scholarly journals Transcriptomic Signatures for Ovulation in Vertebrates

2016 ◽  
Author(s):  
Dongteng Liu ◽  
Michael S. Brewer ◽  
Shixi Chen ◽  
Wanshu Hong ◽  
Yong Zhu
Keyword(s):  
Inflammatory Response ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Telomere Maintenance ◽  
Large Set ◽  
Follicular Cells ◽  
Zebrafish Model ◽  
Online Databases ◽  
Conserved Genes ◽  
Gene Transcripts

AbstractRecently, we found anovulation in nuclear progestin receptor (Pgr) knockout (Pgr-KO) zebrafish, which offers a new model for examining Pgr regulated genes and pathways that are important for ovulation and fertility. In this study, we examined expression of all transcripts using RNA-Seq in pre-ovulatory follicular cells collected after the final oocyte maturation, but prior to ovulation, from wild-type (WT) or Pgr-KO fish. Differential expression analysis revealed 2,888 genes significantly differentially expressed between WT and Pgr-KO fish. Among those, 1,230 gene transcripts were significantly more expressed, while 1,658 genes were significantly less expressed in WT than those in Pgr-KO. We then retrieved and compared transcriptional data from online databases and further identified 661 conserved genes in fish, mice, and humans, that showed similar levels of high (283 genes) or low (387) expression in animals that were ovulating compared to those with no ovulation. For the first time, ovulatory genes and their involved biological processes and pathways were also visualized using Enrichment Map and Cytoscape. Intriguingly, enrichment analysis indicated the genes with higher expression were involved in multiple ovulatory pathways and processes such as inflammatory response, angiogenesis, cytokine production, cell migration, chemotaxis, MAPK, focal adhesion, and cytoskeleton reorganization. In contrast, the genes with lower expression were mainly involved DNA replication, DNA repair, DNA methylation, RNA processing, telomere maintenance, spindle assembling, nuclear acid transport, catabolic processes, nuclear and cell division. Our results indicate that a large set of genes (>3,000) are differentially regulated in the follicular cells in zebrafish prior to ovulation, terminating programs including growth and proliferation, and beginning processes including the inflammatory response and apoptosis. Further studies are required to establish relationships among these genes and an ovulatory circuit in zebrafish model.

Identification of Candidate Genetic Markers and a Novel 4-genes Diagnostic Model in Osteoarthritis through Integrating Multiple Microarray Data

2020 ◽  
Vol 23 (8) ◽  
pp. 805-813
Author(s):  
Ai Jiang ◽  
Peng Xu ◽  
Zhenda Zhao ◽  
Qizhao Tan ◽  
Shang Sun ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Microarray Data ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Functional Enrichment ◽  
Joint Disease ◽  
Support Vector ◽  
Diagnostic Model ◽  
Data Sets

Background: Osteoarthritis (OA) is a joint disease that leads to a high disability rate and a low quality of life. With the development of modern molecular biology techniques, some key genes and diagnostic markers have been reported. However, the etiology and pathogenesis of OA are still unknown. Objective: To develop a gene signature in OA. Method: In this study, five microarray data sets were integrated to conduct a comprehensive network and pathway analysis of the biological functions of OA related genes, which can provide valuable information and further explore the etiology and pathogenesis of OA. Results and Discussion: Differential expression analysis identified 180 genes with significantly expressed expression in OA. Functional enrichment analysis showed that the up-regulated genes were associated with rheumatoid arthritis (p < 0.01). Down-regulated genes regulate the biological processes of negative regulation of kinase activity and some signaling pathways such as MAPK signaling pathway (p < 0.001) and IL-17 signaling pathway (p < 0.001). In addition, the OA specific protein-protein interaction (PPI) network was constructed based on the differentially expressed genes. The analysis of network topological attributes showed that differentially upregulated VEGFA, MYC, ATF3 and JUN genes were hub genes of the network, which may influence the occurrence and development of OA through regulating cell cycle or apoptosis, and were potential biomarkers of OA. Finally, the support vector machine (SVM) method was used to establish the diagnosis model of OA, which not only had excellent predictive power in internal and external data sets (AUC > 0.9), but also had high predictive performance in different chip platforms (AUC > 0.9) and also had effective ability in blood samples (AUC > 0.8). Conclusion: The 4-genes diagnostic model may be of great help to the early diagnosis and prediction of OA.

Identification of key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma

2020 ◽  
Vol 15 ◽  
Author(s):  
Wei Han ◽  
Dongchen Lu ◽  
Chonggao Wang ◽  
Mengdi Cui ◽  
Kai Lu
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differential Expression Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Integrated Analysis ◽  
Papillary Thyroid ◽  
Gene Set Enrichment ◽  
Mirna Expression Data

Background: In the past decades, the incidence of thyroid cancer (TC) has been gradually increasing, owing to the widespread use of ultrasound scanning devices. However, the key mRNAs, miRNAs, and mRNA-miRNA network in papillary thyroid carcinoma (PTC) has not been fully understood. Material and Methods: In this study, multiple bioinformatics methods were employed, including differential expression analysis, gene set enrichment analysis, and miRNA-mRNA interaction network construction. Results: First, we investigated the key miRNAs that regulated significantly more differentially expressed genes based on GSEA method. Second, we searched for the key miRNAs based on the mRNA-miRNA interaction subnetwork involved in PTC. We identified hsa-mir-1275, hsa-mir-1291, hsa-mir-206 and hsa-mir-375 as the key miRNAs involved in PTC pathogenesis. Conclusion: The integrated analysis of the gene and miRNA expression data not only identified key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma, but also improved our understanding of the pathogenesis of PTC.

Abstract 392: The Plasma Proteome of Tangier Disease Patients Reveals Perturbations of Diabetic and Inflammatory Pathways

2016 ◽  
Vol 36 (suppl_1) ◽  
Author(s):  
James T McParland ◽  
Evanthia Pashos ◽  
Daniel J Rader ◽  
Marina Cuchel
Keyword(s):  
Inflammatory Response ◽  
Type Ii Diabetes ◽  
Enrichment Analysis ◽  
Nonparametric Test ◽  
Type Ii Diabetes Mellitus ◽  
Gene Set Enrichment Analysis ◽  
P Value ◽  
Type Ii ◽  
Tangier Disease ◽  
Inflammatory Pathways

Aim: The ATP-binding cassette transporter 1 (ABCA1) is a membrane protein well known for its role in cholesterol efflux and HDL formation. Recently, ABCA1 has been implicated as playing a key role in other processes, such as insulin secretion and inflammatory response. We sought to further investigate these potential roles through a quantitative proteomics approach. Specifically, we hypothesized that we could detect differential protein signatures in the plasma of Tangier patients that correspond to pathways involved in diabetes and inflammation. Methods: We used SOMAscan® technology (SomaLogic, Boulder, CO, USA) to analyze plasma collected from 5 Tangier disease patients (homozygotes or compound heterozygotes for functional ABCA1 mutations) and 7 normolipidemic controls. We tested for differences in the levels of approximately 1,000 plasma proteins using a nonparametric test (KS). We then performed Ingenuity Canonical Pathway analysis to examine if proteins linked to diabetes and inflammation pathways were significantly more likely to be differentially abundant in the plasma. We corroborated the results using Gene Set Enrichment Analysis (GSEA). Results: We found an enrichment in differentially abundant proteins involved in type II diabetes mellitus signaling (p-value=0.0002) and inflammatory pathways, such as granulocyte adhesion and diapedesis (p-value=2.2*10 -12 ). These results were also corroborated by GSEA, where gene sets corresponding to GO biological processes such as immune response (p-value=0.008) and inflammatory response (p-value=0.032) ranked at the top of the enrichment results. Conclusions: The results from this pilot study support the concept that ABCA1 is implicated in pathways affecting immune and inflammatory response and type II diabetes.

scholarly journals Deregulation of Trace Amine-Associated Receptors (TAAR) Expression and Signaling Mode in Melanoma

Biomolecules ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 114
Author(s):  
Anastasia N. Vaganova ◽  
Savelii R. Kuvarzin ◽  
Anastasia M. Sycheva ◽  
Raul R. Gainetdinov
Keyword(s):  
Malignant Tumors ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Clinicopathological Characteristics ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Low Concentrations ◽  
Trace Amine ◽  
Specific Association ◽  
Amine Compounds

Trace amine-associated receptors (TAARs) interact with amine compounds called “trace amines” which are present in tissues at low concentrations. Recently, TAARs expression in neoplastic tumors was reported. In this study, TAARs expression was analyzed in public RNAseq datasets in nevi and melanoma samples and compared to the expression of dopamine receptors (DRDs) that are known to be involved in melanoma pathogenesis. It was found that all DRDs and TAARs are expressed in nevi at comparable levels. Differential expression analysis demonstrated the drastic decrease of TAAR1, TAAR2, TAAR5, TAAR6, and TAAR8 expression in melanomas compared to benign nevi with only TAAR6, TAAR8, and TAAR9 remaining detectable in malignant tumors. No association of TAARs expression levels and melanoma clinicopathological characteristics was observed. TAARs co-expressed genes in melanoma and nevi were selected by correlation values for comparative pathway enrichment analysis between malignant and benign neoplasia. It was found that coexpression of TAARs with genes inquired in neurotransmitter signaling is lost in melanoma, and tumor-specific association of TAAR6 expression with the mTOR pathway and inflammatory signaling is observed. It is not excluded that TAARs may have certain functions in melanoma pathogenesis, the significance of which to tumor progression is yet to be understood.

scholarly journals Integrated Transcriptional Profiling Analysis and Immune-Related Risk Model Construction for Intracranial Aneurysm Rupture

2021 ◽  
Vol 15 ◽  
Author(s):  
Dezhi Shan ◽  
Xing Guo ◽  
Guozheng Yang ◽  
Zheng He ◽  
Rongrong Zhao ◽  
...  
Keyword(s):  
Immune Response ◽  
Inflammatory Response ◽  
Signaling Pathway ◽  
Immune Cell ◽  
Risk Model ◽  
Enrichment Analysis ◽  
Cell Infiltration ◽  
Enzyme Linked Immunosorbent Assay ◽  
Immune Cell Infiltration ◽  
Related Risk

Intracranial aneurysms (IAs) may cause lethal subarachnoid hemorrhage upon rupture, but the molecular mechanisms are poorly understood. The aims of this study were to analyze the transcriptional profiles to explore the functions and regulatory networks of differentially expressed genes (DEGs) in IA rupture by bioinformatics methods and to identify the underlying mechanisms. In this study, 1,471 DEGs were obtained, of which 619 were upregulated and 852 were downregulated. Gene enrichment analysis showed that the DEGs were mainly enriched in the inflammatory response, immune response, neutrophil chemotaxis, and macrophage differentiation. Related pathways include the regulation of actin cytoskeleton, leukocyte transendothelial migration, nuclear factor κB signaling pathway, Toll-like receptor signaling pathway, tumor necrosis factor signaling pathway, and chemokine signaling pathway. The enrichment analysis of 20 hub genes, subnetworks, and significant enrichment modules of weighted gene coexpression network analysis showed that the inflammatory response and immune response had a causal relationship with the rupture of unruptured IAs (UIAs). Next, the CIBERSORT method was used to analyze immune cell infiltration into ruptured IAs (RIAs) and UIAs. Macrophage infiltration into RIAs increased significantly compared with that into UIAs. The result of principal component analysis revealed that there was a difference between RIAs and UIAs in immune cell infiltration. A 4-gene immune-related risk model for IA rupture (IRMIR), containing CXCR4, CXCL3, CX3CL1, and CXCL16, was established using the glmnet package in R software. The receiver operating characteristic value revealed that the model represented an excellent clinical situation for potential application. Enzyme-linked immunosorbent assay was performed and showed that the concentrations of CXCR4 and CXCL3 in serum from RIA patients were significantly higher than those in serum from UIA patients. Finally, a competing endogenous RNA network was constructed to provide a potential explanation for the mechanism of immune cell infiltration into IAs. Our findings highlighted the importance of immune cell infiltration into RIAs, providing a direction for further research.

scholarly journals Identification and Validation of Immune-Related LncRNA Prognostic Signature for Lung Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Guomin Wu ◽  
Qihao Wang ◽  
Ting Zhu ◽  
Linhai Fu ◽  
Zhupeng Li ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Lung Adenocarcinoma ◽  
Clinical Features ◽  
Cox Regression ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Immune Infiltration

This study aimed to establish a prognostic risk model for lung adenocarcinoma (LUAD). We firstly divided 535 LUAD samples in TCGA-LUAD into high-, medium-, and low-immune infiltration groups by consensus clustering analysis according to immunological competence assessment by single-sample gene set enrichment analysis (ssGSEA). Profile of long non-coding RNAs (lncRNAs) in normal samples and LUAD samples in TCGA was used for a differential expression analysis in the high- and low-immune infiltration groups. A total of 1,570 immune-related differential lncRNAs in LUAD were obtained by intersecting the above results. Afterward, univariate COX regression analysis and multivariate stepwise COX regression analysis were conducted to screen prognosis-related lncRNAs, and an eight-immune-related-lncRNA prognostic signature was finally acquired (AL365181.2, AC012213.4, DRAIC, MRGPRG-AS1, AP002478.1, AC092168.2, FAM30A, and LINC02412). Kaplan–Meier analysis and ROC analysis indicated that the eight-lncRNA-based model was accurate to predict the prognosis of LUAD patients. Simultaneously, univariate COX regression analysis and multivariate COX regression analysis were undertaken on clinical features and risk scores. It was illustrated that the risk score was a prognostic factor independent from clinical features. Moreover, immune data of LUAD in the TIMER database were analyzed. The eight-immune-related-lncRNA prognostic signature was related to the infiltration of B cells, CD4+ T cells, and dendritic cells. GSEA enrichment analysis revealed significant differences in high- and low-risk groups in pathways like pentose phosphate pathway, ubiquitin mediated proteolysis, and P53 signaling pathway. This study helps to treat LUAD patients and explore molecules related to LUAD immune infiltration to deeply understand the specific mechanism.

scholarly journals Screening and bioinformatics analysis of key biomarkers in acute myocardial infarction

Pteridines ◽  
2021 ◽  
Vol 32 (1) ◽  
pp. 79-92
Author(s):  
Dongmei Wei ◽  
Rui Li ◽  
Tao Si ◽  
Hankang He ◽  
Wei Wu
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Immune Response ◽  
Inflammatory Response ◽  
Receptor Binding ◽  
Decisive Role ◽  
Enrichment Analysis ◽  
Neutrophil Chemotaxis ◽  
Ppi Network ◽  
Extracellular Region

Abstract Acute myocardial infarction (AMI) is the most severe manifestation of coronary artery disease. Considerable efforts have been made to elucidate its etiology and pathology, but the genetic factors that play a decisive role in the occurrence of AMI are still unclear. To determine the molecular mechanism of the occurrence and development of AMI, four microarray datasets, namely, GSE29111, GSE48060, GSE66360, and GSE97320, were downloaded from the Gene Expression Omnibus (GEO) database. We analyzed the four GEO datasets to obtain the differential expression genes (DEGs) of patients with AMI and patients with non-AMI and then performed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and Protein-protein interaction (PPI) network analysis. A total of 41 DEGs were identified, including 39 upregulated genes and 2 downregulated genes. The enriched functions and pathways of the DEGs included the inflammatory response, neutrophil chemotaxis, immune response, extracellular space, positive regulation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) transcription factor activity, response to lipopolysaccharide, receptor for advanced glycation end products (RAGE) receptor binding, innate immune response, defense response to bacterium, and receptor activity. The cytoHubba plug-in in Cytoscape was used to select the most significant hub gene from the PPI network. Ten hub genes were identified, and GO enrichment analysis revealed that these genes were mainly enriched in inflammatory response, neutrophil chemotaxis, immune response, RAGE receptor binding, and extracellular region. In conclusion, this study integrated four datasets and used bioinformatics methods to analyze the gene chips of AMI samples and control samples and identified DEGs that may be involved in the occurrence and development of AMI. The study provides reliable molecular biomarkers for AMI screening, diagnosis, and prognosis.

scholarly journals Whole-organism Transcriptomic Insight Into the Effects of Cytco, A Novel Nematotoxic Protein on the Pine Wood Nematode Bursaphelenchus Xylophilus 

2021 ◽  
Author(s):  
Ye Chen ◽  
Xiang Zhou ◽  
Kai Guo ◽  
Sha-Ni Chen ◽  
Xiu Su
Keyword(s):  
Enrichment Analysis ◽  
Transcriptome Profiling ◽  
Bursaphelenchus Xylophilus ◽  
Control Measures ◽  
Effective Control ◽  
Large Set ◽  
Pine Wood Nematode ◽  
Pine Wood ◽  
Protein Toxin ◽  
Insight Into

Abstract Background: The pine wood nematode Bursaphelenchus xylophilus is a worldwide destructive pest on Pinus trees and lacks effective control measures. Screening nematotoxic protein toxins has been conducted to develop new strategies for nematode control. Results: The present study provided initial insights into the responses of B. xylophilus exposed to a nematocidal cytolytic-like protein (CytCo) based on the transcriptome profiling. A large set of differentially expressed genes (1266 DEGs) were found related to nematode development, reproduction, metabolism, motion, and immune system. In response to the toxic protein, B. xylophilus upregulated DEGs encoding cuticle collagens, transporters, and cytochrome P450. In addition, many DEGs related to cell death, lipid metabolism, major sperm proteins, proteinases/peptidases, phosphatases, kinases, virulence factors, and transthyretin-like proteins were downregulated. And Gene Ontology enrichment analysis showed that CytCo treatment significantly affecting DEGs functioning in muscle contraction, lipid localization, MAPK cascade. The pathway richness of Kyoto Encyclopedia of Genes and Genomes showed that the DEGs were concentrated in lysosome and fatty acid degradation. The weight co-expression network analysis indicated that the hub genes affected by CytCo were associated with the nematode cuticular collagen. Conclusions: These results showed that the CytCo protein toxin could interference gene expression to produce multiple nematotoxic effects, providing initial insight into its control potential of pine wood nematode.

scholarly journals MicroRNA-based regulation of genomics and transcriptomics of inflammatory cytokines in COVID-19

2021 ◽  
Author(s):  
Manoj Khokhar ◽  
Sojit Tomo ◽  
Purvi Purohit
Keyword(s):  
Transcription Factors ◽  
Inflammatory Response ◽  
In Silico ◽  
Wide Spectrum ◽  
Interaction Network ◽  
In Silico Analysis ◽  
Enrichment Analysis ◽  
Microarray Dataset ◽  
Therapeutic Strategies ◽  
Protein Protein Interaction

Background: Coronavirus disease 2019 is characterized by the elevation of a wide spectrum of inflammatory mediators which are associated with poor disease outcomes. We aimed at an in-silico analysis of regulatory microRNA and their transcription factors (TF) for these inflammatory genes that may help to devise potential therapeutic strategies in the future. Methods: The cytokine regulating immune-expressed genes (CRIEG) were sorted from literature and GEO microarray dataset and their co-differentially expressed miRNA and transcription factors were predicted from publicly available databases. Enrichment analysis was done through mienturnet, MiEAA, and Gene Ontology, and pathways predicted by KEGG and Reactome pathways. The functional and regulatory features were analyzed and visualized through Cytoscape. Results: Sixteen CRIEG were observed to have a significant protein-protein interaction network. The ontological analysis revealed significantly enriched pathways for biological processes, molecular functions, and cellular components. The search performed in the miRNA database yielded 10 miRNAs that are significantly involved in the regulation of these genes and their transcription factors. Conclusion: An In-Silico representation of a network involving miRNAs, CRIEGs, and TF which take part in the inflammatory response in COVID-19 has been elucidated. These regulatory factors may have potentially critical roles in the inflammatory response in COVID-19 and may be explored further for the development of targeted therapeutic strategies and mechanistic validation.

scholarly journals obaDIA: one-step biological analysis pipeline for data-independent acquisition and other quantitative proteomics data

2020 ◽  
Author(s):  
Jun Yan ◽  
Hongning Zhai ◽  
Ling Zhu ◽  
Sasha Sa ◽  
Xiaojun Ding
Keyword(s):  
Protein Level ◽  
Quantitative Proteomics ◽  
Differential Expression Analysis ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Supplementary Information ◽  
Proteomics Data ◽  
Data Independent Acquisition ◽  
One Step ◽  
Automatic Tool

Abstract Motivation Data mining and data quality evaluation are indispensable constituents of quantitative proteomics, but few integrated tools available. Results We introduced obaDIA, a one-step pipeline to generate visualizable and comprehensive results for quantitative proteomics data. obaDIA supports fragment-level, peptide-level and protein-level abundance matrices from DIA technique, as well as protein-level abundance matrices from other quantitative proteomic techniques. The result contains abundance matrix statistics, differential expression analysis, protein functional annotation and enrichment analysis. Additionally, enrichment strategies which use total proteins or expressed proteins as background are optional, and HTML based interactive visualization for differentially expressed proteins in the KEGG pathway is offered, which helps biological significance mining. In short, obaDIA is an automatic tool for bioinformatics analysis for quantitative proteomics. Availability and implementation obaDIA is freely available from https://github.com/yjthu/obaDIA.git. Supplementary information Supplementary data are available at Bioinformatics online.

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