavily on augmentation strategies, which can introduce noise and instability. ObjectivesThis study aims to introduce and demonstrate a novel, versatile framework called GatorST, which explicitly combines graph-based modeling with advanced learning strategies to generate spatially informed representations of ST data. GatorST is designed to improve various downstream tasks, including identification of spatial domains, gene expression imputation, batch effect removal, and trajectory inference. MethodsGatorST constructs a spot-spot graph by connecting each node to its k nearest spatial neighbors and extracts two-hop neighborhood subgraphs to capture local context. At the global level, gene expression profiles are clustered using soft K-means to generate pseudo-labels, which serve as weak supervision signals within a contrastive learning framework. This process encourages the alignment of embeddings with shared pseudo-labels while separating those with different labels. GatorST further adopts an episodic training strategy inspired by meta-learning, wherein each episode consists of a support set for contrastive optimization and a disjoint query set for embedding classification, guided by the pseudo-labeled data. This design enables the model to classify unseen samples based on learned embeddings, thereby enhancing its generalization to new spatial contexts. ResultsComprehensive comparisons with fifteen state-of-the-art methods across fourteen spatial transcriptomics datasets demonstrate that GatorST consistently achieves superior performance in identifying spatial domains, imputing gene expressions, and removing batch effects. The results showcase the versatility and strong generalization capabilities of GatorST across diverse tissue types and experimental settings. ConclusionGatorST effectively integrates spatial topology and global gene expression through graph-based modeling, pseudo-labeling, and contrastive meta-learning. This framework generates biologically meaningful representations and significantly improves key downstream tasks, including spatial domain identification, gene expression imputation, batch effect removal, and trajectory inference.

bioinformatics↗

bioRxiv2025

Electric fields trigger ceramide-dependent budding of exosome vesicles into multivesicular endosomes and boost the generation of exosomes

Exosomes hold immense therapeutic and diagnostic potential, yet their clinical translation remains constrained by low yields. Physiological electric fields (EFs), naturally occurring during wound healing and embryo development, have unexplored roles in exosome biogenesis. Here, we demonstrate that physiological-strength EFs (Direct Current, 50-200 mV/mm) dramatically enhance cellular exosome secretion, achieving a nearly 100-fold increase in a strength-dependent manner. Mechanistically, EFs augmented intraluminal vesicle formation within multivesicular bodies. We proposed a novel EF-driven membrane electroassembly and vesiculogenesis hypothesis and tested it using giant plasma membrane vesicles. We reconstructed EF-induced membrane remodeling and observed EFs driving inward budding of nanoscale exosome-like vesicles. Notably, alternating current EFs (50-400 Hz) exhibited significantly diminished efficacy compared to direct current EFs, highlighting membrane electropolarization-dependent modulation. Pharmacological inhibition of the lipid raft and ceramide almost abolishes EF-induced exosome secretion. Inhibition of the PI3K partially attenuated EF-triggered exosome release. Our findings not only unveil EFs as a potent physiological regulator of exosome secretion but also establish a novel, high-yield production strategy leveraging bioelectric cues. Significant statementWe reported that the bodys natural bioelectricity, the faint electric currents in healing wounds and embryo development, can trigger cells to release 100 times more "natural nanoscale vesicle couriers" called exosomes. This pure physical method is far more efficient than current available technologies, paving the way for breakthroughs in cancer early detection, stem cell therapies, and precision medicine. We found that gentle electric fields can "blow" the cell membrane to release exosomes like "soap bubbles". This explains how bioelectricity controls cell communication during development and wound healing. In short, harnessing the bodys hidden "electric language" unlocks a fast and natural way to mass-produce exosomes.

cell biology↗

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

Oblique Thick Light-Sheet Microscopy with Spatiotemporal 3D Localization for RNA Imaging in Intact 50 μm-Thick Sections

Neuron typing in intact brain sections demands 3D imaging reconciling thickness compatibility with large-area coverage--a persistent challenge for RNA imaging methods limited by either restricted fields-of-view (<1 mm2) or thin-section constraints (<20 m). Here we introduce oblique thick light-sheet microscopy integrated with spatiotemporal 3D localization, enabling multiplexed RNA imaging across 50 m-thick tissue sections and centimeter-scale regions. The 45{degrees} illumination geometry achieves optical-interference-free imaging in >100 m-thick tissues during single-plane scans, while a spatiotemporal localization algorithm recovers submicron resolution by pinpointing fluorescence in situ hybridization (FISH) spots within volumetric excitation. This strategy reveals layer-spanning neuronal distributions and region-specific expression gradients unattainable with conventional RNA imaging approaches. By resolving the historical trade-off between imaging depth and spatial coverage, our platform advances whole-brain transcriptomics, enabling 3D neuron typing capability critical for deciphering brain-wide cellular architectures.

biophysics↗

bioRxiv2025

Structural insight into the transcription activation mechanism of the phage Mor/C family activators

Bacteriophage Mu, a temperate phage that infects E. coli K-12 and other enteric bacteria, precisely controls its replication cycle through hijacking host RNA polymerase (RNAP) by the middle operon regulator Mor and the late gene transcription activator C. Though a dimeric arrangement and significant conformational changes are proposed for the distinct Mor/C family activators, the underlying transcription activation mechanism remains unclear. In this study, we present two cryo-EM structures of the transcription activation complex (Mor-TAC and C-TAC) with phage Mu middle and late gene promoters, respectively. Remarkably, the Mor/C activators bind to promoter DNA as a centrosymmetric tetramer rather than as the proposed dimer, concurrently stabilizing by the N-terminal dimerization domains and C-termini. The C-terminal DNA binding domains and two anti-{beta}-strands simultaneously interact with two adjacent DNA major grooves. The activators also engage a variety of interactions with the conserved domains (CTD, {sigma}70R4, and {beta} FTH) of RNAP, providing evidences for a recruitment mechanism. In addition, single-molecule FRET assays show that C significantly enhances RPitc formation, suggesting a different multi-step activation mechanism for C. Collectively, these findings reveal the unique transcription activation mechanism of tetrameric Mor/C family activators, unraveling a novel mode of phage hijacking and bacterial transcription regulation.

biochemistry↗

bioRxiv2025

Divergence of root system traits in soybean between breeding and diversity lines

Roots are critical for supporting basic plant functions such as anchoring in various substrates, uptake of water and nutrients, and hosting symbiotic relationships. In crops, indirect changes to root system architecture (RSA) have occurred largely as a result of selection for yield or other related aboveground traits. In cultivated soybean (Glycine max), evidence of changes to RSA resulting from breeding for crop performance has been inconsistent, with some studies supporting an overall decrease in performance-related trait values, such as root length and density, and other work showing the opposite. The current study sets out to ask whether there is any systematic differentiation in RSA between a set of elite breeding lines (n=8) of soybean developed for the Midwest United States and a group of biogeographically diverse landraces from the USDA Soybean Germplasm Collection (n=16. Groups are compared across three distinct developmental stages (V2-V6, V7-R2, R3-R7) and two contrasting soil environments. In total, 432 root systems were phenotyped for 12 structural traits derived from 2D images along with root and shoot biomass. A new 3D root modeling approach leveraging photogrammetry-derived pointclouds is additionally tested on a subset of 30 contrasting root systems. Results indicate that the diversity lines had smaller root systems overall but greater phenotypic plasticity in response to soil environment as compared to breeding lines. Additionally, the study finds evidence for trade-offs between above-ground and below-ground trait plasticity. Core ideasO_LIPrevious work suggests crop root system architecture (RSA) has changed as a result of indirect selection C_LIO_LIThis study compares RSA in elite breeding lines with that of diverse landraces in cultivated soybean C_LIO_LIA total of 432 root systems are analyzed across 24 genotypes, two soil environments and three developmental stages C_LIO_LIFindings show diversity lines have smaller root systems but greater plasticity in response to soil environment C_LI

plant biology↗

bioRxiv2025

Electromotility can be disassociated from gating charge movement in outer hair cells of conditional alpha2 spectrin knockout mice.

Electromotility in mammalian outer hair cells (OHC) is the mechanism underlying cochlear amplification. It is brought about by the piezoelectric-like property of the membrane protein prestin (Slc26a5) that lies in the OHCs lateral plasma membrane. Prestin connects to an underlying cytoskeletal network of circumferential actin filaments that bridge longitudinal spectrin filaments. This network, in turn, lies between the plasma membrane and a closely apposed ER-like tubular array of subsurface cisternae (SSC). Two previous papers examining spectrin knockouts in embryonic hair cells were confined to analyzing the effects on the apical cuticular plate and overlying stereocilia. In this paper, we examine the effects of conditional knockouts of alpha2 spectrin in postnatal OHCs. We find a significant auditory phenotype likely due to the novel disassociation of prestins gating charge movement from OHC electromotility. In addition, OHCs show enlargement in their SSC and plasma membrane-SSC space with preserved cuticular plates and overlying stereocilia, which contrasts with the findings in embryonic knockouts.

physiology↗

bioRxiv2025

SpaIM: Single-cell Spatial Transcriptomics Imputation via Style Transfer

Spatial transcriptomics (ST) technologies have revolutionized our understanding of cellular ecosystems. However, these technologies face challenges such as sparse gene signals and limited gene detection capacities, which hinder their ability to fully capture comprehensive spatial gene expression profiles. To address these limitations, we propose leveraging single-cell RNA sequencing (scRNA-seq), which provides comprehensive gene expression data but lacks spatial context, to enrich ST profiles. Herein, we introduce SpaIM, an innovative style transfer learning model that utilizes scRNA-seq information to predict unmeasured gene expressions in ST data, thereby improving gene coverage and expressions. SpaIM segregates scRNA-seq and ST data into data-agnostic contents and data-specific styles, with the contents capture the commonalities between the two data types, while the styles highlight their unique differences. By integrating the strengths of scRNA-seq and ST, SpaIM overcomes data sparsity and limited gene coverage issues, making significant advancements over 12 existing methods. This improvement is demonstrated across 53 diverse ST datasets, spanning sequencing- and imaging-based spatial technologies in various tissue types. Additionally, SpaIM enhances downstream analyses, including the detection of ligand-receptor interactions, spatial domain characterization, and identification of differentially expressed genes. Released as open-source software, SpaIM increases accessibility for spatial transcriptomics analysis. In summary, SpaIM represents a pioneering approach to enrich spatial transcriptomics using scRNA-seq data, enabling precise gene expression imputation and advancing the field of spatial transcriptomics research.

bioinformatics↗

bioRxiv2025

AncestryHub: A web server for local ancestry analysis

SummaryAncestryHub is a web version of local ancestry analysis software. It contains four built-in software and a set of built-in population reference panels. AncestryHub will significantly reduce the efforts and requirements for the users on their personal computational skills and computational hardware environment for ancestry analysis. Availabilityhttps://www.ancestryhub.4dgenome.com Contact: lima@4dgenome.com

bioinformatics↗

bioRxiv2024

Lysosomal calcium signalling contributes to the acute α-adrenergic response via calcium-stimulated adenylyl cyclase 1 and 8

Inositol trisphosphate (IP3), a calcium (Ca2+)-mobilizing second messenger, releases Ca2+ from the sarcoplasmic reticulum (SR) via IP3 receptors and modulates adenylyl cyclase (AC) activity in atrial myocytes. Lysosomes participate in Ca2+ homeostasis by mobilising Ca2+ in response to Nicotinic Acid Adenine Dinucleotide Phosphate (NAADP). We postulate that both downstream activation of Ca2+ sensitive AC (AC1 and AC8) and lysosomal Ca2+ signalling in response to IP3R activation contribute to atrial myocyte function and pacemaking. Ectopic application of phenylephrine (PE) increased chronotropy and inotropy and this response was reduced in the presence of NAADP pathway inhibitors (BZ-194 and SAN4825) and Bafilomycin A1. PE increased cyclic adenosine 3-5 monophosphate (cAMP) activity in neonatal rat atrial myocytes (NRAMs) and this was inhibited by NAADP pathway inhibitors. This inhibition was not observed in neonatal rat ventricular myocytes (NRVMs), revealing specificity of this response to NRAMs. We investigated expression of AC1 and AC8 as a possible explanation to these observations. Genetic perturbation of AC1 and AC8 by double-knockout of Adcy1 and Adcy8 in a mouse model showed a decrease in positive chronotropic and inotropic response upon cumulative dose of PE in atrial tissue, reduced PE stimulated amplitude of Ca2+ transient in isolated atrial myocytes and presented decreased cytosolic cAMP levels in response to PE in neonatal atrial myocytes that was not inhibited by NAADP pathway inhibitors. Our data identifies a link between NAADP and -adrenergic signalling pathways in atrial myocytes, highlighting that lysosomal Ca2+ is an important component of -adrenergic stimulation in the cardiac atria and warrants further investigation.

physiology↗

bioRxiv2024

TET2-mediated epigenetic modification promotes stress senescence of pancreatic β cells in type 2 diabetes mellitus

Epigenetic modification plays a key role in {beta} cell senescence. In the regulation of gene expression, there is a complex and close relationship between DNA methylation and histone modification. In order to explore its specific mechanism in T2DM {beta} cell senescence, we used postbisulfite aptamer labeling of genome-wide bisulfite-SEQ, chromatin immunocoprecipitation-SEQ, RNA-SEQ, CRISPR/Cas9 TETs knockout, RNA interference, TET2 inhibitors, lentiviral overexpression, and gene knockout mouse models. Our study found that demethylase TET2 was localized in the islets of mice, and the expression level increased with age. TET2 knockout in pancreatic {beta} cells can hypermethylate PTEN, up-regulate MOF and enrich H4K16ac, and reduce the level of aging markers. This study confirmed that TET2-mediated PTEN DNA methylation can promote a new mechanism of {beta} cell senescence by regulating H4K16ac, providing a new molecular mechanism and therapeutic target for T2DM {beta} cell senescence therapy.

cell biology↗

bioRxiv2024

Gene Expression Prediction from Histology Images via Hypergraph Neural Networks

Spatial transcriptomics reveals the spatial distribution of genes in complex tissues, providing crucial insights into biological processes, disease mechanisms, and drug development. The prediction of gene expression based on cost-effective histology images is a promising yet challenging field of research. Existing methods for gene prediction from histology images exhibit two major limitations. First, they ignore the intricate relationship between cell morphological information and gene expression. Second, these methods do not fully utilize the different latent stages of features extracted from the images. To address these limitations, we propose a novel hypergraph neural network model, HGGEP, to predict gene expressions from histology images. HGGEP includes a gradient enhancement module to enhance the models perception of cell morphological information. A lightweight backbone network extracts multiple latent stage features from the image, followed by attention mechanisms to refine the representation of features at each latent stage and capture their relations with nearby features. To explore higher-order associations among multiple latent stage features, we stack them and feed into the hypergraph to establish associations among features at different scales. Experimental results on multiple datasets from disease samples including cancers and tumor disease, demonstrate the superior performance of our HGGEP model than existing methods. Key PointsWe develop a novel histology image-based gene prediction model named HGGEP, which demonstrates high accuracy and robust performance. To reveal the intricate relationship between cell morphology and gene expression in images, we propose a gradient enhancement module, which effectively improves the models capability in perceiving cell morphology in images. HGGEP includes a hypergraph module that efficiently models higher-order associations among features across multiple latent stages, resulting in significant performance improvement.

bioinformatics↗

bioRxiv2024

G-Quadruplex Structures in 16S rRNA Regions Correlate with Thermal Adaptation in Prokaryotes

G-quadruplex (G4) structure is a nucleic acid secondary structure formed by sequences rich in guanine, playing essential roles in various biological processes such as gene regulation, maintenance of genome stability, and adaptation to environmental stresses. Although prokaryotes growing at high temperatures have higher GC contents, the pattern of G4 structure presence associated with GC content variation in thermal adaptation within genomes and ribosomal genes is rarely reported. In this study, we analyzed 681 bacterial genomes to investigate the role of G4 structures in thermal adaptation. Our findings revealed a strong positive correlation between G4 patterns in the region encoding 16S rRNA genes and optimal growth temperatures (Topt), whereas genomic GC content and overall G4 patterns did not show significant correlations with Topt. Evolutionary analysis showed significant differences in G4 stability between Thermotoga (Topt[≥] 80 {degrees}C) and Pseudothermotoga (60{degrees}C [≤] Topt < 80{degrees}C) species, with Thermotoga species exhibiting higher G4 stability, indicating stronger selective pressure for G4 stability under extreme conditions. Circular dichroism analysis showed that specific base mutations at key sites resulted in the absence of G4 thermal stability and structural integrity in Thermotoga compared to Pseudothermotoga. Collectively, this study suggests that the G4 structures in 16S rRNA encoding regions emerged as key indicators of thermal adaptation and contributes to our understanding of the molecular basis of thermal adaptation.

microbiology↗

bioRxiv2024

Activation of two noncanonical R proteins by an insect effector confers plant immunity to aphid infestation

Molecular characterization of resistance genes is crucial for efficiently understanding and fortifying plant immunity against insect herbivores. Here we report that RMES1A and RMES1B proteins confer resistance to the sorghum aphid Melanaphis sorghi when activated by an insect effector MsEF1. Map-based cloning plus genetic analysis of knockout mutants confirm that RMES1A and RMES1B are both required for aphid resistance. Upon aphid attack, RMES1A and RMES1B expression is elevated in the sclerenchyma cells and vascular bundles of leaves; the two proteins interact with MsEF1 in the exocysts, thus upregulating key defense processes such as reactive oxygen species burst. Structural modeling predicts that RMES1A and RMES1B each carry an ATP binding site and two leucine-rich-repeat domains but lack coiled-coil or Toll/Interleukin-1 receptor/resistance domain, thus likely representing a new type of resistance controlling proteins in plants. Our work reveals new genes and mechanisms for further deciphering and improving plant immunity to insect pests.

genetics↗

bioRxiv2024

Lysosomal signalling pathways influence heart rhythm, and regulate atrial function

In the heart, endogenous nicotinic acid adenine dinucleotide phosphate (NAADP) triggers lysosomal calcium (Ca2+) release to augment sarcoplasmic reticulum (SR) Ca2+ sequestration, producing larger Ca2+ transients. However, the role of lysosomal Ca2+ signals in pacemaker activity, a distinct Ca2+-operated function of the sinoatrial node (SAN), or in the atrial myocardium has not been investigated. Pharmacological or genetic ablation of the NAADP pathway inhibits the spontaneous beating rate response to beta-adrenergic stimulation in intact SAN. We found intracellular signaling microdomains between lysosomes and neighboring SR or mitochondria in mouse, and goat tissue. The spatial relationship between lysosomes and other Ca2+-handling organelles are altered in goat atrial fibrillation. Furthermore, we demonstrate atrial myocytes produce cAMP in response to lysosomal signaling, adding a novel trigger for cyclic nucleotide signaling. Our findings support the hypothesis that lysosomal Ca2+ signaling contributes to regulation of cardiomyocyte cAMP levels and pacemaker activity.

physiology↗

bioRxiv2024

Structural insights into transcription regulation of the global virulence factor PhoP from Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb), remaining as the leading cause of the worldwide threat Tuberculosis, relies heavily on its transcriptional reprogramming of diverse stress genes to swiftly adapt to adverse environments and ensure infections. The global virulence factor PhoP plays a pivotal role in coordinating transcription activation or repression of the essential phosphate-nitrogen metabolic remodeling genes. However, what defines PhoP to deferentially act as an activator or a repressor remains largely unexplored. Here, we determine one cryo-EM structure of Mtb RNAP-promoter open complex, three cryo-EM structures of PhoP-dependent transcription activation complexes (PhoP-TACs) consisting of Mtb RNA polymerase (RNAP), different number of PhoP molecules binding to different types of well-characterized consensus promoters, and one cryo-EM structure of Mtb PhoP-dependent transcription repression complex (PhoP-TRC) comprising of Mtb RNAP, PhoP, the nitrogen metabolism regulator GlnR and their co-regulated promoter. Structural comparisons reveal phosphorylation of PhoP is required for stabilization of PhoP-TACs, PhoP specifically recognizes promoters as novel tandem dimers and recruits RNAP through extensively interacting with its conserved {beta} flap and {sigma}AR4 domains. Strikingly, the distinct promoter spacer length and PhoP-GlnR interactions in PhoP-TRC constrain the upstream DNA into a distinct topology and retain PhoP in a novel dragging repression mode. Collectively, these data highlight the dual regulatory mechanisms of PhoP-dependent transcription regulation in governing stress adaptation. These findings provide structural basis for developing potential anti-tuberculosis drugs and/or interventions.

microbiology↗

bioRxiv2024

xSiGra: Explainable model for single-cell spatial data elucidation

Recent advancements in spatial imaging technologies have revolutionized the acquisition of high-resolution multi-channel images, gene expressions, and spatial locations at the single-cell level. Our study introduces xSiGra, an interpretable graph-based AI model, designed to elucidate interpretable features of identified spatial cell types, by harnessing multi-modal features from spatial imaging technologies. By constructing a spatial cellular graph with immunohistology images and gene expression as node attributes, xSiGra employs hybrid graph transformer models to delineate spatial cell types. Additionally, xSiGra integrates a novel variant of Grad-CAM component to uncover interpretable features, including pivotal genes and cells for various cell types, thereby facilitating deeper biological insights from spatial data. Through rigorous benchmarking against existing methods, xSiGra demonstrates superior performance across diverse spatial imaging datasets. Application of xSiGra on a lung tumor slice unveils the importance score of cells, illustrating that cellular activity is not solely determined by itself but also impacted by neighboring cells. Moreover, leveraging the identified interpretable genes, xSiGra reveals endothelial cell subset interacting with tumor cells, indicating its heterogeneous underlying mechanisms within the complex cellular communications.

bioinformatics↗