Salinity is a significant threat that causes considerable yield losses in date palm. The root endophytic fungus Piriformospora indica has proven effective in providing salt stress tolerance to host plants. However, the underlying molecular mechanism facilitating the date palm\'s response to P. indica inoculation, and its involvement in the salt stress tolerance, remains unknown. In this study, the colonization of P. indica on date palm seedlings exposed to saline conditions was observed through confocal microscopy, and its impact on gene expressions was evaluated using the transcriptomic analysis. Our findings show that P. indica colonization reinforced the cortical cells, prevented them from plasmolysis and cell death under salinity. The RNAseq analysis produced clean reads ranging from 62,040,451 to 3,652,095 across the treatment groups, successfully assembling into 30,600 annotated genes. Out of them, the number of differentially expressed genes (DEGs) varied across the treatments: i.e., 2523, 2031, and 1936 DEGs were upregulated, while 2323, 959, and 3546 were downregulated in Salt, Fungi, and Fungi+Salt groups, respectively. Furthermore, principal component analysis based on transcriptome profiles revealed discrete clustering of samples from different treatment groups. KEGG and GO pathways enrichment analysis highlighted variation in the number and types of enriched pathways among the treatments. Our study indicated variations in gene expression related to plant hormone biosynthesis and signal transduction (auxin, abscisic acid, gibberellin, and ethylene), ABC transporters, sodium/hydrogen exchanger, cation HKT transporter, transcription factors such as WRKY and MYBs, and the plant immune system (lipoxygenase and jasmonate) of the date palm seedlings. By characterizing the transcriptome of date palm roots under salt stress and with colonization of P. indica, the present findings provide valuable perspectives on the molecular mechanisms responsible for inducing salinity stress tolerance in plants.

Asthma is a heterogeneous airway inflammatory disease that can be classified according to the inflammatory phenotype. The pathogenesis, clinical features, response to hormone therapy, and prognosis of different inflammatory phenotypes differ significantly. This condition also refers to age-related chronic ailments. Here, we intend to identify the function of aging-related genes in different inflammatory phenotypes of asthma using bioinformatic analyses. Initially, the research adopted the GSEA analysis to understand the fundamental mechanisms that govern different inflammatory phenotypes of asthma pathogenesis and use the CIBERSORT algorithm to assess the immune cell composition. The differentially expressed genes (DEGs) of eosinophilic asthma (EA), neutrophilic asthma (NA), and paucigranulocytic asthma (PGA) were identified through the limma R package. Aging-related genes, screened from multiple databases, were intersected with DEGs of asthma to obtain the asthma-aging-related DEGs. Then, the GO and KEGG pathway enrichment analyses showed that the NA- and EA-aging-related DEGs are involved in the various cytokine-mediated signaling pathways. PPI network and correlation analysis were performed to identify and evaluate the correlation of the hub genes. Further, the clinical characteristics of asthma-aging-related DEGs were explored through ROC analysis. 3 and 12 aging-related DEGs in EA and NA patients show high diagnostic accuracy, respectively (AUC >0.7). This study provided valuable insights into aging-related gene therapy for phenotype-specific asthma. Moreover, the study suggests that effective interventions against asthma may operate by disrupting the detrimental cycle of \"aging induces metabolic diseases, which exacerbate aging\".

UNASSIGNED: Several studies have revealed that Epstein-Barr virus (EBV) infection raised the likelihood of developing Alzheimer\'s disease (AD) via infecting B lymphocytes. The purpose of the current investigation was to assess the possible association between EBV infection and AD.
UNASSIGNED: The microarray datasets GSE49628, GSE126379, GSE122063, and GSE132903 were utilized to extract DEGs by using the GEO2R tool of the GEO platform. The STRING tool was used to determine the interaction between the DEGs, and Cytoscape was used to visualize the results. The DEGs that were found underwent function analysis, including pathway and GO, using the DAVID 2021 and ClueGo/CluePedia. By using MNC, MCC, Degree, and Radiality of cytoHubba, we identified seven common key genes. Gene co-expression analysis was performed through the GeneMANIA web tool. Furthermore, expression analysis of key genes was performed through GTEx software, which have been identified in various human brain regions. The miRNA-gene interaction was performed through the miRNet v 2.0 tool. DsigDB on the Enrichr platform was utilized to extract therapeutic drugs connected to key genes.
UNASSIGNED: In GEO2R analysis of datasets with |log2FC|≥ 0.5 and p-value <0.05, 8386, 10,434, 7408, and 759 genes were identified. A total of 141 common DEGs were identified by combining the extracted genes of different datasets. A total of 141 nodes and 207 edges were found during the PPI analysis. The DEG GO analysis with substantial alterations disclosed that they are associated to molecular functions and biological processes, such as positive regulation of neuron death, autophagy regulation of mitochondrion, response of cell to insulin stimulus, calcium signaling regulation, organelle transport along microtubules, protein kinase activity, and phosphoserine binding. Kyoto Encyclopedia of Genes and Genomes analysis discovered the correlation between the DEGs in pathways of neurodegeneration: multiple disease, cell cycle, and cGMP-PKG signaling pathway. Finally, YWHAH, YWHAG, YWHAB, YWHAZ, MAP2K1, PPP2CA, and TUBB genes were identified that are strongly linked to EBV and AD. Three miRNAs, i.e., hsa-mir-15a-5p, hsa-let-7a-5p, and hsa-mir-7-5p, were identified to regulate most of hub genes that are associated with EBV and AD. Further top 10 significant therapeutic drugs were predicted.
UNASSIGNED: We have discovered new biomarkers and therapeutic targets for AD, as well as the possible biological mechanisms whereby infection with EBV may be involved in AD susceptibility for the first time.

UNASSIGNED: This study aims to identify differentially expressed genes (DEGs) between high-risk and non-high-risk groups in neuroblastoma (NB), construct a prognostic model, and establish a risk score formula.
UNASSIGNED: The NB dataset GSE49710 (n = 498) from the GEO database served as the training cohort to select DEGs between high-risk and non-high-risk NB groups. Cellular senescence-related genes were obtained from the Aging Atlas database. Intersection genes from both datasets were identified as key genes of cellular senescence-related genes (SRGs). A prognostic model was constructed using Univariate Cox regression analysis and the Lasso algorithm with SRGs. Validation was performed using the E-MTAB-8248 cohort (n = 223). The expression levels of AURKA and CENPA were evaluated via RT-qPCR in two clinical NB sample groups.
UNASSIGNED: Eight SRGs were identified, and a prognostic model comprising five genes related to cellular senescence was constructed. AURKA and CENPA showed significant expression in clinical samples and were closely associated with cellular senescence.
UNASSIGNED: The prognostic model consisted with five cellular senescence related genes effectively predicts the prognosis of NB patients. AURKA and CENPA represent promising targets in NB for predicting cellular senescence, offering potential insights for NB therapy.

BACKGROUND: The pathogenesis of noncystic fibrosis bronchiectasis in adults is complex, and the relevant molecular mechanisms remain unclear. In this study, we constructed a panoramic map of bronchiectasis mRNA, explored the potential molecular mechanisms, and identified potential therapeutic targets, thus providing a new clinical perspective for the preventive management of bronchiectasis and its acute exacerbation.
METHODS: The mRNA profiles of peripheral blood and bronchiectasis tissues were obtained through transcriptome sequencing and public databases, and bioinformatics methods were used to screen for differentially expressed genes (DEGs). The DEGs were then subjected to biological function and pathway analyses. Some DEGs were validated using a real-time quantitative polymerase chain reaction (RT-qPCR) in peripheral blood. Spearman\'s correlation analysis was used to analyse the correlation between DEGs and clinical indicators.
RESULTS: Based on transcriptome sequencing and public databases, the mRNA profile of bronchiectasis was determined. DEGs were obtained from the peripheral blood sequencing dataset (985 DEGs), tissue sequencing dataset (2919 DEGs), and GSE97258 dataset (1083 DEGs). Bioinformatics analysis showed that upregulated DEGs had enriched neutrophil-related pathways, and downregulated DEGs had enriched ribosome-related pathways. RT-qPCR testing confirmed the upregulated expression of VCAN, SESTD1, SLC12A1, CD177, IFI44L, SIGLEC1, and RSAD2 in bronchiectasis. These genes were related to many clinical parameters, such as neutrophils, C-reactive protein, and procalcitonin (P < 0.05).
CONCLUSIONS: Transcriptomic methods were used to construct a panoramic map of bronchiectasis mRNA expression. The findings showed that neutrophil activation, chronic inflammation, immune regulation, impaired ribosomal function, oxidative phosphorylation, and energy metabolism disorders are important factors in the development of bronchiectasis. VCAN, SESTD1, SLC12A1, CD177, IFI44L, SIGLEC1, and RSAD2 may play important roles in the pathogenesis of bronchiectasis and are potential therapeutic targets.

Aspergillus carbonarius causes severe decays on berries in vineyards and is among the main fungal species responsible for grape contamination by ochratoxin A (OTA), which is the foremost mycotoxin produced by this fungus. The main goal of this study was to investigate at the transcriptome level the comparative profiles between two table grape varieties (Victoria and Fraoula, the white and red variety, respectively) after their inoculation with a virulent OTA-producing A. carbonarius strain. The two varieties revealed quite different transcriptomic signatures and the expression profiles of the differential expressed genes (DEGs) highlighted distinct and variety-specific responses during the infection period. The significant enrichment of pathways related to the modulation of transcriptional dynamics towards the activation of defence responses, the triggering of the metabolic shunt for the biosynthesis of secondary metabolites, mainly phenylpropanoids, and the upregulation of DEGs encoding phytoalexins, transcription factors, and genes involved in plant-pathogen interaction and immune signaling transduction was revealed in an early time point in Fraoula, whereas, in Victoria, any transcriptional reprogramming was observed after a delay. However, both varieties, to some extent, also showed common expression dynamics for specific DEG families, such as those encoding for laccases and stilbene synthases. Jasmonate (JA) may play a critical modulator role in the defence machinery as various JA-biosynthetic DEGs were upregulated. Along with the broader modulation of the transcriptome that was observed in white grape, expression profiles of specific A. carbonarius genes related to pathogenesis, fungal sporulation, and conidiation highlight the higher susceptibility of Victoria. Furthermore, the A. carbonarius transcriptional patterns directly associated with the regulation of the pathogen OTA-biosynthesis gene cluster were more highly induced in Victoria than in Fraoula. The latter was less contaminated by OTA and showed substantially lower sporulation. These findings contribute to uncovering the interplay beyond this plant-microbe interaction.

UNASSIGNED: The relationship between human immunodeficiency virus (HIV) infection and pulmonary arterial hypertension (PAH) has garnered significant scrutiny. Individuals with HIV infection have a higher risk of developing PAH. However, the specific mechanism of HIV-associated PAH remains unclear. Our study aims at investigating the shared biomarkers in HIV infection and PAH and predicting the potential therapeutic target for HIV-associated PAH.
UNASSIGNED: Data for HIV infection and PAH were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) analysis was performed to detect shared genes in HIV infection and PAH. Enrichment analysis was conducted to identify the function of common DEGs. Protein-protein interaction (PPI) analysis was used to detect key genes. These crucial genes were subsequently verified by RT-qPCR. Finally, candidate drugs were identified by using the Drug Signatures Database (DSigDB).
UNASSIGNED: Nineteen common DEGs were identified in HIV infection and PAH. Enrichment analysis exhibited that the functions of these genes were mainly enriched in inflammatory responses, mainly including cellular immunity and interaction between viral proteins and cytokines. By constructing PPI networks, we identified the key gene CC-type chemokine ligand 5 (CCL5), and we verified that CCL5 was highly expressed in hypoxia induced human pulmonary artery endothelial cells (hPAECs) and human pulmonary artery smooth muscle cells (hPASMCs). In addition, we predicted 10 potential drugs targeting CCL5 by Autodock Vina.
UNASSIGNED: This study revealed that CCL5 might be a common biomarker of HIV infection and PAH and provided a new therapeutic target for HIV-associated PAH. However, further clinical validation is still indispensable.

Lung Squamous Cell Carcinoma is characterised by significant alterations in RNA expression patterns, and a lack of early symptoms and diagnosis results in poor survival rates. Our study aimed to identify the hub genes involved in LUSC by differential expression analysis and their influence on overall survival rates in patients. Thus, identifying genes with the potential to serve as biomarkers and therapeutic targets. RNA sequence data for LUSC was obtained from TCGA and analysed using R Studio. Survival analysis was performed on DE genes. PPI network and hub gene analysis was performed on survival-relevant genes. Enrichment analysis was conducted on the PPI network to elucidate the functional roles of hub genes. Our analysis identified 2774 DEGs in LUSC patient datasets. Survival analysis revealed 511 genes with a significant impact on patient survival. Among these, 20 hub genes-FN1, ACTB, HGF, PDGFRB, PTEN, SNAI1, TGFBR1, ESR1, SERPINE1, THBS1, PDGFRA, VWF, BMP2, LEP, VTN, PXN, ABL1, ITGA3 and ANXA5-were found to have lower expression levels associated with better patient survival, whereas high expression of SOX2 correlated with longer survival. Enrichment analysis indicated that these hub genes are involved in critical cellular and cancer-related pathways. Our study has identified six key hub genes that are differentially expressed and exhibit significant influence over LUSC patient survival outcomes. Further, in vitro and in vivo studies must be conducted on the key genes for their utilisation as therapeutic targets and biomarkers in LUSC.

A two-group comparison test is generally performed on RNA sequencing data to detect differentially expressed genes (DEGs). However, the accuracy of this method is low due to the small sample size. To address this, we propose a method using fuzzy clustering that artificially generates data with expression patterns similar to those of DEGs to identify genes that are highly likely to be classified into the same cluster as the initial cluster data. The proposed method is advantageous in that it does not perform any test. Furthermore, a certain level of accuracy can be maintained even when the sample size is biased, and we show that such a situation may improve the accuracy of the proposed method. We compared the proposed method with the conventional method using simulations. In the simulations, we changed the sample size and difference between the expression levels of group 1 and group 2 in the DEGs to obtain the desired accuracy of the proposed method. The results show that the proposed method is superior in all cases under the conditions simulated. We also show that the effect of the difference between group 1 and group 2 on the accuracy is more prominent when the sample size is biased.

Hulless barley is a cold-resistant crop widely planted in the northwest plateau of China. It is also the main food crop in this region. Phosphorus (P), as one of the important essential nutrient elements, regulates plant growth and defense. This study aimed to analyze the development and related molecular mechanisms of hulless barley under P deficiency and explore the regulatory genes so as to provide a basis for subsequent molecular breeding research. Transcriptome analysis was performed on the root and leaf samples of hulless barley cultured with different concentrations of KH2PO4 (1 mM and 10 μM) Hoagland solution. A total of 46,439 genes were finally obtained by the combined analysis of leaf and root samples. Among them, 325 and 453 genes had more than twofold differences in expression. These differentially expressed genes (DEGs) mainly participated in the abiotic stress biosynthetic process through Gene Ontology prediction. Moreover, the Kyoto Encyclopedia of Genes and Genomes showed that DEGs were mainly involved in photosynthesis, plant hormone signal transduction, glycolysis, phenylpropanoid biosynthesis, and synthesis of metabolites. These pathways also appeared in other abiotic stresses. Plants initiated multiple hormone synergistic regulatory mechanisms to maintain growth under P-deficient conditions. Transcription factors (TFs) also proved these predictions. The enrichment of ARR-B TFs, which positively regulated the phosphorelay-mediated cytokinin signal transduction, and some other TFs (AP2, GRAS, and ARF) was related to plant hormone regulation. Some DEGs showed different values in their FPKM (fragment per kilobase of transcript per million mapped reads), but the expression trends of genes responding to stress and phosphorylation remained highly consistent. Therefore, in the case of P deficiency, the first response of plants was the expression of stress-related genes. The effects of this stress on plant metabolites need to be further studied to improve the relevant regulatory mechanisms so as to further understand the importance of P in the development and stress resistance of hulless barley.