LncRNA SNHG8 is identified as a key regulator of acute myocardial infarction by RNA-seq analysis

Abstract Background Long noncoding RNAs (lncRNAs) are involved in numerous physiological functions. However, their mechanisms in acute myocardial infarction (AMI) are not well understood. Methods We performed an RNA-seq analysis to explore the molecular mechanism of AMI by constructing a lncRNA-miRNA-mRNA axis based on the ceRNA hypothesis. The target microRNA data were used to design a global AMI triple network. Thereafter, a functional enrichment analysis and clustering topological analyses were conducted by using the triple network. The expression of lncRNA SNHG8, SOCS3 and ICAM1 was measured by qRT-PCR. The prognostic values of lncRNA SNHG8, SOCS3 and ICAM1 were evaluated using a receiver operating characteristic (ROC) curve. Results An AMI lncRNA-miRNA-mRNA network was constructed that included two mRNAs, one miRNA and one lncRNA. After RT-PCR validation of lncRNA SNHG8, SOCS3 and ICAM1 between the AMI and normal samples, only lncRNA SNHG8 had significant diagnostic value for further analysis. The ROC curve showed that SNHG8 presented an AUC of 0.850, while the AUC of SOCS3 was 0.633 and that of ICAM1 was 0.594. After a pairwise comparison, we found that SNHG8 was statistically significant (PSNHG8-ICAM1 = 0.002; PSNHG8-SOCS3 = 0.031). The results of a functional enrichment analysis of the interacting genes and microRNAs showed that the shared lncRNA SNHG8 may be a new factor in AMI. Conclusions Our investigation of the lncRNA-miRNA-mRNA regulatory networks in AMI revealed a novel lncRNA, lncRNA SNHG8, as a risk factor for AMI and expanded our understanding of the mechanisms involved in the pathogenesis of AMI.

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An integrated analysis of mRNAs, lncRNAs, and miRNAs based on weighted gene co-expression network analysis involved in bovine endometritis

Scientific Reports ◽

10.1038/s41598-021-97319-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Negin Sheybani ◽

Mohammad Reza Bakhtiarizadeh ◽

Abdolreza Salehi

Keyword(s):

Network Analysis ◽

Protein Interactions ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Biological Pathways ◽

Functional Enrichment ◽

Integrated Analysis ◽

Rna Seq

AbstractIn dairy cattle, endometritis is a severe infectious disease that occurs following parturition. It is clear that genetic factors are involved in the etiology of endometritis, however, the molecular pathogenesis of endometritis is not entirely understood. In this study, a system biology approach was used to better understand the molecular mechanisms underlying the development of endometritis. Forty transcriptomic datasets comprising of 20 RNA-Seq (GSE66825) and 20 miRNA-Seq (GSE66826) were obtained from the GEO database. Next, the co-expressed modules were constructed based on RNA-Seq (Rb-modules) and miRNA-Seq (mb-modules) data, separately, using a weighted gene co-expression network analysis (WGCNA) approach. Preservation analysis was used to find the non-preserved Rb-modules in endometritis samples. Afterward, the non-preserved Rb-modules were assigned to the mb-modules to construct the integrated regulatory networks. Just highly connected genes (hubs) in the networks were considered and functional enrichment analysis was used to identify the biological pathways associated with the development of the disease. Furthermore, additional bioinformatic analysis including protein–protein interactions network and miRNA target prediction were applied to enhance the reliability of the results. Thirty-five Rb-modules and 10 mb-modules were identified and 19 and 10 modules were non-preserved, respectively, which were enriched in biological pathways related to endometritis like inflammation and ciliogenesis. Two non-preserved Rb-modules were significantly assigned to three mb-modules and three and two important sub-networks in the Rb-modules were identified, respectively, including important mRNAs, lncRNAs and miRNAs genes like IRAK1, CASP3, CCDC40, CCDC39, ZMYND10, FOXJ1, TLR4, IL10, STAT3, FN1, AKT1, CD68, ENSBTAG00000049936, ENSBTAG00000050527, ENSBTAG00000051242, ENSBTAG00000049287, bta-miR-449, bta-miR-484, bta-miR-149, bta-miR-30b and bta-miR-423. The potential roles of these genes have been previously demonstrated in endometritis or related pathways, which reinforced putative functions of the suggested integrated regulatory networks in the endometritis pathogenesis. These findings may help further elucidate the underlying mechanisms of bovine endometritis.

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HEMGN and SLC2A1 might be potential diagnostic biomarkers of steroid-induced osteonecrosis of femoral head: study based on WGCNA and DEGs screening

BMC Musculoskeletal Disorders ◽

10.1186/s12891-021-03958-7 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Zhixin Wu ◽

Yinxian Wen ◽

Guanlan Fan ◽

Hangyuan He ◽

Siqi Zhou ◽

...

Keyword(s):

Femoral Head ◽

Roc Curve ◽

Enrichment Analysis ◽

Diagnostic Value ◽

Functional Enrichment ◽

Pathway Enrichment Analysis ◽

Overlapping Genes ◽

Hub Genes ◽

Diagnostic Biomarkers ◽

Key Genes

Abstract Background Steroid-induced osteonecrosis of the femoral head (SONFH) is a chronic and crippling bone disease. This study aims to reveal novel diagnostic biomarkers of SONFH. Methods The GSE123568 dataset based on peripheral blood samples from 10 healthy individuals and 30 SONFH patients was used for weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) screening. The genes in the module related to SONFH and the DEGs were extracted for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Genes with |gene significance| > 0.7 and |module membership| > 0.8 were selected as hub genes in modules. The DEGs with the degree of connectivity ≥5 were chosen as hub genes in DEGs. Subsequently, the overlapping genes of hub genes in modules and hub genes in DEGs were selected as key genes for SONFH. And then, the key genes were verified in another dataset, and the diagnostic value of key genes was evaluated by receiver operating characteristic (ROC) curve. Results Nine gene co-expression modules were constructed via WGCNA. The brown module with 1258 genes was most significantly correlated with SONFH and was identified as the key module for SONFH. The results of functional enrichment analysis showed that the genes in the key module were mainly enriched in the inflammatory response, apoptotic process and osteoclast differentiation. A total of 91 genes were identified as hub genes in the key module. Besides, 145 DEGs were identified by DEGs screening and 26 genes were identified as hub genes of DEGs. Overlapping genes of hub genes in the key module and hub genes in DEGs, including RHAG, RNF14, HEMGN, and SLC2A1, were further selected as key genes for SONFH. The diagnostic value of these key genes for SONFH was confirmed by ROC curve. The validation results of these key genes in GSE26316 dataset showed that only HEMGN and SLC2A1 were downregulated in the SONFH group, suggesting that they were more likely to be diagnostic biomarkers of SOFNH than RHAG and RNF14. Conclusions Our study identified that two key genes, HEMGN and SLC2A1, might be potential diagnostic biomarkers of SONFH.

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Demethylation alters transcriptome profiling of buds and leaves in ‘Kyoho’ grape

BMC Plant Biology ◽

10.1186/s12870-020-02754-0 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Haoran Jia ◽

Zibo Zhang ◽

Ehsan Sadeghnezhad ◽

Qianqian Pang ◽

Shangyun Li ◽

...

Keyword(s):

Gene Expression ◽

Regulatory Networks ◽

Epigenetic Modification ◽

Deep Understanding ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Glutathione Metabolism ◽

Endogenous Factors

Abstract Background Grape buds and leaves are directly associated with the physiology and metabolic activities of the plant, which is monitored by epigenetic modifications induced by environment and endogenous factors. Methylation is one of the epigenetic regulators that could be involved in DNA levels and affect gene expression in response to stimuli. Therefore, changes of gene expression profile in leaves and bud through inhibitors of DNA methylation provide a deep understanding of epigenetic effects in regulatory networks. Results In this study, we carried out a transcriptome analysis of ‘Kyoho’ buds and leaves under 5-azacytidine (5-azaC) exposure and screened a large number of differentially expressed genes (DEGs). GO and KEGG annotations showed that they are mainly involved in photosynthesis, flavonoid synthesis, glutathione metabolism, and other metabolic processes. Functional enrichment analysis also provided a holistic perspective on the transcriptome profile when 5-azaC bound to methyltransferase and induced demethylation. Enrichment analysis of transcription factors (TFs) also showed that the MYB, C2H2, and bHLH families are involved in the regulation of responsive genes under epigenetic changes. Furthermore, hormone-related genes have also undergone significant changes, especially gibberellin (GA) and abscisic acid (ABA)-related genes that responded to bud germination. We also used protein-protein interaction network to determine hub proteins in response to demethylation. Conclusions These findings provide new insights into the establishment of molecular regulatory networks according to how methylation as an epigenetic modification alters transcriptome patterns in bud and leaves of grape.

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Integrated DNA Methylation and Gene Expression Analysis Identified S100A8 and S100A9 in the Pathogenesis of Obesity

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.631650 ◽

2021 ◽

Vol 8 ◽

Author(s):

Ningyuan Chen ◽

Liu Miao ◽

Wei Lin ◽

Donghua Zou ◽

Ling Huang ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Mrna Expression ◽

Regulatory Networks ◽

Enrichment Analysis ◽

Microarray Dataset ◽

Functional Enrichment Analysis ◽

Normal Subjects ◽

Functional Enrichment ◽

Differentially Methylated Genes

Background: To explore the association of DNA methylation and gene expression in the pathology of obesity.Methods: (1) Genomic DNA methylation and mRNA expression profile of visceral adipose tissue (VAT) were performed in a comprehensive database of gene expression in obese and normal subjects. (2) Functional enrichment analysis and construction of differential methylation gene regulatory networks were performed. (3) Validation of the two different methylation sites and corresponding gene expression was done in a separate microarray dataset. (4) Correlation analysis was performed on DNA methylation and mRNA expression data.Results: A total of 77 differentially expressed mRNAs matched with differentially methylated genes. Analysis revealed two different methylation sites corresponding to two unique genes—s100a8-cg09174555 and s100a9-cg03165378. Through the verification test of two interesting different expression positions [differentially methylated positions (DMPs)] and their corresponding gene expression, we found that methylation in these genes was negatively correlated to gene expression in the obesity group. Higher S100A8 and S100A9 expressions in obese subjects were validated in a separate microarray dataset.Conclusion: This study confirmed the relationship between DNA methylation and gene expression and emphasized the important role of S100A8 and S100A9 in the pathogenesis of obesity.

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Identification of associated molecular events in Helicobacter pylori infection and gastric cancer through integrated computational analysis of Microarray and RNA-Seq datasets

10.21203/rs.3.rs-1189424/v1 ◽

2021 ◽

Author(s):

Sabaoon Zeb ◽

Rehan Zafar Paracha ◽

Maryum Nisar ◽

Rimsha Khalid ◽

Zartasha Mustansar ◽

...

Keyword(s):

Gastric Cancer ◽

Helicobacter Pylori ◽

Cancer Progression ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

World Health ◽

Separate Analysis ◽

Rna Seq ◽

Molecular Events

Abstract According to the World Health Organization, Gastric cancer (GC) is the third leading cause of death worldwide, where, the major precursor of cancer progression is infection with Helicobacter pylori. It has been reported that 50% of the total populace is infected with H.pylori, while in 80% the ulcer emerges in later stages of the infection. Although extensive separate analysis has been performed on H.pylori infection and GC data, however, there is a need to perform comparative analysis to identify the cross-talk between the conditions and to hunt significant molecular events that occurs during H.pylori induced GC. The aim of this multi-population study was to identify common molecular events and potential bio-markers against H.pylori induced GC. We performed microarray and RNA-seq analysis on publicly available H.pylori infection, gastritis, H.pylori induced GC and GC datasets to obtain Differentially Expressed Genes (DEGs). After obtaining the DEGs, integrative analysis, functional enrichment analysis and network biology approaches were utilized to identify common markers and hub genes between various disease conditions. Functional enrichment analysis revealed the DEGs of H.pylori infection, gastritis, H.pylori induced GC and GC were strongly associated with spliceosome, adherens junction, focal adhesion and ribosome. Being one of the common DEG, and highly interactive hub protein in the networks of all the conditions, translationally controlled tumour protein (TPT1) was identified as a significant predictive biomarker for early prognosis and diagnosis of H.pylori induced GC. Therefore, the mechanisms behind TPT1 should be further studied using in vitro cell-based functional assays, to determine its role in the progression of H.pylori induced GC.

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A Novel Three-miRNA Signature Identified Using Bioinformatics Predicts Survival in Esophageal Carcinoma

BioMed Research International ◽

10.1155/2020/5973082 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

KunZhe Wu ◽

ChunDong Zhang ◽

Cheng Zhang ◽

DongQiu Dai

Keyword(s):

Growth Factor ◽

Esophageal Carcinoma ◽

Target Genes ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Rna Seq ◽

Mirna Signature ◽

Cox Regression Analysis ◽

Ppi Networks

Objective. We identified differentially expressed microRNAs (DEMs) between esophageal carcinoma (ESCA) tissues and normal esophageal tissues. We then constructed a novel three-miRNA signature to predict the prognosis of ESCA patients using bioinformatics analysis. Materials and Methods. We combined two microarray profiling datasets from the Gene Expression Omnibus (GEO) database and RNA-seq datasets from the Cancer Genome Atlas (TCGA) database to analyze DEMs in ESCA. The clinical data from 168 ESCA patients were selected from the TCGA database to assess the prognostic role of the DEMs. The TargetScan, miRDB, miRWalk, and DIANA websites were used to predict the miRNA target genes. Functional enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery (David), and protein-protein interaction (PPI) networks were obtained using the Search Tool for the Retrieval of Interacting Genes database (STRING). Results. With cut-off criteria of P<0.05 and |log2FC| > 1.0, 33 overlapping DEMs, including 27 upregulated and 6 downregulated miRNAs, were identified from GEO microarray datasets and TCGA RNA-seq count datasets. The Kaplan–Meier survival analysis indicated that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) was significantly associated with the overall survival of ESCA patients. The results of univariate and multivariate Cox regression analysis showed that the three-miRNA signature was a potential prognostic factor in ESCA. Furthermore, the gene functional enrichment analysis revealed that the target genes of the three miRNAs participate in various cancer-related pathways, including viral carcinogenesis, forkhead box O (FoxO), vascular endothelial growth factor (VEGF), human epidermal growth factor receptor 2 (ErbB2), and mammalian target of rapamycin (mTOR) signaling pathways. In the PPI network, three target genes (MAPK1, RB1, and CLTC) with a high degree of connectivity were selected as hub genes. Conclusions. Our results revealed that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) is a potential novel prognostic biomarker for ESCA.

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GLRX5 as a Differential Diagnosis Marker for Kashin-Beck Disease and Osteoarthritis and Its Clinical Significance

10.21203/rs.3.rs-971437/v1 ◽

2021 ◽

Author(s):

Qinglong Wang ◽

Zhe Zhao ◽

Wantao Wang ◽

Zhipeng Huang ◽

Wenbo Wang

Keyword(s):

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

R Package ◽

Diagnostic Value ◽

Functional Enrichment ◽

Pathway Enrichment Analysis ◽

Diagnostic Biomarkers ◽

Non Invasive ◽

Gene Correlation ◽

Beck Disease

Abstract Background: Kashin-Beck disease (KBD) is currently an endemic form of osteoarthritis. In this study, we explored novel KBD diagnostic biomarkers.Methods: The GSE59446 dataset was used to conduct Weighted Gene Co-expression Network Analysis (WGCNA) and differentially expressed genes (DEGs) analysis with peripheral blood samples of 100 healthy individuals and 100 KBD patients. As part of the gene ontology pathway enrichment analysis, genes related to SONFH and DEGs were selected from the extraction module. Then, central DEGs were selected for LASSO analysis, and, based on SVM-RFE and DEG results, overlapping genes were identified as key KBD genes. Next, we analyzed the correlations between the selected genes and age, gender, and other factors to eliminate their influences on gene expression. Finally, we evaluated the diagnostic value of key KBD genes using case information collected by us.Results: Seven gene co-expression modules were created using WGCNA. The turquoise module was identified as a KBD key module since it showed the highest correlation to KBD. The functional enrichment analysis revealed that the genes associated with this key module were mainly involved in mitochondrial reactions, protein heterooligomerization, and negatively regulating cysteine-type endopeptidase-dependent apoptotic processes. Additionally, 12 key genes were identified using the LASSO analysis, 5 major genes using SVM-RFE analysis, and 36 DEGs were screened through the "limma" R package. The GLRX5 gene - pivotal in DEGs, LASSO, and SVM-RFE - was further aggregated as the key KBD gene. Correlation analyses confirmed the GLRX5 diagnostic value for KBD and that it was not related to age, gender, and other factors. Finally, data from our patients demonstrated that GLRX5 can be a KBD diagnostic biomarker.Conclusions: We demonstrated that the target gene GLRX5 can be a KBD non-invasive diagnosis biomarker.

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Genome-wide phylogenetic analysis, expression pattern, and transcriptional regulatory network of the pig C/EBP gene family

10.21203/rs.3.rs-96827/v1 ◽

2020 ◽

Author(s):

Chaoxin Zhang ◽

Tao Wang ◽

Shengwei Liu ◽

Bing Zhang ◽

Xue Li ◽

...

Keyword(s):

Phylogenetic Analysis ◽

Regulatory Network ◽

Target Genes ◽

Transcriptional Regulatory Network ◽

Expression Patterns ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Rna Seq ◽

Group I

Abstract Background: The vertebrate C/EBP transcription factors regulate many important biological processes, such as cell proliferation, differentiation, signal transduction, inflammation, and energy metabolism. The first C/EBP protein was identified in rat liver nuclei. Development of sequencing technology resulted in identification of the C/EBP genes in various species. In this study, a bioinformatics approach was used to determine the distribution of the members of the C/EBP family in vertebrates. A phylogenetic tree was constructed to analyze the C/EBP genes in vertebrates. Based on RNA-seq data, the expression patterns of pig C/EBP members in various tissues were analyzed. In addition, a gene transcription regulatory network was constructed with pig C/EBP members as the core.Results: We identified a total of 92 C/EBP genes in 17 vertebrate genomes. Phylogenetic analysis showed that all C/EBP TFs were classified into two groups; group I contained C/EBPβ TFs, and group II contained the remaining C/EBP TFs. The C/EBPα, C/EBPβ, C/EBPδ, C/EBPγ, and C/EBPζ genes were expressed ubiquitously with inconsistent expression patterns in various tissues. Moreover, a pig C/EBP regulatory network was constructed, including C/EBP genes, TFs, and miRNAs. A total of 39 FFL motifs were detected in the pig C/EBP regulatory network. Based on the RNA-seq data, gene expression patterns related to this FFL sub-network were analyzed in 27 adult Duroc tissues. Certain FFL motifs may be tissue specific. Functional enrichment analysis indicated that C/EBP and its target genes are involved in many important biological pathways. Conclusions: These results provide valuable information that clarifies the evolutionary relationships of the C/EBP family and contributes to the understanding of the biological function of C/EBP genes.

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Association of Circulating, Inflammatory-Response Exosomal mRNAs With Acute Myocardial Infarction

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.712061 ◽

2021 ◽

Vol 8 ◽

Author(s):

Guo-dong He ◽

Yu-qing Huang ◽

Lin Liu ◽

Jia-yi Huang ◽

Kenneth Lo ◽

...

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Inflammatory Response ◽

Immune Cell ◽

Stable Coronary Artery Disease ◽

Enrichment Analysis ◽

Cell Types ◽

Diagnostic Value ◽

Acute Inflammatory Response ◽

Clinical Value

Background: Although many cardiovascular disease studies have focused on the microRNAs of circulating exosomes, the profile and the potential clinical diagnostic value of plasma exosomal long RNAs (exoLRs) are unknown for acute myocardial infarction (AMI).Methods: In this study, the exoLR profile of 10 AMI patients, eight stable coronary artery disease (CAD) patients, and 10 healthy individuals was assessed by RNA sequencing. Bioinformatic approaches were used to investigate the characteristics and potential clinical value of exoLRs.Results: Exosomal mRNAs comprised the majority of total exoLRs. Immune cell types analyzed by CIBERSORT showed that neutrophils and monocytes were significantly enriched in AMI patients, consistent with clinical baseline values. Biological process enrichment analysis and co-expression network analysis demonstrated neutrophil activation processes to be enriched in AMI patients. Furthermore, two exosomal mRNAs, ALPL and CXCR2, were identified as AMI biomarkers that may be useful for evaluation of the acute inflammatory response mediated by neutrophils.Conclusions: ExoLRs were assessed in AMI patients and found to be associated with the acute inflammatory response mediated by neutrophils. Exosomal mRNAs, ALPL and CXCR2, were identified as potentially useful biomarkers for the study of AMI.

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Integrated Analysis of lncRNA and mRNA Reveals Novel Insights into Wool Bending in Zhongwei Goat

Animals ◽

10.3390/ani11113326 ◽

2021 ◽

Vol 11 (11) ◽

pp. 3326

Author(s):

Xiaobo Li ◽

Zhanfa Liu ◽

Shaohui Ye ◽

Yue Liu ◽

Qian Chen ◽

...

Keyword(s):

Signaling Pathway ◽

Target Genes ◽

Economic Value ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Hair Follicles ◽

Functional Enrichment ◽

Integrated Analysis ◽

Rna Seq ◽

Camp Signaling Pathway

Chinese Zhongwei goat is a rare and precious fur breed as its lamb fur is a well-known fur product. Wool bending of lamb fur of the Zhongwei goat is its most striking feature. However, the curvature of the wool decreases gradually with growth, which significantly affects its quality and economic value. The mechanism regulating the phenotypic changes of hair bending is still unclear. In the present study, the skin tissues of Zhongwei goats at 45 days (curving wool) and 108 days (slight-curving wool) after birth were taken as the research objects, and the expression profiling of long non-coding RNAs (lncRNAs) and mRNAs were analyzed based on the Ribo Zero RNA sequencing (RNA-seq) method. In total, 46,013 mRNAs and 13,549 lncRNAs were identified, of which 352 were differentially expressed mRNAs and 60 were. lncRNAs. Functional enrichment analysis of the target genes of lncRNAs were mainly enriched in PI3K-Akt, Arachidonic acid metabolic, cAMP, Wnt, and other signaling pathways. The qRT-PCR results of eight selected lncRNAs and target genes were consistent with the sequencing result, which indicated our data were reliable. Through the analysis of the weighted gene co-expression network, 13 co-expression modules were identified. The turquoise module contained a large number of differential expressed lncRNAs, which were mainly enriched in the PI3K-Akt signaling pathway and cAMP signaling pathway. The predicted LOC102172600 and LOC102191729 might affect the development of hair follicles and the curvature of wool by regulating the target genes. Our study provides novel insights into the potential roles of lncRNAs in the regulation of wool bending. In addition, the study offers a theoretical basis for further study of goat wool growth, so as to be a guidance and reference for breeding and improvement in the future.

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