Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is s...Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).展开更多
Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair perip...Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair peripheral nerve injury may uncover the molecular mechanisms and signal cascades underlying peripheral nerve repair and provide potential strategies for improving the low axon regeneration capacity of the central nervous system.In this study,we applied weighted gene co-expression network analysis to identify differentially expressed genes in proximal and distal sciatic nerve segments from rats with sciatic nerve injury.We identified 31 and 15 co-expression modules from the proximal and distal sciatic nerve segments,respectively.Functional enrichment analysis revealed that the differentially expressed genes in proximal modules promoted regeneration,while the differentially expressed genes in distal modules promoted neurodegeneration.Next,we constructed hub gene networks for selected modules and identified a key hub gene,Kif22,which was up-regulated in both nerve segments.In vitro experiments confirmed that Kif22 knockdown inhibited proliferation and migration of Schwann cells by modulating the activity of the extracellular signal-regulated kinase signaling pathway.Collectively,our findings provide a comparative framework of gene modules that are co-expressed in injured proximal and distal sciatic nerve segments,and identify Kif22 as a potential therapeutic target for promoting peripheral nerve injury repair via Schwann cell proliferation and migration.All animal experiments were approved by the Institutional Animal Ethics Committee of Nantong University,China(approval No.S20210322-008)on March 22,2021.展开更多
AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression lev...AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.展开更多
Objective Alzheimer's disease(AD)is the most common cause of dementia.The pathophysiology of the disease mostly remains unearthed,thereby challenging drug development for AD.This study aims to screen high throughp...Objective Alzheimer's disease(AD)is the most common cause of dementia.The pathophysiology of the disease mostly remains unearthed,thereby challenging drug development for AD.This study aims to screen high throughput gene expression data using weighted co-expression network analysis(WGCNA)to explore the potential therapeutic targets.Methods The dataset of GSE36980 was obtained from the Gene Expression Omnibus(GEO)database.Normalization,quality control,filtration,and soft-threshold calculation were carried out before clustering the co-expressed genes into different modules.Furthermore,the correlation coefiidents between the modules and clinical traits were computed to identify the key modules.Gene ontology and pathway enrichment analyses were performed on the key module genes.The STRING database was used to construct the protein-protein interaction(PPI)networks,which were further analyzed by Cytoscape app(MCODE).Finally,validation of hub genes was conducted by external GEO datasets of GSE 1297 and GSE 28146.Results Co-expressed genes were clustered into 27 modules,among which 6 modules were identified as the key module relating to AD occurrence.These key modules are primarily involved in chemical synaptic transmission(G0:0007268),the tricarboxylic acid(TCA)cycle and respiratory electron transport(R-HSA-1428517).WDR47,OXCT1,C3orfl4,ATP6V1A,SLC25A14,NAPB were found as the hub genes and their expression were validated by external datasets.Conclusions Through modules co-expression network analyses and PPI network analyses,we identified the hub genes of AD,including WDR47,0XCT1,C3orfl4i ATP6V1A,SLC25A14 and NAPB.Among them,three hub genes(ATP6V1A,SLC25A14,OXCT1)might contribute to AD pathogenesis through pathway of TCA cycle.展开更多
Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict t...Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.展开更多
Cardiomyopathies represent the most common clinical and genetic heterogeneous group of diseases that affect the heart function.Though progress has been made to elucidate the process,molecular mechanisms of different c...Cardiomyopathies represent the most common clinical and genetic heterogeneous group of diseases that affect the heart function.Though progress has been made to elucidate the process,molecular mechanisms of different classes of cardiomyopathies remain elusive.This paper aims to describe the similarities and differences in molecular features of dilated cardiomyopathy(DCM)and ischemic cardiomyopathy(ICM).We firstly detected the co-expressed modules using the weighted gene co-expression network analysis(WGCNA).Significant modules associated with DCM/ICM were identified by the Pearson correlation coefficient(PCC)between the modules and the phenotype of DCM/ICM.The differentially expressed genes in the modules were selected to perform functional enrichment.The potential transcription factors(TFs)prediction was conducted for transcription regulation of hub genes.Apoptosis and cardiac conduction were perturbed in DCM and ICM,respectively.TFs demonstrated that the biomarkers and the transcription regulations in DCM and ICM were different,which helps make more accurate discrimination between them at molecular levels.In conclusion,comprehensive analyses of the molecular features may advance our understanding of DCM and ICM causes and progression.Thus,this understanding may promote the development of innovative diagnoses and treatments.展开更多
Zinc(Zn)malnutrition is a major public health issue.Genetic biofortification of Zn in rice grain can alleviate global Zn malnutrition.Therefore,elucidating the genetic mechanisms regulating Zn deprivation response in ...Zinc(Zn)malnutrition is a major public health issue.Genetic biofortification of Zn in rice grain can alleviate global Zn malnutrition.Therefore,elucidating the genetic mechanisms regulating Zn deprivation response in rice is essential to identify elite genes useful for breeding high grain Zn rice varieties.Here,a meta-analysis of previous RNA-Seq studies involving Zn deficient conditions was conducted using the weighted gene co-expression network analysis(WGCNA)and other in silico prediction tools to identify modules(denoting cluster of genes with related expression pattern)of co-expressed genes,modular genes which are conserved differentially expressed genes(DEGs)across independent RNA-Seq studies,and the molecular pathways of the conserved modular DEGs.WGCNA identified 16 modules of co-expressed genes.Twenty-eight and five modular DEGs were conserved in leaf and crown,and root tissues across two independent RNA-Seq studies.Functional enrichment analysis showed that 24 of the 28 conserved modular DEGs from leaf and crown tissues significantly up-regulated 2 Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways and 15 Gene Ontology(GO)terms,including the substrate-specific transmembrane transporter and the small molecule metabolic process.Further,the well-studied transcription factors(OsWOX11 and OsbHLH120),protein kinase(OsCDPK20 and OsMPK17),and miRNAs(OSA-MIR397A and OSA-MIR397B)were predicted to target some of the identified conserved modular DEGs.Out of the 24 conserved and up-regulated modular DEGs,19 were yet to be experimentally validated as Zn deficiency responsive genes.Findings from this study provide a comprehensive insight on the molecular mechanisms of Zn deficiency response and may facilitate gene and pathway prioritization for improving Zn use efficiency and Zn biofortification in rice.展开更多
BACKGROUND Psoriasis is a chronic inflammatory skin disease,the pathogenesis of which is more complicated and often requires long-term treatment.In particular,moderate to severe psoriasis usually requires systemic tre...BACKGROUND Psoriasis is a chronic inflammatory skin disease,the pathogenesis of which is more complicated and often requires long-term treatment.In particular,moderate to severe psoriasis usually requires systemic treatment.Psoriasis is also associated with many diseases,such as cardiometabolic diseases,malignant tumors,infections,and mood disorders.Psoriasis can appear at any age,and lead to a substantial burden for individuals and society.At present,psoriasis is still a treatable,but incurable,disease.Previous studies have found that micro RNAs(mi RNAs)play an important regulatory role in the progression of various diseases.Currently,mi RNAs studies in psoriasis and dermatology are relatively new.Therefore,the identification of key mi RNAs in psoriasis is helpful to elucidate the molecular mechanism of psoriasis.AIM To identify key molecular markers and signaling pathways to provide potential basis for the treatment and management of psoriasis.METHODS The mi RNA and m RNA data were obtained from the Gene Expression Omnibus database.Then,differentially expressed m RNAs(DEm RNAs)and differentially expressed mi RNAs(DEmi RNAs)were screened out by limma R package.Subsequently,DEm RNAs were analyzed for Gene Ontology and Kyoto Encyclopedia of Genes and Genomics functional enrichment.The“WGCNA”R package was used to analyze the co-expression network of all mi RNAs.In addition,we constructed mi RNA-m RNA regulatory networks based on identified hub mi RNAs.Finally,in vitro validation was performed.All experimental procedures were approved by the ethics committee of Chinese PLA General Hospital(S2021-012-01).RESULTS A total of 639 DEm RNAs and 84 DEmi RNAs were identified.DEm RNAs screening criteria were adjusted P(adj.P)value<0.01 and|log Fold Change|(|log FC|)>1.DEmi RNAs screening criteria were adj.P value<0.01 and|logFC|>1.5.KEGG functional analysis demonstrated that DEm RNAs were significantly enriched in immune-related biological functions,for example,tolllike receptor signaling pathway,cytokine-cytokine receptor interaction,and chemokine signaling pathway.In weighted gene co-expression network analysis,turquoise module was the hub module.Moreover,10 hub mi RNAs were identified.Among these 10 hub mi RNAs,only 8 hub mi RNAs predicted the corresponding target m RNAs.97 negatively regulated mi RNA-m RNA pairs were involved in the mi RNA-m RNA regulatory network,for example,hsa-mi R-21-5 pclaudin 8(CLDN8),hsa-mi R-30 a-3 p-interleukin-1 B(IL-1 B),and hsa-mi R-181 a-5 p/hsa-mi R-30 c-2-3 p-C-X-C motif chemokine ligand 9(CXCL9).Real-time polymerase chain reaction results showed that IL-1 B and CXCL9 were up-regulated and CLDN8 was down-regulated in psoriasis with statistically significant differences.CONCLUSION The identification of potential key molecular markers and signaling pathways provides potential research directions for further understanding the molecular mechanisms of psoriasis.This may also provide new research ideas for the prevention and treatment of psoriasis in the future.展开更多
Weighted Gene Co-expression Network Analysis (WGCNA) is a powerful tool which is applied to investigate the relationship between gene expression levels and patient clinic traits[1;2]. In this study, we identified four...Weighted Gene Co-expression Network Analysis (WGCNA) is a powerful tool which is applied to investigate the relationship between gene expression levels and patient clinic traits[1;2]. In this study, we identified four co-expression modules significantly correlated with clinic traits. Module blue positively correlated with radiotherapy treatment;module purple positively correlates with tumor location (sclera) and negatively correlates with patient age;展开更多
Gene co-expression networks provide an important tool for systems biology studies. Using microarray data from the Array Express database, we constructed an Arabidopsis gene co-expression network, termed At GGM2014, ba...Gene co-expression networks provide an important tool for systems biology studies. Using microarray data from the Array Express database, we constructed an Arabidopsis gene co-expression network, termed At GGM2014, based on the graphical Gaussian model, which contains 102,644 co-expression gene pairs among 18,068 genes. The network was grouped into 622 gene co-expression modules. These modules function in diverse house-keeping, cell cycle, development, hormone response, metabolism, and stress response pathways. We developed a tool to facilitate easy visualization of the expression patterns of these modules either in a tissue context or their regulation under different treatment conditions. The results indicate that at least six modules with tissue-specific expression pattern failed to record modular regulation under various stress conditions. This discrepancy could be best explained by the fact that experiments to study plant stress responses focused mainly on leaves and less on roots, and thus failed to recover specific regulation pattern in other tissues. Overall, the modular structures revealed by our network provide extensive information to generate testable hypotheses about diverse plant signaling pathways. At GGM2014 offers a constructive tool for plant systems biology studies.展开更多
A system-level understanding of the regulation and coordination mechanisms of gene expression is essential for studying the complexity of biological processes in health and disease.With the rapid development of single...A system-level understanding of the regulation and coordination mechanisms of gene expression is essential for studying the complexity of biological processes in health and disease.With the rapid development of single-cell RNA sequencing technologies,it is now possible to investigate gene interactions in a cell type-specific manner.Here we propose the scLink method,which uses statistical network modeling to understand the co-expression relationships among genes and construct sparse gene co-expression networks from single-cell gene expression data.We use both simulation and real data studies to demonstrate the advantages of scLink and its ability to improve single-cell gene network analysis.The scLink R package is available at https://github.com/Vivianstats/scLink.展开更多
Summary:Renal cancer is a common genitourinary malignance,of which clear cell renal cell carcinoma(ccRCC)has high aggressiveness and leads to most cancer-related deaths.Identification of sensitive and reliable biomark...Summary:Renal cancer is a common genitourinary malignance,of which clear cell renal cell carcinoma(ccRCC)has high aggressiveness and leads to most cancer-related deaths.Identification of sensitive and reliable biomarkers for predicting tumorigenesis and progression has great significance in guiding the diagnosis and treatment of ccRCC.Here,we identified 2397 common difTerentially expressed genes(DEGs)using paired normal and tumor ccRCC tissues from GSE53757 and The Cancer Genome Atlas(TCGA).Then,we performed weighted gene co-expression network analysis and protein-protein interaction network analysis,17 candidate hub genes were identified.These candidate hub genes were further validated in GSE36895 and Oncomine database and 14 real hub genes were identified.All the hub genes were up-regulated and significantly positively correlated with pathological stage and histologic grade of ccRCC.Survival analysis showed that the higher expression level of each hub gene tended to predict a worse clinical outcome.ROC analysis showed that all the hub genes can accurately distinguish between tumor and normal samples,and between early stage and advanced stage ccRCC.Moreover,all the hub genes were positively associated with distant metastasis,lymph node infiltration,tumor recurrence and the expression of MKi67,suggesting these genes might promote tumor proliferation,invasion and metastasis.Furthermore,the functional annotation demonstrated that most genes were enriched in cell-cycle related biological function.In summary,our study identified 14 potential biomarkers for predicting tumorigenesis and progression,which might contribute to early diagnosis,prognosis prediction and therapeutic intervention.展开更多
Background： Gene co-expression and differential co-expression analysis has been increasingly used to study co- functional and co-regulatory biological mechanisms from large scale transcriptomics data sets. Methods： ...Background： Gene co-expression and differential co-expression analysis has been increasingly used to study co- functional and co-regulatory biological mechanisms from large scale transcriptomics data sets. Methods： In this study, we develop a nonparametric approach to identify hub genes and modules in a large co- expression network with low computational and memory cost, namely MRHCA. Results： We have applied the method to simulated transcriptomics data sets and demonstrated MRHCA can accurately identify hub genes and estimate size of co-expression modules. With applying MRHCA and differential co- expression analysis to E. coil and TCGA cancer data, we have identified significant condition specific activated genes in E. coil and distinct gene expression regulatory mechanisms between the cancer types with high copy number variation and small somatic mutations. Conclusion： Our analysis has demonstrated MRItCA can （i） deal with large association networks, （ii） rigorously assess statistical significance for hubs and module sizes, （iii） identify co-expression modules with low associations, （iv） detect small and significant modules, and （v） allow genes to be present in more than one modules, compared with existing methods.展开更多
Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interacti...Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interaction network for these QTGs has not yet been established.In this study,we use 18K-rice lines to identify QTGs and their epistatic interactions affecting rice heading date.We identify 264 pairs of interacting quantitative trait loci(QTL)and construct a comprehensive genetic network of these QTL.On average,the epistatic effects of QTL pairs are estimated to be approximately 12.5%of additive effects of identified QTL.Importantly,epistasis varies among different alleles of several heading date genes.Additionally,57 pairs of interacting QTGs are also significant in their epistatic effects on 12 other agronomic traits.The identified QTL genetic interactions are further validated using near-isogenic lines,yeast two-hybrid,and split-luciferase complementation assays.Overall,this study provides a genetic network of rice heading date genes,which plays a crucial role in regulating rice heading date and influencing multiple related agronomic traits.This network serves as a foundation for understanding the genetic mechanisms of rice quantitative traits and for advancing rice molecular breeding.展开更多
Testis specific protein Y-encoded（TSPY） is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic ca...Testis specific protein Y-encoded（TSPY） is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic cancers including liver cancer but not in adjacent normal tissues, suggesting that ectopic TSPY expression could be associated with oncogenesis in non-germ cell cancers. Various studies demonstrated that TSPY expression promotes growth and proliferation in cancer cells; however, its relationship to other oncogenic events in TSPY-positive cancers remains unknown. The present study seeks to correlate TSPY expression with other molecular features in clinical cancer samples, by analyses of RNA-seq transcriptome and DNA methylation data in the Cancer Genome Atlas（TCGA） database. A total of 53 genes,including oncogenic lineage protein 28 homolog B（LIN28B） gene and RNA-binding motif protein Y-linked（RBMY） gene, are identified to be consistently co-expressed with TSPY, and have been collectively designated as the TSPY co-expression network（TCN）. TCN genes were simultaneously activated in subsets of liver hepatocellular carcinoma（30%） and lung adenocarcinoma（10%） regardless of pathological stage, but only minimally in other cancer types. Further analysis revealed that the DNA methylation level was globally lower in the TCN-active than TCN-silent cancers. The specific expression and methylation patterns of TCN genes suggest that they could be useful as biomarkers for the diagnosis,prognosis and clinical management of cancers, especially those for liver and lung cancers, associated with TSPY co-expression network genes.展开更多
The ripening process of grape is an important stage during grape growth and development. During this process, color of grape skin is the most obvious change. The molecular mechanism for the ripening of grape(a non-cli...The ripening process of grape is an important stage during grape growth and development. During this process, color of grape skin is the most obvious change. The molecular mechanism for the ripening of grape(a non-climacteric fruit, which ripens without ethylene and respiration bursts) is still unclear. Although numerous studies have been done on the changes in the contents of metabolites during grape ripening, the differentially expressed genes at veraison and maturity stages have not been systematically analyzed. In this study, 1 524 genes that are significantly differentially expressed in grape(Pinot Noir) skin at veraison and maturity stages were identified, and a co-expression network of these genes was built. Some of the eight co-expression modules we identified may be closely related to the synthesis or metabolism of anthocyanins, sugar acids, and other flavor substances. The transcription factor families WRKY, b ZIP, HSF and WOX may play an important role in the regulation of anthocyanin synthesis or metabolism. The results provide a foundation for further study of the molecular mechanism of grape ripening.展开更多
Objective:To use the gene chip of pseudomonas aeruginosa as a research sample and to explore it at an omics level,aiming at elucidating the co-expression network characteristics of the virulence genes exoS and exoU of...Objective:To use the gene chip of pseudomonas aeruginosa as a research sample and to explore it at an omics level,aiming at elucidating the co-expression network characteristics of the virulence genes exoS and exoU of pseudomonas aeruginosa in the lower respiratory tract from the perspective of molecular biology and identifying its key regulatory genes.Methods:From March 2016 to May 2018,312 patients infected with pseudomonas aeruginosa in the lower respiratory tract who were admitted to Department of Respiratory Medicine of Baogang Hospital and given follow-up treatments in the hospital were selected as subjects by use of cluster sampling.Alveolar lavage fluid and sputum collected from those patients were used as biological specimens.The genes of pseudomonas aeruginosa were detected with the help of oligonucleotide probes to make a pre-processing of chip data.A total of 8 common antibiotics(ceftazidime,gentamicin,piperacillin,amikacin,ciprofloxacin,levofloxacin,doripenem and ticarcillin)against Gram-negative bacteria were selected to determine the drug resistance of biological specimens.MCODE algorithm was used to construct a co-expression network model of the drug-resistance genes focused on exoS/exoU.Results:The expression level of exoS/exoU in the drug-resistance group was significantly higher than that in the non-resistance group(p<0.05).The top 5 differentially expressed genes in the alveolar lavage fluid specimens from the drug-resistance group were RAC1,ITGB1,ITGB5,CRK and IGF1R in the order from high to low.In the sputum specimens,the top 5 differentially expressed genes were RAC1,CRK,IGF1R,ITGB1 and ITGB5.In the alveolar lavage fluid specimens,only RAC1 had a positive correlation with the expression of exoS and exoU(p<0.05).In the sputum specimens,RAC1,ITGB1,ITGB5,CRK and IGF1R were positively correlated with the expression of exoS and exoU(p<0.05).The genes included in the co-expression network contained exoS,exoU,RAC1,ITGB1,ITGB5,CRK,CAMK2D,RHOA,FLNA,IGF1R,TGFBR2 and FOS.Among them,RAC1 had a highest score in the aspect of regulatory ability(72.00)and the largest number of regulatory genes(6);followed by ITGB1,ITGB5 and CRK genes.Conclusions:The high expression of exoS and exoU in the sputum specimens suggests that pseudomonas aeruginosa has a higher probability to get resistant to antibiotics;RAC1,ITGB1,ITGB5 and CRK genes may be the key genes that can regulate the expression of exoS and exoU.展开更多
BACKGROUND Lotus plumule and its active components have demonstrated inhibitory effects on gastric cancer(GC).However,the molecular mechanism of lotus plumule against GC remains unclear and requires further investigat...BACKGROUND Lotus plumule and its active components have demonstrated inhibitory effects on gastric cancer(GC).However,the molecular mechanism of lotus plumule against GC remains unclear and requires further investigation.AIM To identify the key hub genes associated with the anti-GC effects of lotus plumule.METHODS This study investigated the potential targets of traditional Chinese medicine for inhibiting GC using weighted gene co-expression network analysis and bio-informatics.Initially,the active components and targets of the lotus plumule and the differentially expressed genes associated with GC were identified.Sub-sequently,a protein-protein interaction network was constructed to elucidate the interactions between drug targets and disease-related genes,facilitating the identification of hub genes within the network.The clinical significance of these hub genes was evaluated,and their upstream transcription factors and down-stream targets were identified.The binding ability of a hub gene with its down-stream targets was verified using molecular docking technology.Finally,molecular docking was performed to evaluate the binding affinity between the active ingredients of lotus plumule and the hub gene.RESULTS This study identified 26 genes closely associated with GC.Machine learning analysis and external validation narrowed the list to four genes:Aldo-keto reductase family 1 member B10,fructose-bisphosphatase 1,protein arginine methyltransferase 1,and carbonic anhydrase 9.These genes indicated a strong correlation with anti-GC activity.CONCLUSION Lotus plumule exhibits anti-GC effects.This study identified four hub genes with potential as novel targets for diagnosing and treating GC,providing innovative perspectives for its clinical management.展开更多
Background:Tetralogy of Fallot(TOF),the predominant cyanotic congenital heart defect,arisesfrom multifactorial gene-envirorment interactions disrup ting cardiac developmental networks.This studyinvestiga ted TOF-speci...Background:Tetralogy of Fallot(TOF),the predominant cyanotic congenital heart defect,arisesfrom multifactorial gene-envirorment interactions disrup ting cardiac developmental networks.This studyinvestiga ted TOF-specific transcriptional alterations and identified high-confidence candidate genes.Methods:Based on GSE36761 transcriptome data,a weighted gene co-exp ression network analysis(WGCNA)andprotein-protein interaction(PPI)network were conducted to identify TOF-related sub-netrwork and Hub genes.The potentialbiological functions among these genes were revealed by enrichment analysis.Genetic,epigeneticand transcriptional alteration in the Fub genes were analyzed with leveraged public resources:a methylationdataset(CSE62629)and two single-cell datasets(EGAS00001003996 and GSE126128),Results:Eight Hub geneswere identified using the WGCNA network and PPl network,and functional errichment analysis revealedthatGJA1,RUNX2,FTK7,PRICKLE1,and SPRP1 were involved in the morphogenesis of an epithelium,anddysregulation of the signaling were also found in the other two TOF datasets,Furthermore,the study foundthat the promoters of GJA1,RUNX2,FTK7,and PRICKLE1 genes were hypermethylated and that GJA1 andSFRP1 are highly expressed in mouse second heart field cells and neural crest cells,and the la tter is expressedin human embry onic outflow tract cells.Since RUNX2 was not expressed in human and mouse embryonichearts,GJA1,FTK7,PRICKLE1,and SPRP1 were ultimately identified as TOF candidate genes.Conclusion:Based on the WGCNA network and various bioinformatics analysis approaches,we screened 4 TOF candidatepathogenic genes,and found that the signaling pathways related to the morphogenesis of an epithelium maybe involved in the pathogenesis of TOF.展开更多
The present paper predicted the function of unknow genes by analyzing the co-expression data of Arabidopsis thaliana from biological pathway based on the shortest-path algorithm. This paper proposed that transitive co...The present paper predicted the function of unknow genes by analyzing the co-expression data of Arabidopsis thaliana from biological pathway based on the shortest-path algorithm. This paper proposed that transitive co-expression among genes can be used as an important attribute to link genes of the same biological pathway. The genes from the same biological pathway with similar functions are strongly correlated in expression. Moreover,the function of unknown genes can be predicted by the known genes where they are strongly correlated in expression lying on the same shortest-path from the biological pathway. Analyzing the Arabidopsis thaliana from the biological pathway,this study showed that this method can reliably reveal function of the unknown Arabidopsis thaliana genes and the approach of predicting gene function by transitiving co-expression in shortest-path is feasible and effective.展开更多
基金supported by the Notional Natural Science Foundation of China,No.81960417 (to JX)Guangxi Key Research and Development Program,No.GuiKeA B20159027 (to JX)the Natural Science Foundation of Guangxi Zhuang Autonomous Region,No.2022GXNSFBA035545 (to YG)。
文摘Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).
基金supported by the National Major Project of Research and Development of China,No.2017YFA0104701(to BY)the National Natural Science Foundation of China,No.32000725(to QQC)+1 种基金the Natural Science Foundation of Jiangsu Province of China,No.BK20200973(to QQC)the Jiangsu Provincial University Innovation Training Key Project of China,No.202010304021Z(to ML)。
文摘Peripheral nerve injury repair requires a certain degree of cooperation between axon regeneration and Wallerian degeneration.Therefore,investigating how axon regeneration and degeneration work together to repair peripheral nerve injury may uncover the molecular mechanisms and signal cascades underlying peripheral nerve repair and provide potential strategies for improving the low axon regeneration capacity of the central nervous system.In this study,we applied weighted gene co-expression network analysis to identify differentially expressed genes in proximal and distal sciatic nerve segments from rats with sciatic nerve injury.We identified 31 and 15 co-expression modules from the proximal and distal sciatic nerve segments,respectively.Functional enrichment analysis revealed that the differentially expressed genes in proximal modules promoted regeneration,while the differentially expressed genes in distal modules promoted neurodegeneration.Next,we constructed hub gene networks for selected modules and identified a key hub gene,Kif22,which was up-regulated in both nerve segments.In vitro experiments confirmed that Kif22 knockdown inhibited proliferation and migration of Schwann cells by modulating the activity of the extracellular signal-regulated kinase signaling pathway.Collectively,our findings provide a comparative framework of gene modules that are co-expressed in injured proximal and distal sciatic nerve segments,and identify Kif22 as a potential therapeutic target for promoting peripheral nerve injury repair via Schwann cell proliferation and migration.All animal experiments were approved by the Institutional Animal Ethics Committee of Nantong University,China(approval No.S20210322-008)on March 22,2021.
基金Supported by the National Natural Science Foundation of China(No.81271019No.61463046)Gansu Province Science Foundation for Youths(No.145RJYA282)
文摘AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.
基金Fund supported by the National Natural Science Foundation of China(81460598 and 81660644)the Natural Science Foundation of Jiangsu Province(BK20170267)Guangxi Special Fund for the First-Class Discipline Construction Project(05019038).
文摘Objective Alzheimer's disease(AD)is the most common cause of dementia.The pathophysiology of the disease mostly remains unearthed,thereby challenging drug development for AD.This study aims to screen high throughput gene expression data using weighted co-expression network analysis(WGCNA)to explore the potential therapeutic targets.Methods The dataset of GSE36980 was obtained from the Gene Expression Omnibus(GEO)database.Normalization,quality control,filtration,and soft-threshold calculation were carried out before clustering the co-expressed genes into different modules.Furthermore,the correlation coefiidents between the modules and clinical traits were computed to identify the key modules.Gene ontology and pathway enrichment analyses were performed on the key module genes.The STRING database was used to construct the protein-protein interaction(PPI)networks,which were further analyzed by Cytoscape app(MCODE).Finally,validation of hub genes was conducted by external GEO datasets of GSE 1297 and GSE 28146.Results Co-expressed genes were clustered into 27 modules,among which 6 modules were identified as the key module relating to AD occurrence.These key modules are primarily involved in chemical synaptic transmission(G0:0007268),the tricarboxylic acid(TCA)cycle and respiratory electron transport(R-HSA-1428517).WDR47,OXCT1,C3orfl4,ATP6V1A,SLC25A14,NAPB were found as the hub genes and their expression were validated by external datasets.Conclusions Through modules co-expression network analyses and PPI network analyses,we identified the hub genes of AD,including WDR47,0XCT1,C3orfl4i ATP6V1A,SLC25A14 and NAPB.Among them,three hub genes(ATP6V1A,SLC25A14,OXCT1)might contribute to AD pathogenesis through pathway of TCA cycle.
文摘Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.
基金supported by the National Natural Science Foundation of China under Grants No.61720106004 and No.61872405the Key R&D Project of Sichuan Province,China under Grants No.20ZDYF2772 and No.2020YFS0243.
文摘Cardiomyopathies represent the most common clinical and genetic heterogeneous group of diseases that affect the heart function.Though progress has been made to elucidate the process,molecular mechanisms of different classes of cardiomyopathies remain elusive.This paper aims to describe the similarities and differences in molecular features of dilated cardiomyopathy(DCM)and ischemic cardiomyopathy(ICM).We firstly detected the co-expressed modules using the weighted gene co-expression network analysis(WGCNA).Significant modules associated with DCM/ICM were identified by the Pearson correlation coefficient(PCC)between the modules and the phenotype of DCM/ICM.The differentially expressed genes in the modules were selected to perform functional enrichment.The potential transcription factors(TFs)prediction was conducted for transcription regulation of hub genes.Apoptosis and cardiac conduction were perturbed in DCM and ICM,respectively.TFs demonstrated that the biomarkers and the transcription regulations in DCM and ICM were different,which helps make more accurate discrimination between them at molecular levels.In conclusion,comprehensive analyses of the molecular features may advance our understanding of DCM and ICM causes and progression.Thus,this understanding may promote the development of innovative diagnoses and treatments.
基金financially supported by the Chinese Academy of Agricultural Sciences-Agricultural Science and Technology Innovation Programthe Shenzhen Science and Technology Program (Grant No. JCYJ20200109150650397)
文摘Zinc(Zn)malnutrition is a major public health issue.Genetic biofortification of Zn in rice grain can alleviate global Zn malnutrition.Therefore,elucidating the genetic mechanisms regulating Zn deprivation response in rice is essential to identify elite genes useful for breeding high grain Zn rice varieties.Here,a meta-analysis of previous RNA-Seq studies involving Zn deficient conditions was conducted using the weighted gene co-expression network analysis(WGCNA)and other in silico prediction tools to identify modules(denoting cluster of genes with related expression pattern)of co-expressed genes,modular genes which are conserved differentially expressed genes(DEGs)across independent RNA-Seq studies,and the molecular pathways of the conserved modular DEGs.WGCNA identified 16 modules of co-expressed genes.Twenty-eight and five modular DEGs were conserved in leaf and crown,and root tissues across two independent RNA-Seq studies.Functional enrichment analysis showed that 24 of the 28 conserved modular DEGs from leaf and crown tissues significantly up-regulated 2 Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways and 15 Gene Ontology(GO)terms,including the substrate-specific transmembrane transporter and the small molecule metabolic process.Further,the well-studied transcription factors(OsWOX11 and OsbHLH120),protein kinase(OsCDPK20 and OsMPK17),and miRNAs(OSA-MIR397A and OSA-MIR397B)were predicted to target some of the identified conserved modular DEGs.Out of the 24 conserved and up-regulated modular DEGs,19 were yet to be experimentally validated as Zn deficiency responsive genes.Findings from this study provide a comprehensive insight on the molecular mechanisms of Zn deficiency response and may facilitate gene and pathway prioritization for improving Zn use efficiency and Zn biofortification in rice.
文摘BACKGROUND Psoriasis is a chronic inflammatory skin disease,the pathogenesis of which is more complicated and often requires long-term treatment.In particular,moderate to severe psoriasis usually requires systemic treatment.Psoriasis is also associated with many diseases,such as cardiometabolic diseases,malignant tumors,infections,and mood disorders.Psoriasis can appear at any age,and lead to a substantial burden for individuals and society.At present,psoriasis is still a treatable,but incurable,disease.Previous studies have found that micro RNAs(mi RNAs)play an important regulatory role in the progression of various diseases.Currently,mi RNAs studies in psoriasis and dermatology are relatively new.Therefore,the identification of key mi RNAs in psoriasis is helpful to elucidate the molecular mechanism of psoriasis.AIM To identify key molecular markers and signaling pathways to provide potential basis for the treatment and management of psoriasis.METHODS The mi RNA and m RNA data were obtained from the Gene Expression Omnibus database.Then,differentially expressed m RNAs(DEm RNAs)and differentially expressed mi RNAs(DEmi RNAs)were screened out by limma R package.Subsequently,DEm RNAs were analyzed for Gene Ontology and Kyoto Encyclopedia of Genes and Genomics functional enrichment.The“WGCNA”R package was used to analyze the co-expression network of all mi RNAs.In addition,we constructed mi RNA-m RNA regulatory networks based on identified hub mi RNAs.Finally,in vitro validation was performed.All experimental procedures were approved by the ethics committee of Chinese PLA General Hospital(S2021-012-01).RESULTS A total of 639 DEm RNAs and 84 DEmi RNAs were identified.DEm RNAs screening criteria were adjusted P(adj.P)value<0.01 and|log Fold Change|(|log FC|)>1.DEmi RNAs screening criteria were adj.P value<0.01 and|logFC|>1.5.KEGG functional analysis demonstrated that DEm RNAs were significantly enriched in immune-related biological functions,for example,tolllike receptor signaling pathway,cytokine-cytokine receptor interaction,and chemokine signaling pathway.In weighted gene co-expression network analysis,turquoise module was the hub module.Moreover,10 hub mi RNAs were identified.Among these 10 hub mi RNAs,only 8 hub mi RNAs predicted the corresponding target m RNAs.97 negatively regulated mi RNA-m RNA pairs were involved in the mi RNA-m RNA regulatory network,for example,hsa-mi R-21-5 pclaudin 8(CLDN8),hsa-mi R-30 a-3 p-interleukin-1 B(IL-1 B),and hsa-mi R-181 a-5 p/hsa-mi R-30 c-2-3 p-C-X-C motif chemokine ligand 9(CXCL9).Real-time polymerase chain reaction results showed that IL-1 B and CXCL9 were up-regulated and CLDN8 was down-regulated in psoriasis with statistically significant differences.CONCLUSION The identification of potential key molecular markers and signaling pathways provides potential research directions for further understanding the molecular mechanisms of psoriasis.This may also provide new research ideas for the prevention and treatment of psoriasis in the future.
文摘Weighted Gene Co-expression Network Analysis (WGCNA) is a powerful tool which is applied to investigate the relationship between gene expression levels and patient clinic traits[1;2]. In this study, we identified four co-expression modules significantly correlated with clinic traits. Module blue positively correlated with radiotherapy treatment;module purple positively correlates with tumor location (sclera) and negatively correlates with patient age;
基金supported by US National Science Foundation grants DBI-0723722 and DBI-1042344 to SPDKUC Davis funds to SPDK
文摘Gene co-expression networks provide an important tool for systems biology studies. Using microarray data from the Array Express database, we constructed an Arabidopsis gene co-expression network, termed At GGM2014, based on the graphical Gaussian model, which contains 102,644 co-expression gene pairs among 18,068 genes. The network was grouped into 622 gene co-expression modules. These modules function in diverse house-keeping, cell cycle, development, hormone response, metabolism, and stress response pathways. We developed a tool to facilitate easy visualization of the expression patterns of these modules either in a tissue context or their regulation under different treatment conditions. The results indicate that at least six modules with tissue-specific expression pattern failed to record modular regulation under various stress conditions. This discrepancy could be best explained by the fact that experiments to study plant stress responses focused mainly on leaves and less on roots, and thus failed to recover specific regulation pattern in other tissues. Overall, the modular structures revealed by our network provide extensive information to generate testable hypotheses about diverse plant signaling pathways. At GGM2014 offers a constructive tool for plant systems biology studies.
基金This work was supported by the Rutgers School of Public Health Pilot Grant,USA,the Rutgers Busch Biomedical Grant,USA,and the New Jersey Alliance for Clinical and Translational Science Mini-methods Grant(a component of the US National Institutes of Health under Grant No.UL1TR0030117),USA,to WVLComputational resources were provided by the Office of Advanced Research Computing at Rutgers,The State University of New Jersey,USA,under the National Institutes of Health Grant No.S10OD012346.
文摘A system-level understanding of the regulation and coordination mechanisms of gene expression is essential for studying the complexity of biological processes in health and disease.With the rapid development of single-cell RNA sequencing technologies,it is now possible to investigate gene interactions in a cell type-specific manner.Here we propose the scLink method,which uses statistical network modeling to understand the co-expression relationships among genes and construct sparse gene co-expression networks from single-cell gene expression data.We use both simulation and real data studies to demonstrate the advantages of scLink and its ability to improve single-cell gene network analysis.The scLink R package is available at https://github.com/Vivianstats/scLink.
基金This work was supported by grants from the National Natural Science Foundation of China(No.81270354)Natural Science for Youth Foundation(No.81300213).
文摘Summary:Renal cancer is a common genitourinary malignance,of which clear cell renal cell carcinoma(ccRCC)has high aggressiveness and leads to most cancer-related deaths.Identification of sensitive and reliable biomarkers for predicting tumorigenesis and progression has great significance in guiding the diagnosis and treatment of ccRCC.Here,we identified 2397 common difTerentially expressed genes(DEGs)using paired normal and tumor ccRCC tissues from GSE53757 and The Cancer Genome Atlas(TCGA).Then,we performed weighted gene co-expression network analysis and protein-protein interaction network analysis,17 candidate hub genes were identified.These candidate hub genes were further validated in GSE36895 and Oncomine database and 14 real hub genes were identified.All the hub genes were up-regulated and significantly positively correlated with pathological stage and histologic grade of ccRCC.Survival analysis showed that the higher expression level of each hub gene tended to predict a worse clinical outcome.ROC analysis showed that all the hub genes can accurately distinguish between tumor and normal samples,and between early stage and advanced stage ccRCC.Moreover,all the hub genes were positively associated with distant metastasis,lymph node infiltration,tumor recurrence and the expression of MKi67,suggesting these genes might promote tumor proliferation,invasion and metastasis.Furthermore,the functional annotation demonstrated that most genes were enriched in cell-cycle related biological function.In summary,our study identified 14 potential biomarkers for predicting tumorigenesis and progression,which might contribute to early diagnosis,prognosis prediction and therapeutic intervention.
文摘Background： Gene co-expression and differential co-expression analysis has been increasingly used to study co- functional and co-regulatory biological mechanisms from large scale transcriptomics data sets. Methods： In this study, we develop a nonparametric approach to identify hub genes and modules in a large co- expression network with low computational and memory cost, namely MRHCA. Results： We have applied the method to simulated transcriptomics data sets and demonstrated MRHCA can accurately identify hub genes and estimate size of co-expression modules. With applying MRHCA and differential co- expression analysis to E. coil and TCGA cancer data, we have identified significant condition specific activated genes in E. coil and distinct gene expression regulatory mechanisms between the cancer types with high copy number variation and small somatic mutations. Conclusion： Our analysis has demonstrated MRItCA can （i） deal with large association networks, （ii） rigorously assess statistical significance for hubs and module sizes, （iii） identify co-expression modules with low associations, （iv） detect small and significant modules, and （v） allow genes to be present in more than one modules, compared with existing methods.
基金supported by the National Natural Science Foundation of China(32222064 and 32341030)the Natural Science Foundation of Shanghai(22ZR1445800)Zhejiang Provincial Natural Science Foundation of China(LQ24C130008).
文摘Several quantitative trait genes(QTGs)related to rice heading date,a key factor for crop development and yield,have been identified,along with complex interactions among genes.However,a comprehensive genetic interaction network for these QTGs has not yet been established.In this study,we use 18K-rice lines to identify QTGs and their epistatic interactions affecting rice heading date.We identify 264 pairs of interacting quantitative trait loci(QTL)and construct a comprehensive genetic network of these QTL.On average,the epistatic effects of QTL pairs are estimated to be approximately 12.5%of additive effects of identified QTL.Importantly,epistasis varies among different alleles of several heading date genes.Additionally,57 pairs of interacting QTGs are also significant in their epistatic effects on 12 other agronomic traits.The identified QTL genetic interactions are further validated using near-isogenic lines,yeast two-hybrid,and split-luciferase complementation assays.Overall,this study provides a genetic network of rice heading date genes,which plays a crucial role in regulating rice heading date and influencing multiple related agronomic traits.This network serves as a foundation for understanding the genetic mechanisms of rice quantitative traits and for advancing rice molecular breeding.
基金partially supported by a Merit-Reviewed grant from the Department of Veterans Affairsa Peer-Reviewed Cancer Research Program grant from the Department of Defense (W81XWH-16-1-0488) to Y-FCL
文摘Testis specific protein Y-encoded（TSPY） is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic cancers including liver cancer but not in adjacent normal tissues, suggesting that ectopic TSPY expression could be associated with oncogenesis in non-germ cell cancers. Various studies demonstrated that TSPY expression promotes growth and proliferation in cancer cells; however, its relationship to other oncogenic events in TSPY-positive cancers remains unknown. The present study seeks to correlate TSPY expression with other molecular features in clinical cancer samples, by analyses of RNA-seq transcriptome and DNA methylation data in the Cancer Genome Atlas（TCGA） database. A total of 53 genes,including oncogenic lineage protein 28 homolog B（LIN28B） gene and RNA-binding motif protein Y-linked（RBMY） gene, are identified to be consistently co-expressed with TSPY, and have been collectively designated as the TSPY co-expression network（TCN）. TCN genes were simultaneously activated in subsets of liver hepatocellular carcinoma（30%） and lung adenocarcinoma（10%） regardless of pathological stage, but only minimally in other cancer types. Further analysis revealed that the DNA methylation level was globally lower in the TCN-active than TCN-silent cancers. The specific expression and methylation patterns of TCN genes suggest that they could be useful as biomarkers for the diagnosis,prognosis and clinical management of cancers, especially those for liver and lung cancers, associated with TSPY co-expression network genes.
基金Supported by Major Agricultural Application Technology Innovation Project of Shandong Province"Development of Landmark Wines and Integrated Application of Key Technologies in Shandong Province"Major Agricultural Application Technology Innovation Project of Shandong Province"Research and Application of Precision Control of Maturation and Product Innovation of Featured Brewing Grape"Agricultural Scientific and Technological Innovation Project of Shandong Academy of Agricultural Sciences(CXGC2016D01)
文摘The ripening process of grape is an important stage during grape growth and development. During this process, color of grape skin is the most obvious change. The molecular mechanism for the ripening of grape(a non-climacteric fruit, which ripens without ethylene and respiration bursts) is still unclear. Although numerous studies have been done on the changes in the contents of metabolites during grape ripening, the differentially expressed genes at veraison and maturity stages have not been systematically analyzed. In this study, 1 524 genes that are significantly differentially expressed in grape(Pinot Noir) skin at veraison and maturity stages were identified, and a co-expression network of these genes was built. Some of the eight co-expression modules we identified may be closely related to the synthesis or metabolism of anthocyanins, sugar acids, and other flavor substances. The transcription factor families WRKY, b ZIP, HSF and WOX may play an important role in the regulation of anthocyanin synthesis or metabolism. The results provide a foundation for further study of the molecular mechanism of grape ripening.
文摘Objective:To use the gene chip of pseudomonas aeruginosa as a research sample and to explore it at an omics level,aiming at elucidating the co-expression network characteristics of the virulence genes exoS and exoU of pseudomonas aeruginosa in the lower respiratory tract from the perspective of molecular biology and identifying its key regulatory genes.Methods:From March 2016 to May 2018,312 patients infected with pseudomonas aeruginosa in the lower respiratory tract who were admitted to Department of Respiratory Medicine of Baogang Hospital and given follow-up treatments in the hospital were selected as subjects by use of cluster sampling.Alveolar lavage fluid and sputum collected from those patients were used as biological specimens.The genes of pseudomonas aeruginosa were detected with the help of oligonucleotide probes to make a pre-processing of chip data.A total of 8 common antibiotics(ceftazidime,gentamicin,piperacillin,amikacin,ciprofloxacin,levofloxacin,doripenem and ticarcillin)against Gram-negative bacteria were selected to determine the drug resistance of biological specimens.MCODE algorithm was used to construct a co-expression network model of the drug-resistance genes focused on exoS/exoU.Results:The expression level of exoS/exoU in the drug-resistance group was significantly higher than that in the non-resistance group(p<0.05).The top 5 differentially expressed genes in the alveolar lavage fluid specimens from the drug-resistance group were RAC1,ITGB1,ITGB5,CRK and IGF1R in the order from high to low.In the sputum specimens,the top 5 differentially expressed genes were RAC1,CRK,IGF1R,ITGB1 and ITGB5.In the alveolar lavage fluid specimens,only RAC1 had a positive correlation with the expression of exoS and exoU(p<0.05).In the sputum specimens,RAC1,ITGB1,ITGB5,CRK and IGF1R were positively correlated with the expression of exoS and exoU(p<0.05).The genes included in the co-expression network contained exoS,exoU,RAC1,ITGB1,ITGB5,CRK,CAMK2D,RHOA,FLNA,IGF1R,TGFBR2 and FOS.Among them,RAC1 had a highest score in the aspect of regulatory ability(72.00)and the largest number of regulatory genes(6);followed by ITGB1,ITGB5 and CRK genes.Conclusions:The high expression of exoS and exoU in the sputum specimens suggests that pseudomonas aeruginosa has a higher probability to get resistant to antibiotics;RAC1,ITGB1,ITGB5 and CRK genes may be the key genes that can regulate the expression of exoS and exoU.
基金Supported by Ningxia Key Research and Development Program,No.2023BEG02015Talent Development Projects of Young Qihuang of National Administration of Traditional Chinese Medicine(2020).
文摘BACKGROUND Lotus plumule and its active components have demonstrated inhibitory effects on gastric cancer(GC).However,the molecular mechanism of lotus plumule against GC remains unclear and requires further investigation.AIM To identify the key hub genes associated with the anti-GC effects of lotus plumule.METHODS This study investigated the potential targets of traditional Chinese medicine for inhibiting GC using weighted gene co-expression network analysis and bio-informatics.Initially,the active components and targets of the lotus plumule and the differentially expressed genes associated with GC were identified.Sub-sequently,a protein-protein interaction network was constructed to elucidate the interactions between drug targets and disease-related genes,facilitating the identification of hub genes within the network.The clinical significance of these hub genes was evaluated,and their upstream transcription factors and down-stream targets were identified.The binding ability of a hub gene with its down-stream targets was verified using molecular docking technology.Finally,molecular docking was performed to evaluate the binding affinity between the active ingredients of lotus plumule and the hub gene.RESULTS This study identified 26 genes closely associated with GC.Machine learning analysis and external validation narrowed the list to four genes:Aldo-keto reductase family 1 member B10,fructose-bisphosphatase 1,protein arginine methyltransferase 1,and carbonic anhydrase 9.These genes indicated a strong correlation with anti-GC activity.CONCLUSION Lotus plumule exhibits anti-GC effects.This study identified four hub genes with potential as novel targets for diagnosing and treating GC,providing innovative perspectives for its clinical management.
基金supported by the National Natural Science Found ation of China(No.8230045i for Zhen Wang,82302230 for jiawei Shi,82202194 for Jing Wang and 82171961 for Haiyan Cao).
文摘Background:Tetralogy of Fallot(TOF),the predominant cyanotic congenital heart defect,arisesfrom multifactorial gene-envirorment interactions disrup ting cardiac developmental networks.This studyinvestiga ted TOF-specific transcriptional alterations and identified high-confidence candidate genes.Methods:Based on GSE36761 transcriptome data,a weighted gene co-exp ression network analysis(WGCNA)andprotein-protein interaction(PPI)network were conducted to identify TOF-related sub-netrwork and Hub genes.The potentialbiological functions among these genes were revealed by enrichment analysis.Genetic,epigeneticand transcriptional alteration in the Fub genes were analyzed with leveraged public resources:a methylationdataset(CSE62629)and two single-cell datasets(EGAS00001003996 and GSE126128),Results:Eight Hub geneswere identified using the WGCNA network and PPl network,and functional errichment analysis revealedthatGJA1,RUNX2,FTK7,PRICKLE1,and SPRP1 were involved in the morphogenesis of an epithelium,anddysregulation of the signaling were also found in the other two TOF datasets,Furthermore,the study foundthat the promoters of GJA1,RUNX2,FTK7,and PRICKLE1 genes were hypermethylated and that GJA1 andSFRP1 are highly expressed in mouse second heart field cells and neural crest cells,and the la tter is expressedin human embry onic outflow tract cells.Since RUNX2 was not expressed in human and mouse embryonichearts,GJA1,FTK7,PRICKLE1,and SPRP1 were ultimately identified as TOF candidate genes.Conclusion:Based on the WGCNA network and various bioinformatics analysis approaches,we screened 4 TOF candidatepathogenic genes,and found that the signaling pathways related to the morphogenesis of an epithelium maybe involved in the pathogenesis of TOF.
基金Supported by Shanghai Municipal Education Committee Educationand Scientific Research (Grant No. 07ZZ60)~~
文摘The present paper predicted the function of unknow genes by analyzing the co-expression data of Arabidopsis thaliana from biological pathway based on the shortest-path algorithm. This paper proposed that transitive co-expression among genes can be used as an important attribute to link genes of the same biological pathway. The genes from the same biological pathway with similar functions are strongly correlated in expression. Moreover,the function of unknown genes can be predicted by the known genes where they are strongly correlated in expression lying on the same shortest-path from the biological pathway. Analyzing the Arabidopsis thaliana from the biological pathway,this study showed that this method can reliably reveal function of the unknown Arabidopsis thaliana genes and the approach of predicting gene function by transitiving co-expression in shortest-path is feasible and effective.
