scholarly journals Global DNA methylation pattern involved in the modulation of differentiation potential of adipogenic and myogenic precursors in skeletal muscle of pigs

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin Zhang ◽  
Wenjuan Sun ◽  
Linjuan He ◽  
Liqi Wang ◽  
Kai Qiu ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Dna Methylation ◽  
Signaling Pathway ◽  
Myogenic Differentiation ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Methylation Pattern ◽  
Pathway Enrichment Analysis ◽  
Differentiation Potential ◽  
Muscle Homeostasis

Abstract Background Skeletal muscle is a complex and heterogeneous tissue accounting for approximately 40% of body weight. Excessive ectopic lipid accumulation in the muscle fascicle would undermine the integrity of skeletal muscle in humans but endow muscle with marbling-related characteristics in farm animals. Therefore, the balance of myogenesis and adipogenesis is of great significance for skeletal muscle homeostasis. Significant DNA methylation occurs during myogenesis and adipogenesis; however, DNA methylation pattern of myogenic and adipogenic precursors derived from skeletal muscle remains unknown yet. Methods In this study, reduced representation bisulfite sequencing was performed to analyze genome-wide DNA methylation of adipogenic and myogenic precursors derived from the skeletal muscle of neonatal pigs. Integrated analysis of DNA methylation and transcription profiles was further conducted. Based on the results of pathway enrichment analysis, myogenic precursors were transfected with CACNA2D2-overexpression plasmids to explore the function of CACNA2D2 in myogenic differentiation. Results As a result, 11,361 differentially methylated regions mainly located in intergenic region and introns were identified. Furthermore, 153 genes with different DNA methylation and gene expression level between adipogenic and myogenic precursors were characterized. Subsequently, pathway enrichment analysis revealed that DNA methylation programing was involved in the regulation of adipogenic and myogenic differentiation potential through mediating the crosstalk among pathways including focal adhesion, regulation of actin cytoskeleton, MAPK signaling pathway, and calcium signaling pathway. In particular, we characterized a new role of CACNA2D2 in inhibiting myogenic differentiation by suppressing JNK/MAPK signaling pathway. Conclusions This study depicted a comprehensive landmark of DNA methylome of skeletal muscle-derived myogenic and adipogenic precursors, highlighted the critical role of CACNA2D2 in regulating myogenic differentiation, and illustrated the possible regulatory ways of DNA methylation on cell fate commitment and skeletal muscle homeostasis.

scholarly journals Global transcriptomic analysis reveals Lnc-ADAMTS9 exerting an essential role in myogenesis through modulating the ERK signaling pathway

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Liqi Wang ◽  
Ting He ◽  
Xin Zhang ◽  
Yubo Wang ◽  
Kai Qiu ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Signaling Pathway ◽  
Essential Role ◽  
Myogenic Differentiation ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Differentially Expressed ◽  
Farm Animals ◽  
Erk Signaling ◽  
Intracellular Ca

Abstract Background Long non-coding RNAs (lncRNAs) are emerging key regulators involved in a variety of biological processes such as cell differentiation and development. The balance between myogenesis and adipogenesis is crucial for skeletal muscle homeostasis in humans and meat quality in farm animals. The present study aimed to reveal the global transcriptomic profiles of adipogenic (Adi-) and myogenic (Myo-) precursors derived from porcine skeletal muscle and identify lncRNAs involved in the modulation of myogenesis homeostasis in porcine skeletal muscle. Results In this study, a total of 655 novel individual lncRNAs including differentially expressed 24 lncRNAs, and 755 differentially expressed mRNAs were identified (fold change ≥2 or ≤ 0.5 and adjusted P < 0.05). Integrated results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis accompanied by the variation of intracellular Ca2+ concentration highlighted Lnc-ADAMTS9 involved in the modulation of myogenesis homeostasis in porcine skeletal muscle. Although Lnc-ADAMTS9 knock-down did not alter the mRNA expression of ADAMTS9, we demonstrated that Lnc-ADAMTS9 can promote myogenic proliferation and myogenic differentiation of myogenic precursors through inhibiting the ERK/MAPK signaling pathway. Conclusion We deciphered a comprehensive catalog of mRNAs and lncRNAs that might be involved in the regulation of myogenesis and adipogenesis homeostasis in the skeletal muscle of pigs. The Lnc-ADAMTS9 exerts an essential role in myogenesis through the ERK signaling pathway.

Characterization of Methylation Patterns in Diffuse Large B Cell Lymphoma By Genome-Wide Methylation Analysis

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1243-1243
Author(s):  
Fengyi Zhao ◽  
Lei Zhang ◽  
Yan Qin ◽  
Ming-Zhe Han ◽  
Xiaohong Han ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Signaling Pathway ◽  
Methylation Level ◽  
Enrichment Analysis ◽  
B Cell Lymphoma ◽  
Mapk Signaling ◽  
Mapk Signaling Pathway ◽  
Pathway Enrichment Analysis ◽  
Ffpe Tissues ◽  
Methylation Patterns

Background: Diffuse large B cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma worldwide. Although the reference standard for identifying of the cell types is considered of gene expression profiling (GEP). But immunohistochemistry (IHC) is the most common method commercially available. The purpose of this study was to characterize the circulating cell-free DNA (cfDNA) methylation profile in DLBCL and to compare this profile with methylation observed in formalin fixed paraffin-embedded (FFPE) tissues. Additional efforts were made to correlate the observed methylation patterns with prognostic analysis and selected clinical features. Methods: The cfDNA and DNA of FFPE were extracted from 72 patients and 39 patients respectively. We assessed DNA methylation from plasma samples obtained from 29 individuals with GCB DLBCL at the time before treatment along with 43 samples of non-GCB DLBCL as controls. DNA from FFPE tissues were extracted from 11 individuals of GCB DLBCL and 28 individuals with non-GCB DLBCL. DNA methylation was analyzed with the Infinium MethylationEPIC BeadChip that quantitatively measures the methylation levels of more than 850,000 CpG sites across the genome. M values were used for visualization and intuitive interpretation of the results. Moreover, pathway enrichment analysis was performed with the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database. Results: We found a total of 207 significant differentional differentially methylated positions (DMPs) of cfDNA between the GCB and non-GCB groups, identified with a p value of 0.001 (Fig. 1A). Of these, 65 presented at least 10% (|Δbeta| > 0.1) difference in the methylation level between GCB and non-GCB. 29 (44.6%) were found hypermethylated in GCB DLBCL, while 36 (55.4%) appeared hypomethylated (Fig. 1B). The distribution of the DMPs identified according to their location relative to CpG islands (CGI) were represented in Fig. 1C. Unsupervised clustering performed on DNA methylation values for the 207 DMPs identified is presented in Fig. 1D. These results highlight the differences between GCB and non-GCB samples. There are 1549 significant DMPs of DNA from FFPE between the GCB and non-GCB groups, identified with a p value of 0.001 (Fig. 1E). Of these, 1512 presented at least 10% (|Δbeta| > 0.1) difference in the methylation level between GCB and non-GCB . 1370 (90.6%) were found hypermethylated in GCB DLBCL, while 142 (9.4%) appeared hypomethylated (Fig. 1F). The distribution of the DMPs identified according to their location relative to CpG islands (CGI) were represented in Fig. 1G. Unsupervised clustering performed on DNA methylation values for the 1549 DMPs identified is presented in Fig. 1H. These results highlight the differences between GCB and non-GCB in FFPE samples which according with that in serum. The KEGG pathway enrichment analysis of DNA from FFPE tissue methylation revealed that the process "PI3K/Akt, Ras, MAPK signaling pathway" and "Human papillomavirus infection" are likely major contributors to Hans pathological type. In addition, the enrichment analysis of cfDNA methylation revealed that the process "MAPK signaling pathway" is likely the most important factor. Furthermore, we also have analyzed the methylation level between refractory or relapsed (R/R) DLBCL patients and individuals with a good prognosis. The differential methylation patterns were also found both in serums and FFPE tissues. Conclusions: The DNA methylation differs in GCB and non-GCB DLBCL patients. MAPK signaling pathway plays an important role in it. The mechanism needs to be further explored. Figure 1 Disclosures No relevant conflicts of interest to declare.

scholarly journals Comprehensive circRNA Expression Profile and Construction of circRNAs-Related ceRNA Network in a Mouse Model of Autism

2021 ◽  
Vol 11 ◽  
Author(s):  
Ji Wang ◽  
Zhongxiu Yang ◽  
Canming Chen ◽  
Yang Xu ◽  
Hongguang Wang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Expression Profile ◽  
Enrichment Analysis ◽  
Notch Signaling Pathway ◽  
Mapk Signaling ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Common Disease ◽  
Cerna Network

Autism is a common disease that seriously affects the quality of life. The role of circular RNAs (circRNAs) in autism remains largely unexplored. We aimed to detect the circRNA expression profile and construct a circRNA-based competing endogenous RNA (ceRNA) network in autism. Valproate acid was used to establish an in vivo model of autism in mice. A total of 1,059 differentially expressed circRNAs (477 upregulated and 582 downregulated) in autism group was identified by RNA sequencing. The expression of novel_circ_015779 and novel_circ_035247 were detected by real-time PCR. A ceRNA network based on altered circRNAs was established, with 9,715 nodes and 150,408 edges. Module analysis was conducted followed by GO and KEGG pathway enrichment analysis. The top three modules were all correlated with autism-related pathways involving “TGF-beta signaling pathway,” “Notch signaling pathway,” “MAPK signaling pathway,” “long term depression,” “thyroid hormone signaling pathway,” etc. The present study reveals a novel circRNA involved mechanisms in the pathogenesis of autism.

scholarly journals Uncovering the Mechanisms and Molecular Targets of Weibing Formula 1 against Gastritis: Coupling Network Pharmacology with GEO Database

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Ke Chen ◽  
Luojian Zhang ◽  
Zhen Qu ◽  
Feng Wan ◽  
Jia Li ◽  
...  
Keyword(s):  
Real Time ◽  
Signaling Pathway ◽  
Quantitative Pcr ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Gene Expression Omnibus ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Real Time Quantitative Pcr

Weibing Formula 1, a classic traditional formula, has been widely used clinically to treat gastritis in recent years. However, the potential pharmacological mechanism of Weibing Formula 1 is still unclear to date. A network pharmacology-based strategy was performed to uncover the underlying mechanisms of Weibing Formula 1 against gastritis. Furthermore, we structured the drug-active ingredients-genes–disease network and PPI network of shared targets, and function enrichment analysis of these targets was carried out. Ultimately, Gene Expression Omnibus (GEO) datasets and real-time quantitative PCR were used to verify the related genes. We found 251 potential targets corresponding to 135 bioactive components of Weibing Formula 1. Then, 327 gastritis-related targets were known gastritis-related targets. Among which, 60 common targets were shared between potential targets of Weibing Formula 1 and known gastritis-related targets. The results of pathway enrichment analysis displayed that 60 common targets mostly participated in various pathways related to Toll-like receptor signaling pathway, MAPK signaling pathway, cytokine-cytokine receptor interaction pathway, chemokine signaling pathway, and apoptosis. Based on the GSE60427 dataset, 15 common genes were shared between differentially expressed genes and 60 candidate targets. The verification results of the GSE5081 dataset showed that except for DUOX2 and VCAM1, the other 13 genes were significantly upregulated in gastritis, which was consistent with the results in the GSE60427 dataset. More importantly, real-time quantitative PCR results showed that the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly upregulated and NOS2, EGFR, and IL-10 were downregulated in gastritis patients, while the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly downregulated and NOS2, EGFR, and IL-10 were upregulated after the treatment of Weibing Formula 1. PTGS2, NOS2, EGFR, MMP9, CXCL2, CXCL8, and IL-10 may be the important direct targets of Weibing Formula 1 in gastritis treatment. Our study revealed the mechanism of Weibing Formula 1 in gastritis from an overall and systematic perspective, providing a theoretical basis for further knowing and application of this formula in the future.

scholarly journals Exploring the Pharmacological Mechanism of Duhuo Jisheng Decoction in Treating Osteoporosis Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Zhencheng Xiong ◽  
Can Zheng ◽  
Yanan Chang ◽  
Kuankuan Liu ◽  
Li Shu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds ◽  
Treatment Of Osteoporosis ◽  
Target Proteins

Objective. The purpose of this work is to study the mechanism of action of Duhuo Jisheng Decoction (DHJSD) in the treatment of osteoporosis based on the methods of bioinformatics and network pharmacology. Methods. In this study, the active compounds of each medicinal ingredient of DHJSD and their corresponding targets were obtained from TCMSP database. Osteoporosis was treated as search query in GeneCards, MalaCards, DisGeNET, Therapeutic Target Database (TTD), Comparative Toxicogenomics Database (CTD), and OMIM databases to obtain disease-related genes. The overlapping targets of DHJSD and osteoporosis were identified, and then GO and KEGG enrichment analysis were performed. Cytoscape was employed to construct DHJSD-compounds-target genes-osteoporosis network and protein-protein interaction (PPI) network. CytoHubba was utilized to select the hub genes. The activities of binding of hub genes and key components were confirmed by molecular docking. Results. 174 active compounds and their 205 related potential targets were identified in DHJSD for the treatment of osteoporosis, including 10 hub genes (AKT1, ALB, IL6, MAPK3, VEGFA, JUN, CASP3, EGFR, MYC, and EGF). Pathway enrichment analysis of target proteins indicated that osteoclast differentiation, AGE-RAGE signaling pathway in diabetic complications, Wnt signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, JAK-STAT signaling pathway, calcium signaling pathway, and TNF signaling pathway were the specifically major pathways regulated by DHJSD against osteoporosis. Further verification based on molecular docking results showed that the small molecule compounds (Quercetin, Kaempferol, Beta-sitosterol, Beta-carotene, and Formononetin) contained in DHJSD generally have excellent binding affinity to the macromolecular target proteins encoded by the top 10 genes. Conclusion. This study reveals the characteristics of multi-component, multi-target, and multi-pathway of DHJSD against osteoporosis and provides novel insights for verifying the mechanism of DHJSD in the treatment of osteoporosis.

scholarly journals Bioinformatics Analysis of the Regulatory lncRNA-miRNA-mRNA Network in Patients with Neuropathic Pain

2020 ◽  
Author(s):  
Huai-Gen Zhang ◽  
Li Liu ◽  
Zhi-Ping Song ◽  
Da-Ying Zhang
Keyword(s):  
Neuropathic Pain ◽  
Signaling Pathway ◽  
Interaction Analysis ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Biological Information ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interaction ◽  
Potential Therapeutic Application

Abstract Background: Neuropathic pain (NP) is the main form of chronic pain, caused by damage to the nervous system and dysfunction. Methods: Here, we explore the key molecules involved in the development of NP condition via identification of lncRNA-miRNA-mRNA expression pattern of patients with NP. We identified differentially expressed miRNAs, lncRNA and mRNA through a comprehensive analysis strategy. Subsequently, we used bioinformatics approach to perform pathway enrichment analysis on DEGs and protein-protein interaction analysis. Combined with the three datasets, the lncRNA-miRNA-mRNA network was constructed. It will then be used as targets for drug prediction. Results: The results showed that a total of 8,251 DEGs (4,193 upregulated and 4,058 downregulated) were identified from the three microarray datasets, 959 DEmiRs (455 upregulated and 504 downregulated), 2,848 DElncs (1,324 upregulated and 1,524 downregulated). GO analysis showed that DEGs are mainly enriched in blood circulation, regulation of membrane potential and regulation of ion transmembrane transport. KEGG results showed that DEGs are enriched in neuroactive ligand-receptor interaction, PI3K-Akt signaling pathway and MAPK signaling pathway. When the correlation is set to above 0.8, a total of 31 lncRNAs, 36 miRNAs and 24 mRNAs were screened in the lncRNA-miRNA-mRNAs network. The results of drug prediction indicated the targeted drugs mainly include INDOMETHACIN, GLUTAMIC ACID and PIRACETAM. Conclusion: The lncRNA-miRNA-mRNA network has been carried out a comprehensive biological information analysis and predicted the potential therapeutic application of drugs in patients with NP. The corresponding data has a certain reference for studying the pathological mechanism of NP.

scholarly journals CDR1as related miRNA-mRNA networks in differentiating goat skeletal muscle satellite cells

2020 ◽  
Author(s):  
Bismark Kyei ◽  
Li Li ◽  
Liu Yang ◽  
Siyuan Zhan ◽  
Juntao Li ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Signaling Pathway ◽  
Satellite Cells ◽  
Muscle Development ◽  
Myogenic Differentiation ◽  
Mapk Signaling ◽  
Circular Rnas ◽  
Messenger Rnas ◽  
Muscle Satellite Cells ◽  
Skeletal Muscle Satellite Cells

Abstract Background: Myogenesis is a complex process controlled by several coding and non-coding RNAs (ncRNAs) such as circular RNAs (circRNAs) that well-known function as endogenous microRNAs (miRNAs) sponges. Over the past few years, numerous circRNAs have been known and their roles in biological processes have begun to be understood. Cerebellar Degeneration-Related protein 1 antisense (CDR1as), the most spotlighted circRNA as miR-7 sponge that has been blooming circRNAs’ research for a decade, and can potentially sponge several miRNAs in disease and muscle physiology. Nevertheless, the linear-RNAs-differed character that the acute interventions for circRNAs do not affect miRNAs levels, and has retarded the transcriptome-wide discovery of miRNAs sponged by. Therefore, the purpose of this study was to provide the transcriptomic effect of CDR1as during muscle differentiation.Methods: siCDR1as and siDICER1 were transfected into goat skeletal muscle satellite cells (SMSCs). RNA-seq technology and bioinformatics tools were used to analyze genes that are deregulated by siCDR1as and siDICER1. quantitative PCR was used to verify the expression levels of the differentially expressed mRNAs and miRNAs. Results: Here, to systematically identify miRNAs targeting CDR1as, we employed the critical enzyme DICER1 that governs the biogenesis of miRNAs. The deficiency of either DICER1 or CDR1as inhibited myogenic differentiation of SMSCs, and knockdown of DICER1 decreased the expression of CDR1as. Moreover, we screened for the targeted messenger RNAs (mRNAs) and miRNAs in SMSCs transfected with siDICER1 or siCDR1as respectively and found out that some well-known muscle-related pathways such as phosphoinositide 3-kinase (PI3K)-AKT signaling pathway, Rap1 signaling pathway, and MAPK signaling pathway were enriched in all groups. Further, regarding the miRNAs identified in siDICER1 and siCDR1as together with the sequence complementary information, we identified 11 miRNAs including miR-1, miR-206, and miR-27a-5p which are more likely to be novel targets for CDR1as. Conclusion: In summary, our study provides a perspective on the potential functions and relationship between CDR1as and DICER1 during muscle development.

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.

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