Biology subjects

Yao, G.

Publications and source records attributed to Yao, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Integrated anthocyanin profiling and transcriptome analysis identify candidate genes associated with petal color variation in Cyclamen persicum

Petal coloration is a key ornamental trait in Cyclamen persicum Mill. and is closely associated with anthocyanin composition and relative accumulation, yet the major anthocyanins and candidate molecular factors associated with color variation remain unclear. In this study, anthocyanin profiling and transcriptome analysis were integrated to investigate three Cyclamen materials with distinct petal colors, BXK, FXK, and SHXK. Anthocyanin profiling showed clear separation among the three materials, indicating that petal color divergence was associated with differences in anthocyanin composition and relative abundance. Petunidin-, peonidin-, delphinidin-, malvidin-, and cyanidin-related derivatives exhibited distinct accumulation patterns. Transcriptome analysis revealed marked transcriptional divergence, with phenylpropanoid and flavonoid biosynthesis repeatedly enriched across comparisons, whereas isoflavonoid and flavone and flavonol biosynthesis were enriched in selected comparisons. Mapping differentially expressed genes onto the anthocyanin biosynthetic pathway revealed branch-specific expression patterns of structural genes, including CHS, F3H/F3'H, F3'5'H, DFR, and ANS. Notably, Cluster-26256.0, annotated as a putative anthocyanidin synthase gene, showed a progressive increase in expression from BXK to FXK and SHXK, consistent with increasing petal pigmentation. Several DFR-related transcripts also showed relatively high expression in SHXK. Co-expression analysis linked key anthocyanins, structural genes, and transcription factors, while qRT-PCR generally confirmed RNA-seq trends. These results suggest that late anthocyanin biosynthesis, particularly ANS-related transcriptional variation, may contribute to dark red petal coloration. This study provides a metabolite-transcript framework for Cyclamen petal coloration and identifies ANS-related genes as priority candidates for future functional studies and flower-color breeding.

plant biology↗

bioRxiv2026

A curated human lactylome and protein language model framework enable accurate prediction and reveal local determinants of lysine lactylation

Lysine lactylation is a dynamic post-translational modification that can alter protein function and has been implicated in diverse physiological and pathological processes. Accurate identification of lactylation sites is therefore important for defining its regulatory landscape and for generating testable hypotheses about lactylation-associated mechanisms. Here, we introduce CLEAR-Lactyl and AttentionKla. CLEAR-Lactyl is a curated benchmark dataset of human lysine lactylation comprising 16,604 positive sites. AttentionKla is a deep learning framework trained on CLEAR-Lactyl that employs a pre-trained protein language model fine-tuned with LoRA; it significantly outperforms existing tools, and the factors contributing to its performance gain have been dissected through comprehensive ablation studies. Its utility in predicting novel lactylation sites and in sequence-directed modulation of lactylation levels has been experimentally validated in cellular assays. Together, CLEAR-Lactyl and AttentionKla provide a powerful platform for lysine lactylation research and offer an extensible framework for the precise modulation of other post-translational modifications.

bioinformatics↗

bioRxiv2026

Environmental complexity reveals memory-guided search as the locus of learning in prey capture

Ethological behavior requires the integration of perception, memory, and decision-making, yet standard laboratory tasks are often too simplified to recruit these processes jointly. Here, mice that were expert hunters in a bare arena were challenged to capture live insect prey among objects that occlude vision and afford opportunities to hide. This revealed an axis of learning absent in an empty arena: mice improved not by refining pursuit but by reorganizing how they searched for concealed prey. An agent-based model showed that short-term memory and learning of object-specific values are sufficient to account for the behavior demonstrated by mice. A compact ethogram of object-directed actions revealed that animals selectively acquired the interactions most likely to expose prey. These results show that environmental complexity recruits memory- and value-guided search strategies. Reproducible with inexpensive materials, the paradigm and its open-source analyses offer a sensitive read-out of cognitive processes largely unobservable in conventional assays.

neuroscience↗

bioRxiv2025

Quiescence Induction Triggers Acute Accumulation of DNA Double-Strand Breaks That Drive Quiescence Heterogeneity

DNA double-strand breaks (DSBs) represent one of the most serious threats to genome integrity. Endogenous DSBs chiefly arise from cell cycle activities such as DNA replication and division, while dormant, non-proliferative cells are generally considered protected from such damage. Here we report that induction of quiescence by growth restriction in human retinal pigment epithelial (RPE) cells unexpectedly leads to rapid accumulation of DSBs within hours, reaching levels that exceed those in continuously proliferating cells. These DSBs occur in a cell cycle stage-dependent manner, predominantly in cells past the restriction point when quiescence is induced. Mechanistically, this DSB accumulation results from continued cell cycle activity under growth restriction conditions, accompanied by downregulation of DSB repair genes, allowing these breaks to persist during quiescence. Cells that accumulate more DSBs during quiescence induction enter a deeper state of quiescence, requiring stronger growth stimulation for cell cycle re-entry. Notably, cell cycle re-entry depends on DSB repair mediated by DNA-PK, an intrinsically error-prone process. Our findings establish quiescence induction as a previously unrecognized source of latent genome instability, with implications for tissue maintenance and aging where transitions between quiescence and proliferation are critical.

cell biology↗

bioRxiv2025

Human Body Single-Cell Atlas of 3D Genome Organization and DNA Methylation

Higher-order chromatin structure and DNA methylation are critical for gene regulation, but how these vary across the human body remains unclear. We performed multi-omic profiling of 3D genome structure and DNA methylation for 86,689 single nuclei across 16 human tissues, identifying 35 major and 206 cell subtypes. We revealed extensive changes in CG and non-CG methylation across almost all cell types and characterized 3D chromatin structure at an unprecedented cellular resolution. Intriguingly, extensive discrepancies exist between cell types delineated by DNA methylation and genome structure, indicating that the role of distinct epigenomic features in maintaining cell identity may vary by lineage. This study expands our understanding of the diversity of DNA methylation and chromatin structure and offers an extensive reference for exploring gene regulation in human health and disease.

genomics↗

bioRxiv2025

Epithelial-mesenchymal transition couples with cell cycle arrest at various stages

Numerous computational approaches have been developed to infer cell state transition trajectories from snapshot single-cell data. Most approaches first require projecting high-dimensional data onto a low-dimensional representation; however, this can distort the dynamics of the system. Using epithelial-to-mesenchymal transition (EMT) as a test system, we show that both biology-guided low-dimensional representations and trajectory simulations in high-dimensional state space, not representations obtained with brute force dimensionality-reduction methods, reveal two broad paths of TGF-{beta} induced EMT. The paths arise from the coupling between cell cycle and EMT at either the G1 or G2/M phase, contributing to cell-cycle related EMT heterogeneity. Subsequent multi-plex immunostaining studies confirmed the multiple predicted paths at the protein level. The present study highlights the heterogeneity of EMT paths, emphasizes that caution should be taken when inferring transition dynamics from snapshot single-cell data in two- or three-dimensional representations, and shows that incorporating dynamical information can improve prediction accuracy.

systems biology↗

bioRxiv2024

Combining Glycosidases and Nanopore Technology for Glycan Sequencing

The efficient characterization of glycan structures remains a critical challenge. Direct glycan sequencing technologies with improved sensitivity and throughput are still needed. Here, we propose a glycan sequencing strategy based on glycosidase -assisted nanopore sensing. We used engineered nanopore -hemolysin (M113R/T115A), which provided high-resolution discrimination of monosaccharide volume differences and sensitivity to variations in glycan chain length. By utilizing the specificity of glycosidases, we sequentially hydrolyzed the terminal residues of the glycan chains and detected the characteristic shifts in electrical signals generated by the translocation of hydrolysis products. The accuracy of recognition of hydrolysis fragments achieved over 90 % using machine learning. This allowed us to efficiently and conveniently determine the sequence of consecutive monosaccharide units in the glycan chains. Based on this principle, we conducted a proof-of-concept demonstration on actual samples and verified the accuracy via HPLC-MS. We achieved the sequencing of consecutive units in glycan chains, confirming the theoretical feasibility of glycosidase -assisted nanopore glycan sequencing. With future optimization, the development of arrayed nanopore glycan sequencing technology based on hydrolysis strategy will provide an innovative approach for rapid decoding of glycans, which could promote the progress of glycomics research and glycobiology.

biochemistry↗

bioRxiv2024

Employing biological sex as a primary variable can restrict our understanding of behavioral diversity (and sex differences) in psychostimulant activity.

BackgroundIn addition to representing distinct biological sex groups, males and females are also individuals expressing behavioral diversity. Our MISSING (Mapping Intrinsic Sex Similarities as an Integral quality of Normalized Groups) model suggests that, with respect to behavior, grouping according to the individual reveals groups with differences that exceed biological sex-related differences, but this needs further clarification. We hypothesized that, compared to the current model (grouping by biological sex), the MISSING model (grouping by individual attributes) was the more effective grouping strategy to identify behavioral diversity. MethodsWe conducted experiments in rats to determine the locomotor activity (in 90 min) following intraperitoneal injections of saline (n = 12 males, n = 11 females) and cocaine (n = 8 males, n = 11 females). For the current model, we compared males versus females using unpaired t-tests. For the MISSING model, we identified clusters of individuals (males and females) using normal mixtures clustering analysis of several behavioral variables and employed unpaired t-tests to compare clusters and Two-way ANOVA to determine if there were any SEX by cluster interactions. For both models, we employed linear regression analysis to compare relationships between variables and Two-way repeated measures ANOVA to analyze locomotor activity time course. ResultsFor both the saline and cocaine groups, the MISSING model identified two behavioral clusters with differences that exceeded any differences due to biological sex. ConclusionsThe MISSING model suggests that employing biological sex as a primary variable can obscure our understanding of sex and individual differences in psychostimulant activity.

neuroscience↗

bioRxiv2024

CILP from Cartilage Intermediate Zone Inhibits Hyaline Cartilage Fibrosis and Chondrocyte Ferroptosis via Keap1-Nrf2 Axis in Early Osteoarthritis Exercise Therapy

By analyzing the single-cell RNA-Seq libraries, the roles of cartilage intermediate layer protein (CILP) and the cartilage intermediate zone in early osteoarthritis (OA) exercise therapy were explored. An early OA rat model was established via a 4-week anterior cruciate ligament transection. The effect of moderate exercise was confirmed using histology, the open-field test, and gait analysis. The response of the cartilage intermediate zone to mechanical stimulation was explored using multiplex fluorescent immunohistochemical staining. Radiomics was used to evaluate the relatively damaged and undamaged areas in the cartilage of patients with OA. CILP was OE and KD in early OA chondrocytes, and quantitative proteomics, yeast one-hybrid, co-immunoprecipitation, Nrf2 and ubiquitination assays were used to investigate its mechanism. We found that moderate exercise upregulates CILP in the cartilage intermediate zone. CILP recovers the type II/I collagen, Sox9, and -SMA expression ratios, and reduces Keap1-Nrf2 dimer stability, inhibiting Nrf2 ubiquitination and promoting Nrf2 nuclear translocation. Nrf2 nuclear translocation activates SLC7A11, HO-1, GPX4, and SOD-1 expression, decreases MDA content, and increases GSH content, inhibiting chondrocyte ferroptosis and promoting fibrocartilage hyalinization. In conclusion, the exercise-induced cartilage intermediate zone and CILP-Keap1-Nrf2 axis inhibit hyaline cartilage fibrosis and chondrocyte ferroptosis to alleviate early OA.

cell biology↗

bioRxiv2024

Additive and partially dominant effects contribute to crop heterosis

Heterosis, or hybrid vigor, describes the superior performance of F1 hybrids relative to their parents. Despite its significant importance in crop breeding, the molecular mechanisms underlying heterosis remain debated, mainly attributable to discrepancies across genotypes, traits, tissues, populations, developmental stages, growth environments, and species. In this study, we systematically identified heterosis-associated genes and metabolites from parental molecular differences in rice and functionally validated three genes for heterosis of seedling length. We incorporated these heterosis-associated molecules into network modules and explained the variance of heterosis. The predominant inheritance patterns of these molecules were additive and partially dominant effects, namely at mid-parent levels or values between mid-parent and parental levels, respectively. These two genetic effects contributed to heterosis of 17 agronomic traits in rice, including grain yield and plant height across developmental stages. They also explained yield heterosis in diverse hybrid populations and distinct growth environments in both rice and maize, as well as biomass heterosis in Arabidopsis. Notably, additive and partially dominant effects were associated with parental genomic variants in rice, and the number of these variants correlated significantly with heterosis of agronomic traits. Furthermore, we demonstrated the significant impact of parental genomic, transcriptomic, and metabolomic variation in phenylpropanoid biosynthesis on heterosis for seedling length/plant height. Unlike classical heterosis models primarily focused on genomic sequence variation, our findings provide quantitative insights from genomic downstream information into the molecular mechanisms of plant heterosis, highlighting their potential for improving breeding efficiency of hybrid crops.

plant biology↗

bioRxiv2023

Discrimination of Isomeric Glycans via High-sensitive Engineered Nanopore

Glycan isomers are the basis for forming the spatial structure of glycans, which poses great challenges to glycan structural analysis and hinders the study of the relationship between structure and function. An economical and convenient analytical method with high resolution is still in demand. Here, we designed an engineered -hemolysin nanopore with double-mutants (-HL M113R/T115A) to achieve sensing of glycans with different glycosidic linkages. By extracting three parameters to depict a 3D scatter plot, four glycans with different degrees of polymerization and glycosidic bonds could be distinguished. Through molecular dynamics (MD), we further elucidated the motion trajectories of two different glycosidic bonds in the pore region. In addition, the sensing ability was also applied in the direct identification of glycans in mixture systems. The obtained nanopore data permitted us to achieve a separation accuracy of over 90% independent of the assistance of machine learning algorithms. Designing biological nanopores with high discrimination and sensitivity for glycans with different lineages paves the way for nanopore glycan profiling and potentially sequencing.

bioengineering↗

bioRxiv2023

Identification of an allele-specific transcription factor binding interaction that regulates PLA2G2A gene expression

The secreted phospholipase A2 (sPLA2) isoform, sPLA2-IIA, has been implicated in a variety of diseases and conditions, including bacteremia, cardiovascular disease, COVID-19, sepsis, adult respiratory distress syndrome, and certain cancers. Given its significant role in these conditions, understanding the regulatory mechanisms impacting its levels is crucial. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs), including rs11573156, that are associated with circulating levels of sPLA2-IIA. Through Genotype-Tissue Expression (GTEx), 234 expression quantitative trait loci (eQTLs) were identified for the gene that encodes for sPLA2-IIA, PLA2G2A. SNP2TFBS (https://ccg.epfl.ch/snp2tfbs/) was utilized to ascertain the binding affinities between transcription factors (TFs) to both the reference and alternative alleles of identified SNPs. Subsequently, ChIP-seq peaks highlighted the TF combinations that specifically bind to the SNP, rs11573156. SP1 emerged as a significant TF/SNP pair in liver cells, with rs11573156/SP1 interaction being most prominent in liver, prostate, ovary, and adipose tissues. Further analysis revealed that the upregulation of PLA2G2A transcript levels through the rs11573156 variant was affected by tissue SP1 protein levels. By leveraging an ordinary differential equation, structured upon Michaelis-Menten enzyme kinetics assumptions, we modeled the PLA2G2A transcriptions dependence on SP1 protein levels, incorporating the SNPs influence. Collectively, these data strongly suggest that the binding affinity differences of SP1 for the different rs11573156 alleles can influence PLA2G2A expression. This, in turn, can modulate sPLA2-IIA levels, impacting a wide range of human diseases.

bioinformatics↗

bioRxiv2023

Modeling the Depth of Cellular Dormancy from RNA-sequencing data

High-throughput transcriptome RNA sequencing is a powerful tool for understanding dynamic biological processes. Here, we present a computational framework, implemented in an R package QDSWorkflow, to characterize heterogeneous cellular dormancy depth using RNA-sequencing data from bulk samples and single cells.

systems biology↗

bioRxiv2022

The influence of N-methylation on the ansamers of an amatoxin: Gly5Sar-amanullin

Amatoxins are strong inhibitors of RNA polymerase II, and cause cell death. Because of their cytotoxicity they are candidates for anti-cancer drugs, and understanding their structure-activity relationship is crucial. Amatoxins have a rigid bicyclic scaffold which consists of a cyclic octapeptide bridged by cysteine and tryptophan side chain forming a tryptathionine bridge. Here we show the influence of the N-methylation on the amatoxin scaffold by studying Gly5Sar-amanullin with MD simulations and NMR experiments. Since we have shown recently that the amatoxin scaffold allows for two isomeric forms (ansamers), we studied both isomers of Gly5Sar-amanullin. We found that both isomers of Gly5Sar-amanullin form two long-living conformations which is unusual for amatoxins, and that they are differently affected by the N-methylation. The natural Gly5Sar-amanullin forfeits the hydrogen bonds to Gly5 due to the N-methylation, which is expected from existing crystal structures for alpha-amanitin. Our results however indicate that this does not cause more flexibility due to a shift in the hydrogen bond pattern. In the unnatural isomer, we observe an interesting cis-trans-isomerisation of the backbone angles in Trp4 and Gly7, which is enabled by the N-methylation. We expect that our perspective on the effect of N-methylation in amatoxins could be a starting point for further SAR-studies which are urgently needed for the design of better anti-cancer agents.

molecular biology↗

bioRxiv2022

Identifying Strong Modulators of Cellular Quiescence Depth Across Different Quiescent Cells and Conditions

The proper balance and transition between cellular quiescence and proliferation are critical to tissue homeostasis, repair, and regeneration. The likelihood of quiescence-to-proliferation transition is inversely correlated with quiescence depth, and deep quiescent cells are less likely to exit quiescence and reenter the cell cycle than shallow quiescent cells. The regulatory mechanisms of quiescence depth are poorly understood but essential for developing strategies against hypo- or hyper-proliferation diseases such as aging and cancer. Our earlier studies have demonstrated that the activation threshold of the bistable Rb-E2F gene network switch (ThE2F) controls quiescence depth. We have also identified coarse- and fine-tuning ThE2F modulators in rat embryonic fibroblasts. To examine whether other quiescent cells (including most adult stem and progenitor cells) under different environmental conditions use the same or different modulators of quiescence depth, here we studied the behaviors of 30,000 theoretical quiescent cell models that each support a functional Rb-E2F bistable switch with a unique parameter set. We found that although the vastly heterogeneous quiescent cell models exhibited no apparent parameter patterns, they converged at two alternative groups of strong quiescence-depth modulators (G1 cyclin/cdk-related and Rb/E2F complex-related). Our further machine learning (decision tree) analysis suggested that the Rb protein level and dephosphorylation rate in quiescent cells determine which modulator group to use to regulate quiescence depth.

systems biology↗

bioRxiv2022

MorphoGNN: Morphological Embedding for Single Neuron with Graph Neural Networks

With the development of optical imaging systems, neuroscientists can now obtain large datasets of morphological structure at a single neuron scale positioned across the whole mouse brain. However, the enormous amount of morphological data challenges the classic approach of neuron classification, indexing and other analysis tasks. In this paper, we propose MorphoGNN, a single neuron morphological embedding based on the graph neural networks (GNN). This method learns the spatial structure information between the nodes of reconstructed neuron fibers by its nearest neighbors on each layer and captures the lower-dimensional representation of a single neuron through an end-to-end model. This model is composed of densely connected edge convolution (EdgeConv) layers and a double pooling operator, regularized with joint cross-entropy loss and triplet loss. An increasing population of the neighbor nodes meets the need of learning more information with features expanding at the deep layer. We tested the proposed embeddings on the neuron classification and retrieval tasks. Our method achieves competitive performance both on the general point cloud dataset and the neuron morphology dataset.

neuroscience↗

bioRxiv2022

Aucubin promoted neuron functional recovery by suppressing inflammation and neuronal apoptosis in a spinal cord injury model

Spinal cord injury (SCI) can cause severe motor impairment. Post-SCI treatment has focused primarily on secondary injury, with neuroinflammation and neuronal apoptosis as the primary therapeutic targets. Aucubin (Au), a Chinese herbal medicine, exerts anti-inflammatory and neuroprotective effects. The therapeutic effects of Au in SCI have not been reported. We showed that Au can promote functional recovery after SCI. Recovery may occur through the toll-like receptor 4 (TLR4)/nuclear factor kappa B (NF-{kappa}B) pathway to promote M2/M1 polarization in microglia and inhibit mitochondrial dysfunction to reduce neuronal apoptosis. These biochemical changes result in reduced secondary injury and facilitate axon regeneration. Therefore, Au may be a promising post-SCI therapeutic medication.

cell biology↗

bioRxiv2021

Extracellular Fluid Flow Induces Shallow Quiescence through Physical and Biochemical Cues

The balance between cell quiescence and proliferation is fundamental to tissue physiology and homeostasis. Recent studies have shown that quiescence is not a passive and homogeneous state but actively maintained and heterogeneous. These cellular characteristics associated with quiescence were observed primarily in cultured cells under a static medium. However, cells in vivo face different microenvironmental conditions, particularly, under interstitial fluid flows distributed through extracellular matrices. Interstitial fluid flow exerts shear stress on cells and matrix strain, and results in continuous replacement of extracellular factors. In this study, by analyzing individual cells under varying fluid flow rates in microfluidic devices, we found that extracellular fluid flow alters cellular quiescence depth through flow-induced physical and biochemical cues. Specifically, increasing the flow rate drives cells to shallower quiescence and become more likely to reenter the cell cycle upon growth stimulation. Furthermore, we found that increasing shear stress or extracellular factor replacement individually, without altering other parameters, also results in shallow quiescence. We integrated the experimental results into a mathematical model to gain insight and predict the effects of varying extracellular fluid flow conditions on cellular quiescence depth. Our findings uncover a previously unappreciated mechanism that likely underlies the heterogeneous responses of quiescent cells for tissue repair and regeneration in physiological tissue microenvironments.

cell biology↗