Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics.

Spatially resolved transcriptomics (SRT) has emerged as a powerful tool for investigating gene expression in spatial contexts, providing insights into the molecular mechanisms underlying organ development and disease pathology. However, the expression sparsity poses a computational challenge to integrate other modalities (e.g. histological images and spatial locations) that are simultaneously captured in SRT datasets for spatial clustering and variation analyses. In this study, to meet such a challenge, we propose multi-modal domain adaption for spatial transcriptomics (stMDA), a novel multi-modal unsupervised domain adaptation method, which integrates gene expression and other modalities to reveal the spatial functional landscape. Specifically, stMDA first learns the modality-specific representations from spatial multi-modal data using multiple neural network architectures and then aligns the spatial distributions across modal representations to integrate these multi-modal representations, thus facilitating the integration of global and spatially local information and improving the consistency of clustering assignments. Our results demonstrate that stMDA outperforms existing methods in identifying spatial domains across diverse platforms and species. Furthermore, stMDA excels in identifying spatially variable genes with high prognostic potential in cancer tissues. In conclusion, stMDA as a new tool of multi-modal data integration provides a powerful and flexible framework for analyzing SRT datasets, thereby advancing our understanding of intricate biological systems.

Spatially contrastive variational autoencoder for deciphering tissue heterogeneity from spatially resolved transcriptomics.

Recent advances in spatially resolved transcriptomics (SRT) have brought ever-increasing opportunities to characterize expression landscape in the context of tissue spatiality. Nevertheless, there still exist multiple challenges to accurately detect spatial functional regions in tissue. Here, we present a novel contrastive learning framework, SPAtially Contrastive variational AutoEncoder (SpaCAE), which contrasts transcriptomic signals of each spot and its spatial neighbors to achieve fine-grained tissue structures detection. By employing a graph embedding variational autoencoder and incorporating a deep contrastive strategy, SpaCAE achieves a balance between spatial local information and global information of expression, enabling effective learning of representations with spatial constraints. Particularly, SpaCAE provides a graph deconvolutional decoder to address the smoothing effect of local spatial structure on expression's self-supervised learning, an aspect often overlooked by current graph neural networks. We demonstrated that SpaCAE could achieve effective performance on SRT data generated from multiple technologies for spatial domains identification and data denoising, making it a remarkable tool to obtain novel insights from SRT studies.

Spatially aware self-representation learning for tissue structure characterization and spatial functional genes identification.

Spatially resolved transcriptomics (SRT) enable the comprehensive characterization of transcriptomic profiles in the context of tissue microenvironments. Unveiling spatial transcriptional heterogeneity needs to effectively incorporate spatial information accounting for the substantial spatial correlation of expression measurements. Here, we develop a computational method, SpaSRL (spatially aware self-representation learning), which flexibly enhances and decodes spatial transcriptional signals to simultaneously achieve spatial domain detection and spatial functional genes identification. This novel tunable spatially aware strategy of SpaSRL not only balances spatial and transcriptional coherence for the two tasks, but also can transfer spatial correlation constraint between them based on a unified model. In addition, this joint analysis by SpaSRL deciphers accurate and fine-grained tissue structures and ensures the effective extraction of biologically informative genes underlying spatial architecture. We verified the superiority of SpaSRL on spatial domain detection, spatial functional genes identification and data denoising using multiple SRT datasets obtained by different platforms and tissue sections. Our results illustrate SpaSRL's utility in flexible integration of spatial information and novel discovery of biological insights from spatial transcriptomic datasets.

YAP1-CPNE3 positive feedback pathway promotes gastric cancer cell progression.

Hippo-Yes-associated protein 1 (YAP1) plays an important role in gastric cancer (GC) progression; however, its regulatory network remains unclear. In this study, we identified Copine III (CPNE3) was identified as a novel direct target gene regulated by the YAP1/TEADs transcription factor complex. The downregulation of CPNE3 inhibited proliferation and invasion, and increased the chemosensitivity of GC cells, whereas the overexpression of CPNE3 had the opposite biological effects. Mechanistically, CPNE3 binds to the YAP1 protein in the cytoplasm, inhibiting YAP1 ubiquitination and degradation mediated by the E3 ubiquitination ligase ß-transducin repeat-containing protein (ß-TRCP). Thereby activating the transcription of YAP1 downstream target genes, which creates a positive feedback cycle to facilitate GC progression. Immunohistochemical analysis demonstrated significant upregulation of CPNE3 in GC tissues. Survival and Cox regression analyses indicated that high CPNE3 expression was an independent prognostic marker for GC. This study elucidated the pivotal involvement of an aberrantly activated CPNE3/YAP1 positive feedback loop in the malignant progression of GC, thereby uncovering novel prognostic factors and therapeutic targets in GC.

Combined analysis of the effects of hypoxia and oxidative stress on DNA methylation and the transcriptome in HTR-8/SVneo trophoblast cells.

The alterations in DNA methylation and transcriptome in trophoblast cells under conditions of low oxygen and oxidative stress have major implications for pregnancy-related disorders. However, the exact mechanism is still not fully understood. In this study, we established models of hypoxia (H group) and oxidative stress (HR group) using HTR-8/SVneo trophoblast cells and performed combined analysis of genome-wide DNA methylation changes using reduced representation bisulphite sequencing and transcriptome expression changes using RNA sequencing. Our findings revealed that the H group exhibited a higher number of differentially methylated genes and differentially expressed genes than the HR group. In the H group, only 0.90% of all differentially expressed genes displayed simultaneous changes in DNA methylation and transcriptome expression. After the threshold was expanded, this number increased to 6.29% in the HR group. Notably, both the H group and HR group exhibited concurrent alterations in DNA methylation and transcriptome expression within Axon guidance and MAPK signalling pathway. Among the top 25 differentially methylated KEGG pathways in the promoter region, 11 pathways were commonly enriched in H group and HR group, accounting for 44.00%. Among the top 25 KEGG pathways in transcriptome with significant differences between the H group and HR group, 10 pathways were consistent, accounting for 40.00%. By integrating our previous data on DNA methylation from preeclamptic placental tissues, we identified that the ANKRD37 and PFKFB3 genes may contribute to the pathogenesis of preeclampsia through DNA methylation-mediated transcriptome expression under hypoxic conditions.

Genome-wide analysis of AP2/ERF transcription factors that regulate fruit development of Chinese prickly ash.

BACKGROUND: AP2/ERF is a large family of plant transcription factor proteins that play essential roles in signal transduction, plant growth and development, and responses to various stresses. The AP2/ERF family has been identified and verified by functional analysis in various plants, but so far there has been no comprehensive study of these factors in Chinese prickly ash. Phylogenetic, motif, and functional analyses combined with transcriptome analysis of Chinese prickly ash fruits at different developmental stages (30, 60, and 90 days after anthesis) were conducted in this study. RESULTS: The analysis identified 146 ZbAP2/ERF genes that could be classified into 15 subgroups. The motif analysis revealed the presence of different motifs or elements in each group that may explain the functional differences between the groups. ZbERF13.2, ZbRAP2-12, and ZbERF2.1 showed high levels of expression in the early stages of fruit development. ZbRAP2-4, and ZbERF3.1 were significantly expressed at the fruit coloring stage (R2 and G2). ZbERF16 were significantly expressed at fruit ripening and expression level increased as the fruit continued to develop. Relative gene expression levels of 6 representative ZbAP2/ERFs assessed by RT-qPCR agreed with transcriptome analysis results. CONCLUSIONS: These genes identified by screening can be used as candidate genes that affect fruit development. The results of the analysis can help guide future genetic improvement of Chinese prickly ash and enrich our understanding of AP2/ERF transcription factors and their regulatory functions in plants.

Metabolome Sequencing Reveals that Protein Arginine-N-Methyltransferase 1 Promotes the Progression of Invasive Micropapillary Carcinoma of the Breast and Predicts a Poor Prognosis.

Invasive micropapillary carcinoma (IMPC) of the breast is a special histopathologic type of cancer with a high recurrence rate and the biological features of invasion and metastasis. Previous spatial transcriptome studies indicated extensive metabolic reprogramming in IMPC, which contributes to tumor cell heterogeneity. However, the impact of metabolome alterations on IMPC biological behavior is unclear. Herein, endogenous metabolite-targeted metabolomic analysis was done on frozen tumor tissue samples from 25 patients with breast IMPC and 34 patients with invasive ductal carcinoma not otherwise specified (IDC-NOS) by liquid chromatography-mass spectrometry. An IMPC-like state, which is an intermediate transitional morphologic phenotype between IMPC and IDC-NOS, was observed. The metabolic type of IMPC and IDC-NOS was related to breast cancer molecular type. Arginine methylation modification and 4-hydroxy-phenylpyruvate metabolic changes play a major role in the metabolic reprogramming of IMPC. High protein arginine-N-methyltransferase (PRMT) 1 expression was an independent factor related to the poor prognosis of patients with IMPC in terms of disease-free survival. PRMT1 promoted H4R3me2a, which induced tumor cell proliferation via cell cycle regulation and facilitated tumor cell metastasis via the tumor necrosis factor signaling pathway. This study identified the metabolic type-related features and intermediate transition morphology of IMPC. The identification of potential targets of PRMT1 has the potential to provide a basis for the precise diagnosis and treatment of breast IMPC.

Allelic phenotype prediction of phenylketonuria based on the machine learning method.

BACKGROUND: Phenylketonuria (PKU) is caused by mutations in the phenylalanine hydroxylase (PAH) gene. Our study aimed to predict the phenotype using the allelic genotype. METHODS: A total of 1291 PKU patients with 623 various variants were used as the training dataset for predicting allelic phenotypes. We designed a common machine learning framework to predict allelic genotypes associated with the phenotype. RESULTS: We identified 235 different mutations and 623 various allelic genotypes. The features extracted from the structure of mutations and graph properties of the PKU network to predict the phenotype of PKU were named PPML (PKU phenotype predicted by machine learning). The phenotype of PKU was classified into three different categories: classical PKU (cPKU), mild PKU (mPKU) and mild hyperphenylalaninemia (MHP). Three hub nodes (c.728G>A for cPKU, c.721 for mPKU and c.158G>A for HPA) were used as each classification center, and 5 node attributes were extracted from the network graph for machine learning training features. The area under the ROC curve was AUC = 0.832 for cPKU, AUC = 0.678 for mPKU and AUC = 0.874 for MHP. This suggests that PPML is a powerful method to predict allelic phenotypes in PKU and can be used for genetic counseling of PKU families. CONCLUSIONS: The web version of PPML predicts PKU allele classification supported by applicable real cases and prediction results. It is an online database that can be used for PKU phenotype prediction http://www.bioinfogenetics.info/PPML/ .

Nicotinamide N-Methyltransferase (NNMT) is Involved in Gastric Adenocarcinoma Immune Infiltration by Driving Amino Acid Metabolism.

Objectives: This study investigates the role of Nicotinamide N-methyltransferase (NNMT) in immune infiltration modulation through amino acid metabolism in gastric adenocarcinoma (STAD). Methods: Utilizing data from The Cancer Genome Atlas (TCGA) and validated with clinical samples, we analyzed NNMT expression and its prognostic implications in STAD. Differential amino acid profiles between cancerous and adjacent normal tissues were assessed, along with their associations with NNMT. Results: NNMT exhibits heightened expression in STAD cancer tissues, positively correlating with tumor immune infiltration. Additionally, twenty-eight amino acids display differential expression in gastric tissue, with their metabolic enzymes showing connections to NNMT. Conclusions: Elevated NNMT expression in STAD tissues potentially influences amino acid metabolism, thereby affecting immune infiltration dynamics and tumorigenesis in gastric adenocarcinoma.

Biocontrol Efficacy and Induced Resistance of Paenibacillus polymyxa J2-4 Against Meloidogyne incognita Infection in Cucumber.

Meloidogyne incognita is one of the most destructive agricultural pathogens around the world, resulting in severe damage to yield and quality in agricultural production. Biological control promises to be a great potential alternative to chemical agents against M. incognita. Paenibacillus polymyxa J2-4, isolated from ginger plants injured by M. incognita, has shown excellent biocontrol efficacy against M. incognita in cucumber. In vitro experiments with the strain J2-4 resulted in a correct mortality rate of 88.79% (24 h) and 98.57% (48 h) for second-stage juveniles (J2s) of M. incognita. Strain J2-4 significantly suppressed nematode infection on potted plants, with a 65.94% reduction in galls and a 51.64% reduction in eggs compared with the control. The split-root assay demonstrated that strain J2-4 not only reduced J2s' invasion but also inhibited nematode development through the dependence on salicylic acid and jasmonic acid signaling of strain J2-4 induction of plant resistance in local and systemic roots of cucumbers. Genomic analysis of strain J2-4 indicated biosynthetic gene clusters encoding polymyxin, fusaricidin B, paenilan, and tridecaptin. In addition, genetic analysis showed that none of the genes encoding virulence factors were detected in the genome of J2-4 compared with the pathogenic Bacillus species. Taking all the data together, we conclude that P. polymyxa J2-4 has potential as a biological control agent against M. incognita on cucumbers and can be considered biologically safe when used in agriculture.

Identification of lipid-modifying drug targets for autoimmune diseases: insights from drug target mendelian randomization.

BACKGROUNDS: A growing body of evidence has highlighted the interactions of lipids metabolism and immune regulation. Nevertheless, there is still a lack of evidence regarding the causality between lipids and autoimmune diseases (ADs), as well as their possibility as drug targets for ADs. OBJECTIVES: This study was conducted to comprehensively understand the casual associations between lipid traits and ADs, and evaluate the therapeutic possibility of lipid-lowering drug targets on ADs. METHODS: Genetic variants for lipid traits and variants encoding targets of various lipid-lowering drugs were derived from Global Lipid Genetics Consortium (GLGC) and verified in Drug Bank. Summary data of ADs were obtained from MRC Integrative Epidemiology Unit (MER-IEU) database and FinnGen consortium, respectively. The causal inferences between lipid traits/genetic agents of lipid-lowering targets and ADs were evaluated by Mendelian randomization (MR), summary data-based MR (SMR), and multivariable MR (MVMR) analyses. Enrichment analysis and protein interaction network were employed to reveal the functional characteristics and biological relevance of potential therapeutic lipid-lowering targets. RESULTS: There was no evidence of causal effects regarding 5 lipid traits and 9 lipid-lowering drug targets on ADs. Genetically proxied 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) inhibition was associated with a reduced risk of rheumatoid arthritis (RA) in both discovery (OR [odds ratio] = 0.45, 95%CI: 0.32, 0.63, P = 6.79 × 10- 06) and replicate datasets (OR = 0.37, 95%CI: 0.23, 0.61, P = 7.81 × 10- 05). SMR analyses supported that genetically proxied HMGCR inhibition had causal effects on RA in whole blood (OR = 0.48, 95%CI: 0.29, 0.82, P = 6.86 × 10- 03) and skeletal muscle sites (OR = 0.75, 95%CI: 0.56, 0.99, P = 4.48 × 10- 02). After controlling for blood pressure, body mass index (BMI), smoking and drinking alchohol, HMGCR suppression showed a direct causal effect on a lower risk of RA (OR = 0.33, 95%CI: 0.40, 0.96, P = 0.042). CONCLUSIONS: Our study reveals causal links of genetically proxied HMGCR inhibition (lipid-lowering drug targets) and HMGCR expression inhibition with a decreased risk of RA, suggesting that HMGCR may serve as candidate drug targets for the treatment and prevention of RA.

Synergistic suppression of BDNF via epigenetic mechanism deteriorating learning and memory impairment caused by Mn and Pb co-exposure.

Microglia, the resident immune cells of the central nervous system (CNS), play a dual role in neurotoxicity by releasing the NLR Family Pyrin Domain Containing 3 (NLRP3) inflammasome and brain-derived neurotrophic factor (BDNF) in response to environmental stress. Suppression of BDNF is implicated in learning and memory impairment induced by exposure to manganese (Mn) or lead (Pb) individually. Methyl CpG Binding Protein 2 (MeCp2) and its phosphorylation status are related to BDNF suppression. Protein phosphatase2A (PP2A), a member of the serine/threonine phosphatases family, dephosphorylates substrates based on the methylation state of its catalytic C subunit (PP2Ac). However, the specific impairment patterns and molecular mechanisms resulting from co-exposure to Mn and Pb remain unclear. Therefore, the purpose of this study was to explore the effects of Mn and Pb exposure, alone and in combination, on inducing neurotoxicity in the hippocampus of mice and BV2 cells, and to determine whether simultaneous exposure to both metals exacerbate their toxicity. Our findings reveal that co-exposure to Mn and Pb leads to severe learning and memory impairment in mice, which correlates with the accumulation of metals in the hippocampus and synergistic suppression of BDNF. This suppression is accompanied by up-regulation of the epigenetic repressor MeCp2 and its phosphorylation status, as well as demethylation of PP2Ac. Furthermore, inhibition of PP2Ac demethylation using ABL127, an inhibitor for its protein phosphatase methylesterase1 (PME1), or knockdown of MeCp2 via siRNA transfection in vitro effectively increases BDNF expression and mitigates BV2 cell damage induced by Mn and Pb co-exposure. We also observe abnormal activation of microglia characterized by enhanced release of the NLRP3 inflammasome, Casepase-1 and pro-inflammatory cytokines IL-1ß, in the hippocampus of mice and BV2 cells. In summary, our experiments demonstrate that simultaneous exposure to Mn and Pb results in more severe hippocampus-dependent learning and memory impairment, which is attributed to epigenetic suppression of BDNF mediated by PP2A regulation.

Alternative splicing of the human rhomboid family-1 gene RHBDF1 inhibits epidermal growth factor receptor activation.

The human rhomboid-5 homolog-1 (RHBDF1) is a multi-transmembrane protein present mainly on the endoplasmic reticulum. RHBDF1 has been implicated in the activation of epidermal growth factor receptor (EGFR)-derived cell growth signals and other activities critical to cellular responses to stressful conditions, but details of this activation mechanism are unclear. Here, we report a RHBDF1 mRNA transcript alternative splicing variant X6 (RHBDF1 X6 or RHX6) that antagonizes RHBDF1 activities. We found that while the RHBDF1 gene is marginally expressed in breast tumor-adjacent normal tissues, it is markedly elevated in the tumor tissues. In sharp contrast, the RHX6 mRNA represents the primary RHBDF1 variant in normal breast epithelial cells and tumor-adjacent normal tissues but is diminished in breast cancer cells and tumors. We demonstrate that, functionally, RHX6 acts as an inhibitor of RHBDF1 activities. We show that artificially overexpressing RHX6 in breast cancer cells leads to retarded proliferation, migration, and decreased production of epithelial-mesenchymal transition-related adhesion molecules. Mechanically, RHX6 is able to inhibit the maturation of TACE, a protease that processes pro-TGFα, a pro-ligand of EGFR, and to prevent intracellular transportation of pro-TGFα to the cell surface. Additionally, we show that the production of RHX6 is under the control of the alternative splicing regulator RNA binding motif protein-4 (RBM4). Our findings suggest that differential splicing of the RHBDF1 gene transcript may have a regulatory role in the development of epithelial cell cancers.

Jujube metabolome selection determined the edible properties acquired during domestication.

Plants supply both food and medicinal compounds, which are ascribed to diverse metabolites produced by plants. However, studies on domestication-driven changes in the metabolome and genetic basis of bioactive molecules in perennial fruit trees are generally lacking. Here, we conducted multidimensional analyses revealing a singular domestication event involving the genomic and metabolomic selection of jujube trees (Ziziphus jujuba Mill.). The genomic selection for domesticated genes was highly enriched in metabolic pathways, including carbohydrates and specialized metabolism. Domesticated metabolome profiling indicated that 187 metabolites exhibited significant divergence as a result of directional selection. Malic acid was directly selected during domestication, and the simultaneous selection of specialized metabolites, including triterpenes, consequently lead to edible properties. Cyclopeptide alkaloids (CPAs) were specifically targeted for the divergence between dry and fresh cultivars. We identified 1080 significantly associated loci for 986 metabolites. Among them, 15 triterpenes were directly selected at six major loci, allowing the identification of a homologous cluster containing seven 2,3-oxidosqualene cyclases (OSCs). An OSC gene was found to contribute to the reduction in the content of triterpenes during domestication. The complete pathway for synthesizing ursolic acid was dissected by integration of the metabolome and transcriptome. Additionally, an N-methyltransferase involved in the biosynthesis of CPA and responsible for inter-cultivar content variation was identified. The present study promotes our understanding of the selection process of the global metabolome subsequent to fruit tree domestication and facilitates the genetic manipulation of specialized metabolites to enhance their edible traits.

Unleashing the potential of combining FGFR inhibitor and immune checkpoint blockade for FGF/FGFR signaling in tumor microenvironment.

BACKGROUND: Fibroblast growth factors (FGFs) and their receptors (FGFRs) play a crucial role in cell fate and angiogenesis, with dysregulation of the signaling axis driving tumorigenesis. Therefore, many studies have targeted FGF/FGFR signaling for cancer therapy and several FGFR inhibitors have promising results in different tumors but treatment efficiency may still be improved. The clinical use of immune checkpoint blockade (ICB) has resulted in sustained remission for patients. MAIN: Although there is limited data linking FGFR inhibitors and immunotherapy, preclinical research suggest that FGF/FGFR signaling is involved in regulating the tumor microenvironment (TME) including immune cells, vasculogenesis, and epithelial-mesenchymal transition (EMT). This raises the possibility that ICB in combination with FGFR-tyrosine kinase inhibitors (FGFR-TKIs) may be feasible for treatment option for patients with dysregulated FGF/FGFR signaling. CONCLUSION: Here, we review the role of FGF/FGFR signaling in TME regulation and the potential mechanisms of FGFR-TKI in combination with ICB. In addition, we review clinical data surrounding ICB alone or in combination with FGFR-TKI for the treatment of FGFR-dysregulated tumors, highlighting that FGFR inhibitors may sensitize the response to ICB by impacting various stages of the "cancer-immune cycle".

Identification of phenylketonuria patient genotypes using single-gene full-length sequencing.

BACKGROUND: Phenylketonuria (PKU) is a common, autosomal recessive inborn error of metabolism caused by PAH gene variants. After routine genetic analysis methods were applied, approximately 5% of PKU patients were still not diagnosed with a definite genotype. METHODS: In this study, for the first time, we identified PKU patients with unknown genotypes via single-gene full-length sequencing. RESULTS: The detection rate of PKU genotype increased from 94.6 to 99.4%, an increase of approximately 5%. The variants c.1199 + 502A > T and 1065 + 241C > A were found at a high frequency in Chinese PKU patients. CONCLUSION: Our study suggest that single-gene full-length sequencing is a rapid, efficient and cost-effective tool to improve the genotype detection rate of PKU patients. Moreover, we provides additional case data to support pathogenicity of deep intronic variants in PAH.

Volatile Organic Compounds of Bacillus pumilus Strain S1-10 Exhibit Fumigant Activity Against Meloidogyne incognita.

Root-knot nematodes (RKNs) are highly specialized parasites that cause significant yield losses worldwide. In this study, we isolated Bacillus pumilus strain S1-10 from the rhizosphere soil of Zingiber officinale Rosc. plants and evaluated its fumigant activity against Meloidogyne incognita. S1-10 exhibited a strong repellent effect on second-stage juveniles (J2s) of M. incognita, and in vitro assays indicated that S1-10 volatile organic compounds (VOCs) suppressed J2 activity and egg hatching. Under greenhouse conditions, 71 and 79% reductions of nematodes and eggs were detected on plants treated with S-10 VOCs compared with controls. Ten VOCs were identified through gas chromatography and mass spectrometry (GC-MS), of which 2-(methylamino)-ethanol (2-ME) had strong fumigant activity against J2s of M. incognita, with an LC50 value of 1.5 mM at 12 h. These results indicate that S1-10 represents a potential novel biocontrol agent for RKNs.

Biological Characteristics and Functional Analysis of the Linoleic Acid Synthase Gene ZjFAD2 in Jujube.

Jujube fruit is rich in linoleic acid and other bioactive components and has great potential to be used for the development of functional foods. However, the roles of FAD2 genes in linoleic acid biosynthesis in jujube fruit remain unclear. Here, we identified 15 major components in jujube and found that linoleic acid was the main unsaturated fatty acid; major differences in the content and distribution of linoleic acid in the pulp and seeds were observed, and levels of linoleic acid decreased during fruit maturation. Analysis of the fatty acid metabolome, genome, and gene expression patterns of cultivated and wild-type jujube revealed five ZjFAD2 family members highly related to linoleic acid biosynthesis. The heterologous expression of these five ZjFAD2 family members in tobacco revealed that all five of these genes increased the content of linoleic acid. Additionally, transient expression of these genes in jujube fruit and the virus-induced gene silencing (VIGS) test further confirmed the key roles of ZjFAD2-11 and ZjFAD2-1 in the biosynthesis of linoleic acid. The results of this research provide valuable insights into the molecular mechanism underlying linoleic acid synthesis in jujube and will aid the development of quality-oriented breeding strategies.

Methyl Jasmonate- and Salicylic Acid-Induced Transcription Factor ZjWRKY18 Regulates Triterpenoid Accumulation and Salt Stress Tolerance in Jujube.

Triterpenoids are important, pharmacologically active substances in jujube (Ziziphus jujuba Mill.), and play an important role in the plant's resistance to abiotic stress. However, regulation of their biosynthesis, and the underlying mechanism of their balance with stress resistance, remain poorly understood. In this study, we screened and functionally characterized the ZjWRKY18 transcription factor, which is associated with triterpenoid accumulation. The transcription factor is induced by methyl jasmonate and salicylic acid, and its activity was observed by gene overexpression and silencing experiments, combined with analyses of transcripts and metabolites. ZjWRKY18 gene silencing decreased the transcription of triterpenoid synthesis pathway genes and the corresponding triterpenoid content. Overexpression of the gene promoted the biosynthesis of jujube triterpenoids, as well as triterpenoids in tobacco and Arabidopsis thaliana. In addition, ZjWRKY18 binds to W-box sequences to activate promoters of 3-hydroxy-3-methyl glutaryl coenzyme A reductase and farnesyl pyrophosphate synthase, suggesting that ZjWRKY18 positively regulates the triterpenoid synthesis pathway. Overexpression of ZjWRKY18 also increased tolerance to salt stress in tobacco and Arabidopsis thaliana. These results highlight the potential use of ZjWRKY18 to improve triterpenoid biosynthesis and salt stress tolerance in plants, and provide a strong basis for metabolic engineering to improve the content of triterpenoids and breeding of jujube varieties that are resistant to stress.

Transcriptomic Complexity of Culm Growth and Development in Different Types of Moso Bamboo.

Moso bamboo is capable of both sexual and asexual reproduction during natural growth, resulting in four distinct types of culms: the bamboo shoot-culm, the seedling stem, the leptomorph rhizome, and a long-ignored culm-the outward-rhizome. Sometimes, when the outward rhizomes break through the soil, they continue to grow longitudinally and develop into a new individual. However, the roles of alternative transcription start sites (aTSS) or termination sites (aTTS) as well as alternative splicing (AS) have not been comprehensively studied for their development. To re-annotate the moso bamboo genome and identify genome-wide aTSS, aTTS, and AS in growing culms, we utilized single-molecule long-read sequencing technology. In total, 169,433 non-redundant isoforms and 14,840 new gene loci were identified. Among 1311 lncRNAs, most of which showed a positive correlation with their target mRNAs, one-third of these IncRNAs were preferentially expressed in winter bamboo shoots. In addition, the predominant AS type observed in moso bamboo was intron retention, while aTSS and aTTS events occurred more frequently than AS. Notably, most genes with AS events were also accompanied by aTSS and aTTS events. Outward rhizome growth in moso bamboo was associated with a significant increase in intron retention, possibly due to changes in the growth environment. As different types of moso bamboo culms grow and develop, a significant number of isoforms undergo changes in their conserved domains due to the regulation of aTSS, aTTS, and AS. As a result, these isoforms may play different roles than their original functions. These isoforms then performed different functions from their original roles, contributing to the transcriptomic complexity of moso bamboo. Overall, this study provided a comprehensive overview of the transcriptomic changes underlying different types of moso bamboo culm growth and development.