Biology subjects

zhang, w.

Publications and source records attributed to zhang, w..

11 recordsLinked to original sources

bioRxiv2026

Noncanonical Circular RNAs and Potential Functions

Circular RNAs (circRNAs) are ubiquitous in eukaryotes; dysregulated circRNA expression is linked to diseases, including lung cancer. In contrast to canonical circRNAs arising from exon-intron boundaries, noncanonical circRNAs originating within exonic, intronic, and intergenic regions have typically been dismissed as transcriptional noise or technical artifacts. To explore circRNA diversity and appreciate their functions, we developed an algorithm to identify both canonical and noncanonical circRNAs without relying on genome annotation, enabling the identification of circRNAs of all types and in newly sequenced or poorly annotated species. Results from lung cancer cells revealed that noncanonical circRNAs constituted over two-thirds of the circRNA population and were expressed more abundantly than canonical circRNAs, and genes with fewer and shorter exons were hotspots for noncanonical circRNA and circRNA isoform production. Further analyses showed that many noncanonical circRNAs were indeed endogenous circRNAs transcribed within cells rather than experimental artifacts, were potentially translated into proteins or peptides, and were conserved across species. Moreover, we validated 65 noncanonical circRNAs in NCI-H23 cells using multiple bioassays and demonstrated that both exonic and intergenic noncanonical circRNAs influenced cell viability. CircRNA profiles in tumor and tumor-adjacent tissues of lung cancer patients revealed tissue-specific expression and differentially expressed canonical and noncanonical circRNAs from cognate genes involved in cancer-related pathways, indicating their potential clinical relevance. This study confirmed the authenticity of noncanonical circRNAs and provided the first experimental evidence that noncanonical circRNAs influence cancer cell phenotypes. These findings broaden our understanding of circRNA biology, highlighting their widespread genomic distribution, diverse functions, and potential clinical relevance.

molecular biology↗

bioRxiv2025

Comparison of QuPath and HALO platforms for analysis of the tumor microenvironment in prostate cancer

QuPath, an open-source digital pathology platform, has gained widespread use for image analysis in biomedical research since its release in 2016. However, its reproducibility and reliability compared to commercial software, such as HALO, requires further validation, particularly for multiplex immunofluorescence (mIF) analysis. In this study, we performed a direct comparison of QuPath and HALO using a mIF-stained prostate cancer tissue microarray (TMA) inclusive of 192 unique cores. We evaluated performance across three key analytical modules: immune cell phenotyping, tumor infiltration with immune cells, and nearest neighbor analysis. Furthermore, we integrated QuPath with CytoMap, an open-source spatial analysis tool, to perform unsupervised clustering of immune cell infiltration--a feature not available in HALO. Our results demonstrated high concordance between two platforms, with correlation coefficients exceeding 0.89 for immune cell density, distance and pattern of cell organization in tumor microenvironment (TME). A neighborhood analysis using CytoMap was further performed and provided a more detailed spatial analysis of immune cell distribution across different prostate cancer grades. A significant increase of CD103+ T cell infiltration into TME was observed in prostate cancer, which might be associated with the expression level of its ligand (E-cadherin) in the tumor region. In conclusion, our findings validate QuPath as a robust and reproducible alternative to commercial platforms for fluorescence-based digital pathology. By demonstrating QuPaths capability to perform high-quality quantitative analysis with additional flexibility for integration with external tools, our study underscores its potential for advancing tumor microenvironment research in translational oncology.

pathology↗

bioRxiv2024

Ultrastable and Versatile FoxP3 Ensembles on Microsatellites

Microsatellites are essential genomic components increasingly linked to transcriptional regulation. FoxP3, a transcription factor critical for regulatory T cell (Treg) development, recognizes TTTG repeat microsatellites by forming multimers along DNA. However, FoxP3 also binds a broader range of TnG repeats (n=2-5), often at the edges of accessible chromatin regions. This raises questions about how FoxP3 adapts to sequence variability and the potential role of nucleosomes. Using cryo-electron microscopy and single-molecule analyses, we show that FoxP3 assembles into distinct supramolecular structures depending on DNA sequence. This structural plasticity enables FoxP3 to bridge 2-4 DNA duplexes, forming ultrastable structures that coordinate multiple genomic loci. Nucleosomes further facilitate FoxP3 assembly by inducing local DNA bending, creating a nucleus that recruits distal DNA elements through multiway bridging. Our findings thus reveal FoxP3s unusual ability to shapeshift to accommodate evolutionarily dynamic microsatellites and its potential to reinforce chromatin boundaries and three-dimensional genomic architecture.

biochemistry↗

bioRxiv2024

Complex genetic architecture underlying the plasticity of tobacco leaf width provides insight into across-environment genomic prediction

Phenotypic plasticity refers to the ability of a given genotype to produce multiple phenotypes in response to changing environmental conditions. Understanding the genetic basis of phenotypic plasticity and developing predictive models for agronomic traits are crucial for future agricultural adaptation to climate change. In this study, we investigated the genetic basis of leaf width mean (LWm) and plasticity (LWp) in a tobacco multiparent advanced generation inter-cross (MAGIC) population which consisting of 594 individuals. We identified 14 quantitative trait loci (QTLs) significantly associated with LWm, 43 with LWp. Our findings suggest that dynamic changes in QTL effects across environments, along with polygenic effects, may underlie the genetic basis of leaf width plasticity. Among them, qLW14 was narrowed down to a 3 Mb structural variation region. When this fragment was deleted in tobacco, plants exhibited increased leaf width, but only under specific environmental conditions. This finding suggests that the key gene within qLW14 may act as a negative regulator of leaf width through interactions with specific environmental factors. By integrating genetic diversity, environments variation, and their interactions into a GEAI model, we were able to build a framework for cross-environment prediction, improving prediction accuracy by 8.7% when compared to traditional model. Overall, this study highlights the complex genetic basis underlying LWp, involving multiple alleles and genotype-environment interactions. These findings provide valuable insights into the role of phenotypic plasticity in plant adaptation to environmental changes.

genetics↗

bioRxiv2024

Inferring gene regulatory networks by hypergraph variational autoencoder

In constructing Gene Regulatory Networks (GRNs), it is crucial to consider cellular heterogeneity and differential gene regulatory modules. However, traditional methods have predominantly focused on cellular heterogeneity, approaching the subject from a relatively narrow scope. We present HyperG-VAE, a Bayesian deep generative model that utilizes a hypergraph to model single-cell RNA sequencing (scRNA-seq) data. HyperG-VAE employs a cell encoder with a Structural Equation Model to address cellular heterogeneity and build GRNs, alongside a gene encoder using hypergraph self-attention to identify gene modules. Encoders are synergistically optimized by a decoder, enabling HyperG-VAE to excel in GRN inference, single-cell clustering, and data visualization, evidenced by benchmarks. Additionally, HyperG-VAE effectively reveals gene regulation patterns and shows robustness in varied downstream analyses, demonstrated using B cell development data in bone marrow. The interplay of encoders by the overlapping genes between predicted GRNs and gene modules is further validated by gene set enrichment analysis, underscoring that the gene encoder boosts the GRN inference. HyperG-VAE proves efficient in scRNA-seq data analysis and GRN inference.

bioinformatics↗

bioRxiv2023

Microglial IL-1β plays a protective role in epilepsy

Epilepsy is a neurological disorder characterized by recurrent seizures that affect about 50 million people worldwide. Although the exact mechanisms underlying epilepsy remain elusive, it is known that neuroinflammation contributes to the pathogenesis of the disease. Microglia, the resident immune cells of the central nervous system, play a key role in neuroinflammation and are activated in response to seizures. Interleukin-1{beta} (IL-1{beta}) is a pro-inflammatory cytokine produced by microglia and other immune cells. While IL-1{beta} has been implicated in the pathogenesis of various neurological disorders, recent studies have revealed a protective role for microglial IL-1{beta} in epilepsy. This paper aims to review the current knowledge about microglial IL-1{beta} and its potential therapeutic implications for epilepsy.

molecular biology↗

bioRxiv2022

Comprehensive investigation and regulatory function of lncRNAs engaged in western honey bee larval immune response to Ascosphaera apis invasion

Ascosphaera apis is a fungal pathogen that exclusively infects bee larvae, causing chalkbrood disease, which results in severe damage for beekeeping industry. Long non-coding RNAs (lncRNAs) are versatile regulators in various biological processes such as immune defense and host-pathogen interaction. However, expression pattern and regulatory role of lncRNAs involved in immune response of bee host to A. apis invasion is still very limited. Here, Apis mellifera ligustica 4-, 5-, and 6-day-old larvae inoculated by A. apis spores (AmT1, AmT2, and AmT3 groups) and corresponding un-inoculated larval guts (AmCK1, AmCK2, and AmCK3 groups) were prepared and subjected to deep sequencing, followed by identification of lncRNAs, analysis of differentially expressed lncRNAs (DElncRNAs), and investigation of DElncRNA-regulated host immune responses. In total, 3 746 A. m. ligustica lncRNAs were identified, including 78 sense lncRNAs, 891 antisense lncRNAs, 1 893 intergenic lncRNAs, 346 bidirectional lncRNAs, and 210 intronic lncRNAs. Compared with corresponding un-inoculated larval guts, 357, 236, and 505 DElncRNAs were discovered in the A. apis-inoculated 4-, 5-, and 6-day-old larval guts. Additionally, there were 32 shared DElncRNAs. In AmCK1 vs AmT1, AmCK2 vs AmT2, and AmCK3 vs AmT3 comparison groups, 217, 129, and 272 DElncRNAs were respectively predicted to regulate neighboring genes via cis-acting manner, and these targets were associated with a series of GO terms and KEGG pathways of great importance, such as response to stimulus and Jak-STAT signal pathway. Moreover, competing endogenous RNA (ceRNA) network analysis indicated that 197, 95, and 356 DElncRNAs in the aforementioned three comparison groups could target 10, eight, and 21 DEmiRNAs and further target 147, 79, and 315 DEmRNAs, forming complex regulatory networks. Further investigation suggested that these targets were relevant to several key cellular and humoral immune pathways, such as phagosome and MAPK signaling pathway. Ultimately, the expression trends of nine randomly selected DElncRNAs were verified by RT-qPCR, indicative of the authenticity and reliability of our transcriptome data. Findings in this current work not only provide candidate DElncRNAs for functional study, but also lay a foundation for unclosing the mechanism underlying DElncRNA-regulated larval immune responses to A. apis infection.

pathology↗

bioRxiv2020

Prediction of LncRNA Encoded Small Peptides inGlioma and The Oligomer Channel Functional AnalysisUsing in Silico Approaches

Glioma is lethal malignant brain cancers, many reports have shown that abnormalities in the behavior of water and ion channels play an important role in regulating glioma proliferation, migration, apoptosis and differentiation. Recently, new studies have suggested that some long noncoding RNAs (lncRNAs) containing small open reading frames (smORFs), can encode small peptides and form oligomers for water or ion regulation. However, because these peptides are difficult to identify, their functional mechanisms are far from being clearly understood. In this study, we used bioinformatic methods and softwares to identify and evaluate lncRNAs in gliomas that may encode small transmembrane peptides. Combining ab initio homology modeling, molecular dynamics simulations and energetic calculations, we constructed a predictive model and predicted the oligomer channel activity of peptides by identifying the lncRNA ORFs. We found that one key hub lncRNA, DLEU1, which contains two smORFs (ORF1 and ORF8) could encode small peptides that form pentameric channels. The mechanics of water and ion (Na + and Cl-) transport through this pentameric channel were simulated. The potential of mean force (PMF) of the H2O molecules along the two ORF-encoded peptide channels indicated that the energy barrier was different between ORF1 and ORF8. The ORF1-encoded peptide pentamer acted as a self-assembled water channel but not as an ion channel, and the ORF8 neither permeating ions nor water. This work provides new methods and theoretical support for further elucidation of the function of lncRNA-encoded small peptides and their role in cancer. Additionally, it provides a theoretical basis for drug development.

biophysics↗

bioRxiv2018

Response of soil microbial communities to alpine meadow degradation severity levels in the Qinghai-Tibet Plateau

Soil microbial community structure is an effective indicator to reflect changes in soil quality. Little is known about the effect of alpine meadow degradation on the soil bacterial and fungal community. In this study, we used the Illumina MiSeq sequencing method to analyze the microbial community structure of alpine meadow soil in five different degradation levels (i.e., non-degraded (ND), slightly degraded (LD), moderately degraded (MD), severely degraded (SD), and very severely degraded (VD)) in the Qinghai-Tibet Plateau. Proteobacteria, Actinobacteria, and Acidobacteria were the mainly bacterial phyla in meadow soil across all five degradation levels investigated. Basidiomycota was the mainly fungal phylum in ND; however, we found a shift from Basidiomycota to Ascomycota with an increase (severity) in degradation level. The overall proportion of Cortinariaceae exhibited high fungal variability, and reads were highest in ND (62.80%). Heatmaps of bacterial genera and fungal families showed a two-cluster sample division on a genus/family level: (1) an ND and LD group and (2) an SD, VD, and MD group. Redundancy analysis (RDA) showed that 79.7%and 71.3% of the variance in bacterial and fungal composition, respectively, could be explained by soil nutrient conditions (soil organic carbon, total nitrogen, and moisture) and plant properties (below-ground biomass). Our results indicate that meadow degradation affects both plant and soil properties and consequently drives changes in soil microbial community structure.

microbiology↗

bioRxiv2018

Biolistic transformation of Haematococcus pluvialis with constructs based on the flanking sequences of its endogenous alpha tubulin gene

The complete sequence information of the alpha tubulin (tub) genes was obtained from both Haematococcus pluvialis NIES144 and SCCAP K0084., Putative transcriptional elements and polyadenylation signals were identified respectively in their 5 and 3 flanking regions. Three selection cassettes of tub/aadA, tub/hyr and tub/ble with 3 different antibiotic-resistant genes fused between the 5 and 3 flanking sequences of the tub gene were constructed and utilized for biolistic transformation of H.pluvialis. Antibiotic resistant transformants were obtained in the bombardments with the tub/aadA cassette in 2 strains. It was found that, the foreign tub/aadA DNA could be completely transferred and inherited in their genome through non-homologous recombination. Moreover, transcripts of the insert and spectinomycin resistance were identified. Transformation efficiencies up to 3x10-5 per g DNA could be obtained in H.pluvialis NIES144 or SCCAP K0084 through utilization of a culture with a high percentage of flagellate cells and by optimizing bombarding protocol. The presented selection marker and optimized transforming procedures in this report should strengthen the platform technology for genetical manipulation and modification of H.pluvialis.

molecular biology↗

bioRxiv2018

IQGAP3 Overexpression Correlates with Poor Prognosis and Radiation Therapy Resistance in Breast Cancer

Background: IQ motif-containing GTPase activating protein 3 (IQGAP3), the latest found protein of IQGAP family, may act as a crucial factor in the process of cancer development and progression; however, its clinical value in breast cancer remains unestablished so far. Our team explored the correlation between IQGAP3 expression profile and the clinicopathological features in breast cancer. Methods: IQGAP3 levels in breast cancer cell lines and tumor tissues were detected by real-time PCR and western blotting and compared to the normal control groups. Protein expression of IQGAP3 was evaluated immunohistochemically in specimens (archived paraffin embedded) of 257 breast cancer patients. We also analyze the association between IQGAP3 expression and the clinical characters and prognosis. The relationship between IQGAP3 expression and sensitivity to radiation therapy was determined by subgroup analysis. Results: There was significant upregulation of IQGAP3 in breast cancer cell lines and human tumor tissues at both the mRNA and protein level compared to the normal ones. In addition, 110/257 (42.8%) of archived paraffin embedded breast cancer specimens had high protein expression of IQGAP3. High expression of IQGAP3 was significantly related to clinical stage (P=0.001), T category (P=0.002), N category (P=0.001), locoregional recurrence(P=0.002), distant metastasis (P=0.001), and vital status (P=0.001). Univariate and multivariate statistical analysis showed that IQGAP3 was an independent prognostic factor of the whole cohort breast cancer patients (P=0.003, P=0.001). Subgroup analysis revealed IQGAP3 expression correlates with radiation therapy resistance and was also an independent predictor for radiation therapy outcome. Conclusions: Our findings suggest that high IQGAP3 expression predicts poor prognosis and radiation therapy resistance in breast cancer. In addition, IQGAP3 may be a reliable novel biomarker to provide personalized prognostication and identify patients who can profit from more aggressive RT regimen for improving the survival of breast cancer patients.

cancer biology↗