scholarly journals Expression Analysis of Circular RNAs in Young and Sexually Mature Boar Testes

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1430
Author(s):  
Fei Zhang ◽  
Xiaodong Zhang ◽  
Wei Ning ◽  
Xiangdong Zhang ◽  
Zhenyuan Ru ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Enrichment Analysis ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Testicular Development ◽  
Adhesion Junctions ◽  
Camp Signaling Pathway ◽  
Stem Cell Pluripotency ◽  
Hormone Biosynthesis ◽  
Host Genes

Testicular development is critical for male animals’ reproduction and is tightly regulated by epigenetic factors. Circular RNAs (circRNAs) were recently identified in the testes of humans and bulls. However, the expression profile of circRNAs and their potential biological functions in boar testicular development remain unclear. We identified 34,521 and 31,803 circRNAs in piglet (30 d) and adult (210 d) boar testes by high-throughput sequencing, respectively. Bioinformatics analysis revealed that these circRNAs are widely distributed on autosomes and sex chromosomes. Some of the host genes can generate multiple circRNAs. A total of 2326 differentially expressed circRNAs (DECs) derived from 1526 host genes was found in testicular development, of which 1003 circRNAs were up-regulated in adult boar testes and 1323 circRNAs were down-regulated. Furthermore, gene ontology analysis of host genes of DECs revealed that these circRNAs are mainly involved in regulating spermatogenesis, cilia motility, and hormone biosynthesis. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that the DECs are markedly enriched to stem cell pluripotency regulation, tight junctions, adhesion junctions, and cAMP signaling pathway. These results indicate that circRNAs are abundantly expressed in boar testes and exhibit dynamic changes during testicular development.

scholarly journals Identification of Candidate Circular RNAs Underlying Intramuscular Fat Content in the Donkey

2020 ◽  
Vol 11 ◽  
Author(s):  
Bojiang Li ◽  
Chunyu Feng ◽  
Shiyu Zhu ◽  
Junpeng Zhang ◽  
David M. Irwin ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Intramuscular Fat ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Beta Oxidation ◽  
Longissimus Dorsi Muscle ◽  
And Function ◽  
Fatty Acid Beta Oxidation ◽  
Imf Content ◽  
Host Genes

Intramuscular fat (IMF) content is a crucial indicator of meat quality. Circular RNAs (circRNAs) are a large class of endogenous RNAs that are involved in many physiological processes. However, the expression and function of circRNA in IMF in the donkey remains unresolved. Here we performed an expression profiling of circRNAs in the donkey longissimus dorsi muscle and identified 12,727 candidate circRNAs. Among these, 70% were derived from the exons of protein genes. Furthermore, a total of 127 differentially expressed (DE) circRNAs were identified in high (H) and low (L) IMF content groups, including 63 upregulated and 64 downregulated circRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the host genes of the DE circRNAs showed that the host genes were enriched in lipid metabolism related GO terms (e.g., fatty acid beta-oxidation using acyl-CoA dehydrogenase and MLL3/4 complex), and signaling pathways (e.g., TGF-beta and lysine degradation signaling pathway). Further analyses indicated that 127 DE circRNAs were predicted to potentially interact with miRNAs, leading to the construction of circRNA-miRNA regulatory network. Multiple circRNAs can potentially function as sponges of miRNAs that regulate the differentiation of adipocytes. Our results provide valuable expression profile information for circRNA in the donkey and new insight into the regulatory mechanisms of circRNAs in the regulation of IMF content.

scholarly journals Identification of Differentially Expressed circRNAs, miRNAs, and Genes in Patients Associated with Cartilaginous Endplate Degeneration

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Haiwei Xu ◽  
Yongjin Li ◽  
Jianhua Li ◽  
Zhenxin Huo ◽  
Guowang Li ◽  
...  
Keyword(s):  
Experimental Studies ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Protein Protein Interaction ◽  
Global Challenge ◽  
Cartilaginous Endplate ◽  
Host Genes

Background. Intervertebral disc degeneration (IDD) disease is a global challenge because of its predominant pathogenic factor in triggering low back pain, whereas cartilaginous endplate degeneration (CEPD) is the main cause of IDD. Accumulating evidence have indicated that the differentially expressed microRNAs (DEMs) and differentially expressed genes (DEGs) have been determined to be involved in multiple biological processes to mediate CEPD progression. However, the differentially expressed circular RNAs (DECs) and their potential biofunctions in CEPD have not been identified. Methods. GSE153761 dataset was analyzed using R software to predict DECs, DEMs, and DEGs. Pathway enrichment analysis of DEGs and host genes of DECs and protein-protein interaction network of DEGs were conducted to explore their potential biofunctions. Furthermore, we explore the potential relationship between DEGs and DECs. Results. There were 74 DECs, 17 DEMs, and 68 DEGs upregulated whereas 50 DECs, 16 DEMs, and 67 DEGs downregulated in CEPD group. Pathway analysis unveiled that these RNAs might regulate CEPD via mediating inflammatory response, ECM metabolism, chondrocytes apoptosis, and chondrocytes growth. A total of 17 overlapping genes were predicted between the host genes of DEGs and DECs, such as SDC1 and MAOA. Moreover, 6 upregulated DECs, of which hsa_circ_0052830 was the most upregulated circRNA in CEPD, were derived from the host genes SDC1, whereas 8 downregulated DECs were derived from the host genes MAOA. Conclusion. This will provide novel clues for future experimental studies to elucidate the pathomechanism of CEPD and therapeutic targets for CEPD-related diseases.

Predicting functional circular RNA-based competitive endogenous RNA network in gastric carcinoma using novel bioinformatics analysis

2021 ◽  
pp. 153537022110487
Author(s):  
Zirui Zhu ◽  
Rui Huang ◽  
Baojun Huang
Keyword(s):  
Messenger Rna ◽  
Expression Profiles ◽  
Clinical Stage ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Rank Aggregation ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Competitive Endogenous Rna

Gastric cancer (GC) remains one of the most prevalent types of malignancies worldwide, and also one of the most reported lethal tumor-related diseases. Circular RNAs (circRNAs) have been certified to be trapped in multiple aspects of GC pathogenesis. Yet, the mechanism of this regulation is mostly undefined. This research is designed to discover the vital circRNA-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in GC. Expression profiles with diverse levels including circRNAs, miRNAs, and mRNAs were all determined using microarray public datasets from Gene Expression Ominous (GEO). The differential circRNAs expressions were recognized against the published robust rank aggregation algorithm. Besides, a circRNA-based competitive endogenous RNA (ceRNA) interaction network was visualized via Cytoscape software (version 3.8.0). Functional and pathway enrichment analysis associated with differentially expressed targeted mRNAs were conducted using Cytoscape and an online bioinformatics database. Furthermore, an interconnected protein–protein interaction association network which consisted of 51 mRNAs was predicted, and hub genes were screened using STRING and CytoHubba. Then, several hub genes were chosen to explore their expression associated with survival rate and clinical stage in GEPIA and Kaplan-Meier Plotter databases. Finally, a carefully designed circRNA-related ceRNA regulatory subnetwork including four circRNAs, six miRNAs, and eight key hub genes was structured using the online bioinformatics tool.

scholarly journals Identification of Potential Prognostic Competing Triplets in High-Grade Serous Ovarian Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Jian Zhao ◽  
Xiaofeng Song ◽  
Tianyi Xu ◽  
Qichang Yang ◽  
Jingjing Liu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
High Throughput Sequencing ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
P53 Signaling ◽  
Oocyte Meiosis ◽  
The Difference ◽  
Division Cell ◽  
The Impact

Increasing lncRNA-associated competing triplets were found to play important roles in cancers. With the accumulation of high-throughput sequencing data in public databases, the size of available tumor samples is becoming larger and larger, which introduces new challenges to identify competing triplets. Here, we developed a novel method, called LncMiM, to detect the lncRNA–miRNA–mRNA competing triplets in ovarian cancer with tumor samples from the TCGA database. In LncMiM, non-linear correlation analysis is used to cover the problem of weak correlations between miRNA–target pairs, which is mainly due to the difference in the magnitude of the expression level. In addition, besides the miRNA, the impact of lncRNA and mRNA on the interactions in triplets is also considered to improve the identification sensitivity of LncMiM without reducing its accuracy. By using LncMiM, a total of 847 lncRNA-associated competing triplets were found. All the competing triplets form a miRNA–lncRNA pair centered regulatory network, in which ZFAS1, SNHG29, GAS5, AC112491.1, and AC099850.4 are the top five lncRNAs with most connections. The results of biological process and KEGG pathway enrichment analysis indicates that the competing triplets are mainly associated with cell division, cell proliferation, cell cycle, oocyte meiosis, oxidative phosphorylation, ribosome, and p53 signaling pathway. Through survival analysis, 107 potential prognostic biomarkers are found in the competing triplets, including FGD5-AS1, HCP5, HMGN4, TACC3, and so on. LncMiM is available at https://github.com/xiaofengsong/LncMiM.

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 Investigating the Mechanism of Guizhi Fuling Formula in the Treatment of Primary Dysmenorrhea based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Lu Sun ◽  
Zining Wang ◽  
Jian Li ◽  
Li Xu ◽  
Xiaoou Xue
Keyword(s):  
Molecular Docking ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Primary Dysmenorrhea ◽  
Potential Mechanism ◽  
Protein Protein Interaction ◽  
Long Time ◽  
Hormone Biosynthesis ◽  
Relationship Of

Abstract Background: Primary dysmenorrhea(PD)is the most common gynecologic disorder.Despite the prevalence is high, it is often underdiagnosed,undertreated and normalized even by patients themselves. Guizhi Fuling Formula (GFF) is experientially used for the treatment of PD in a long time. Therefore, the efficiency and potential mechanism are waiting to identify.Methods: We adopted network pharmacology integrated molecular docking strategy in this study.Based on published literatures, the relative compounds of GFF were selected preliminarily. Secondly, the putative targets of PD were obtained by wide-searching DisGeNET, OMIM, Drugbank and GeneCards databases.With protein-protein interaction(PPI) analysis, GO and KEGG pathway enrichment analysis and molecular docking ,we systematically evaluated the relationship of herb ingredients and disease targets.Results: The results showed that 30 ingredients of GFF and 43 hub targets made a difference.Under the further analysis,8 targets(EGFR,AKT1,PTGS2,TNF,ESR1,AHR,CTNNB1,CXCL8) were recognized as key therapeutic targets with excellent binding. The enrichment analyses indicated that the GFF had the potential to influence varieties of biological pathways, especially the pathways in cancer and steroid hormone biosynthesis, which play an important part in the pathogenesis of primary dysmenorrhea.Conclusion: GFF influenced primary dysmenorrhea through the synergistic effect of multiple components, multiple targets, and multiple pathways.This study predictedthe potential mechanism, hope that could made contribution for clinical application and scientific research.

scholarly journals Identification and Characterization of Extrachromosomal Circular DNA in Human Placentas With Fetal Growth Restriction

2021 ◽  
Vol 12 ◽  
Author(s):  
Huan Yang ◽  
Jie He ◽  
Shuai Huang ◽  
Hongbing Yang ◽  
Qingjie Yi ◽  
...  
Keyword(s):  
Fetal Growth ◽  
Fetal Growth Restriction ◽  
Enrichment Analysis ◽  
Maternal Plasma ◽  
Growth Restriction ◽  
Formation Mechanisms ◽  
Pathway Enrichment Analysis ◽  
Circular Dnas ◽  
New Biomarkers ◽  
Host Genes

Many studies have confirmed that extrachromosomal circular DNAs (eccDNAs/ecDNAs) exist in tumor and normal cells independently of the chromosome and are essential for oncogene plasticity and drug resistance. Studies have confirmed that there are many eccDNAs/ecDNAs in maternal plasma derived from the fetus. Fetal growth restriction (FGR) is a pregnancy-related disease associated with high newborn morbidity and mortality. However, the characteristics and nature of eccDNAs/ecDNAs in FGR are poorly understood. This study aims to deconstruct the properties and potential functions of eccDNAs/ecDNAs in FGR. We performed circle-seq to identify the expression profile of eccDNAs/ecDNAs, analyzed by bioinformatics, and verified by real-time Polymerase Chain Reaction (PCR) combined with southern blot in FGR compared with the normal groups. A total of 45,131 eccDNAs/ecDNAs (including 2,118 unique ones) were identified, which had significantly higher abundance in FRG group than in normal group, and was bimodal in length, peaking at ~146bp and ~340bp, respectively. Gestational age may be one independent factor affecting the production of eccDNAs/ecDNAs, most of which come from genomic regions with high gene density, with a 4~12bp repeat around the junction, and their origin had a certain genetic preference. In addition, some of the host-genes overlapped with non-coding RNAs (ncRNAs) partially or even completely. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that host-genes on the differentially expressed eccDNAs/ecDNAs (DEEECs/DEECs) were mainly enriched in immune-related functions and pathways. The presence of some ecDNAs were verified, and whose variability were consistent with the circle-seq results. We identified and characterized eccDNAs/ecDNAs in placentas with FGR, and elucidated the formation mechanisms and the networks with ncRNAs, which provide a new vision for the screening of new biomarkers and therapeutic targets for FGR.

scholarly journals Identification of Key Genes and Pathways in SARS-CoV-2 Infection using Bioinformatics Analysis

2020 ◽  
Author(s):  
Zhe Wang ◽  
Chenhao Jiang ◽  
Xuxuan Zhang ◽  
Yingna Zhang ◽  
Yan Ren ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Expression Profiles ◽  
Severe Pneumonia ◽  
Enrichment Analysis ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Airway Epithelial ◽  
Hub Genes ◽  
Bioinformatics Analyses ◽  
Human Airway

Abstract Background: Coronavirus disease 2019 (COVID-19) is a disease that causes fatal disorders including severe pneumonia. Our study aimed to utilize bioinformatics method to analyze the expression profiling by high throughput sequencing in human bronchial organoids/primary human airway epithelial infected with SARS-CoV-2 to identify the potentially crucial genes and pathways associated with COVID-19.Methods: We analyzed microarray datasets GSE153970 and GSE150819 derived from the GEO database. Firstly, the Differentially expressed genes （DEGs） in human bronchial organoids/primary human airway epithelial infected with SARS-CoV-2. Next, the DEGs were used for GO and KEGG pathway enrichment analysis. Then, the PPI network was constructed and Cytoscape was used to find the key genes.Results: Gene expression profiles of GSE153970 and GSE150819, in all 12 samples were analyzed. A total of 145 DEGs and 5 hub genes were identified in SARS-CoV-2. Meanwhile, we found that the 145 genes are associated with immune responses and the top 5 hub genes including CXCL8, CXCL1, CXCL2, CCL20, and CSF2 were mainly related to leukocyte migration, endoplasmic reticulum lumen, receptor ligand activity. In addition, the results also showed that the hub genes were associated with Cytokine−cytokine receptor interaction, IL−17 signaling pathway, and Rheumatoid arthritis in SARS-CoV-2 infection.Conclusion: The five crucial genes consisting of CXCL8, CXCL1, CXCL2, CCL20, and CSF2 were considered as hub genes of SARS-CoV-2, which may be used as diagnostic biomarkers or molecular targets for the treatment of SARS-CoV-2. It is evidenced that bioinformatics analyses in SARS-CoV-2 can be useful for understanding the underlying molecular mechanism and exploring effective therapeutic targets.

scholarly journals Multiple Regulatory Networks Are Activated during Cold Stress in Medicago sativa L.

2018 ◽  
Vol 19 (10) ◽  
pp. 3169 ◽  
Author(s):  
Qiang Zhou ◽  
Dong Luo ◽  
Xutian Chai ◽  
Yuguo Wu ◽  
Yanrong Wang ◽  
...  
Keyword(s):  
Cold Stress ◽  
Medicago Sativa ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Sequencing Platform ◽  
Medicago Sativa L ◽  
Perennial Legume

Cultivated alfalfa (Medicago sativa L.) is one of the most important perennial legume forages in the world, and it has considerable potential as a valuable forage crop for livestock. However, the molecular mechanisms underlying alfalfa responses to cold stress are largely unknown. In this study, the transcriptome changes in alfalfa under cold stress at 4 °C for 2, 6, 24, and 48 h (three replicates for each time point) were analyzed using the high-throughput sequencing platform, BGISEQ-500, resulting in the identification of 50,809 annotated unigenes and 5283 differentially expressed genes (DEGs). Metabolic pathway enrichment analysis demonstrated that the DEGs were involved in carbohydrate metabolism, photosynthesis, plant hormone signal transduction, and the biosynthesis of amino acids. Moreover, the physiological changes of glutathione and proline content, catalase, and peroxidase activity were in accordance with dynamic transcript profiles of the relevant genes. Additionally, some transcription factors might play important roles in the alfalfa response to cold stress, as determined by the expression pattern of the related genes during 48 h of cold stress treatment. These findings provide valuable information for identifying and characterizing important components in the cold signaling network in alfalfa and enhancing the understanding of the molecular mechanisms underlying alfalfa responses to cold stress.

scholarly journals Small Nucleolar RNA and Small Nucleolar RNA Host Gene Signatures as Biomarkers for Pancreatic Cancer

2020 ◽  
Author(s):  
Shuwen Han ◽  
Yangyang Xie ◽  
Xi Yang ◽  
Siqi Dai ◽  
Xiaoyu Dai
Keyword(s):  
Pancreatic Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Small Nucleolar Rna ◽  
Cerna Network ◽  
Tcga Dataset ◽  
Nucleolar Rna ◽  
Host Genes

Abstract Objective: The objective of this study was to identify key molecules including small nucleolar RNAs (snoRNAs) and small nucleolar RNA host genes (SNHGs) involved in pancreatic cancer.Methods: First, we screened the differentially expressed snoRNAs (DEsnoRNAs) and trend-related snoRNAs based on the cancer genome atlas (TCGA) dataset for pancreatic cancer, and then performed methylation correlation analysis, survival analysis, and extraction of snoRNA host genes for Gene ontology (GO) functional and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Next, DESNHGs and trend-related SNHGs were screened according to the TCGA dataset for pancreatic cancer, and a competing endogenous RNA (ceRNA) network was constructed for pathway and functional enrichment analysis. Results: A total of eight DEsnoRNAs and 93 trend-related snoRNAs were extracted. Then, ten host genes of the snoRNAs were identified. Functional analysis suggested that the ten host genes were significantly enriched in several GO terms including mitotic chromosome condensation and endocytosis pathway. SNORA38B was considered to associate with survival and prognosis. The SNORD17 and SNORA11 were considered to negatively correlate with methylation. In addition, two trend-related SNHGs were extracted. Additionally, a ceRNA network was constructed with 11 miRNAs, one lncRNAs, and one mRNA. SNHG24 mainly correlated with GnRH secretion and neuroactive ligand-receptor interaction in pancreatic cancer. Conclusion: The identified snoRNAs and SNHGs could serve as potential markers for the early detection of pancreatic cancer.

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