scholarly journals Hub microRNAs and genes in the development of atrial fibrillation identified by weighted gene co-expression network analysis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qiang Qu ◽  
Jin-Yu Sun ◽  
Zhen-Ye Zhang ◽  
Yue Su ◽  
Shan-Shan Li ◽  
...  
Keyword(s):  
Network Analysis ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Expression Patterns ◽  
Mirna Gene ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Interaction Patterns ◽  
Hub Genes ◽  
Key Genes

AbstractCo-expression network may contribute to better understanding molecular interaction patterns underlying cellular processes. To explore microRNAs (miRNAs) expression patterns correlated with AF, we performed weighted gene co-expression network analysis (WGCNA) based on the dataset GSE28954. Thereafter, we predicted target genes using experimentally verified databases (ENOCRI, miRTarBase, and Tarbase), and overlapped genes with differentially expressed genes (DEGs) from GSE79768 were identified as key genes. Integrated analysis of association between hub miRNAs and key genes was conducted to screen hub genes. In general, we identified 3 differentially expressed miRNAs (DEMs) and 320 DEGs, predominantly enriched in inflammation-related functional items. Two significant modules (red and blue) and hub miRNAs (hsa-miR-146b-5p and hsa-miR-378a-5p), which highly correlated with AF-related phenotype, were detected by WGCNA. By overlapping the DEGs and predicted target genes, 38 genes were screened out. Finally, 9 genes (i.e. ATP13A3, BMP2, CXCL1, GABPA, LIF, MAP3K8, NPY1R, S100A12, SLC16A2) located at the core region in the miRNA-gene interaction network were identified as hub genes. In conclusion, our study identified 2 hub miRNAs and 9 hub genes, which may improve the understanding of molecular mechanisms and help to reveal potential therapeutic targets against AF.

scholarly journals Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Xinhong Liu ◽  
Feng Chen ◽  
Fang Tan ◽  
Fang Li ◽  
Ruokun Yi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcription Factors ◽  
Target Genes ◽  
Differential Expression Analysis ◽  
Mirna Gene ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Epithelial Tissue ◽  
Hub Genes ◽  
Geo Database

Background. Breast cancer is a malignant tumor that occurs in the epithelial tissue of the breast gland and has become the most common malignancy in women. The regulation of the expression of related genes by microRNA (miRNA) plays an important role in breast cancer. We constructed a comprehensive breast cancer-miRNA-gene interaction map. Methods. Three miRNA microarray datasets (GSE26659, GSE45666, and GSE58210) were obtained from the GEO database. Then, the R software “LIMMA” package was used to identify differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The BRCA GE-mRNA datasets (GSE109169 and GSE139038) were downloaded from the GEO database for identifying differentially expressed genes (DE-genes). Next, GO annotation and KEGG pathway enrichment analysis were conducted. A PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes were further evaluated. Results. We found 6 upregulated differentially expressed- (DE-) miRNAs and 18 downregulated DE-miRNAs by analyzing 3 Gene Expression Omnibus databases, and we predicted the upstream transcription factors and downstream target genes for these DE-miRNAs. Then, we used the GEO database to perform differential analysis on breast cancer mRNA and obtained differentially expressed mRNA. We found 10 hub genes of upregulated DE-miRNAs and 10 hub genes of downregulated DE-miRNAs through interaction analysis. Conclusions. In this study, we have performed an integrated bioinformatics analysis to construct a more comprehensive BRCA-miRNA-gene network and provide new targets and research directions for the treatment and prognosis of BRCA.

scholarly journals Integrated analysis of sex-biased mRNA and miRNA expression profiles in the gonad of the discus fish (Symphysodon aequifasciatus)

2018 ◽  
Author(s):  
yuanshuai Fu ◽  
Zhe Xu ◽  
Zaizhong Chen ◽  
Bin Wen ◽  
Jianzhong Gao
Keyword(s):  
Molecular Mechanisms ◽  
Target Genes ◽  
High Efficiency ◽  
Expression Profiles ◽  
Gonad Development ◽  
Differentially Expressed ◽  
Cdna Libraries ◽  
Integrated Analysis ◽  
Illumina Hiseq ◽  
Differentially Expressed Mirnas

The discus fish (Symphysodon aequifasciatus) is an ornamental fish that is well-known around the world. Phenotype investigation indicated that there are no significant differences in appearance between males and females of the discus fish. To better understand the sexual development mechanisms and obtain a high efficiency sex identification method in the artificial reproduction process of the discus fish, we constructed six cDNA libraries from three adult testes and three adult ovaries, and perform RNA-sequencing for identifying sex-biased candidate genes, microRNA (miRNA), and metabolic pathway using the Illumina Hiseq 4000. A total of 50,082 non-redundant genes (unigenes) were identified, of which 18,570 unigenes were significantly overexpressed in testes, and 11,182 unigenes were significantly overexpressed in ovaries, and 8 differentially expressed unigenes were validated by quantitative Real-Time PCR (qPCR). A total of 551 miRNAs were identified, of which 47 miRNAs were differentially expressed between testes and ovaries, and 7 differentially expressed miRNAs and one non-differential miRNA were validated by qPCR. Twenty-four of these differentially expressed miRNAs and their 15 predicted target genes constituted 41 important miRNA-mRNA interaction pairs, which may be important candidates for sex-related miRNAs and sex-related genes in the discus fish. Some of vital sex-related metabolic pathways were also identified that may play key roles in regulating gonad development of the discus fish. These results can provide important insights to better understand molecular mechanisms for sexual dimorphism in gonads development.

scholarly journals Genome-Wide Detection of Key Genes and Epigenetic Markers for Chicken Fatty Liver

2020 ◽  
Vol 21 (5) ◽  
pp. 1800
Author(s):  
Xiaodong Tan ◽  
Ranran Liu ◽  
Siyuan Xing ◽  
Yonghong Zhang ◽  
Qinghe Li ◽  
...  
Keyword(s):  
Fatty Liver ◽  
Noncoding Rna ◽  
Production Efficiency ◽  
Target Genes ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Epigenetic Markers ◽  
Differentially Methylated Genes ◽  
Key Genes ◽  
Immune Related Genes

Chickens are one of the most important sources of meat worldwide, and the occurrence of fatty liver syndrome (FLS) is closely related to production efficiency. However, the potential mechanism of FLS remains poorly understood. An integrated analysis of data from whole-genome bisulfite sequencing and long noncoding RNA (lncRNA) sequencing was conducted. A total of 1177 differentially expressed genes (DEGs) and 1442 differentially methylated genes (DMGs) were found. There were 72% of 83 lipid- and glucose-related genes upregulated; 81% of 150 immune-related genes were downregulated in fatty livers. Part of those genes was within differentially methylated regions (DMRs). Besides, sixty-seven lncRNAs were identified differentially expressed and divided into 13 clusters based on their expression pattern. Some lipid- and glucose-related lncRNAs (e.g., LNC_006756, LNC_012355, and LNC_005024) and immune-related lncRNAs (e.g., LNC_010111, LNC_010862, and LNC_001272) were found through a co-expression network and functional annotation. From the expression and epigenetic profiles, 23 target genes (e.g., HAO1, ABCD3, and BLMH) were found to be hub genes that were regulated by both methylation and lncRNAs. We have provided comprehensive epigenetic and transcriptomic profiles on FLS in chicken, and the identification of key genes and epigenetic markers will expand our understanding of the molecular mechanism of chicken FLS.

scholarly journals Genome-wide profiling of miRNA expression patterns in tubal endometriosis

Reproduction ◽  
2019 ◽  
Vol 157 (6) ◽  
pp. 525-534 ◽  
Author(s):  
Hang Qi ◽  
Guiling Liang ◽  
Jin Yu ◽  
Xiaofeng Wang ◽  
Yan Liang ◽  
...  
Keyword(s):  
Pathway Analysis ◽  
Mirna Expression ◽  
Gene Networks ◽  
Target Genes ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Mirna Gene ◽  
Differentially Expressed ◽  
Signal Pathways ◽  
Differentially Expressed Mirnas

MicroRNA (miRNA) expression profiles in tubal endometriosis (EM) are still poorly understood. In this study, we analyzed the differential expression of miRNAs and the related gene networks and signaling pathways in tubal EM. Four tubal epithelium samples from tubal EM patients and five normal tubal epithelium samples from uterine leiomyoma patients were collected for miRNA microarray. Bioinformatics analyses, including Ingenuity Pathway Analysis (IPA), Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. Quantitative real-time polymerase chain reaction (qRT-PCR) validation of five miRNAs was performed in six tubal epithelium samples from tubal EM and six from control. A total of 17 significantly differentially expressed miRNAs and 4343 potential miRNA-target genes involved in tubal EM were identified (fold change >1.5 and FDR-adjustedPvalue <0.05). IPA indicated connections between miRNAs, target genes and other gynecological diseases like endometrial carcinoma. GO and KEGG analysis revealed that most of the identified genes were involved in the mTOR signaling pathway, SNARE interactions in vesicular transport and endocytosis. We constructed an miRNA-gene-disease network using target gene prediction. Functional analysis showed that the mTOR pathway was connected closely to tubal EM. Our results demonstrate for the first time the differentially expressed miRNAs and the related signal pathways involved in the pathogenesis of tubal EM which contribute to elucidating the pathogenic mechanism of tubal EM-related infertility.

scholarly journals Weighted gene co-expression network analysis to identify key modules and hub genes associated with paucigranulocytic asthma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Min Li ◽  
Wenye Zhu ◽  
Chu Wang ◽  
Yuanyuan Zheng ◽  
Shibo Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Immune Status ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Hub Genes

Abstract Background Asthma is a heterogeneous disease that can be divided into four inflammatory phenotypes: eosinophilic asthma (EA), neutrophilic asthma (NA), mixed granulocytic asthma (MGA), and paucigranulocytic asthma (PGA). While research has mainly focused on EA and NA, the understanding of PGA is limited. In this study, we aimed to identify underlying mechanisms and hub genes of PGA. Methods Based on the dataset from Gene Expression Omnibus(GEO), weighted gene coexpression network analysis (WGCNA), differentially expressed genes (DEGs) analysis and protein–protein interaction (PPI) network analysis were conducted to construct a gene network and to identify key gene modules and hub genes. Functional enrichment analyses were performed to investigate the biological process, pathways and immune status of PGA. The hub genes were validated in a separate dataset. Results Compared to non-PGA, PGA had a different gene expression pattern, in which 449 genes were differentially expressed. One gene module significantly associated with PGA was identified. Intersection between the differentially expressed genes (DEGs) and the genes from the module that were most relevant to PGA were mainly enriched in inflammation and immune response regulation. The single sample Gene Set Enrichment Analysis (ssGSEA) suggested a decreased immune infiltration and function in PGA. Finally six hub genes of PGA were identified, including ADCY2, CXCL1, FPRL1, GPR109B, GPR109A and ADCY3, which were validated in a separate dataset of GSE137268. Conclusions Our study characterized distinct gene expression patterns, biological processes and immune status of PGA and identified hub genes, which may improve the understanding of underlying mechanism and provide potential therapeutic targets for PGA.

scholarly journals Identification of potential biomarkers and candidate small molecule drugs in glioblastoma

2020 ◽  
Author(s):  
Wei-cheng Lu ◽  
Hui Xie ◽  
Ce Yuan ◽  
Jin-jiang Li ◽  
Zhao-yang Li ◽  
...  
Keyword(s):  
Protein Expression ◽  
Small Molecule ◽  
Molecular Mechanisms ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Hub Genes ◽  
Expression Levels ◽  
Small Molecule Drugs ◽  
Key Genes

Abstract Background and aims:Glioblastoma (GBM) is a common and aggressive primary brain tumor, and the prognosis for GBM patients remains poor. This study aimed to identify the key genes associated with the development of GBM and provide new diagnostic and therapies for GBM. Methods:Three microarray datasets (GSE111260, GSE103227, and GSE104267) were selected from Gene Expression Omnibus (GEO) database for integrated analysis. The differential expressed genes (DEGs) between GBM and normal tissues were identified. Then, prognosis-related DEGs were screened by survival analysis, followed by functional enrichment analysis. The protein-protein interaction (PPI) network was constructed to explore the hub genes associated with GBM. The mRNA and protein expression levels of hub genes were respectively validated in silico using The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases. Subsequently, the small molecule drugs of GBM were predicted by using Connectivity Map (CMAP) database. Results:A total of 78 prognosis-related DEGs were identified, of which10 hub genes with higher degree were obtained by PPI analysis. The mRNA expression and protein expression levels of CETN2, MKI67, ARL13B, and SETDB1 were overexpressed in GBM tissues, while the expression levels of CALN1, ELAVL3, ADCY3, SYN2, SLC12A5, and SOD1 were down-regulated in GBM tissues. Additionally, these genes were significantly associated with the prognosis of GBM. We eventually predicted the 10 most vital small molecule drugs, which potentially imitate or reverse GBM carcinogenic status. Cycloserine and 11-deoxy-16,16-dimethylprostaglandin E2 might be considered as potential therapeutic drugs of GBM. Conclusions:Our study provided 10 key genes for diagnosis, prognosis, and therapy for GBM. These findings might contribute to a better comprehension of molecular mechanisms of GBM development, and provide new perspective for further GBM research. However, specific regulatory mechanism of these genes needed further elaboration.

scholarly journals Integrated analysis of the proteome and transcriptome in human ischemic cardiomyopathy

2020 ◽  
Author(s):  
Kai Zhang ◽  
Xianyu Qin ◽  
Min Wu ◽  
Pengju Wen ◽  
Yueheng Wu ◽  
...  
Keyword(s):  
Ischemic Cardiomyopathy ◽  
Molecular Mechanisms ◽  
Left Ventricular ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Central Position ◽  
Mortality And Morbidity ◽  
Protein Levels ◽  
Data Independent Acquisition ◽  
Key Genes

Abstract Background: Ischemic cardiomyopathy (ICM) is the primary cause of heart failure, which leads to an unacceptable rate of mortality and morbidity. The molecular mechanisms involved in ICM remains incompletely understood. This study aimed to investigate the molecular mechanisms of ICM by integrated proteome and transcriptome analyses.Methods and Results: Data independent acquisition (DIA) mass spectrometry and RNA-seq technologies were performed in left ventricular species from 5 ICM patients and 5 unused non-failing donors. A total of 546 differentially expressed proteins (DEPs) and 1080 mRNAs (DEGs) were identified in ICM compared with control, which were mainly involved in inflammatory/immune response, response to stress (such as hypoxia and reactive oxidative species), oxidative stress, and ECM (extracellular matrix) organization. Moreover, though the low correlation between transcriptome and proteome, 41 key genes were identified, which showed the same expression directions at mRNA and protein levels. Among them, HSP90AA1 occupied a central position in the PPI network. Furthermore, a differentially expressed lncRNA-mRNA-protein network was constructed, which consisted of 13, 11, and 11 differentially expressed lncRNAs, mRNAs, and proteins, respectively, and the expression of this network were validated by qRT-PCR.Conclusion: This identified some key genes and a lncRNA-mRNA-protein regulatory network involved in ICM, which should provide a framework for an in-depth interrogation into the complex molecular mechanisms of ICM.

scholarly journals Integrated analysis of lncRNA and mRNA transcriptomes reveals the potential regulatory role of lncRNA in kiwifruit ripening and softening

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yiting Chen ◽  
Chunzhen Cheng ◽  
Xin Feng ◽  
Ruilian Lai ◽  
Minxia Gao ◽  
...  
Keyword(s):  
Noncoding Rna ◽  
Target Genes ◽  
Expression Patterns ◽  
Ethylene Biosynthesis ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Ethylene Response Factor ◽  
Acid Oxidase ◽  
Fruit Softening ◽  
Oxidase Gene

AbstractKiwifruit has gained increasing attention worldwide for its unique flavor and high nutritional value. Rapid softening after harvest greatly shortens its shelf-life and reduces the commercial value. Therefore, it is imperative and urgent to identify and clarify its softening mechanism. This study aimed to analyze and compare the long noncoding RNA (lncRNA) and mRNA expression patterns in ABA-treated (ABA) and room temperature (RT)-stored fruits with those in freshly harvested fruits (CK) as control. A total of 697 differentially expressed genes (DEGs) and 81 differentially expressed lncRNAs (DELs) were identified while comparing ABA with CK, and 458 DEGs and 143 DELs were detected while comparing RT with CK. The Kyoto Encyclopedia of Genes and Genomes analysis of the identified DEGs and the target genes of DELs revealed that genes involved in starch and sucrose metabolism, brassinosteroid biosynthesis, plant hormone signal transduction, and flavonoid biosynthesis accounted for a large part. The co-localization networks, including 38 DEGs and 31 DELs in ABA vs. CK, and 25 DEGs and 25 DELs in RT vs. CK, were also performed. Genes related to fruit ripening, such as genes encoding β-galactosidase, mannan endo-1,4-β-mannosidase, pectinesterase/pectinesterase inhibitor, and NAC transcription factor, were present in the co-localization network, suggesting that lncRNAs were involved in regulating kiwifruit ripening. Notably, several ethylene biosynthesis- and signaling-related genes, including one 1-aminocyclopropane-1-carboxylic acid oxidase gene and three ethylene response factor genes, were found in the co-localization network of ABA vs. CK, suggesting that the promoting effect of ABA on ethylene biosynthesis and fruit softening might be embodied by increasing the expression of these lncRNAs. These results may help understand the regulatory mechanism of lncRNAs in ripening and ABA-induced fruit softening of kiwifruit.

scholarly journals Integrated Gene Co-expression Analysis and Metabolites Profiling Highlight the Important Role of ZmHIR3 in Maize Resistance to Gibberella Stalk Rot

2021 ◽  
Vol 12 ◽  
Author(s):  
Yali Sun ◽  
Xinsen Ruan ◽  
Qing Wang ◽  
Yu Zhou ◽  
Fang Wang ◽  
...  
Keyword(s):  
Cell Death ◽  
Resistance Genes ◽  
Quantitative Trait ◽  
Molecular Mechanisms ◽  
Differentially Expressed ◽  
Joint Analysis ◽  
Hub Genes ◽  
Positive Role ◽  
Stalk Rot ◽  
Key Genes

Gibberella stalk rot (GSR) caused by Fusarium graminearum is one of the most devastating diseases causing significant yield loss of maize, and GSR resistance is a quantitative trait controlled by multiple genes. Although a few quantitative trait loci/resistance genes have been identified, the molecular mechanisms underlying GSR resistance remain largely unexplored. To identify potential resistance genes and to better understand the molecular mechanism of GSR resistance, a joint analysis using a comparative transcriptomic and metabolomic approaches was conducted using two inbred lines with contrasting GSR resistance, K09 (resistant) and A08 (susceptible), upon infection with F. graminearum. While a substantial number of differentially expressed genes associated with various defense-related signaling pathways were identified between two lines, multiple hub genes likely associated with GSR resistance were pinpointed using Weighted Gene Correlation Network Analysis and K-means clustering. Moreover, a core set of metabolites, including anthocyanins, associated with the hub genes was determined. Among the complex co-expression networks, ZmHIR3 showed strong correlation with multiple key genes, and genetic and histological studies showed that zmhir3 mutant is more susceptible to GSR, accompanied by enhanced cell death in the stem in response to infection with F. graminearum. Taken together, our study identified differentially expressed key genes and metabolites, as well as co-expression networks associated with distinct infection stages of F. graminearum. Moreover, ZmHIR3 likely plays a positive role in disease resistance to GSR, probably through the transcriptional regulation of key genes, functional metabolites, and the control of cell death.

scholarly journals Analyzing the interactions of circRNAs, miRNAs, and mRNAs to predict ceRNA networks in human acute type A aortic dissection

2019 ◽  
Author(s):  
maoxun huang ◽  
hulin piao ◽  
yong wang ◽  
weitie wang ◽  
bo li ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Critical Role ◽  
Type A ◽  
Integrated Analysis ◽  
Acute Type ◽  
Type A Aortic Dissection ◽  
Cerna Network ◽  
Key Genes

Abstract Background: Acute type A aortic dissection(ATAAD) is a life-threatening vascular disease. However, its underlying mechanism is still not well understood. Here, circular RNAs(circRNAs) were shown to function as competitive endogenous RNAs (ceRNAs) to regulate the effect of microRNAs(miRNAs) on their target genes may play a critical role in ATAAD. However, comprehensive identification and integrated analysis of the circRNA-miRNA-mRNA network in ATAAD have not been performed. Results: The gene expression profile of circRNAs, miRNAs, and mRNAs was performed between 6 ATAAD patients and 6 age-matched normal ascending aortic wall tissues patients were analyzed using the Arraystar human RNAs microarray. We identified that the expression of 12576 circRNAs,1603 miRNAs, and 14596 mRNAs were found to be differentially expressed(DE). Gene ontology(GO) and Kyoto Encyclopedia of Genes and Genomes pathway analyses(KEGG) were performed on these DE mRNAs and miRNA-mediated target genes of circRNAs. Furthermore, we used a multi-step computational framework and several bioinformatics methods to construct a ceRNA network containing circRNAs, miRNAs, and mRNAs based on co-expression analysis between the DE genes. The constructed ceRNA regulatory network containing 25 circRNAs, 17 miRNAs and 72 mRNAs. In the whole ceRNA network. We identified that plenty of key genes, such as hsa_circRNA_404522, hsa_circRNA_0022920, hsa_circ_0075881, hsa-miRNA1285-3p, hsa-miRNA-1285-3p, hsa-miRNA-637, hsa-miRNA-650, TINAGL1, JPH4, PLXNA2, TGFBR1, and THSD4. Furthermore, we also integrated the circRNA-miRNA-mRNA regulatory modules of the key genes. Conclusions: This study found a profile of dysregulated circRNAs, miRNA and mRNAs, and competitive circRNA-miRNA–mRNA regulatory networks were comprehensively integrated and predicted to be involved in ATAAD by GO and KEGG pathway analysis. It might be prospective clinical markers associated with ATAAD, and it is worthwhile to perform further studies to reveal the underlying link between these key genes and the molecular mechanisms of AD. Keywords：aortic dissection; circRNAs; miRNAs; mRNAs; ceRNA

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