Biology subjects

Zhao, X.

Publications and source records attributed to Zhao, X..

At least 199 records · Page 11Linked to original sources

bioRxiv2024

Zebrahub-Multiome: Uncovering Gene Regulatory Network Dynamics During Zebrafish Embryogenesis

During embryonic development, gene regulatory networks (GRNs) drive molecular differentiation of cell types. However, the temporal dynamics of these networks remain poorly understood. Here, we present Zebrahub-Multiome, a single-cell multiomic atlas that captures chromatin accessibility and gene expression from 94,562 cells across six stages of zebrafish embryogenesis (10-24 hours post-fertilization), capturing key developmental stages from the end of gastrulation to the onset of organogenesis. By measuring regulatory element activity alongside transcriptional output from the same cells, we identify 640,000 cis-regulatory elements organized into 402 hierarchically structured modules corresponding to specific developmental pathways. Early embryonic stages employ broadly shared regulatory programs that progressively fragment into lineage-specific modules. Timeresolved gene regulatory network inference reveals that transcription factors undergo functional transitions - from multilineage regulators to specialized, lineage-committed factors. These quantitative measurements reveal the regulatory network rewiring that drives cell fate specification. Our interactive web portal (zebrahub.org/epigenomics) enables exploration of gene dynamics, regulatory networks, and perturbation predictions, providing a quantitative framework for understanding vertebrate developmental regulation.

developmental biology↗

bioRxiv2024

TET2 contributes to gluconeogenesis and pathology of type 2 diabetes

The control of gluconeogenesis is critical for glucose homeostasis and the pathology of type 2 diabetes (T2D). Here, we uncover a novel function of TET2 in the regulation of gluconeogenesis. In mice, both fasting and a high-fat diet (HFD) stimulate the expression of TET2, and TET2 knockout impairs glucose production. Mechanistically, FBP1, a rate-limiting enzyme in gluconeogenesis, is positively regulated by TET2 in liver cells. TET2 is recruited by HNF4, contributing to the demethylation of FBP1 promoter and activating its expression in response to glucagon stimulation. Moreover, metformin treatment increases the phosphorylation of HNF4 on Ser313, which prevents its interaction with TET2, thereby decreasing the expression level of FBP1 and ameliorating the pathology of T2D. Collectively, we identify an HNF4-TET2-FBP1 axis in the control of gluconeogenesis, which contributes to the therapeutic effect of metformin on T2D and provides a potential target for the clinical treatment of T2D.

cell biology↗

bioRxiv2024

Complex genetic variation in nearly complete human genomes

Diverse sets of complete human genomes are required to construct a pangenome reference and to understand the extent of complex structural variation. Here, we sequence 65 diverse human genomes and build 130 haplotype-resolved assemblies (130 Mbp median continuity), closing 92% of all previous assembly gaps1,2 and reaching telomere-to-telomere (T2T) status for 39% of the chromosomes. We highlight complete sequence continuity of complex loci, including the major histocompatibility complex (MHC), SMN1/SMN2, NBPF8, and AMY1/AMY2, and fully resolve 1,852 complex structural variants (SVs). In addition, we completely assemble and validate 1,246 human centromeres. We find up to 30-fold variation in -satellite high-order repeat (HOR) array length and characterize the pattern of mobile element insertions into -satellite HOR arrays. While most centromeres predict a single site of kinetochore attachment, epigenetic analysis suggests the presence of two hypomethylated regions for 7% of centromeres. Combining our data with the draft pangenome reference1 significantly enhances genotyping accuracy from short-read data, enabling whole-genome inference3 to a median quality value (QV) of 45. Using this approach, 26,115 SVs per sample are detected, substantially increasing the number of SVs now amenable to downstream disease association studies.

genomics↗

bioRxiv2024

snCED-seq: High-fidelity cryogenic enzymatic dissociation of nuclei for single-nucleus RNA-seq of FFPE tissues

Profiling cellular heterogeneity in formalin-fixed paraffin-embedded (FFPE) tissues is key to characterizing clinical specimens for biomarkers, therapeutic targets, and drug responses. Recent advancements in single-nucleus RNA sequencing (snRNA-seq) techniques tailored for FFPE tissues have demonstrated their feasibility. However, isolation of high-quality nuclei from FFPE tissue with current methods remains challenging due to RNA cross-linking. We, therefore, proposed a novel strategy for the preparation of high-fidelity nuclei from FFPE samples, cryogenic enzymatic dissociation (CED) method, and performed snRandom-seq (snCED-seq) for polyformaldehyde (PFA)-fixed and FFPE brains to verify its applicability. The method is compatible with both PFA-based and FFPE brains or other organs with less hands-on time and lower reagent costs, and produced 10 times more nuclei than the homogenate method, without secondary degradation of RNA, and maximized the retention of RNA molecules within nuclei. snCED-seq shows 1.5-2 times gene and UMI numbers per nucleus, higher gene detection sensitivity and RNA coverage, and a minor rate of mitochondrial and ribosomal genes, compared with the nuclei from traditional method. The correlation gene expression of nucleus from the post-fixed and the frozen sample can be up to 94 %, and the gene expression of our nuclei was more abundant. Moreover, we applied snCED-seq to cellular heterogeneity study of the specimen on Alzheimers Disease (AD) to demonstrate a pilot application. Scarce Cajal Retzius cells in older mice were robustly detected in our data, and we successfully identified two subpopulations of disease-associated in astrocytes, microglia and oligodendrocytes, respectively. Meanwhile, we found that most cell types are affected at the transcriptional level by AD pathology, and there is a disease susceptibility gene set that affects these cell types similarly. Our method provides powerful nuclei for snRNA-seq studies for FFPE specimens, and even helps to reveal multi-omics information of clinical samples.

bioengineering↗

bioRxiv2024

Integrated Transcriptome and Metabolome Analyses Reveal the Mechanism Regulating Bulbil Initiation and Development in Cystopteris chinensis

Cystopteris chinensis is an endangered fern endemic to China, which only has a small wild population due to its poor reproductive ability. However, we recently found that it can produce bulbils on its pinnule to generate new plants but the molecular mechanism underlying this unique phenomenon remained unknown. In this study, we have identified four distinct stages in the initiation and development of bulbils based on morphological and anatomical observation. We performed transcriptome and metabolome analyses on the collected samples at each stage. Through KEGG enrichment analysis, it was found that the phytohormone signal transduction, starch and sucrose metabolism, phenylpropanoid biosynthesis, and flavonoid biosynthesis pathways play a significant role in regulating bulbil initiation and development. Specifically, the involvement of three phytohormones and sugar substances was identified in the process of bulbil initiation. Our study provides the first detailed observation of the bulbils in C. chinensis and explains their initiation and development at the molecular level. However, more in-depth studies are needed to discover the functions of key genes controlling the formation of bulbils to conserve the endangered C. chinensis population.

plant biology↗

bioRxiv2024

m6AConquer: a Data Resource for Unified Quantification and Integration of m6A Detection Techniques

N6-methyladenosine (m6A) is the most prevalent RNA modification in mammalian cells and the most extensively studied epitranscriptomic mark. More than 10 m6A detection techniques have been proposed to measure m6A stoichiometry at either the site or peak level. However, these detection techniques are processed through heterogeneous pipelines, using different computational filters and reference features, leading to difficulties in fully harnessing data integration and analysis across orthogonal m6A detection techniques. Our m6AConquer (Consistent Quantification of External m6A RNA Modification Data) tackles this challenge by establishing a consistent multi-omics data-sharing standard, summarizing quantitative m6A data from 10 detection techniques using a unified reference feature set. Furthermore, we standardize site calling and m6A count matrix normalization procedures across platforms through a computational framework that accounts for over-dispersion in m6A levels. Available m6A detection techniques can be categorized into four types: antibody-assisted, chemical-assisted, enzyme-assisted, and direct-RNA sequencing. We leverage this categorization to develop a reproducibility-based integration framework that enables the reliable detection of high-confidence m6A sites confirmed across orthogonal techniques. Empirical evaluations report that both the site-calling and the integration framework outperform common alternatives, enhancing biological relevance. We apply interpretable machine learning models on our integrated high-confidence sites, and the result consistently identify proximity to intron-exon junctions as the driving predictor of m6A site coordinates across different techniques, demonstrating the high quality of the data curated in m6AConquer. m6AConquer webserver is freely accessible under: http://rnamd.org/m6aconquer. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/612173v1_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@f9d1a8org.highwire.dtl.DTLVardef@1339b41org.highwire.dtl.DTLVardef@115ececorg.highwire.dtl.DTLVardef@7580aa_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Ultrack: pushing the limits of cell tracking across biological scales

Tracking live cells across 2D, 3D, and multi-channel time-lapse recordings is crucial for understanding tissue-scale biological processes. Despite advancements in imaging technology, achieving accurate cell tracking remains challenging, particularly in complex and crowded tissues where cell segmentation is often ambiguous. We present Ultrack, a versatile and scalable cell-tracking method that tackles this challenge by considering candidate segmentations derived from multiple algorithms and parameter sets. Ultrack employs temporal consistency to select optimal segments, ensuring robust performance even under segmentation uncertainty. We validate our method on diverse datasets, including terabyte-scale developmental time-lapses of zebrafish, fruit fly, and nematode embryos, as well as multi-color and label-free cellular imaging. We show that Ultrack achieves state-of-the-art performance on the Cell Tracking Challenge and demonstrates superior accuracy in tracking densely packed embryonic cells over extended periods. Moreover, we propose an approach to tracking validation via dual-channel sparse labeling that enables high-fidelity ground truth generation, pushing the boundaries of long-term cell tracking assessment. Our method is freely available as a Python package with Fiji and napari plugins and can be deployed in a high-performance computing environment, facilitating widespread adoption by the research community.

developmental biology↗

bioRxiv2024

Identification of a new ORF3a-E fusion subgenomic RNA of SARS-CoV-2 and its biological features in the infection process

Subgenomic RNAs (sgRNAs) are discontinuous transcription products of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that are involved in viral gene expression and replication, but their exact functions are still being studied. Here, we report the identification of a new type of sgRNA, the fusion ORF3a-E-sgRNA, involved in the infection process of SARS-CoV-2. This sgRNA codes both ORF3a and E and can be detected throughout the viral life cycle in SARS-CoV-2-infected cells with high copy numbers. ORF3a-E-sgRNA guides more ORF3a translation and promotes the expression of cellular ribosomal protein S3 (RPS3) and the binding of eukaryotic translation initiation factor 4E (eIF4E). Single-cell sequencing of a SARS-CoV-2-infected human bronchial epithelial cell line (16HBE) revealed that maintenance of this stable translational environment by ORF3a-E-sgRNA is important for the SARS-CoV-2 assembly and release capabilities and is also beneficial for viral evasion of host innate immunity. More importantly, the transcription level of ORF3a-E-sgRNA contributes to differences in infection processes between the Wuhan strain and XBB strain of SARS-CoV-2.

microbiology↗

bioRxiv2024

MED26-enriched condensates drive erythropoiesis through modulating transcription pausing

The Mediator complex regulates various aspects of hematopoietic development, but whether composition of the Mediator complex undergoes dynamic changes for diversifying transcription and functional outputs is unknown. Here, we found that MED26, a subunit in the core Mediator complex, played a distinctive role in facilitating transcription pausing essential for erythroid development. While most Mediator subunits drastically decreased during this process, MED26 remained relatively abundant. Intriguingly, in the early stages, more than half of MED26 occupancy sites did not co-localize with MED1, a representative Mediator subunit, suggesting these subunits exert context-dependent gene regulation. We revealed that MED26-enriched loci were associated with RNA polymerase pausing. MED26 manifested a markedly preferential recruitment of pausing-related factors, leading to an increase in Pol pausing critical for genome-wide transcription repression during erythropoiesis. Moreover, MED26 exhibited pronounced condensate-forming capability, which was necessary for its function in promoting erythropoiesis and recruiting pausing-related factors. Collectively, this study provides mechanistic insights into the functional coordination of distinct Mediator subunits during development and highlights the switch of transcription condensates towards a MED26 enriched form, which modulates transcription pausing to facilitate transcription repression and erythroid development.

cell biology↗

bioRxiv2024

Modeling statin-induced myopathy with human iPSCs reveals that impaired proteostasis underlies the myotoxicity and is targetable for the prevention

Statins, HMG-CoA reductase inhibitors, have been widely prescribed to lower circulating low-density lipoprotein cholesterol levels and reduce the risk of cardiovascular disease. Although statins are well tolerated, statin-associated muscle symptoms (SAMS) are the major adverse effect and cause statin intolerance. Therefore, understanding the molecular mechanisms of SAMS and identifying effective strategies for its prevention are of significant clinical importance; however, both remain unclear. Here we establish a model of statin-induced myopathy (SIM) with human induced pluripotent stem cell (hiPSC)-derived myocytes (iPSC-MCs) and investigate the effect of statins on protein homeostasis (proteostasis) that affects skeletal muscle wasting and myotoxicity. We show that treating hiPSC-MCs with statins induces atrophic phenotype and myotoxicity, establishing a hiPSC-based SIM model. We then examine whether statins impair the balance between protein synthesis and degradation. The results show that statins not only suppress protein synthesis but also promote protein degradation by upregulating the expression of the muscle-specific E3 ubiquitin ligase Atrogin-1 in a mevalonate pathway-dependent manner. Mechanistically, blocking the mevalonate pathway inactivates the protein kinase Akt, leading to the inhibition of mTORC1 and GSK3{beta} but the activation of FOXO1. These changes explain the statin-induced impairment in proteostasis. Finally, we show that pharmacological blockage of FOXO1 prevents SIM in hiPSC-MCs, implicating FOXO1 as a key mediator of SIM. Taken together, this study suggests that the mevalonate pathway is critical for maintaining skeletal muscle proteostasis and identifies FOXO1 as a potential target for preventing SIM.

pharmacology and toxicology↗

bioRxiv2024

MagnoliidsGDB：An integrated functional genomics database for Magnoliids

In this study, we present MagnoliidsGDB, an integrated functional genomics database specifically developed for magnoliids, a group of plants known for their unique characteristics and medicinal properties. As of March 2024, MagnoliidsGDB has collected 31 genome sequences from 24 species, 149 resequencing datastes from 4 species, 842 transcriptomic datasets from 20 species, and metabolomic data from 15 species. This comprehensive resource allows researchers to explore the genomic, transcriptomic, and metabolomic variations of magnoliids. The user-friendly search and analysis functionalities of MagnoliidsGDB facilitate the study of genomic variations, gene functions, plant evolution and key metabolites of magnoliids. We hope this database will contribute to the study of magnoliids and increase our understanding of the origin, variation, and molecular basis of the unique biological features of magnoliids.

evolutionary biology↗

bioRxiv2024

Indiv-Brain: Individualized Brain Network Partition Learned from Individual fMRI Data using Deep Clustering with Vertex-level Attention

Individualized functional network partitioning is increasingly critical in elucidating individual differences in cognition, development, and behavior. The previous studies grouped brain regions that were pre-defined by common brain parcellations into individualized brain networks. The employment of common brain region parcellations ignores the individual variations in brain structure and reduces the spatial resolution of the results. Moreover, some studies trained models on a group of subjects to guide individual network partitioning. These methods largely depend on the sample size and encounter challenges in the case of limited subject data. In this paper, we propose Indiv-Brain which automatically partition brain vertices into different brain networks based on individual fMRI data without any prior brain parcellation. The Indiv-Brain consists of three sequential modules: stacked denoising autoencoder (SDAE) for mapping the raw fMRI data to a latent embedding space, masked vertex modeling (MVM) for learning attention-enhanced representations of brain vertices, and deep embedding clustering with spatial attention (DEC-A) for unsupervised clustering on the learned vertex representations. The experiments on Human Connectome Project (HCP) demonstrate that the accuracy of Indiv-Brain outperforms existing methods. We compared the model with methods like SDAE, DEC, IDEC, and k-means. For the results of 8 subjects, the accuracy of Indiv-Brain was consistently the highest, averaging 6.65 percentage points higher than the IDEC method. To the best of our knowledge, this is the first study to obtain individualized brain network partition based on individual fMRI data with deep learning models. Our study provides a novel insight into understanding individualized brain networks, especially suitable for special patients.

neuroscience↗

bioRxiv2024

DeepSME: De Novo Nanopore Basecalling of Motif-insensitive DNA Methylation and Alignment-free Digital Information Decryptions at Single-Molecule Level

Hidden messages in DNA molecules by employing chemical modifications has been suggested for private data storage and transmission at high information density. However, rapidly decoding these "molecular keys" with corresponding basecallers remains challenging. We present DeepSME, a nanopore sequencing and deep-learning based framework towards single-molecule encryption, demonstrated by using 5-hydroxymethylcytosine (5hmC) substitution for individual nucleotide recognition rather than sequential interactions. This non-natural, motif-insensitive methylation disrupts ion current, resulting in a readout failure of 67.2%-100%, concealing the privacy within the DNAs. We further develop an alignment-free DeepSME basecaller as a key to reconstitute the digital information. Our three-stage training pipeline, expands k-mer size from 46 to 49, achieving over 92% precision and recall from scratch. DeepSME deciphers fully 5hmC concealed text and image within 16x coverage depth with an F1-score of 86.4%, surpassing all the state-of-the-art basecallers. Demonstrated on edge computing devices, DeepSME holds supreme potential for DNA-based private communications and broader bioengineering and medical applications.

bioinformatics↗

bioRxiv2024

Genetic differentiation and adaptive evolution of buff-tailed bumblebees in Asia

Bumblebees are ecologically and economically important pollinating insects, so their declines resulting from environmental changes have received intensive attention. Understanding how environmental factors shape the genetic differentiation of natural populations and identifying the genetic basis of local adaptation will provide insights into how species may cope with environmental changes. The buff-tailed bumblebee (Bombus terrestris) has a wide natural distribution range and has been successfully domesticated to produce commercial colonies for greenhouse pollination. Previous population genetics studies on B. terrestris have mainly focused on populations in Europe; however, populations in Asia, representing the eastern side of its natural distribution, have been less thoroughly sampled. To fill this gap, we collected wild B. terrestris samples from Asia, as well as wild B. terrestris from Europe and samples from domesticated colonies. We conducted whole-genome resequencing for 77 collected B. terrestris workers and performed population genomics analysis. Our results revealed significant genetic differentiation (FST= 0.076) between buff-tailed bumblebees in Europe and Asia, along with notable morphological and physiological differences. Consequently, B. terrestris in Asia represents a distinct new genetic resource. Demographic analysis suggested that the population size of buff-tailed bumblebees had increased during historic cold periods, confirming their cold-adapted characteristics. Selective sweep analysis identified 331 genes under selection in the genomes of Asian B. terrestris, likely involved in their adaptation to high ultraviolet radiation, low temperature, and low precipitation in their habitats. Our research provides insights into the population genetic structure and genetic basis of local adaptation in the buff-tailed bumblebee, which will be useful for its conservation and management.

bioinformatics↗

bioRxiv2024

PMS2 has both pro-mutagenic and anti-mutagenic effects on repeat instability in the Repeat Expansion Diseases

Expansion of a disease-specific tandem repeat is responsible for >45 Repeat Expansion Diseases (REDs). The expansion mutation in each of these diseases has different pathological consequences and most are currently incurable. If the underlying mechanism of mutation is shared, a strategy that slows repeat expansion in one RED may be applicable to multiple REDs. However, the fact that PMS2, a component of the MutL mismatch repair complex, promotes expansion in some models and protects against it in others suggests that the expansion mechanisms may differ. We show here using mouse models of two REDs caused by different repeats that PMS2 has similar effects in both models, with the loss of PMS2 resulting in an increase in expansions in some tissues and a loss of expansion in others. This is consistent with a protective effect of PMS2 in the first case and a role in promoting expansion in the second. Furthermore, we show in mouse embryonic stem cells that lower levels of PMS2 promote expansion while higher levels protect against it, with the ability to promote expansion depending on the PMS2 nuclease domain. Our findings lend support to the hypothesis that REDs share a common expansion mechanism and provide insights into the processes involved. Significance statementCollectively the Repeat Expansion Diseases (REDs) represent a significant health burden. Since the consequences of the expansion mutation differ across diseases, therapeutic approaches that block the underlying mutation are appealing, particularly if the mechanism is shared. However, the conflicting effects of PMS2 loss in different RED models challenges this idea. Here we show using two different RED models that these disparate effects can be reconciled into a single model of repeat expansion, thus increasing confidence that the REDs do all share a common mutational mechanism.

genetics↗

bioRxiv2024

Causal Associations of Circulating Helicobacter pylori Antibodies with 5 Skin Disorders: A Mendelian Randomization Analysis

Helicobacter pylori (H. pylori) infection, a prevalent bacterial ailment affecting the stomach, has been linked to diverse gastrointestinal disorders. Nevertheless, the correlation between H. pylori infection and skin disorders has not been definitively established. We use Mendelian randomization analysis to explore causal relationships with seven pylori antibody levels and five skin diseases, such as rosacea, psoriasis, alopecia areata, pruritus and urticaria. The primary analytical method employed was inverse variance weighted (IVW), and a sensitivity analysis was executed to evaluate the robustness of the primary findings. The results revealed a positive causal relationship between H. pylori catalase antibody levels and AA (IVW: OR = 1.32, 95% CI = 1.07 to 1.61, P = 0.008), as well as a positive causal relationship between H. pylori UreA antibody levels and pruritus (IVW: OR = 1.17, 95% CI = 1.05 to 1.31, P = 0.006). These effects were robust to sensitivity analyses. Our results suggested that H. pylori infection was a risk factor for AA and pruritus. This finding may have implications for the prevention and treatment of these skin disorders.

genomics↗

bioRxiv2024

Stromal KITL/SCF promotes pancreas tissue homeostasis and restrains tumor progression

Components of normal tissue architecture serve as barriers to tumor progression. Inflammatory and wound-healing programs are requisite features of solid tumorigenesis, wherein alterations to immune and non-immune stromal elements enable loss of homeostasis during tumor evolution. The precise mechanisms by which normal stromal cell states limit tissue plasticity and tumorigenesis, and which are lost during tumor progression, remain largely unknown. Here we show that healthy pancreatic mesenchyme expresses the paracrine signaling molecule KITL, also known as stem cell factor, and identify loss of stromal KITL during tumorigenesis as tumor-promoting. Genetic inhibition of mesenchymal KITL in the contexts of homeostasis, injury, and cancer together indicate a role for KITL signaling in maintenance of pancreas tissue architecture, such that loss of the stromal KITL pool increased tumor growth and reduced survival of tumor-bearing mice. Together, these findings implicate loss of mesenchymal KITL as a mechanism for establishing a tumor-permissive microenvironment. Statement of significanceBy analyzing transcriptional programs in healthy and tumor-associated pancreatic mesenchyme, we find that a sub-population of mesenchymal cells in healthy pancreas tissue express the paracrine signaling factor KITL. Loss of mesenchymal KITL is an accompanying and permissive feature of pancreas tumor evolution, with potential implications for cancer interception.

cancer biology↗

bioRxiv2024

Overcrowding Drives Tumor Invasion by Inducing Nanotopographical Transition of Plasma Membrane

During the progression from epithelial neoplasms to invasive carcinoma, cells are subjected to prolonged confinement. However, the response of cancer cells to such mild yet sustained compressive pressure during the initial stages of tumor invasion remain poorly understood. Here, using a spontaneous crowding model to recapitulate the progressive compressive stress caused by cell proliferation, we demonstrated that prolonged crowding alone is sufficient to induce the acquisition of an invasive phenotype and associated gene expression patterns in cancer cells. This invasiveness persisted even after cells were removed from the crowded environment, a phenomenon mediated by mechanomemory. By combining genetic manipulations, mechanical modeling, and biophysical measurements, we revealed that the disaggregation of membrane domains--driven by a nanoscale smooth-corrugated topography transition of plasma membranes induced by Laplace pressure under crowded conditions--is essential for initiating cancer cell invasion. Inhibiting membrane domains disaggregation through membrane-to-cortex-attachment effectively suppresses cancer cell invasion in both cellular crowding models and mouse xenograft models. This study underscores the critical role of tissue-scale mechanics in regulating the biophysics of mechanosensitive membrane domains during the early stages of tumor invasion.

cancer biology↗