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Li, Y.

Publications and source records attributed to Li, Y..

At least 361 records · Page 20Linked to original sources

Short communication: Oral microbiome as a potential proxy for grazing livestock methane emissions

Enteric methane emissions from ruminant livestock contribute to global warming, creating an urgent need for effective mitigation strategies that do not compromise animal productivity and welfare. Methanogenic archaea within the rumen microbiome drive enteric methane emissions. However, large-scale rumen-fluid sampling in commercial production systems is impractical, due to its invasive nature and the associated logistical challenges. This study hypothesised that rumination enables the capture of rumen microbial signals within the oral cavity and using oral microbiome profiles to provide a practical, non-invasive alternative method for proxy methane phenotyping in commercial production systems. To test the hypothesis, we estimated the oral microbiability, defined as the proportion of phenotypic variance in methane emissions explained by oral microbiome variation. Samples were collected from 209 animals across two trials in Queensland, Australia. Oral microbiome samples were obtained from all animals, with paired rumen samples in one trial, and methane emissions were measured using either the sulphur hexafluoride (SF6) tracer technique or the GreenFeed system. Microbial features were characterised using taxonomic and functional annotations, and microbiability was estimated using mixed linear models incorporating microbiome-based relationship matrices. Although the small sample size limited strong conclusions, the oral microbiability estimates reported in this study were comparable to those derived from rumen samples. Functional microbial profiles generally explained a greater proportion of methane variation than taxonomic profiles, suggesting that microbial function is more closely linked to methane production than community composition alone. However, these differences were not statistically significant due to large standard errors. These findings suggest that oral microbiome sampling potentially provides a practical, minimally invasive, scalable proxy method for methane emissions of individual cattle in grazing systems, where direct methane gas measurements are labour-intensive and difficult to implement. Integrating oral microbiome profiles in the existing breeding model with the host genetics, weight and environmental factors could provide a promising pathway for enabling selection for low emissions and advancing reduced emissions livestock farming under real-world production conditions. Lay summaryCattle produce methane as part of their normal digestion and this contributes to climate change. Reducing methane emission in grazing livestock systems is therefore important. However, measuring methane from individual grazing animals is difficult, costly, and often impractical under commercial conditions. The rumen microbiome has been used as a proxy for estimating methane emissions, but collecting rumen samples is invasive and impractical for large-scale use. Because rumination transfers material from the rumen to the mouth, we investigated whether microbes found in cattle mouths could also be used to estimate how much methane an individual animal produced. We suggest that mouth-swab sampling method can be an alternative to rumen fluid sampling because it was less invasive, relatively quick and practically applicable in commercial conditions. Importantly, the microbiome explained a meaningful proportion of the between-animal variation for methane emission. This suggests that collection of mouth swabs is a potentially scalable alternative proxy method to identify cattle that naturally produce less methane. Overall, our findings support the potential use of oral ruminant microbial information to improve breeding and management strategies aimed at reducing methane emissions while maintaining productive livestock systems. Teaser TextThis study demonstrates that collecting oral swabs from the mouths of grazing beef cattle could provide a scalable method to estimate individual methane emissions in commercial production systems, offering a practical alternative to invasive rumen sampling and complex gas measurement systems. These findings support the development of scalable breeding and management strategies for methane mitigation in large-scale livestock production systems.

microbiology↗

A Conserved Geometric Code: Extracellular Matrix Curvature Directs Cell Migration Strategy via Nuclear Mechanosensing

Cells navigate complex tissue microenvironments defined by intricate physical cues, yet how they interpret the three-dimensional geometry of the extracellular matrix (ECM) remains an open question. Current models often fail to account for the tortuous architectures found in physiological tissues. Here, we demonstrate that ECM curvature functions as a tissue-specific geometric code read by the cell nucleus. By mapping collagen architectures across cancers and tissues, we find unique curvature fingerprints preserved during metastasis. Using micro-engineered substrates, we show that high curvature imposes localized nuclear bending stress, triggering a Lamin A/C-cPLA2-Ca2+ mechanotransductive cascade. This sensor rewires the cytoskeleton from longitudinal stress fibers to a cortical actomyosin network, driving a sharp transition from fast mesenchymal migration to a slower, exploratory amoeboid phenotype. We term this "nuclear curvotaxis", establishing a physical principle linking static geometry to dynamic strategy, with implications for predicting metastatic risk, understanding immune exclusion, and designing bio-instructive scaffolds for tissue engineering.

biophysics↗

MINGL Quantifies Borders, Gradients, and Heterogeneity in Multicellular Tissue Organization

Tissues are organized with interacting multicellular organizational units whose interfaces and transitions shape function in health and disease. Current spatial-omics analyses typically assign cells to a single cellular neighborhood--ignoring natural gradients, heterogeneity, and borders. Here we present MINGL (Mixture-based Identification of Neighborhood Gradients with Likelihood estimates), a probabilistic framework that converts existing neighborhood annotations into continuous measures of tissue architecture. MINGL models each cell by multi-membership probabilities across hierarchical organizational units and uses these probabilities to identify enriched cells at interfaces between units, constructs interaction networks across hierarchical scales, quantifies compositional gradient transitions, measures context-specific composition heterogeneity, and provides a starting point for neighborhood resolution. Across multiple spatial-omic datasets spanning melanoma, healthy intestine, and Barretts Esophagus progression, MINGL detected innate immune-enriched interfaces at tumor and anatomical interfaces, plasma cell niches linking cellular neighborhoods, distinct regimes of sharp and gradual transitions between organizational states, and disease-associated neighborhood remodeling. By treating neighborhood assignment uncertainty as a biological signal rather than noise, MINGL unifies discrete and continuous representations of tissue organization and makes tissue architecture measurable, comparable, and scalable across biological scales and spatial-omics platforms.

systems biology↗

An interferon independent innate immune response to double stranded RNA in embryonic stem cells

In vertebrate early embryos and embryonic stem cells, the interferon (IFN)-centered double-stranded RNA (dsRNA) sensing and signaling pathway is markedly suppressed, implying the existence of an alternative repertoire of dsRNA sensors in these stages. We recently reported that dsRNA treatment triggers translation inhibition using Prkra as a sensor in zebrafish and mouse early embryos. Independently, here we show that dsRNA stimulates the expression of a subset of interferon-stimulated genes (ISGs) in the absence of IFN production, establishing a defensive state in mouse embryonic stem cells (mESCs). Upon dsRNA stimulation, the multifunctional DExD/H-box RNA helicase Dhx9 is recruited into dsRNA-induced condensates, where it promotes the recruitment and functional suppression of the Mdm2/Cul4A ubiquitin ligase machinery by excluding their substrate adaptor Ddb1, thereby stabilizing p53 and Stat1. Dhx9, p53 and Stat1 then cooperate to stimulate an ISG response. This signaling is important for the defense against ZIKV infection in mESCs as well as other dsRNA stresses. Such a cascade is conserved in human ESCs, while in zebrafish embryos, p53 but not Stat1 is required for the transcriptional response. Our findings define an immediate, cell-autonomous innate immune pathway operating in ESCs and vertebrate embryos.

immunology↗

Nondimensional nucleus shape parameters reveal mechanostasis during confined migration

Nucleus shape is a sensitive indicator of cell state, influenced by numerous bio-chemical and physiological factors. While prior work has cataloged how perturbations alter nucleus morphology, we address the inverse: inferring underlying molecular changes from nucleus shape alone. We previously developed a mechanical model yielding two nondimensional parameters: flatness index and scale factor, which are surrogate measures for cortical actin tension and nuclear envelope compliance respectively. In this study, we apply these parameters to investigate the dynamics in cellular mechanics during confined migration. We fabricated polydimethylsiloxane (PDMS) microchannels with widths of 3 {micro}m (high confinement) and 10 {micro}m (low confinement) and tracked cells migrating through them. We captured high-frequency 3D nucleus shapes via double fluorescence exclusion microscopy and custom image analysis. Fitting the model and estimating flatness index and scale factor to time-resolved shapes revealed dynamic regulation in 3 {micro}m channels: actin tension decreased and nucleus compliance increased immediately before nucleus entry into the constriction, with rapid restoration to baseline upon exit. No such changes occurred in 10 {micro}m channels, indicating active, confinement-dependent cytoskeletal adaptation. Immunostaining for YAP and lamin-A,C confirmed these model inferences. Our results uncover mechanostasis, active mechanical homeostasis, during confined migration and establish the combination of double fluorescence exclusion microscopy and nondimensional nucleus shape parameters as a powerful, non-invasive tool for single-cell mechanobiology studies.

biophysics↗

The WalRK two-component system in Streptococcus pneumoniae ensures robustness of secondary wall polymer attachment

Capsular polysaccharide (CPS) is essential for Streptococcus pneumoniae virulence. Yet, the mechanism linking CPS to peptidoglycan (PG) remains unclear. Here, we identified a strong negative genetic interaction between the genes encoding the putative capsule ligase CpsA and the WalK histidine kinase, a component of the WalRK two-component system regulating cell wall homeostasis. In the absence of cpsA, capsule polymers compete with wall teichoic acids for ligase activity to PG. This induces cell wall stress and is sensed by the WalRK system. Overexpression of the PG hydrolase pcsB or disruption of the PG-modifying enzymes pgdA and oatA restored growth of strains lacking cpsA and walK. Furthermore, CpsA overproduction compensates for the loss of other LytR-Cps2A-Psr (LCP) ligases, suggesting it can support capsule and wall teichoic acid syntheses. These findings support the model that LCP ligases are semi-redundant, although they may install secondary polymers on a different residue of PG. This work also suggests that WalRK signaling compensates for reduced capsule and WTA attachment by positively regulating PG hydrolases. SIGNIFICANT STATEMENTStreptococcus pneumoniae causes approximately half a million deaths annually. A powerful public health tool for controlling pneumococcal infections is vaccination against the protective capsule. Yet, the mechanisms by which the capsule layer attaches to the underlying cell wall remain poorly defined. This study shows that the conserved capsule gene CpsA is not strictly required for capsule attachment but instead works together with other LytRIZCpsAIZPsr (LCP) ligases. However, it requires the essential WalRK signaling system to maintain cell envelope integrity. Defects in LCP activity are alleviated by WalRKIZdriven upregulation of peptidoglycan hydrolases, overexpression of PcsB, or inactivating peptidoglycan modifications that limit hydrolysis. These findings reveal coordination among flux to capsule synthesis, secondary wall polymer attachment, and cell wall remodeling. TEASERThe WalRK two-component system responds to cell envelope stress caused by reduced LCP ligase activity.

microbiology↗

Versatility of Campylobacter jejuni Bf extracellular vesicles in regulating adaptation and virulence under combined thermal and oxidative stress

The high prevalence of aerotolerant human Campylobacter jejuni isolates suggests a correlation between the ability to survive in aerobic conditions, virulence and resistance to harsh stress conditions. However, the mechanisms are still unclear. Here, we investigated the role of bacterial extracellular vesicles (bEVs) in the adaptation of the clinical aerotolerant C. jejuni Bf strain to thermal and oxidative stress. We show that C. jejuni Bf survives and actively multiplies under this combined stress. Stress exposure induced cell rounding and loss of motility, remodeling of membrane composition, decreased membrane fluidity, and metabolic reprogramming with increased intracellular ATP levels. Lipidomic analyses further revealed that bEVs composition is markedly different from that of the parent membranes indicating that vesicle formation is selective and regulated. Although bEVs were produced in similar amounts under both microaerophilic and stress conditions, stress exposure generated significantly larger vesicles with greater diameter and dry mass, and altered their protein and lipid profiles. bEVs derived from stressed cells showed increased toxicity toward the epithelial barrier of Caco-2 cells. Taken together, these results indicate that C. jejuni bEV secretion is part of a survival strategy that connects environmental adaptation with pathogenicity. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/714464v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@17aa2aforg.highwire.dtl.DTLVardef@4eab9dorg.highwire.dtl.DTLVardef@e4fba8org.highwire.dtl.DTLVardef@146109a_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Historic and contemporary museum specimens implicate Northern Red-backed Vole (Clethrionomys rutilus) as borealpox host as early as 1990s

Borealpox virus (BRPV; formerly Alaskapox) is an orthopoxvirus that has caused seven reported human infections in Alaska since 2015, including a fatal case in 2023. The natural reservoir of BRPV is unknown, although previous investigations have raised the possibility of wild small mammals transmitting the virus to humans, either through direct contact or via domestic cats and dogs. To understand which species may be involved in the maintenance and/or spillover of BRPV in Alaska, we trapped and sampled wild small mammals (including voles, shrews, and squirrels) in 2021 and 2024 near reported human case locations in Fairbanks and the Kenai Peninsula, respectively. We found evidence of previous exposure to orthopoxviruses in five species (including the House Mouse, Mus musculus) and detected BRPV DNA as well as viable virus in Northern Red-backed Voles (Clethrionomys rutilus). Further, screening of tissues from historical museum specimens revealed BRPV DNA in C. rutilus specimens collected in Denali National Park and Preserve in 1998 and 1999, 17 years before the first reported human case of BRPV. Phylogenomic analysis of all human and animal BRPV isolates strongly supports the hypothesis of local human infections through multiple spillover events. These findings suggest C. rutilus as a possible reservoir species for BRPV and indicate that BRPV has been present in Alaskan wild small-mammal populations for at least 25 years. Our study highlights the potential of museum collections to elucidate the temporal, spatial, and host ranges of emerging pathogens. Further museum- and field-based sampling will clarify the true geographic range of BRPV, which is closely related to Old World orthopoxviruses and may be circulating beyond North America.

ecology↗

Paternal behavior is controlled by preoptic Trpc5 neurons

Male parenting behavior is highly conserved and activated only after offspring are born. Here we show that the behavioral switch from infanticide in virgin male mice to caregiving in wild-type sires is associated with enhanced expression and activation of Transient receptor potential channel 5 (Trpc5) in estrogen receptor (Esr1)-expressing neurons in the hypothalamic medial preoptic area (MPOA). While selective deletion of Trpc5 from Esr1MPOA neurons diminishes paternal behavior in sires, overexpression of Trpc5 in these neurons converts the otherwise infanticidal virgin males to exhibit care to pups. Mechanistically, Trpc5-dependent changes in neuronal excitability underlie fatherhood-associated Esr1MPOA neuron plasticity. Notably, Trpc5 overexpression also enhances escape behavior and elicits exploratory diving behavior, suggesting that these neurons control a broader adaptive parenting response in males. These findings establish a Trpc5-dependent MPOA neural signal as a critical regulator of paternal behavior.

neuroscience↗

A Multi-Dataset Transcriptomic Analysis Unravels Core Mechanisms Involving Vitamin D Metabolism and Inflammatory Pathways for Frailty Diagnosis.

Frailty is a prevalent geriatric syndrome, and the shortage of objective biomarkers restricts its early diagnosis and intervention. This study aimed to identify robust molecular signatures and diagnostic markers for frailty using bioinformatics analyses of multiple independent datasets. Two transcriptome datasets (GSE144304, n=80; GSE287726, n=70) were obtained from the GEO database. We performed differential gene expression analysis, GO, KEGG and GSEA enrichment, and machine learning (70% training / 30% validation) to screen and validate core biomarkers. Numerous shared differentially expressed genes were identified. Vitamin D metabolism, ABC transporter, and inflammatory/immune pathways were consistently enriched and confirmed by GSEA. Machine learning models based on these signatures showed favorable diagnostic performance. Our study demonstrates that vitamin D metabolic disorders and chronic inflammation are core molecular features of frailty. The identified biomarkers provide new strategies for basic research, early clinical diagnosis, and therapeutic target development for frailty.

bioinformatics↗

STING suppresses migration of murine triple-negative breast cancer cells E0771 and 4T1 in vitro

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer and lacks effective therapies. The stimulator of interferon genes (STING) has been shown to both suppress and promote migration in various cancer types, but its role in TNBC remains unclear. To investigate this, we established STING-overexpressing murine TNBC cell lines and assessed their migratory and proliferative behavior. STING overexpression significantly suppressed cell migration without affecting cell proliferation. Furthermore, STING overexpression in E0771 cells upregulated expression levels of Itgb1 and Itga6 significantly, but not Icam1, Cxcl3, Itgb2, Lama5, or Rhoa. These findings highlight the potential anti-migratory role of STING beyond immunomodulatory functions.

cancer biology↗

MRN-ATM Pathway Activation in CD4 T-Cell Senescence during Chronic Hepatitis B Virus Infection

T-cell senescence is a hallmark of immune dysfunction in persistent viral infections, characterized by DNA damage accumulation and telomere erosion. However, the mechanisms driving CD4 T-cell senescence in the context of chronic hepatitis B virus (HBV) infection remain poorly defined. In this study, we demonstrated that people with chronic HBV infection exhibited CD4 T-cell senescence, marked by elevated KLRG1, along with increased DNA damage and telomere shortening, compared to HS. Notably, activation of the MRN-ATM (MRE11/RAD50/NBS1-Ataxia Telangiectasia Mutated Protein) pathway was prominent in CD4 T cells from HBV patients. Importantly, suppression of MRN attenuated ATM phosphorylation and its downstream signaling molecules, and inhibition of ATM reduced the production of proinflammatory cytokines in CD4 T cells derived from both HBV patients and HS. These results suggest that in chronic HBV infection, the virus induced CD4 T-cell senescence, telomere erosion, and DNA damage, while concurrent activation of the MRN-ATM pathway may serve as a compensatory mechanism to preserve CD4 T-cell function. Elucidating this relationship between T-cell senescence and DNA damage repair helps to understanding the mechanisms underlying HBV persistence and providing potential therapeutic targets against chronic HBV infection.

immunology↗

InSTaPath: Integrating Spatial Transcriptomics and histoPathology Images via Multimodal Topic Learning

Spatial transcriptomic (ST) technologies enable the measurement of gene expression directly within tissue sections while preserving spatial context. Many ST platforms additionally generate paired histological images alongside spatially resolved transcriptomic profiles. However, most existing computational approaches only incorporate histology images as auxiliary features in representation learning models and typically produce latent embeddings that are difficult to interpret. We present InSTaPath (Integrating Spatial Transcriptomics and histoPathology images), a multimodal topic modeling framework that links transcriptional programs with tissue morphology. InSTaPath converts token-level embeddings extracted from pretrained histology foundation models into discrete image words through vector quantization, enabling histological morphology to be represented in a count-based form analogous to gene expression. InSTaPath then jointly analyzes image-word and gene expression counts to infer shared latent topics that are interpretable through both topic-gene and topic-image-word associations. Across multiple ST datasets, InSTaPath improves spatial domain identification and uncovers biologically meaningful relationships between gene programs and tissue morphology through pathway enrichment and in silico perturbation analyses.

bioinformatics↗

scTimeBench: A streamlined benchmarking platform for single-cell time-series analysis

Temporal modelling of single-cell gene expression is essential for capturing dynamic cellular processes, yet a systematic framework for evaluating time-aware trajectory inference methods has not yet been established. Here, we present a modular and scalable benchmark designed to assess methods across three critical tasks: forecast accuracy (temporal cell alignment) for projecting cells to unseen time points, embedding coherence between original and projected data, and cell-type lineage fidelity. We evaluated nine state-of-the-art methods, which are broadly categorized into 7 forecasting-based and 2 optimal transport (OT)-based methods across eight diverse datasets spanning four species. Our results show that while several methods achieve high forecast accuracy, they often fail to preserve biological signals, both in their latent spaces and in cell lineage reconstruction. Notably, most methods confer low lineage fidelity and often underperform compared to a correlation baseline. We further demonstrate that integrating pseudotime can effectively denoise trajectories by aligning the data snapshots with the intrinsic biological clock in each cell. Finally, to streamline benchmarking for temporal single-cell analysis, we built one of the first self-contained Python packages for the research community: https://github.com/li-lab-mcgill/scTimeBench.

bioinformatics↗

A Surfactant Cocktail Overcomes Air-Water Interface Artifacts in Single-Particle CryoEM

Single-particle cryogenic electron microscopy (cryoEM) is a widely used technique for structure determination of biomacromolecules to near-atomic resolution. Random distributions of these molecules in vitrified ice are necessary to accumulate enough two-dimensional views to generate a complete three-dimensional (3-D) reconstruction. However, interactions between the sample and the air-water interface (AWI) that occur during vitrification often bias the views of the sample, a phenomenon termed preferred orientation, limiting our ability to obtain 3-D reconstructions. Surfactants are often used as sample additives to prevent AWI-induced deterioration, but no general strategy exists for surfactant choice, requiring laborious screening for each sample. To circumvent these issues, we developed SurfACT, a cocktail of diverse surfactants with distinct physicochemical properties that limits AWI-dependent sample denaturation and orientation bias, while mitigating individual surfactant-specific drawbacks. Here we demonstrate SurfACTs effectiveness with four proteins plagued by AWI-induced issues, including two species of hemagglutinin (HA), molybdenum-iron protein (MoFeP) from the nitrogenase enzyme, and aldolase. All four samples show drastically improved viewing distribution and map completeness when SurfACT is applied. Cryogenic electron tomography demonstrates that SurfACT redistributes particles from the AWI into the bulk ice, driving signal recovery and inhibiting denaturation. This versatile sample additive minimizes sample-specific screening and expands the capabilities and range of suitable samples for cryoEM.

biophysics↗

FLEX: A heparin-binding fusion partner engineered from fibroblast growth factor 1 to enhance protein expression, solubility and purity

Expression of aggregation-prone, unstable, or cytotoxic recombinant proteins remains a major bottleneck in both academic and industrial research. Although solubility-enhancing affinity tags can improve expression, they often compromise purification stringency, increase construct size, or require additional downstream processing. Here we report FLEX, a compact 15.5-kDa dual-function fusion tag engineered from human fibroblast growth factor-1 (FGF1) that integrates intrinsic protein-stabilising properties with high-affinity heparin binding. Structure-guided computational redesign of the FGF1 scaffold reduced exposed hydrophobic residues, removed flexible protease-susceptible regions, and expanded the electropositive surface while preserving the canonical heparin-binding interface. FLEX exhibits markedly improved thermal and chemical stability relative to wild-type FGF1 together with enhanced heparin affinity, enabling high-stringency washing and improved purity in a single affinity step. We demonstrate the broad utility of FLEX by expressing and purifying a panel of challenging proteins in Escherichia coli, including cytotoxic Pseudomonas aeruginosa virulence factors that are difficult to obtain in active form. Unexpectedly, FLEX also performed robustly in mammalian expression systems, where transiently expressed FLEX-tagged proteins were recovered at higher yield and purity than with gold standard Myc and Strep tags, including difficult targets such as Tribbles 3 (TRIB3). These findings establish FLEX as a versatile affinity-and-stabilisation tag that improves expression and purification across diverse systems, providing a practical new tool for structural, biochemical, and translational studies of otherwise intractable proteins.

biochemistry↗

Chemically informed representations of amino acids enable learning beyond the canonical protein alphabet

Computational models of proteins typically represent sequences using a fixed twenty-letter alphabet describing canonical amino acids. Although this symbolic representation underlies most machine learning approaches to protein analysis, it abstracts away the chemical structure of residues and cannot naturally encode post-translational modifications (PTMs). As a result, current models struggle to incorporate chemical variation beyond the canonical amino acid alphabet. Here we introduce a chemically informed representation of peptides based on two-dimensional depictions of amino acid structures. Peptides are encoded as mosaics of residue depictions and embedded using a convolutional autoencoder, allowing machine learning models to learn physicochemical features directly from molecular structure. Because these representations capture chemical properties rather than symbolic residue identities, they enable learning across structurally related residues and support generalization to modified amino acids not explicitly observed during training. Applied to Major Histocompatibility Complex class I binding prediction, these embeddings achieve competitive performance while enabling chemically interpretable attribution of the molecular features driving predictions.

bioinformatics↗

Telomere-to-telomere gap-free genome assembly integrated with multi-omics uncovers shading mediated regulation of leaf aroma biosynthesis in aromatic crop Pandanus amaryllifolius

Pandanus amaryllifolius is a valuable aromatic crop widely cultivated in tropical forest understories. Here, A telomere-to-telomere, gap-free genome assembly of the Chinese cultivar Taishan Banlan was generated, and the molecular basis underlying shading-mediated regulation of leaf aroma biosynthesis was elucidated for the first time through integrated genomic, transcriptomic, and metabolomic analyses. Volatile metabolomics identified 1599 volatile organic compounds in leaf tissue, with terpenoids as the primary contributors to leaf aroma. Shading modulated the aroma quality of P. amaryllifolius primarily via terpenoid biosynthesis, yielding aroma profiles dominated by sweet, fruity, green, and woody notes. Integrated transcriptomic profiling revealed that terpenoid biosynthesis is co-regulated by structural genes in the MVA/MEP pathways, TPS family members, and key transcription factors, which collectively modulate the biosynthesis and accumulation of the three core differential terpenoids. Our findings provide valuable resources for the targeted genetic improvement and efficient cultivation optimization of P. amaryllifolius.

genomics↗