RNA Network Research Articles

Revealing the novel metabolism-related genes in the ossification of the ligamentum flavum based on whole transcriptomic data.

The ossification of the ligamentum flavum (OLF) is one of the major causes of thoracic myelopathy. Previous studies indicated there might be a potential link between metabolic disorder and pathogenesis of OLF. The aim of this study was to determine the potential role of metabolic disorder in the pathogenesis of OLF using the strict bioinformatic workflow for metabolism-related genes and experimental validation. A series of bioinformatic approaches based on metabolism-related genes were conducted to compare the metabolism score between OLF tissues and normal ligamentum flavum (LF) tissues using the single sample gene set enrichment analysis. The OLF-related and metabolism-related differentially expressed genes (OMDEGs) were screened out, and the biological functions of OMDEGs were explored, including the Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and protein-protein interaction. The competing endogenous RNA (ceRNA) network based on pairs of miRNA-hub OMDEGs was constructed. The correlation analysis was conducted to explore the potential relationship between metabolic disorder and immunity abnormality in OLF. In the end, the cell experiments were performed to validate the roles of GBE1 and TNF-α in the osteogenic differentiation of LF cells. There was a significant difference of metabolism score between OLF tissues and normal LF tissues. Forty-nine OMDEGs were screened out and their biological functions were determined. The ceRNA network containing three hub OMDEGs and five differentially expressed miRNAs (DEmiRNAs) was built. The correlation analysis between hub OMDEGs and OLF-related infiltrating immune cells indicated that metabolic disorder might contribute to the OLF via altering the local immune status of LF tissues. The cell experiments determined the important roles of GBE1 expression and TNF-α in the osteogenic differentiation of LF cells. This research, for the first time, preliminarily illustrated the vital role of metabolic disorder in the pathogenesis of OLF using strict bioinformatic algorithms and experimental validation for metabolism-related genes, which could provide new insights for investigating disease mechanism and screening effective therapeutic targets of OLF in the future.

Revealing the dynamic whole transcriptome landscape of Clonorchis sinensis: Insights into the regulatory roles of noncoding RNAs and microtubule-related genes in development.

Clonorchis sinensis is a significant zoonotic food-borne parasite that causes a range of hepatobiliary diseases, which in severe cases can even lead to cholangiocarcinoma. To explore new diagnostic and treatment strategies, the dynamic RNA regulatory processes across different developmental stages of C. sinensis were analyzed by using whole-transcriptome sequencing. The chromosomal-level genome of C. sinensis was used for sequence alignment and annotation. In this study, we identified a total of 59,103 RNAs in the whole genome, including 2,384 miRNAs, 25,459 mRNAs, 27,564 lncRNAs and 3,696 circRNAs. Differential expression analysis identified 6,556 differentially expressed mRNAs, 2,231 lncRNAs, 877 miRNAs and 20 circRNAs at different developmental stages. Functional enrichment analysis highlighted the critical role of microtubule-related biological processes in the growth and development of C. sinensis. And coexpression analysis revealed 97 lncRNAs and 85 circRNAs that were coexpressed with 42 differentially expressed mRNAs that associated with microtubules at different developmental stages of C. sinensis. The expression of the microtubule-related genes dynein light chain 2 (DLC2) and dynein light chain 4 (DLC4) increased with C. sinensis development, and DLC2/4 could be inhibited by albendazole. Finally, by constructing competing endogenous RNA (ceRNA) networks, the lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA regulatory relationships were constructed, and the ceRNA networks of MSTRG.14258.5-novel_miR_2287-newGene_28215 and MSTRG.14258.5-novel_miR_2216-CSKR_109340 were verified. This study suggests, through whole transcriptome sequencing, that the context of microtubule regulation may play an essential role in the development and growth of C. sinensis.

Exosomes originating from neural stem cells undergoing necroptosis participate in cellular communication by inducing TSC2 upregulation of recipient cells following spinal cord injury.

We previously demonstrated that inhibiting neural stem cells necroptosis enhances functional recovery after spinal cord injury. While exosomes are recognized as playing a pivotal role in neural stem cells exocrine function, their precise function in spinal cord injury remains unclear. To investigate the role of exosomes generated following neural stem cells necroptosis after spinal cord injury, we conducted single-cell RNA sequencing and validated that neural stem cells originate from ependymal cells and undergo necroptosis in response to spinal cord injury. Subsequently, we established an in vitro necroptosis model using neural stem cells isolated from embryonic mice aged 16-17 days and extracted exosomes. The results showed that necroptosis did not significantly impact the fundamental characteristics or number of exosomes. Transcriptome sequencing of exosomes in necroptosis group identified 108 differentially expressed messenger RNAs, 104 long non-coding RNAs, 720 circular RNAs, and 14 microRNAs compared with the control group. Construction of a competing endogenous RNA network identified the following hub genes: tuberous sclerosis 2 (Tsc2), solute carrier family 16 member 3 (Slc16a3), and forkhead box protein P1 (Foxpl). Notably, a significant elevation in TSC2 expression was observed in spinal cord tissues following spinal cord injury. TSC2-positive cells were localized around SRY-box transcription factor 2-positive cells within the injury zone. Furthermore, in vitro analysis revealed increased TSC2 expression in exosomal receptor cells compared with other cells. Further assessment of cellular communication following spinal cord injury showed that Tsc2 was involved in ependymal cellular communication at 1 and 3 days post-injury through the epidermal growth factor and midkine signaling pathways. In addition, Slc16a3 participated in cellular communication in ependymal cells at 7 days post-injury via the vascular endothelial growth factor and macrophage migration inhibitory factor signaling pathways. Collectively, these findings confirm that exosomes derived from neural stem cells undergoing necroptosis play an important role in cellular communication after spinal cord injury and induce TSC2 upregulation in recipient cells.

Investigation of prognostic values of immune infiltration and LGMN expression in the microenvironment of osteosarcoma

BackgroundOsteosarcoma (OS), the most common primary malignant bone tumor, predominantly affects children and young adults and is characterized by high invasiveness and poor prognosis. Despite therapeutic advancements, the survival rate remains suboptimal, indicating an urgent need for novel biomarkers and therapeutic targets. This study aimed to investigate the prognostic significance of LGMN expression and immune cell infiltration in the tumor microenvironment of OS.MethodsWe performed an integrative bioinformatics analysis utilizing the GEO and TARGET-OS databases to identify differentially expressed genes (DEGs) associated with LGMN in OS. We conducted Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) to explore the biological pathways and functions. Additionally, we constructed protein–protein interaction (PPI) networks, a competing endogenous RNA (ceRNA) network, and applied the CIBERSORT algorithm to quantify immune cell infiltration. The diagnostic and prognostic values of LGMN were evaluated using the area under the receiver operating characteristic (ROC) curve and Cox regression analysis. Furthermore, we employed Consensus Clustering Analysis to explore the heterogeneity within OS samples based on LGMN expression.ResultsThe analysis revealed significant upregulation of LGMN in OS tissues. DEGs were enriched in immune response and antigen processing pathways, suggesting LGMN's role in immune modulation within the TME. The PPI and ceRNA network analyses provided insights into the regulatory mechanisms involving LGMN. Immune cell infiltration analysis indicated a correlation between high LGMN expression and increased abundance of M2 macrophages, implicating an immunosuppressive role. The diagnostic AUC for LGMN was 0.799, demonstrating its potential as a diagnostic biomarker. High LGMN expression correlated with reduced overall survival (OS) and progression-free survival (PFS). Importantly, Consensus Clustering Analysis identified two distinct subtypes of OS, highlighting the heterogeneity and potential for personalized medicine approaches.ConclusionsOur study underscores the prognostic value of LGMN in osteosarcoma and its potential as a therapeutic target. The identification of LGMN-associated immune cell subsets and the discovery of distinct OS subtypes through Consensus Clustering Analysis provide new avenues for understanding the immunosuppressive TME of OS and may aid in the development of personalized treatment strategies. Further validation in larger cohorts is warranted to confirm these findings.

LncRNA DANCR promotes macrophage lipid accumulation through modulation of membrane cholesterol transporters.

The progression of atherosclerosis (AS), the pathological foundation of coronary artery disease (CAD), is featured by massive lipid deposition in the vessel wall. LncRNAs are implicated in lipid disorder and AS, whereas the specific role of lncRNA DANCR in atherogenesis remains unknown. Here, we demonstrated that DANCR promotes macrophage lipid accumulation by regulating the expression of membrane cholesterol transport proteins. qPCR showed that compared to control groups, CAD patients and atherosclerotic mice had higher DANCR levels. Treating human THP-1 macrophages and mouse RAW264.7 macrophages with ox-LDL significantly upregulated the expression levels of DANCR. Oil Red O staining showed that the silence of DANCR robustly reduced, while overexpression of DANCR significantly increased the numbers and size of lipid droplets in ox-LDL-treated THP-1 macrophages. In contrast, the opposite phenomena were observed in DANCR overexpressing cells. The expression of ABCA1, ABCG1, SR-BI, and NBD-cholesterol efflux was increased obviously by DANCR inhibition and decreased by DANCR overexpression, respectively. Furthermore, transfection with DANCR siRNA induced a robust decrease in the levels of CD36, SR-A, and Dil-ox-LDL uptake, while DANCR overexpression amplified the expression of CD36, SR-A and the uptake of Dil-ox-LDL in lipid-laden macrophages. Lastly, we found that the effects of DANCR on macrophage lipid accumulation and the expression of membrane cholesterol transport proteins were not likely related to miR-33a. The present study unraveled the adverse role of DANCR in foam cell formation and its relationship with cholesterol transport proteins. However, the competing endogenous RNA network underlying these phenomena warrants further exploration.

Bioinformatics analysis of potential pathogenesis and risk genes of neuroinflammation-promoted brain injury in intracerebral hemorrhage

IntroductionSpontaneous (non-traumatic) intracerebral hemorrhage (ICH) is one of the major causes of global death. The purpose of our bioinformatics analysis was to detect viable pathophysiological targets and small-molecule drug candidates and to identify the precise secondary mechanisms of brain injury in ICH. Material and methodsThe GSE24265 dataset, consisting of data from four perihematomal brain tissues and seven contralateral brain tissues, was downloaded from the Gene Expression Omnibus (GEO) database and screened for differentially expressed genes (DEGs) in ICH. Online analysis tool GEO2R and Drug Susceptibility Assessment Module within the ACBI Bioinformation tool was used for data differential expression analysis. TargetScan, miRDB, and RNA22 were used to investigate the miRNAs regulating the DEGs. The functional annotation of DEGs was performed using Gene Ontology (GO) resources, and the cell signaling pathway analysis of DEGs was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG). DAVID is used to perform GO function enrichment analysis and KEGG pathway analysis of candidate target genes. Enrichment analysis was performed for delving the molecular mechanism of DEGs, and protein–protein interaction (PPI) networks and microRNA (miRNA)-messenger RNA (mRNA) networks were used to reveal the hub nodes and the related interaction relationships. Hub genes and miRNA-mRNA interaction of PPI network were identified by STRING version 12.0 online software and Cytoscape. Next, the DEGs were analyzed using the L1000CDS2 database to identify small-molecule compounds with potential therapeutic effects. ResultsA total of 325 upregulated genes and 103 downregulated genes associated with ICH were identified. The biological functions of DEGs associated with ICH are mainly involved in the inflammatory response, chemokine activity, and immune response. The KEGG analysis identified several pathways significantly associated with ICH, including but not limited to cytokine-cytokine receptor interaction and MAPK signaling pathway. A PPI network consisting of 188 nodes and 563 edges was constructed using STRING, and 27 hub genes were identified with Cytoscape software. The miRNA-mRNA network with high connectivity contained key 27 mRNAs (from C-C motif chemokine ligand 5 (CCL5), C-C motif chemokine ligand 8 (CCL8), …., to dishevelled-associated activator of morphogenesis 1 (DAAM1), and FRAT regulator of WNT signaling pathway 1 (FRAT1)) and 135 candidate miRNAs. These genes and miRNAs are closely related to secondary brain injury induced by ICH. In addition, a L1000CDS2 analysis of six small-molecule compounds revealed their therapeutic potential. ConclusionsOur study explores the pathogenesis of brain tissue injury promoted by neuroinflammation in ICH and extends the clinical utility of its key genes. At the same time, we constructed a miRNA-mRNA network which may play crucial roles in the pathogenesis of ICH. In addition, we obtained six small molecule compounds that will have anti-inflammatory effects on ICH, including Geldanamycin, Dasatinib, BMS-345541, Saracatinib, and Afatinib.

Correlation of disulfidptosis and periodontitis: New insights and clinical significance

ObjectivesThis study aims to investigate and predict the therapeutic agents associated with disulfidptosis in periodontitis. DesignThe dataset GSE10334 was downloaded from the Gene Expression Omnibus (GEO) database and used to train a least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM–RFE) algorithm to identify genes associated with disulfidptosis in periodontitis. GSE16134 validation sets, polymerase chain reaction (PCR), and gingival immunofluorescence were used to verify the results.Single-gene Gene Set Enrichment Analysis (GSEA) was performed to explore the potential mechanisms and functions of the characterized genes. Immune infiltration and correlation analyses were performed, and competing endogenous RNA (ceRNA) networks were constructed. Effective therapeutic drugs were then predicted using the DGIdb database, and molecular docking was used to validate binding affinity. ResultsSix genes (SLC7A11, SLC3A2, RPN1, NCKAP1, LRPPRC, and NDUFS1) associated with disulfidptosis in periodontitis were obtained. Validation results from external datasets and experiments were consistent with the screening results. Single-gene GSEA analysis was mainly enriched for antigen presentation and immune-related pathways and functions.Immune infiltration and correlation analyses revealed significant regulatory relationships between these genes and plasma cells, resting dendritic cell, and activated NK cells. The ceRNA network was visualized. And ME-344, NV-128, and RILUZOLE, which have good affinity to target genes, were identified as promising agents for the treatment of periodontitis. ConclusionsSLC7A11, SLC3A2, RPN1, NCKAP1, LRPPRC, and NDUFS1 are targets associated with disulfidptosis in periodontitis, and ME-344, NV-128, and RILUZOLE are promising agents for the treatment of periodontitis.

Identification of macrophage differentiation related genes and subtypes linking atherosclerosis plaque processing and metabolic syndrome via integrated bulk and single-cell sequence analysis

Metabolic syndrome(MS) is a separate risk factor for the advancement of atherosclerosis(AS) plaque but mechanism behind this remains unclear. There may be a significant role for the immune system in this process. This study aims to identify potential diagnostic genes in MS patients at a higher risk of developing and progressing to AS. Datasets were retrevied from gene expression omnibus(GEO) database and differentially expressed genes were identified. Hub genes, immune cell dysregulation and AS subtypes were identified using a conbination of muliple bioinformatic analysis, machine learning and consensus clustering. Diagnostic value of hub genes was estimated using a nomogram and ROC analysis. Finally, enrichment analysis, competing endogenous RNA(ceRNA) network, single-cell RNA(scRNA) sequencing analysis and drug-protein interaction prediction was constructed to identify the functional roles, potential regulators and distribution for hub genes. Four hub genes and two macrophage-related subtypes were identified. Their strong diagnostic value was validated and functional process were identified. ScRNA analysis identified the macrophage differentiation regulation function of F13A1. CeRNA network and drug-protein binding modes revealed the potential therapeutic method. Four immune-correlated hub genes(F13A1, MMRN1, SLCO2A1 and ZNF521) were identified with their diagnostic value being assesed, which F13A1 was found strong correlated with macrophage differentiation and could be potential diagnostic and therapeutic marker for AS progression in MS patients.

Transcriptome sequencing reveals non-coding RNAs respond to porcine reproductive and respiratory syndrome virus and Haemophilus parasuis co-infection in Kele piglets.

Co-infection with porcine reproductive and respiratory syndrome virus (PRRSV) and Haemophilus parasuis (HPS) has severely restricted the healthy development of pig breeding. Exploring disease resistance of non-coding RNAs in pigs co-infected with PRRSV and HPS is therefore critical to complement and elucidate the molecular mechanisms of disease resistance in Kele piglets and to innovate the use of local pig germplasm resources in China. RNA-seq of lungs from Kele piglets with single-infection of PRRSV or HPS and co-infection of both pathogens was performed. Two hundred and twenty-five differentially expressed long non-coding RNAs (DElncRNAs) and 30 DEmicroRNAs (DEmiRNAs) were identified and characterized in the PRRSV and HPS co-infection (PRRSV-HPS) group. Compared with the single-infection groups, 146 unique DElncRNAs, 17 unique DEmiRNAs, and 206 target differentially expressed genes (DEGs) were identified in the PRRSV-HPS group. The expression patterns of 20 DEmiRNAs and DElncRNAs confirmed by real-time quantitative polymerase chain reaction (RT-qPCR) were consistent with those determined by high-throughput sequencing. In the PRRSV-HPS group, the target DEGs were enriched in eight immune Gene Ontology terms relating to two unique DEmiRNAs and 16 DElncRNAs, and the unique target DEGs participated the host immune response to pathogens infection by affecting 15 immune-related Kyoto Encyclopedia of Genes and Genomes enrichment pathways. Notably, competitive endogenous RNA (ceRNA) networks of different groups were constructed, and the ssc-miR-671-5p miRNA was validated as a potential regulatory factor to regulate DTX4 and AEBP1 genes to achieve innate antiviral effects and inhibit pulmonary fibrosis by dual-luciferase reporter assays. These results provided insight into further study on the molecular mechanisms of resistance to PRRSV and HPS co-infection in Kele piglets.

Integrated Analysis of Transcriptome Profiles and lncRNA-miRNA-mRNA Competing Endogenous RNA Regulatory Network to Identify Biological Functional Effects of Genes and Pathways Associated with Johne's Disease in Dairy Cattle.

Paratuberculosis or Johne's disease (JD), a chronic granulomatous gastroenteritis caused by Mycobacterium avium subsp. paratuberculosis (MAP), causes huge economic losses and reduces animal welfare in dairy cattle herds worldwide. At present, molecular mechanisms and biological functions involved in immune responses to MAP infection of dairy cattle are not clearly understood. Our purpose was to integrate transcriptomic profiles and competing endogenous RNA (ceRNA) network analyses to identify key messenger RNAs (mRNAs) and regulatory RNAs involved in molecular regulation of peripheral blood mononuclear cells (PBMCs) for MAP infection in dairy cattle. In total, 28 lncRNAs, 42 miRNAs, and 370 mRNAs were identified by integrating gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In this regard, we identified 21 hub genes (CCL20, CCL5, CD40, CSF2, CXCL8, EIF2AK2, FOS, IL10, IL17A, IL1A, IL1B, IRF1, MX2, NFKB1, NFKBIA, PTGS2, SOCS3, TLR4, TNF, TNFAIP3, and VCAM1) involved in MAP infection. Furthermore, eight candidate subnets with eight lncRNAs, 29 miRNAs, and 237 mRNAs were detected through clustering analyses, whereas GO enrichment analysis of identified RNAs revealed 510, 22, and 11 significantly enriched GO terms related to MAP infection in biological process, molecular function, and cellular component categories, respectively. The main metabolic-signaling pathways related to MAP infection that were enriched included the immune system process, defense response, response to cytokine, leukocyte migration, regulation of T cell activation, defense response to bacterium, NOD-like receptor, B cell receptor, TNF, NF-kappa B, IL-17, and T cell receptor signaling pathways. Contributions of transcriptome profiles from MAP-positive and MAP-negative sample groups plus a ceRNA regulatory network underlying phenotypic differences in the intensity of pathogenicity of JD provided novel insights into molecular mechanisms associated with immune system responses to MAP infection in dairy cattle.

Integrated Metabolomics and Transcriptomics Analysis of Anacardic Acid Inhibition of Breast Cancer Cell Viability.

Anacardic acid (AnAc) inhibits the growth of estrogen receptor α (ERα)-positive MCF-7 breast cancer (BC) cells and MDA-MB-231 triple-negative BC (TNBC) cells, without affecting primary breast epithelial cells. RNA sequencing (seq) and network analysis of AnAc-treated MCF-7 and MDA-MB-231 cells suggested that AnAc inhibited lipid biosynthesis and increased endoplasmic reticulum stress. To investigate the impact of AnAc on cellular metabolism, a comprehensive untargeted metabolomics analysis was performed in five independent replicates of control versus AnAc-treated MCF-7 and MDA-MB-231 cells and additional TNBC cell lines: MDA-MB-468, BT-20, and HCC1806. An analysis of the global metabolome identified key metabolic differences between control and AnAc-treated within each BC cell line and between MCF-7 and the TNBC cell lines as well as metabolic diversity among the four TNBC cell lines, reflecting TNBC heterogeneity. AnAc-regulated metabolites were involved in alanine, aspartate, glutamate, and glutathione metabolism; the pentose phosphate pathway; and the citric acid cycle. Integration of the transcriptome and metabolome data for MCF-7 and MDA-MB-231 identified Signal transduction: mTORC1 downstream signaling in both cell lines and additional cell-specific pathways. Together, these data suggest that AnAc treatment differentially alters multiple pools of cellular building blocks, nutrients, and transcripts resulting in reduced BC cell viability.

Exploring the potential biological significance of KDELR family genes in lung adenocarcinoma

The Lys-Asp-Glu-Leu receptor (KDELR) family genes play critical roles in a variety of biological processes in different tumors. Our study aimed to provide a comprehensive analysis of the potential roles of KDELRs in lung adenocarcinoma (LUAD). Utilizing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, as well as clinical samples, we conducted a series of analyses and validations using R software tools and various online resources. The results showed that KDELR family genes and proteins were highly expressed and associated with a poor prognosis of LUAD. Promoter hypomethylation and the competing endogenous RNA (ceRNA) network of PCAT6/hsa-miR-326/KDELR1 might be potential causes of aberrant KDELR1 overexpression in LUAD. Three key Transcription factors (TFs) (SPI1, EP300, and MAZ) and a TFs-miRNAs-KDELRs network (involving 11 TFs) might be involved in modulating KDELRs expression abnormalities. Gene Set Enrichment Analysis (GSEA) indicated enrichment of genes highly expressing KDELR1, KDELR2, and KDELR3 in MTORC1_SIGNALING, P53_PATHWAY, and ANGIOGENESIS. Negative correlations between KDELRs expression and CD8 + T cell infiltration, as well as CTLA-4 expression. Our multiple analyses suggested that the KDELRs are important signaling molecules in LUAD. These results provided novel insights for developing prognostic markers and novel therapies of LUAD.

The endogenous association among MMP2/miR-1248/Circ_0087558/miR-643/ MAP2K6 axis can contribute to brain metastasis in basal-like subtype of breast cancer

Brain metastasis in basal-like breast cancer poses a significant challenge in cancer management due to its aggressive nature and limited treatment options. This study conducted a comprehensive analysis to explore the potential role of circular RNAs (circRNAs) as members of endogenous networks in developing breast cancer brain metastasis.Here, we utilized RNA sequencing data from primary breast cancer and brain metastasis tissue with basal-like subtype (n = 11). After quality controlling and preprocessing of fastq files, gene expression of mRNA and circRNAs were extracted from matched samples and normalized. Then, we employed the weighted gene co-expression network analysis approach to identify brain metastasis-associated circRNA modules (SpearmanCorrelation>0.5, P−value<0.05). Moreover, we found five protein-coding genes of PHLDA1, SLC12A2, MMP2, RGP1, and MAP2K6, significantly upregulated in brain metastatic tissues compared to primary breast cancer (FDR<0.05). These genes were enriched in the "GnRH signaling pathway" and "Fluid shear stress and atherosclerosis" pathways (FDR<0.05).Next, to explore the potential interactions between circRNAs and protein-coding genes, we reconstructed a competing endogenous RNA (ceRNA) network using mutual miRNAs between the circRNA module and upregulated mRNAs. Notably, we could detect two axes of circ_0087558/miR-604/MMP2 and MMP2/miR-1248/Circ_0087558/miR-643/MAP2K6 in ceRNA network.In conclusion, the identified circRNA-miRNA-mRNA axes might be therapeutic targets or diagnostic biomarkers for this challenging subtype of breast cancer. However, due to the small number of samples, further experimental validations are essential.

A Network of Circular RNA and MicroRNA Sequencing Provides Insights into Pigment Deposition of Changshun Blue Eggshell Chickens.

Eggshell color plays important biological roles and attracts the attention of both egg retailers and researchers. However, whether non-coding RNAs are involved in pigment deposition among different eggshell colors remains unknown. In this study, RNA sequencing was used to analyse the uterine gland transcriptome (CircRNA and miRNA) of Changshun chicken blue-shell hens producing four different eggshell color eggs including dark blue PK(DB) and light blue (LB), dark brown and greenish (between blue and pink, DP) and pink (p). We found that miR-192-x, targeting SLC16a7, was expressed in DB, DP, and LB groups compared with the PK group, which indicates that miR-192-x may play a role in the blue eggshell color. KEGG and GO analyses showed that the "metabolic pathways" with targeted genes such BLVRA and HMOX1 were detected in dark and light blue color eggshell chickens, which confirms the different ratios of biliverdin and HO-1 involved in the deposition of blue color. As annotated by connectivity analysis, RASGRF1 and RASGRF2, belonging to the RASGRF family, are involved in the Ras signaling pathway, which plays an important role in cell growth, differentiation, metastasis and apoptosis. Our findings enrich the database of circRNA, miRNAs and genes for chicken uterine tissue, which will be useful in accelerating molecular selection for blue eggshell color layers.

Identification and bioinformatics analysis of genes associated with pyroptosis in spinal cord injury of rat and mouse

The mechanism of spinal cord injury (SCI) is highly complex, and an increasing number of studies have indicated the involvement of pyroptosis in the physiological and pathological processes of secondary SCI. However, there is limited bioinformatics research on pyroptosis-related genes (PRGs) in SCI. This study aims to identify and validate differentially expressed PRGs in the GEO database, perform bioinformatics analysis, and construct regulatory networks to explore potential regulatory mechanisms and therapeutic targets for SCI. We obtained high-throughput sequencing datasets of SCI in rats and mice from the GEO database. Differential analysis was conducted using the “limma” package in R to identify differentially expressed genes (DEGs). These genes were then intersected with previously reported PRGs, resulting in a set of PRGs in SCI. GO and KEGG enrichment analyses, as well as correlation analysis, were performed on the PRGs in both rat and mouse models of SCI. Additionally, a protein–protein interaction (PPI) network was constructed using the STRING website to examine the relationships between proteins. Hub genes were identified using Cytoscape software, and the intersection of the top 5 hub genes in rats and mice were selected for subsequent experimentally validated. Furthermore, a competing endogenous RNA (ceRNA) network was constructed to explore potential regulatory mechanisms. The gene expression profiles of GSE93249, GSE133093, GSE138637, GSE174549, GSE45376, GSE171441_3d and GSE171441_35d were selected in this study. We identified 10 and 12 PRGs in rats and mice datasets respectively. Six common DEGs were identified in the intersection of rats and mice PRGs. Enrichment analysis of these DEGs indicated that GO analysis was mainly focused on inflammation-related factors, while KEGG analysis showed that the most genes were enriched on the NOD-like receptor signaling pathway. We constructed a ceRNA regulatory network that consisted of five important PRGs, as well as 24 miRNAs and 34 lncRNAs. This network revealed potential regulatory mechanisms. Additionally, the three hub genes obtained from the intersection were validated in the rat model, showing high expression of PRGs in SCI. Pyroptosis is involved in secondary SCI and may play a significant role in its pathogenesis. The regulatory mechanisms associated with pyroptosis deserve further in-depth research.

Construction of a potential long noncoding RNA prognostic model involved competitive endogenous RNA for patients with gastric cancer.

Increasing evidence has underscored the role of long noncoding RNAs (lncRNAs) make up the major proportion of the competing endogenous RNAs (ceRNAs) network and can regulate gene expression by competitively binding to miRNAs in the development and progression of tumors. Nevertheless, the role of lncRNA-mediated ceRNAs in gastric cancer (GC) and their regulatory mechanisms have not been elucidated to some extent. This study is aimed at constructing a prognostic risk model for GC based on lncRNAs. A TCGA (The Cancer Genome Atlas) dataset was analyzed using edgeR to identify differentially expressed lncRNAs (DElncRNAs) in GC tissues vs normal tissues. Subsequently, DElncRNAs that could predict GC prognosis were determined using a training set. A prognostic risk model based on the DElncRNAs was then constructed. The performance of the model was tested using a test set. The functions of these lncRNAs in GC were investigated using a lncRNA-miRNA-mRNA network. Analysis of lncRNA expression in 407 TCGA GC cases identified 3 lncRNAs that significantly correlated with prognosis. GC cases with high-risk scores showed markedly poor prognosis relative to those with low-risk scores in both the training and test sets. Univariate and multivariate Cox regression analysis of the relationship between various clinical features and prognosis found that these lncRNAs and stage significantly correlated with GC prognosis. A lncRNA-miRNA-mRNA network based on 3 lncRNAs and functional enrichment analysis of interacting mRNA indicated that these genes are enriched in various intracellular receptor signaling pathways, including regulation of muscle system process, and protein deubiquitylation. The current study provides novel insights into the lncRNA-related ceRNA network in GC and sheds lights on underlying 3 lncRNA biomarkers may be independent prognostic signatures in predicting the survival of GC patients.

Comprehensive transcriptomic analysis unveils macrophage-associated genes for establishing an abdominal aortic aneurysm diagnostic model and molecular therapeutic framework

BackgroundAbdominal aortic aneurysm (AAA) is a highly lethal cardiovascular disease. The aim of this research is to identify new biomarkers and therapeutic targets for the treatment of such deadly diseases.MethodsSingle-sample gene set enrichment analysis (ssGSEA) and CIBERSORT algorithms were used to identify distinct immune cell infiltration types between AAA and normal abdominal aortas. Single-cell RNA sequencing data were used to analyse the hallmark genes of AAA-associated macrophage cell subsets. Six macrophage-related hub genes were identified through weighted gene co-expression network analysis (WGCNA) and validated for expression in clinical samples and AAA mouse models. We screened potential therapeutic drugs for AAA through online Connectivity Map databases (CMap). A network-based approach was used to explore the relationships between the candidate genes and transcription factors (TFs), lncRNAs, and miRNAs. Additionally, we also identified hub genes that can effectively identify AAA and atherosclerosis (AS) through a variety of machine learning algorithms.ResultsWe obtained six macrophage hub genes (IL-1B, CXCL1, SOCS3, SLC2A3, G0S2, and CCL3) that can effectively diagnose abdominal aortic aneurysm. The ROC curves and decision curve analysis (DCA) were combined to further confirm the good diagnostic efficacy of the hub genes. Further analysis revealed that the expression of the six hub genes mentioned above was significantly increased in AAA patients and mice. We also constructed TF regulatory networks and competing endogenous RNA networks (ceRNA) to reveal potential mechanisms of disease occurrence. We also obtained two key genes (ZNF652 and UBR5) through a variety of machine learning algorithms, which can effectively distinguish abdominal aortic aneurysm and atherosclerosis.ConclusionOur findings depict the molecular pharmaceutical network in AAA, providing new ideas for effective diagnosis and treatment of diseases.

Establishment of a circRNA-regulated E3 ubiquitin ligase signature and nomogram to predict immunotherapeutic efficacy and prognosis in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is a common type of malignant tumor where the prognosis is dismal. Circular RNA (CircRNA) is a novel RNA that regulates downstream gene transcription and translation to influence the progression of HCC. However, the regulatory relationship that exists between E3 ligases, which is a class of post-translational modifying proteins, and circRNA remains unclear.MethodsBased on the E3 ubiquitin ligase in the competitive endogenous RNA (ceRNA) network, a circRNA-regulated E3 ubiquitin ligase signature (CRE3UL) was developed. A CRE3UL signature was created using the least absolute shrinkage and selection operator (Lasso) and Cox regression analysis and merged it with clinicopathologic characteristics to generate a nomogram for prognosis prediction. The pRRophetic algorithm was utilized and immunological checkpoints were analyzed to compare the responses of patients in the high-risk group (HRG) and low-risk group (LRG) to targeted therapy and immunotherapy. Finally, experimental research will further elucidate the relationship between E3 ubiquitin ligase signature and HCC.ResultsHRG patients were found to have a worse prognosis than LRG patients. Furthermore, significant variations in prognosis were observed among different subgroups based on various clinical characteristics. The CRE3UL signature was identified as being an independent prognostic indicator. The nomogram that combined clinical characteristics and the CRE3UL signature was found to accurately predict the prognosis of HCC patients and demonstrated greater clinical utility than the current TNM staging approach. According to anticancer medication sensitivity predictions, the tumors of HRG patients were more responsive to gefitinib and nilotinib. From immune-checkpoint markers analysis, immunotherapy was identified as being more probable to assist those in the HRG.ConclusionsWe found a significant correlation between the CRE3UL signature and the tumor microenvironment, enabling precise prognosis prediction for HCC patients. Additionally, a nomogram was developed that performs well in predicting the overall survival (OS) of HCC patients. This provides valuable guidance for clinicians in devising specific personalized treatment strategies.Graphical

Identification of oxidative stress-related biomarkers in chronic rhinosinusitis with nasal polyps using WGCNA combined with machine learning algorithms

Objective: To identify diagnostic markers related to oxidative stress in chronic rhinosinusitis with nasal polyps (CRSwNP) by analyzing transcriptome sequencing data, and to investigate their roles in CRSwNP. Methods: Utilizing four CRSwNP sequencing datasets, differentially expressed genes (DEGs) analysis, weighted gene co-expression network analysis (WGCNA), and three machine learning methods for Hub gene selection were performed in this study. Subsequent validation was carried out using external datasets, as well as real-time quantitative polymerase chain reaction (Real-time qPCR), and immunofluorescence staining of clinical samples. Moreover, the diagnostic efficacy of the genes was assessed by receiver operating characteristic (ROC) curve, followed by functional and pathway enrichment analysis, immune-related analysis, and cell population localization. Additionally, a competing endogenous RNA (CeRNA) network was constructed to predict potential drug targets. Statistical analysis and plotting were conducted using SPSS 26.0 and Graphpad Prism9 software. Results: Through data analysis and clinical validation, CP, SERPINF1 and GSTO2 were identified among 4 138 DEGs as oxidative stress markers related to CRSwNP. Specifically, the expression of CP and SERPINF1 increased in CRSwNP, whereas that of GSTO2 decreased, with statistically significant differences (P<0.05). Additionally, an area under the curve (AUC)>0.7 indicated their effectiveness as diagnostic indicators. Importantly, functional analysis indicated that these genes were mainly related to lipid metabolism, cell adhesion migration, and immunity. Single-cell data analysis revealed that SERPINF1 was mainly distributed in epithelial cells, stromal cells, and fibroblasts, while CP was primarily located in epithelial cells, and GSTO2 was minimally present in the epithelial cells and fibroblasts of nasal polyps. Consequently, a CeRNA regulatory network was constructed for the genes CP and GSTO2. This construction allowed for the prediction of potential drugs that could target CP. Conclusion: This study successfully identifies CP, SERPINF1 and GSTO2 as diagnostic and therapeutic markers related to oxidative stress in CRSwNP.

Comprehensive analysis of circRNA-miRNA-mRNA regulatory network and novel potential biomarkers in eutopic endometrium of adenomyosis

Adenomyosis (ADS) is a common gynecological disorder, and its pathogenesis remains unclear. This study explores the functions of circRNAs in the eutopic endometrium of ADS and their diagnostic efficacy for ADS. High-throughput RNA sequencing was performed on 12 eutopic endometrial samples from ADS patients and 3 control endometrial samples. Additionally, circRNAs were analyzed in conjunction with clinical features. A competitive endogenous RNA network was established based on bioinformatics analysis, comprising 3 circRNAs, 1 miRNA, and 13 mRNAs. In the ADS group, the expression levels of hsa_circ_0008959 and SLC15A4 were significantly reduced, while hsa-miR-124-3p expression was increased. SLC15A4 was associated with cell proliferation and invasion. Decreased expression of hsa_circ_0008959 and SLC15A4, along with high VAS scores and elevated hsa-miR-124-3p levels, were identified as risk factors for ADS development. The combination of hsa_circ_0008959 and VAS scores demonstrated the highest diagnostic value for ADS.