scholarly journals Identifcation of The Ferroptosis-Related Gene Signature In Placenta of Patients With Early-Onset Preeclampsia

2021 ◽  
Author(s):  
Nana Yang ◽  
Qianghua Wang ◽  
Biao Ding ◽  
Yinging Gong ◽  
Yue Wu ◽  
...  
Keyword(s):  
Iron Homeostasis ◽  
Molecular Mechanisms ◽  
Late Onset ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Network Analyses

Abstract Background: The accumulation of ROS resulting from upregulated levels of oxidative stress is commonly implicated in preeclampsia (PE). Ferroptosis is a novel form of iron-dependent cell death instigated by lipid peroxidation likely plays important role in PE pathogenesis. This study aims to investigate expression profiles and functions of the ferroptosis-related genes (FRGs) in early- and late-onset preeclampsia.Methods: The gene expression data and clinical information were downloaded from GEO database. The “limma” R package was used for screening differentially expressed genes. GO(Gene Ontology), Kyoto Encyclopedia of Genes and Genomes(KEGG) and protein protein interaction (PPI) network analyses were conducted to investigate the bioinformatics functions and molecular interactions of significantly different FRGs. Quantitative real-time reverse transcriptase PCR was used to verify the expression of hub FRGs in PE.Results: A total number of 4,215 DEGs were identified between EOPE and preterm cases and 3,356 DEGs were found between EOPE and LOPE subtypes. 20 significantly different FRGs were identified in EOPE, while only 3 in LOPE. Functional enrichment analysis revealed that the differentially expressed FRGs was mainly involved in EOPE and enriched in hypoxia- and iron-related pathways, such as response to hypoxia, iron homeostasis and iron ion binding process. The PPI network analysis and verification by RT-qPCR resulted in the identification of the following six interesting FRGs: FTH1, HIF1A, FTL, IREB2, MAPK8 and PLIN2. Conclusions: EOPE and LOPE owned distinct underlying molecular mechanisms and ferroptosis may be mainly implicated in pathogenesis of EOPE. Further studies are necessary for deeper inquiry into placental ferroptosis and its role in the pathogenesis of EOPE.

Systems Biology Approaches Reveal a Multi-stress Responsive WRKY Transcription Factor and Stress Associated Gene Co-expression Networks in Chickpea

2019 ◽  
Vol 14 (7) ◽  
pp. 591-601 ◽  
Author(s):  
Aravind K. Konda ◽  
Parasappa R. Sabale ◽  
Khela R. Soren ◽  
Shanmugavadivel P. Subramaniam ◽  
Pallavi Singh ◽  
...  
Keyword(s):  
Expression Pattern ◽  
Gene Networks ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Wrky Transcription Factor ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Callose Deposition ◽  
Significant Probability

Background: Chickpea is a nutritional rich premier pulse crop but its production encounters setbacks due to various stresses and understanding of molecular mechanisms can be ascribed foremost importance. Objective: The investigation was carried out to identify the differentially expressed WRKY TFs in chickpea in response to herbicide stress and decipher their interacting partners. Methods: For this purpose, transcriptome wide identification of WRKY TFs in chickpea was done. Behavior of the differentially expressed TFs was compared between other stress conditions. Orthology based cofunctional gene networks were derived from Arabidopsis. Gene ontology and functional enrichment analysis was performed using Blast2GO and STRING software. Gene Coexpression Network (GCN) was constructed in chickpea using publicly available transcriptome data. Expression pattern of the identified gene network was studied in chickpea-Fusarium interactions. Results: A unique WRKY TF (Ca_08086) was found to be significantly (q value = 0.02) upregulated not only under herbicide stress but also in other stresses. Co-functional network of 14 genes, namely Ca_08086, Ca_19657, Ca_01317, Ca_20172, Ca_12226, Ca_15326, Ca_04218, Ca_07256, Ca_14620, Ca_12474, Ca_11595, Ca_15291, Ca_11762 and Ca_03543 were identified. GCN revealed 95 hub genes based on the significant probability scores. Functional annotation indicated role in callose deposition and response to chitin. Interestingly, contrasting expression pattern of the 14 network genes was observed in wilt resistant and susceptible chickpea genotypes, infected with Fusarium. Conclusion: This is the first report of identification of a multi-stress responsive WRKY TF and its associated GCN in chickpea.

scholarly journals Identification of a prognostic long non-coding RNA signature in breast cancer

2020 ◽  
Author(s):  
Gaochen Lan ◽  
Xiaoling Yu ◽  
Yanna Zhao ◽  
Jinjian Lan ◽  
Wan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

scholarly journals Comparative Transcriptome Analysis Suggests Key Roles for 5-Hydroxytryptamlne Receptors in Control of Goose Egg Production

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 455 ◽  
Author(s):  
Qingyuan Ouyang ◽  
Shenqiang Hu ◽  
Guosong Wang ◽  
Jiwei Hu ◽  
Jiaman Zhang ◽  
...  
Keyword(s):  
Egg Production ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Production Performance ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Anser Anser

To date, research on poultry egg production performance has only been conducted within inter or intra-breed groups, while those combining both inter- and intra-breed groups are lacking. Egg production performance is known to differ markedly between Sichuan white goose (Anser cygnoides) and Landes goose (Anser anser). In order to understand the mechanism of egg production performance in geese, we undertook this study. Here, 18 ovarian stromal samples from both Sichuan white goose and Landes goose at the age of 145 days (3 individuals before egg production initiation for each breed) and 730 days (3 high- and low egg production individuals during non-laying periods for each breed) were collected to reveal the genome-wide expression profiles of ovarian mRNAs and lncRNAs between these two geese breeds at different physiological stages. Briefly, 58, 347, 797, 777, and 881 differentially expressed genes (DEGs) and 56, 24, 154, 105, and 224 differentially expressed long non-coding RNAs (DElncRNAs) were found in LLD vs. HLD (low egg production Landes goose vs. high egg production Landes goose), LSC vs. HSC (low egg production Sichuan White goose vs. high egg production Sichuan white goose), YLD vs. YSC (young Landes goose vs. young Sichuan white goose), HLD vs. HSC (high egg production Landes goose vs. high egg production Sichuan white goose), and LLD vs. LSC (low egg production Landes goose vs. low egg production Sichuan white goose) groups, respectively. Functional enrichment analysis of these DEGs and DElncRNAs suggest that the “neuroactive ligand–receptor interaction pathway” is crucial for egg production, and particularly, members of the 5-hydroxytryptamine receptor (HTR) family affect egg production by regulating ovarian metabolic function. Furthermore, the big differences in the secondary structures among HTR1F and HTR1B, HTR2B, and HTR7 may lead to their different expression patterns in goose ovaries of both inter- and intra-breed groups. These results provide novel insights into the mechanisms regulating poultry egg production performance.

scholarly journals Comprehensive Analysis of Differentially Expressed Profiles of mRNA, lncRNA, and circRNA in the Uterus of Seasonal Reproduction Sheep

Genes ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 301 ◽  
Author(s):  
Yongfu La ◽  
Xiaoyun He ◽  
Liping Zhang ◽  
Ran Di ◽  
Xiangyu Wang ◽  
...  
Keyword(s):  
Thyroid Hormone ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Seasonal Reproduction ◽  
Hormone Synthesis ◽  
Long Photoperiod

Photoperiod is one of the important factors leading to seasonal reproduction of sheep. However, the molecular mechanisms underlying the photoperiod regulation of seasonal reproduction remain poorly understood. In this study, we compared the expression profiles of mRNAs, lncRNAs, and circRNAs in uterine tissues from Sunite sheep during three different photoperiods, namely, the short photoperiod (SP), short transfer to long photoperiod (SLP), and long photoperiod (LP). The results showed that 298, 403, and 378 differentially expressed (DE) mRNAs, 171, 491, and 499 DE lncRNAs, and 124, 270, and 400 DE circRNAs were identified between SP and LP, between SP and SLP, and between LP and SLP, respectively. Furthermore, functional enrichment analysis showed that the differentially expressed RNAs were mainly involved in the GnRH signaling pathway, thyroid hormone synthesis, and thyroid hormone signaling pathway. In addition, co-expression networks of lncRNA–mRNA were constructed based on the correlation analysis between the differentially expressed RNAs. Our study provides new insights into the expression changes of RNAs in different photoperiods, which might contribute to understanding the molecular mechanisms of seasonal reproduction in sheep.

Identification Of Putative Gene Signatures Associated With Diagnosis And Prognosis Of Breast Cancer

2021 ◽  
Vol 44 (3) ◽  
pp. E45-54
Author(s):  
Chao Tan ◽  
Fang Zuo ◽  
Mingqian Lu ◽  
Sai Chen ◽  
Zhenzhen Tian ◽  
...  
Keyword(s):  
Risk Model ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Support Vector ◽  
Ppi Network ◽  
Hub Genes ◽  
Putative Gene ◽  
Network Analyses ◽  
Cluster 2

Purpose: This study aimed to identify potential diagnostic and therapeutic biomakers for the development ofbreast cancer (BC). Methods: GSE86374 dataset containing 159 samples was acquired from the Gene Expression Omnibus (GEO) database followed by differentially expressed genes (DEGs) identification and cluster analysis. Corresponding functional enrichment and protein-protein interaction (PPI) network analyses were performed to identify hub genes. Prognostic evaluation using clinical information obtained from TCGA database and hub genes was conducted to screen for crucial indicators for BC progression. The risk model was established and validated. Results: In total, 186 DEGs were identified and grouped into four clusters: 96 in cluster 1; 69 in cluster 2; 16 in  cluster 3; and 5 in cluster 4. Functional enrichment analysis showed that DEGs, including ADH1B in cluster 1,  were dramatically enriched in the tyrosine and drug metabolism pathways, while genes in cluster 2, including  SPP1 and RRM2, played crucial roles in PI3K-Akt and p53 signalling pathway. SPP1 and RRM2 served as hub  genes in the PPI network, resulting in an support vector machine classifier with good accuracy and specificity.Ad ditionally, the results of prognostic analysis suggest that age, metastasis stage, SPP1 and ADH1B were correlated with risk of BC, which was validated by using the established risk model analysis. Conclusion: SPP1, RRM2 and ADH1B appear to play vital roles in the development of BC. Age and TNM stage  were also preferentially associated with risk of developing BC. Evaluation of the risk model based on larger sample size and further experimental validation are required.

scholarly journals Identification and Interaction Analysis of Significant Genes and MicroRNAs in Pterygium

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Siying He ◽  
Hui Sun ◽  
Yifang Huang ◽  
Shiqi Dong ◽  
Chen Qiao ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Interaction Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Differentially Expressed Mirnas

Purpose. MiRNAs have been widely analyzed in the occurrence and development of many diseases, including pterygium. This study aimed to identify the key genes and miRNAs in pterygium and to explore the underlying molecular mechanisms. Methods. MiRNA expression was initially extracted and pooled by published literature. Microarray data about differentially expressed genes was downloaded from Gene Expression Omnibus (GEO) database and analyzed with the R programming language. Functional and pathway enrichment analyses were performed using the database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction network was constructed with the STRING database. The associations between chemicals, differentially expressed miRNAs, and differentially expressed genes were predicted using the online resource. All the networks were constructed using Cytoscape. Results. We found that 35 miRNAs and 301 genes were significantly differentially expressed. Functional enrichment analysis showed that upregulated genes were significantly enriched in extracellular matrix (ECM) organization, while downregulated genes were mainly involved in cell death and apoptotic process. Finally, we concluded the chemical-gene affected network, miRNA-mRNA interacted networks, and significant pathway network. Conclusion. We identified lists of differentially expressed miRNAs and genes and their possible interaction in pterygium. The networks indicated that ECM breakdown and EMT might be two major pathophysiological mechanisms and showed the potential significance of PI3K-Akt signalling pathway. MiR-29b-3p and collagen family (COL4A1 and COL3A1) might be new treatment target in pterygium.

scholarly journals Integrated analysis of lncRNA-miRNA-mRNA ceRNA network in human aortic dissection

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Hao Zhang ◽  
Ce Bian ◽  
Simei Tu ◽  
Fanxing Yin ◽  
Panpan Guo ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Down Regulation ◽  
Tissue Samples ◽  
Cerna Network

Abstract Background Many studies on long chain non-coding RNAs (lncRNAs) are published in recent years. But the roles of lncRNAs in aortic dissection (AD) are still unclear and should be further examined. The present work focused on determining the molecular mechanisms underlying lncRNAs regulation in aortic dissection on the basis of the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network. Methods This study collected the lncRNAs (GSE52093), mRNAs (GSE52093) and miRNAs (GSE92427) expression data within human tissue samples with aortic dissection group and normal group based on Gene Expression Omnibus (GEO) database. Results This study identified three differentially expressed lncRNAs (DELs), 19 differentially expressed miRNAs (DEmiRs) and 1046 differentially expressed mRNAs (DEGs) identified regarding aortic dissection. Furthermore, we constructed a lncRNA-miRNA-mRNA network through three lncRNAs (including two with up-regulation and one with down-regulation), five miRNAs (five with up-regulation), as well as 211 mRNAs (including 103 with up-regulation and 108 with down-regulation). Simultaneously, we conducted functional enrichment and pathway analyses on genes within the as-constructed ceRNA network. According to our PPI/ceRNA network and functional enrichment analysis results, four critical genes were found (E2F2, IGF1R, BDNF and PPP2R1B). In addition, E2F2 level was possibly modulated via lncRNA FAM87A-hsa-miR-31-5p/hsa-miR-7-5p or lncRNA C9orf106-hsa-miR-7-5p. The expression of IGF1R may be regulated by lncRNA FAM87A-hsa-miR-16-5p/hsa-miR-7-5p or lncRNA C9orf106-hsa-miR-7-5p. Conclusion In conclusion, the ceRNA interaction axis we identified is a potentially critical target for treating AD. Our results shed more lights on the possible pathogenic mechanism in AD using a lncRNA-associated ceRNA network.

scholarly journals Hub genes of stroke identified by weighted gene co-expression network analysis

2019 ◽  
Author(s):  
Junhong Li ◽  
Yang Zhai ◽  
Peng Wu ◽  
Yueqiang Hu ◽  
Wei Chen ◽  
...  
Keyword(s):  
Network Analysis ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Neuron Death ◽  
Roc Curve Analysis ◽  
Precise Diagnosis

Abstract Background Microarray-based gene expression profiling has been widely used in biomedical research. Weighted gene co-expression network analysis (WGCNA) can link microarray data directly to clinical traits and to identify rules for predicting pathological stage and prognosis of disease, it has been found useful in many biological processes. Stroke is one of the most common diseases worldwide, yet molecular mechanisms of its pathogenesis are largely unknown. We aimed to construct gene co-expression networks to identify key modules and hub genes associated with the pathogenesis of stroke.Results In this study, we screened out the differentially expressed genes from gene microarray expression profiles, then constructed the free-scale gene co-expression networks to explore the associations between gene sets and clinical features, and to identify key modules and hub genes. Subsequently, functional enrichment and the receiver operating characteristic (ROC) curve analysis were performed. And the results show that a total of 11,747 most variant genes were used for co-expression network construction. Pink and yellow modules were found to be the most significantly related to stroke. Functional enrichment analysis showed that the pink module was mainly involved in regulation of neuron regeneration, and the repair of DNA damage, while the yellow module was mainly enriched in ion transport system dysfunction which were correlated with neuron death. A total of 8 hub genes (PRR11, NEDD9, Notch2, RUNX1-IT1, ANP32A-IT1, ASTN2, SAMHD1 and STIM1) were identified and validated at transcriptional levels (other datasets) and by existing literatures.Conclusions Eight hub genes (PRR11, NEDD9, Notch2, RUNX1-IT1, ANP32A-IT1, ASTN2, SAMHD1 and STIM1) may serve as biomarkers and therapeutic targets for precise diagnosis and treatment of stroke in the future.

scholarly journals Immunogenomic Landscape Analysis of Prognostic Immune-Related Genes in Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Peng Qin ◽  
Mengyu Zhang ◽  
Xue Liu ◽  
Ziming Dong
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Immune Related Genes

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death. HBV infection is an important risk factor for the tumorigenesis of HCC, given that the inflammatory environment is closely related to morbidity and prognosis. Consequently, it is of urgent importance to explore the immunogenomic landscape to supplement the prognosis of HCC. The expression profiles of immune‐related genes (IRGs) were integrated with 377 HCC patients to generate differentially expressed IRGs based on the Cancer Genome Atlas (TCGA) dataset. These IRGs were evaluated and assessed in terms of their diagnostic and prognostic values. A total of 32 differentially expressed immune‐related genes resulted as significantly correlated with the overall survival of HCC patients. The Gene Ontology functional enrichment analysis revealed that these genes were actively involved in cytokine‐cytokine receptor interaction. A prognostic signature based on IRGs (HSPA4, PSME3, PSMD14, FABP6, ISG20L2, TRAF3, NDRG1, NRAS, CSPG5, and IL17D) stratified patients into high-risk versus low-risk groups in terms of overall survival and remained as an independent prognostic factor in multivariate analyses after adjusting for clinical and pathologic factors. Several IRGs (HSPA4, PSME3, PSMD14, FABP6, ISG20L2, TRAF3, NDRG1, NRAS, CSPG5, and IL17D) of clinical significance were screened in the present study, revealing that the proposed clinical-immune signature is a promising risk score for predicting the prognosis of HCC.

scholarly journals Bioinformatics analysis of microarray data to identify the candidate biomarkers of lung adenocarcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7313 ◽  
Author(s):  
Tingting Guo ◽  
Hongtao Ma ◽  
Yubai Zhou
Keyword(s):  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Molecular Mechanisms ◽  
Prion Diseases ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes

Background Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and the most lethal malignant disease worldwide. However, the molecular mechanisms underlying LUAD are not fully understood. Methods Four datasets (GSE118370, GSE85841, GSE43458 and GSE32863) were obtained from the gene expression omnibus (GEO). Identification of differentially expressed genes (DEGs) and functional enrichment analysis were performed using the limma and clusterProfiler packages, respectively. A protein–protein interaction (PPI) network was constructed via Search Tool for the Retrieval of Interacting Genes (STRING) database, and the module analysis was performed by Cytoscape. Then, overall survival analysis was performed using the Kaplan–Meier curve, and prognostic candidate biomarkers were further analyzed using the Oncomine database. Results Totally, 349 DEGs were identified, including 275 downregulated and 74 upregulated genes which were significantly enriched in the biological process of extracellular structure organization, leukocyte migration and response to peptide. The mainly enriched pathways were complement and coagulation cascades, malaria and prion diseases. By extracting key modules from the PPI network, 11 hub genes were screened out. Survival analysis showed that except VSIG4, other hub genes may be involved in the development of LUAD, in which MYH10, METTL7A, FCER1G and TMOD1 have not been reported previously to correlated with LUAD. Briefly, novel hub genes identified in this study will help to deepen our understanding of the molecular mechanisms of LUAD carcinogenesis and progression, and to discover candidate targets for early detection and treatment of LUAD.

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