Biology subjects

Xin, M.

Publications and source records attributed to Xin, M..

17 recordsLinked to original sources

bioRxiv2026

WheatPanRef: a unified linear pan-reference genome for wheat genomics

Linear reference genomes provide coordinates for read mapping, variant discovery and multi-omics data integration, yet assembly-specific coordinate systems limit data reuse, particularly in the large, repetitive and polyploid wheat genome. Here, we present WheatPanRef, a scalable linear pan-reference and coordinate framework that integrates wheat sequence diversity within a stable coordinate system. We reconciled independent Chinese Spring assemblies by resolving structural and sequences discrepancies to constructed a 14.50-Gb consensus sequences CS-NP. Using CS-NP as backbone, we incorporated 4.37 Gb of non-redundant non-CS sequences from 37 diverse wheat accessions, generating WheatPanRef (18.87 Gb). WheatPanRef improves read-alignment performance and captures putative wild-relative introgressions and sequences absent or unanchored in conventional references. Bidirectional coordinate-translation system enables accurate projection between WheatPanRef and individual assemblies without remapping, facilitating genomic resource integration and reuse. WheatPanRef provides a common sequence and coordinate foundation for population-scale wheat genomics, with potential utility for genomic resource integration in other complex crops.

genomics↗

bioRxiv2025

A Tonic Signaling Code Predicts CAR-T Cell Efficacy in Diffuse Midline Glioma

Diffuse midline glioma (DIPG/DMG) is a uniformly fatal pediatric brain tumor with no effective cure. Although CAR T-cell therapy shows promise, clinical outcomes remain inconsistent due to limited persistence and premature exhaustion. Reliable predictive biomarkers are lacking, and proposed exhaustion or stemness markers provide limited utility. Here, we systematically compare multiple CAR-T constructs targeting clinically-relevant antigen B7-H3 and identify antigen-independent CAR activation, or tonic signaling, as a key determinant of therapeutic performance. We find that B7-H3 CAR-T cells with restrained tonic signaling display superior tumor killing, persistence, and resistance to exhaustion, along with reduced CAR membrane clustering, in patient-derived DIPG models. Integrated multi-omics and single-cell profiling further reveal a CAR-T tonic signaling-associated gene signature that outperforms conventional exhaustion or stemness markers in predicting therapeutic efficacy across multiple clinical trials, including DIPG and other tumor types. Together, these findings define a mechanistic and predictive framework to guide CAR design and improve clinical outcomes.

cancer biology↗

bioRxiv2025

Multimodal Validation of the Existence of Transitional Cerebellar Progenitors in the Human Fetal Cerebellum

The developing human cerebellum comprises a series of transient progenitor states that are essential for generating diverse neural subtypes, yet the identity and validation of intermediate cell populations bridging stem-like and lineage-committed neuronal precursors remain limited. In our previous single-cell transcriptomic study, we identified a distinct transitional cerebellar progenitor (TCP) population enriched in specific progenitor zones such as the rhombic lip during human fetal cerebellar development. To address the concerns raised in the Matters Arising regarding the existence of the TCP cells, we provide additional multimodal validations of this population. Rigorous reanalysis of our single-cell transcriptomic data, applying stringent quality control measures, validated the quality of TCP cells and their classification as a transcriptionally distinct population. Multiple orthogonal validations of TCP signature genes (SOX11 and HNRNPH1) using RNAscope in situ hybridization, Xenium-based spatial transcriptomics, and immunohistochemistry on additional fetal cerebellar samples across different stages demonstrated the consistent presence of TCPs in the rhombic lip, transitioning from PRTG+ stem-like zones in the ventricular zone at early developmental stages to the subventricular zone overlapping with EOMES+ unipolar brush cell precursors at later stages. TCP-like populations were also independently identified in two fetal cerebellar single-nucleus transcriptomic atlases, and their gene signature was enriched in a cell population associated with aggressive medulloblastomas. Collectively, these multimodal validations confirm the existence of a transitional progenitor population in the human fetal cerebellum, with implications for cerebellar lineage progression and medulloblastoma origin.

developmental biology↗

bioRxiv2025

Self-contrastive learning enables interference-resilient and generalizable fluorescence microscopy signal detection without interference modeling

Every weak signal in fluorescence microscopy may contain critical biological information. However, the inter-ference resilience required to detect such signals has traditionally relied on task-specific interference modeling, which limits generalizability. Here, we present a self-contrastive learning-based signal detection solution that achieves interference resilience without the need for interference modeling, thereby offering high generalizability. The method, DEep PAttern Fitting (DEPAF), is a module that contrasts asynchronously generated data views from asymmetric model paths to extract signals from interference, while incorporating highly parallel signal recognition and localization in the process. Benchmarking shows that DEPAF substantially improves signal detection performance across diverse imaging modalities and dimensions, especially under challenging conditions such as low SNRs and ultra-high signal densities. It is also compatible with, and consistently enhances the performance of various imaging techniques, such as super-resolution imaging, spatial transcriptomic imaging, and two-photon calcium imaging. Notably, DEPAF relies only on image patches with signal patterns and one tunable hyperparameter to adapt to new tasks, making it accessible to users without domain-specific expertise and lowering the barrier to broader adoption. DEPAF is expected to advance the signal-centric fluorescence microscopy techniques and inspire further advancements, especially in the era of image-based multi-omics.

bioinformatics↗

bioRxiv2024

MethylQUEEN: A Methylation Encoded DNA Foundation Model

DNA 5-methylcytosine (5mC) modification plays a pivotal role in many biological processes, yet 5mC information and pattern hidden behind remains to be explored. Here, we develop Methylation Language Model based on Quintuple Bidirectional Transformer (MethylQUEEN), a novel pre-trained DNA methylation foundation model capable of sensing methylation states and covering the genome-wide methylation landscape. Through tailored methylation-prone pre-training, MethylQUEEN effectively captured epigenetics information hidden within the DNA sequences: it accurately traces DNAs tissue-of-origin, and successfully recovers the expression profile through methylation states. Integrative analysis on MethylQUEENs attention scores also enables us to reveal the unique methylation status of a tissue for precise disease detection, and identifying key regulatory 5mC sites for disease intervention. As a result, MethylQUEEN signifies a new paradigm in methylation analysis for various biological problems. Besides, our study demonstrates the effectiveness of directly integrating methylation information into pre-training, offering new perspectives and methodologies for a range of methylation-related biological processes. It serves as an initial exploration for the development of more comprehensive epigenomic models.

genomics↗

bioRxiv2024

Tracing the genetic diversity of the bread wheat D genome

Bread wheat (Triticum aestivum) became a globally dominant crop after incorporating the D genome from donor species Aegilops tauschii, while evolutionary history shaping the D genome during this process remains elusive. Here, we proposed a renewed evolutionary model linking Ae. tauschii and hexaploid wheat D genome, based on an ancestral haplotype map covering a total of 762 Ae. tauschii and hexaploid wheat accessions. We dissected the evolutionary process of Ae. tauschii lineages and clarified L3 as the most ancient lineage. A few independent intermediate accessions were reported, demonstrating the low-frequent inter-sublineage geneflow enriched the diversity of Ae. tauschii. We discovered that the D genome of hexaploid wheat inherited from a unified ancestral template, but with a mosaic composition that is highly mixed by three Ae. tauschii L2 sublineages located in the Caspian coastal region, suggesting the early agricultural activities facilitate the innovation of D genome compositions that finalized the success of hexaploidization. We further found that the majority (65.6%) of polymorphisms were attributed to novel mutations absent during the spreading of bread wheat, and also identified large Ae. tauschii introgressions from wild Aegilops lineages, expanding the diversity of wheat D genome and introducing beneficial alleles. This work decoded the mystery of the wheat hexaploidization process and the evolutionary significance of the multi-layered origins of the genetic diversity of the bread wheat D genome.

evolutionary biology↗

bioRxiv2024

TREM1 disrupts myeloid bioenergetics and cognitive function in aging and Alzheimer disease models

Human genetics implicate defective myeloid responses in the development of late onset, age-associated Alzheimers disease (AD). Aging is characterized by a decline in myeloid metabolism that triggers maladaptive, neurotoxic immune responses. TREM1 is an amplifier of pro-inflammatory myeloid responses, and here we find that Trem1 deficiency prevents age-dependent changes in myeloid metabolism, inflammation, and hippocampal memory function. Trem1 deficiency rescues age-associated declines in ribose-5P, a glycolytic intermediate and the precursor for purine, pyrimidine, and NAD+ biosynthesis. In vitro, Trem1 deficient microglia are resistant to bioenergetic changes induced by amyloid-{beta}42 oligomers (A{beta}42), suggesting that A{beta}42 stimulation disrupts homeostatic microglial metabolism and immune function via TREM1. In the 5XFAD model of amyloid accumulation, Trem1 haploinsufficiency prevents spatial memory loss, preserves homeostatic microglial morphology, and reduces neuritic dystrophy independent of amyloid accumulation or changes in the disease-associated microglial transcriptomic signature. In aging APPSwe mice, Trem1 deficiency restores synaptic mitochondrial function and cerebral glucose uptake and prevents hippocampal memory decline. In post-mortem human brain, microglial TREM1 expression increases with clinical and neuropathological severity. Thus, TREM1-mediated disruption of myeloid metabolism, both in the periphery and brain, promotes cognitive decline in aging and amyloid accumulation, two major risk factors for AD development.

neuroscience↗

bioRxiv2023

ThermoLink: Bridging Disulfide Bond and EnzymeThermostability through Database Construction andMachine Learning Prediction

Disulfide bonds (SS bonds), covalently formed by sulfur atoms in cysteine residues, play a crucial role in protein folding and structure stability. Due to their significance, artificial disulfide bonds are often introduced to enhance the thermostability of proteins. Although an increasing number of tools can assist with this task, significant amounts of time and resources were often wasted due to inadequate consideration. To enhance the accuracy and efficiency of designing disulfide bonds for protein thermostability improvement, we first collected disulfide-bond data with protein thermostability data from extensive literature sources. Then, various sequence- and structure-based features were extracted, and machine learning models were constructed to predict whether a disulfide bond could improve protein thermostability. Among all models, the neighborhood context model using the Adaboost-DT algorithm performs the best, and the AUC-ROC score and accuracy are 0.773 and 0.714, respectively. Alongside this, we also found that AlphaFold2 exhibits a high superiority in predicting disulfide bonds, and the coevolutionary relationship between residue pairs, to some extent, could also guide artificial disulfide-bond design. The SS-bond data has been integrated into an online server, named ThermoLink, available at guolab.mpu.edu.mo/thermoLink. O_TEXTBOXKey MessagesO_LIWe manually curated a database of disulfide bonds and their impacts on protein thermostability from the literature. C_LIO_LIAlphaFold2 exhibits a high superiority in predicting disulfide bonds, and to some extent, the conservation and co-evolutionary information of the residue pairs involved in disulfide bonds could also guide artificial disulfide-bond design. C_LIO_LIMachine learning models were developed to predict potential disulfide bonds with the aim of improving protein thermostability, offering an extended design strategy beginning with existing SS-bond prediction tools to optimize variant selection. C_LIO_LIThis work provides valuable data and theoretical support for a more precise design of disulfide bonds for improving protein thermostability. C_LI C_TEXTBOX

bioinformatics↗

bioRxiv2022

Cholecystokinin from the Rhinal Cortex Facilitates Motor Skill Learning

Cholecystokinin (CCK) is an essential modulator for neuroplasticity in sensory and emotional domains. Here, we investigated the role of CCK in motor learning using a single pellet reaching task in mice. Mice with a knockout of cck gene (CCK-/-) or blockade of CCK-B receptor (CCKBR) showed defective motor learning ability; the success rate of retrieving reward remained at the baseline level compared to the wildtype mice with significantly increased success rate. We observed no long-term potentiation (LTP) upon high-frequency stimulation (HFS) in the motor cortex of CCK-/- mice, indicating a possible association between motor learning deficiency and neuronal plasticity in the motor cortex. In vivo calcium imaging demonstrated that the deficiency of CCK signalling disrupted the refinement of population neuronal activity in the motor cortex during motor skill training. Anatomical tracing revealed direct projections from CCK-expressing neurons in the rhinal cortex to the motor cortex. Inactivating the CCK neurons in the rhinal cortex using chemogenetic methods significantly suppressed motor learning, and intraperitoneal application of CCK4, a tetrapeptide CCK agonist, rescued the motor learning deficits of CCK-/- mice. In summary, our results suggest that CCK, which could be provided from the rhinal cortex, enables neuroplasticity in the motor cortex leading to motor skill learning.

neuroscience↗

bioRxiv2022

Pangenome-based dynamic trajectories of intracellular gene transfers in Poaceae unveil a high rate of unceasing integration and selective retention in Triticeae

Intracellular gene transfers (IGTs) between the nucleus and organelles, including plastids and mitochondria, constantly reshapes the nuclear genome during evolution. Despite the substantial contribution of IGTs to genome variation, the dynamic trajectories of IGTs at the pangenomic level remain elusive. Here, we propose a novel approach, IGTminer, to map the evolutionary trajectories of IGTs by collinearity and gene reannotation across multiple genome assemblies. IGTminer was applied to create a nuclear organelle gene (NOG) map across 67 genomes covering 15 Poaceae species, including important crops, revealing the polymorphisms and trajectory dynamics of NOGs. The NOGs produced were verified by experimental evidence and resequencing datasets. We found that most of the NOGs were recently transferred and lineage specific, and that Triticeae species tended to have more NOGs than other Poaceae species. Wheat had a higher retention rate of NOGs than maize and rice, and the retained NOGs were likely involved in the photosynthesis and translation pathways. Large numbers of NOG clusters were aggregated in hexaploid wheat during two rounds of polyploidization and contributed to the genetic diversities among modern wheat varieties. Finally, we proposed a radiocarbon-like model illustrating the transfer and elimination dynamics of NOGs, highlighting the unceasing integration and selective retention of NOGs over evolutionary time. In addition, we implemented an interactive webserver for NOG exploration in Poaceae. In summary, this study provides new resources and clues for the roles of IGTs in shaping inter- and intraspecies genome variation and driving plant genome evolution.

evolutionary biology↗

bioRxiv2022

Single-cell Atlas of Human Fetal Cerebellum Decoding Medulloblastoma Origin and Oncogenesis

Medulloblastoma (MB) is the most common malignant childhood brain tumor1,2, yet the origin of the most aggressive subgroup-3 form remains elusive, impeding development of effective targeted treatments. Previous analyses of mouse cerebella3,4 or human counterparts from frozen tissue nuclei5 have not fully defined the compositional heterogeneity of MBs. Here, we undertook an unprecedented single-cell profiling of freshly-isolated human fetal cerebella to establish a reference map delineating hierarchical cellular states in MBs. We identified a unique transitional cerebellar progenitor connecting neural stem cells to neuronal lineages in developing fetal cerebella. Intersectional analysis revealed that the transitional progenitors were enriched in aggressive MB subgroups, including group-3 and metastatic tumors. Single-cell multi-omics revealed underlying regulatory networks in the transitional progenitor populations, including transcriptional determinants HNRNPH1 and SOX11, which are correlated with clinical prognosis in group-3 MBs. Genomic and Hi-C profiling identified de novo long-range chromatin-loops juxtaposing HNRNPH1/SOX11-targeted super-enhancers to cis-regulatory elements of MYC, an oncogenic driver for group-3 MBs. Targeting the transitional progenitor regulators inhibited MYC expression and MYC-driven group-3 MB growth. Our integrated single-cell atlases of human fetal cerebella and MBs reveal potential cell populations predisposed to transformation and regulatory circuitries underlying tumor cell states and oncogenesis, highlighting hitherto unrecognized transitional progenitor intermediates predictive of disease prognosis and potential therapeutic vulnerabilities.

cancer biology↗

bioRxiv2022

Tumor landscape of epithelial ovarian cancer highlights that EGR1 drives tumor invasion at single-cell resolution

Identifying underlying molecular mechanisms and biomarkers of epithelial ovarian carcinoma (EOC) proliferation and metastasis remains challenging. Patients of EOC are usually diagnosed at an advanced stage and the availability of invasion-related targets is limited. Herein, we explored the single-cell RNA sequencing (scRNA-seq) dataset of EOC and defined tumor physiological reprograming compared to bulk RNA-seq. The energy metabolism and anti-apoptotic pathway was found as critical contributors to intratumor heterogeneity. Moreover, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis were positively correlated, which have biologically activity trajectories during epithelial mesenchymal transition (EMT). The HMGH1, EGR1 and RUNX1 were found to be critical inducers of the EMT process in EOC. Experimental validation revealed that suppressed EGR1 decreased the expression of FAS and HSPG2 and associating with EMT progression in EOC. In tumor microenvironment (TME), CAFs were found have significant contribution to tumor immune infiltration and metastasis and accumulation of CAFs was associated with poorer patient survival. In conclusion, physiological features and molecular mechanisms in the TME of EOC were revealed and provided effective targets for the suppression of tumor metastasis.

bioinformatics↗

bioRxiv2021

Inhibition of adrenergic b1-AR/Gas signaling promotes cardiomyocyte proliferation through activation of RhoA-YAP axis

The regeneration potential of the mammalian heart is incredibly limited, as cardiomyocyte proliferation ceases shortly after birth. {beta}-adrenergic receptor ({beta}-AR) blockade has been shown to improve heart functions in response to injury; however, the underlying mechanisms remain poorly understood. Here we inhibited {beta}-AR signaling in the heart using a cardiomyocyte specific {beta}1-adrenergic receptor ({beta}1-AR) blocker (metoprolol) to examine its role in heart maturation and regeneration at the neonatal stage. We found that metoprolol robustly enhanced cardiomyocyte proliferation and promoted cardiac regeneration post myocardial infarction, resulting in reduced scar formation and improved cardiac function. Moreover, the increased cardiomyocyte proliferation was also induced by the genetic deletion of Gnas, the gene encoding G protein alpha subunit (Gs), a downstream effector of {beta}-AR. Genome wide transcriptome analysis revealed that the cardiomyocytes of {beta}-blocker treated and Gnas cKO hearts maintained an immature proliferating status even at the young-adult age, and that the loss of Gs function enhanced the activity of the Hippo-effector YAP, which is associated with immature cardiomyocyte proliferation. Moreover, the increased YAP activity is modulated by RhoA signaling. Our pharmacological and genetic studies reveal a previously unrecognized {beta}1-AR-Gs-YAP signaling axis for regulating cardiac regeneration. These results suggest that inhibiting {beta}-AR-Gs signaling promotes the regenerative capacity and extends the cardiac regenerative window in mice by activating YAP-mediated transcriptional programs. Thus, targeting {beta}-AR-Gs signaling may serve as a novel therapeutic target for the treatment of ischemic heart.

developmental biology↗

bioRxiv2020

Transcriptome profiling reveals the mechanism of ripening and epidermal senescence in passionfruit (Passiflora edulia Sims)

Passion fruit (Passiflora edulia Sims), an important tropical and sub-tropical species, is classified as a respiration climacteric fruit, the quality deteriorates rapidly after harvest. To reveal the mechanisms involved in ripening and rapidly fruit senescence, the phytochemical characteristics and RNA sequencing were conducted in the purple passion fruits with different (1-MCP and PF) treatment. Comprehensive functional annotation and KEGG enrichment analysis showed that the starch and sucrose metabolism, plant hormone signal transduction, phenylpropanoid biosynthesis, flavonid biosynthesis, carotenoid biosynthesis were involved in fruit ripening. Applying with PF and 1-MCP significantly affected transcript levels of passion fruit after harvest storage. A large number of differently expressed unigenes (DEGs) were identified significantly enrichen in starch and sucrose metabolism, plant hormone signal transduction and phenylpropanoid biosynthesis at postharvest stage. The preservative film (PF) and 1-Methylcyclopropene (1-MCP) treatments increased superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD) gene expression and enzyme activities, accelerated the lignin accumulation, decline {beta}-galactosidase ({beta}-Gal), polygalacturonase (PG) and cellulose activities and gene expression to delay cell wall degradation during fruit senescence. The RNA sequencing data of cell wall metabolism and hormone signal transduction pathway related unigenes were verified by RT-qPCR. The results indicated that the cell wall metabolism and hormone signal pathways were notably related to passion fruit ripening. PF and 1-MCP treatment might inhibited ethylene signaling and regulated cell wall metabolism pathways to inhibited cell wall degradation. Our results reveal ripening and senescence related networks during passion fruit ripening, which can provide a foundation for understanding the molecular mechanisms underlying PF and 1-MCP treatment on fruit ripening.

plant biology↗

bioRxiv2020

Molecular mechanism of SARS-Cov-2 components caused ARDS in murine model

COVID-19 has become a major challenge to global health, and until now, no efficient antiviral agents have been developed. The SARS-CoV-2 infection is characterized by pulmonary and systemic inflammation in severe patients, and acute respiratory distress syndrome (ARDS) caused respiratory failure contributes to most mortalities. There is an urgent need for developing effective drugs and vaccines against SARS-CoV-2 and COVID-19 caused ARDS. However, most researchers cannot perform SARS-CoV-2 related researches due to lacking P3 or P4 facility. We developed a non-infectious, highly safety, time-saving SARS-CoV-2 components induced murine model to study the SARS-CoV-2 caused ARDS and cytokine storm syndrome (CSS). We also investigated mAbs and inhibitors which potentially neutralize the pro-inflammatory phenotype of COVID-19, and found that anti-IL-1, anti-IL-6, anti-TNF, anti-GM-CSF mAbs, p38 inhibitor, and JAK inhibitor partially relieved CSS. Besides, anti-IL-6, anti-TNF, anti-GM-CSF mAbs and inhibitors of p38, ERK, and MPO somewhat reduced neutrophilic alveolitis in the lung. In all, we established the murine model mimic of COVID-19, opening a biosafety and less time-consuming avenue for clarifying the mechanism of ARDS and CSS in COVID-19 and developing the therapeutic drugs.

pathology↗

bioRxiv2019

A web-server framework to explore and visualize large genomic variation data in lab and its applications to wheat and its progenitors

BackgroundThe cost of high-throughput sequencing is rapidly decreasing, allowing researchers to investigate genomic variations across hundreds or even thousands of samples in the post-genomic era. The management and exploration of these large-scale genomic variation data require programming skills. The public genotype querying databases of many species are usually centralized and implemented independently, making them difficult to update with new data over time. Currently, there is a lack of a widely used framework for setting up user-friendly web servers for exploring new genomic variation data in diverse species. ResultsHere, we present SnpHub, a Shiny/R-based server framework for retrieving, analysing and visualizing the large-scale genomic variation data that be easily set up on any Linux server. After a pre-building process based on the provided VCF files and genome annotation files, the local server allows users to interactively access SNPs/INDELs and annotation information by locus or gene and for user-defined sample sets through a webpage. Users can freely analyse and visualize genomic variations in heatmaps, phylogenetic trees, haplotype networks, or geographical maps. Sample-specific sequences can be accessed as replaced by SNPs/INDELs. ConclusionsSnpHub can be applied to any species, and we build up a SnpHub portal website for wheat and its progenitors based on published data in present studies. SnpHub and its tutorial are available as http://guoweilong.github.io/SnpHub/.

bioinformatics↗

bioRxiv2019

Extension of the in vivo haploid induction system from diploid maize to hexaploid wheat

Doubled haploid breeding technology has been one of the most important techniques for accelerating crop breeding. In compare to in vivo haploid induction in maize, which is efficient and background independent, wheat haploid production by interspecific hybridization pollinated with maize is influenced by genetic background and requires rescue of young embryos. Here, we analyzed the homologues of maize haploid induction gene MTL/ZmPLA1/NLD in several crop species systematically, the homologues are highly conserved in sorghum, millet and wheat etc. Since wheat is a very important polyploidy crop, as a proof of concept, we demonstrated that the in vivo haploid induction method could be extended from diploid maize to hexaploid wheat by knocking out the wheat homologues (TaPLAs). Result showed that double knock-out mutation could trigger wheat haploid induction at ~ 2%-3%, accompanied by 30% - 60% seed setting rate. The performance of haploid wheat individual showed shorter plant, narrower leaves and male sterile. Our results also revealed that knockout of TaPLA-A and TaPLA-D do not affect pollen viability. This study not only confirmed the function of the induction gene and explored a new approach for haploid production in wheat, but also provided an example that the in vivo haploid induction could be applied in more crop species with different ploidy levels. Furthermore, by combining with gene editing, it would be a fast and powerful platform for traits improvement in polyploidy crops breeding.

plant biology↗