scholarly journals Network Analyses Predict Small RNAs That Might Modulate Gene Expression in the Testis and Epididymis of Bos indicus Bulls

2021 ◽  
Vol 12 ◽  
Author(s):  
Andressa O. de Lima ◽  
Juliana Afonso ◽  
Janette Edson ◽  
Esteban Marcellin ◽  
Robin Palfreyman ◽  
...  
Keyword(s):  
Gene Expression ◽  
Small Rnas ◽  
Molecular Mechanisms ◽  
Bos Indicus ◽  
Male Gamete ◽  
Functional Enrichment ◽  
Pairwise Comparisons ◽  
Network Analyses ◽  
Germ Cell Differentiation ◽  
Network Cluster

Spermatogenesis relies on complex molecular mechanisms, essential for the genesis and differentiation of the male gamete. Germ cell differentiation starts at the testicular parenchyma and finishes in the epididymis, which has three main regions: head, body, and tail. RNA-sequencing data of the testicular parenchyma (TP), head epididymis (HE), and tail epididymis (TE) from four bulls (three biopsies per bull: 12 samples) were subjected to differential expression analyses, functional enrichment analyses, and co-expression analyses. The aim was to investigate the co-expression and infer possible regulatory roles for transcripts involved in the spermatogenesis of Bos indicus bulls. Across the three pairwise comparisons, 3,826 differentially expressed (DE) transcripts were identified, of which 384 are small RNAs. Functional enrichment analysis pointed to gene ontology (GO) terms related to ion channel activity, detoxification of copper, neuroactive receptors, and spermatogenesis. Using the regulatory impact factor (RIF) algorithm, we detected 70 DE small RNAs likely to regulate the DE transcripts considering all pairwise comparisons among tissues. The pattern of small RNA co-expression suggested that these elements are involved in spermatogenesis regulation. The 3,826 DE transcripts (mRNAs and small RNAs) were further subjected to co-expression analyses using the partial correlation and information theory (PCIT) algorithm for network prediction. Significant correlations underpinned the co-expression network, which had 2,216 transcripts connected by 158,807 predicted interactions. The larger network cluster was enriched for male gamete generation and had 15 miRNAs with significant RIF. The miRNA bta-mir-2886 showed the highest number of connections (601) and was predicted to down-regulate ELOVL3, FEZF2, and HOXA13 (negative co-expression correlations and confirmed with TargetScan). In short, we suggest that bta-mir-2886 and other small RNAs might modulate gene expression in the testis and epididymis, in Bos indicus cattle.

scholarly journals Identification of potential crucial genes and pathways associated with vein graft restenosis based on gene expression analysis in experimental rabbits

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4704 ◽  
Author(s):  
Qiang Liu ◽  
Xiujie Yin ◽  
Mingzhu Li ◽  
Li Wan ◽  
Liqiao Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Throughput ◽  
Vein Graft ◽  
Molecular Mechanisms ◽  
Rapid Development ◽  
Bypass Graft ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes ◽  
Network Analyses

Occlusive artery disease (CAD) is the leading cause of death worldwide. Bypass graft surgery remains the most prevalently performed treatment for occlusive arterial disease, and veins are the most frequently used conduits for surgical revascularization. However, the clinical efficacy of bypass graft surgery is highly affected by the long-term potency rates of vein grafts, and no optimal treatments are available for the prevention of vein graft restenosis (VGR) at present. Hence, there is an urgent need to improve our understanding of the molecular mechanisms involved in mediating VGR. The past decade has seen the rapid development of genomic technologies, such as genome sequencing and microarray technologies, which will provide novel insights into potential molecular mechanisms involved in the VGR program. Ironically, high throughput data associated with VGR are extremely scarce. The main goal of the current study was to explore potential crucial genes and pathways associated with VGR and to provide valid biological information for further investigation of VGR. A comprehensive bioinformatics analysis was performed using high throughput gene expression data. Differentially expressed genes (DEGs) were identified using the R and Bioconductor packages. After functional enrichment analysis of the DEGs, protein–protein interaction (PPI) network and sub-PPI network analyses were performed. Finally, nine potential hub genes and fourteen pathways were identified. These hub genes may interact with each other and regulate the VGR program by modulating the cell cycle pathway. Future studies focusing on revealing the specific cellular and molecular mechanisms of these key genes and pathways involved in regulating the VGR program may provide novel therapeutic targets for VGR inhibition.

scholarly journals Manifold learning analysis suggests strategies to align single-cell multimodal data of neuronal electrophysiology and transcriptomics

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jiawei Huang ◽  
Jie Sheng ◽  
Daifeng Wang
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Manifold Learning ◽  
Molecular Mechanisms ◽  
Single Cells ◽  
Cell Types ◽  
Functional Enrichment ◽  
Multimodal Data ◽  
Network Analyses ◽  
Manifold Alignment

AbstractRecent single-cell multimodal data reveal multi-scale characteristics of single cells, such as transcriptomics, morphology, and electrophysiology. However, integrating and analyzing such multimodal data to deeper understand functional genomics and gene regulation in various cellular characteristics remains elusive. To address this, we applied and benchmarked multiple machine learning methods to align gene expression and electrophysiological data of single neuronal cells in the mouse brain from the Brain Initiative. We found that nonlinear manifold learning outperforms other methods. After manifold alignment, the cells form clusters highly corresponding to transcriptomic and morphological cell types, suggesting a strong nonlinear relationship between gene expression and electrophysiology at the cell-type level. Also, the electrophysiological features are highly predictable by gene expression on the latent space from manifold alignment. The aligned cells further show continuous changes of electrophysiological features, implying cross-cluster gene expression transitions. Functional enrichment and gene regulatory network analyses for those cell clusters revealed potential genome functions and molecular mechanisms from gene expression to neuronal electrophysiology.

scholarly journals Detoxification and Immune Transcriptomic Response of the Gill Tissue of Bay Scallop (Argopecten irradians) Following Exposure to the Algicide Palmitoleic Acid

Biomolecules ◽  
2018 ◽  
Vol 8 (4) ◽  
pp. 139 ◽  
Author(s):  
Cheng Chi ◽  
Sib Giri ◽  
Jin Jun ◽  
Hyoun Kim ◽  
Sang Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cytochrome P450 ◽  
Palmitoleic Acid ◽  
Molecular Mechanisms ◽  
Functional Enrichment ◽  
Alexandrium Tamarense ◽  
Read Length ◽  
Related Factor ◽  
Transcriptomic Response ◽  
Bay Scallop

Palmitoleic acid (PA) is an effective algicide against Alexandrium tamarense. However, the toxicological mechanism of PA exposure is unclear. The transcript abundance and differentially expressed genes (DEGs) in gills of bay scallop were investigated following 80 mg/L PA exposure up to 48 h using the Illumina HiSeq 4000 deep-sequencing platform with the recommended read length of 100 bp. De novo assembly of paired-end reads yielded 62,099 unigenes; 5414 genes were identified as being significantly increased, and 4452 were decreased. Based on gene ontology classification and enrichment analysis, the ‘cellular process’, ‘metabolic process’, ‘response to stimulus’, and ‘catalytic process’ with particularly high functional enrichment were revealed. The DEGs, which are related to detoxification and immune responses, revealed that acid phosphatase, fibrinogen C domain-containing protein, cyclic AMP-responsive element-binding protein, glutathione reductase, ATP-binding cassette, nuclear factor erythroid 2-related factor, NADPH2:quinone reductase, and cytochrome P450 4F22, 4B1, and 2C8-related gene expression decreased. In contrast, some genes related to glutathione S-transferase, C-type lectin, superoxide dismutase, toll-like receptors, and cytochrome P450 2C14, 2U1, 3A24 and 4A2 increased. The results of current research will be a valuable resource for the investigation of gene expression stimulated by PA, and will help understanding of the molecular mechanisms underlying the scallops’ response to PA exposure.

scholarly journals Identifcation of The Ferroptosis-Related Gene Signature In Placenta of Patients With Early-Onset Preeclampsia

2021 ◽  
Author(s):  
Nana Yang ◽  
Qianghua Wang ◽  
Biao Ding ◽  
Yinging Gong ◽  
Yue Wu ◽  
...  
Keyword(s):  
Iron Homeostasis ◽  
Molecular Mechanisms ◽  
Late Onset ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Network Analyses

Abstract Background: The accumulation of ROS resulting from upregulated levels of oxidative stress is commonly implicated in preeclampsia (PE). Ferroptosis is a novel form of iron-dependent cell death instigated by lipid peroxidation likely plays important role in PE pathogenesis. This study aims to investigate expression profiles and functions of the ferroptosis-related genes (FRGs) in early- and late-onset preeclampsia.Methods: The gene expression data and clinical information were downloaded from GEO database. The “limma” R package was used for screening differentially expressed genes. GO(Gene Ontology), Kyoto Encyclopedia of Genes and Genomes(KEGG) and protein protein interaction (PPI) network analyses were conducted to investigate the bioinformatics functions and molecular interactions of significantly different FRGs. Quantitative real-time reverse transcriptase PCR was used to verify the expression of hub FRGs in PE.Results: A total number of 4,215 DEGs were identified between EOPE and preterm cases and 3,356 DEGs were found between EOPE and LOPE subtypes. 20 significantly different FRGs were identified in EOPE, while only 3 in LOPE. Functional enrichment analysis revealed that the differentially expressed FRGs was mainly involved in EOPE and enriched in hypoxia- and iron-related pathways, such as response to hypoxia, iron homeostasis and iron ion binding process. The PPI network analysis and verification by RT-qPCR resulted in the identification of the following six interesting FRGs: FTH1, HIF1A, FTL, IREB2, MAPK8 and PLIN2. Conclusions: EOPE and LOPE owned distinct underlying molecular mechanisms and ferroptosis may be mainly implicated in pathogenesis of EOPE. Further studies are necessary for deeper inquiry into placental ferroptosis and its role in the pathogenesis of EOPE.

Identification of Four Key Biomarkers and Small Molecule Drugs Innasopharyngeal Carcinoma by Weighted Gene Co-expression Network Analysis

2020 ◽  
Author(s):  
Xi Pan ◽  
Jian-Hao Liu
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Small Molecule ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Tumor Stage ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Therapeutic Goals ◽  
Small Molecule Drugs

Abstract Background Nasopharyngeal carcinoma (NPC) is a heterogeneous carcinoma that the underlying molecular mechanisms involved in the tumor initiation, progression, and migration are largely unclear. The purpose of the present study was to identify key biomarkers and small-molecule drugs for NPC screening, diagnosis, and therapy via gene expression profile analysis. Methods Raw microarray data of NPC were retrieved from the Gene Expression Omnibus (GEO) database and analyzed to screen out the potential differentially expressed genes (DEGs). The key modules associated with histology grade and tumor stage was identified by using weighted correlation network analysis (WGCNA). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of genes in the key module were performed to identify potential mechanisms. Candidate hub genes were obtained, which based on the criteria of module membership (MM) and high connectivity. Then we used receiver operating characteristic (ROC) curve to evaluate the diagnostic value of hub genes. The Connectivity map database was further used to screen out small-molecule drugs of hub genes. Results A total of 430 DEGs were identified based on two GEO datasets. The green gene module was considered as key module for the tumor stage of NPC via WGCNA analysis. The results of functional enrichment analysis revealed that genes in the green module were enriched in regulation of cell cycle, p53 signaling pathway, cell part morphogenesis. Furthermore, four DEGs-related hub genes in the green module were considered as the final hub genes. Then ROC revealed that the final four hub genes presented with high areas under the curve, suggesting these hub genes may be diagnostic biomarkers for NPC. Meanwhile, we screened out several small-molecule drugs that have provided potentially therapeutic goals for NPC. Conclusions Our research identified four potential prognostic biomarkers and several candidate small-molecule drugs for NPC, which may contribute to the new insights for NPC therapy.

scholarly journals Analysis of potential genetic biomarkers and molecular mechanism of smoking-related postmenopausal osteoporosis using weighted gene co-expression network analysis and machine learning

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257343
Author(s):  
Shaoshuo Li ◽  
Baixing Chen ◽  
Hao Chen ◽  
Zhen Hua ◽  
Yang Shao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Network Analysis ◽  
Postmenopausal Osteoporosis ◽  
Molecular Mechanism ◽  
Molecular Mechanisms ◽  
Functional Enrichment ◽  
Support Vector ◽  
Hub Genes ◽  
Genetic Biomarkers

Objectives Smoking is a significant independent risk factor for postmenopausal osteoporosis, leading to genome variations in postmenopausal smokers. This study investigates potential biomarkers and molecular mechanisms of smoking-related postmenopausal osteoporosis (SRPO). Materials and methods The GSE13850 microarray dataset was downloaded from Gene Expression Omnibus (GEO). Gene modules associated with SRPO were identified using weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) analysis, and pathway and functional enrichment analyses. Feature genes were selected using two machine learning methods: support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF). The diagnostic efficiency of the selected genes was assessed by gene expression analysis and receiver operating characteristic curve. Results Eight highly conserved modules were detected in the WGCNA network, and the genes in the module that was strongly correlated with SRPO were used for constructing the PPI network. A total of 113 hub genes were identified in the core network using topological network analysis. Enrichment analysis results showed that hub genes were closely associated with the regulation of RNA transcription and translation, ATPase activity, and immune-related signaling. Six genes (HNRNPC, PFDN2, PSMC5, RPS16, TCEB2, and UBE2V2) were selected as genetic biomarkers for SRPO by integrating the feature selection of SVM-RFE and RF. Conclusion The present study identified potential genetic biomarkers and provided a novel insight into the underlying molecular mechanism of SRPO.

scholarly journals Chronic adolescent exposure to cannabis in mice leads to long-term sex-biased changes in gene expression networks across brain regions

2021 ◽  
Author(s):  
Yanning Zuo ◽  
Attilio Iemolo ◽  
Patricia Montilla-Perez ◽  
Hai-Ri Li ◽  
Xia Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Brain Regions ◽  
Human Cognition ◽  
Genome Wide Association Studies ◽  
Cognitive Behaviors ◽  
Network Analyses ◽  
With Memory ◽  
Adolescent Exposure

Background: The molecular mechanisms underlying the long-lasting behavioral changes associated with adolescent cannabis use are poorly understood. To this end, we performed gene network analyses of multiple brain regions in adult mice exposed during the entire adolescence to Delta-9-tetrahydrocannabinol (THC), the major psychoactive component of cannabis. Methods: Two weeks after the last exposure to THC (10 mg/kg) or vehicle, we measured cognitive behaviors and profiled the transcriptomes of 5 brain regions from 12 female and 12 male mice. We performed differential gene expression analysis and constructed gene coexpression networks (modules) to identify THC-induced transcriptional alterations at the level of individual genes, gene networks, and biological pathways. We integrated the THC-correlated modules with human traits from genome-wide association studies to identify potential regulators of disease-associated networks. Results: THC impaired cognitive behaviors of mice, with memory being more impacted in females than males, which coincided with larger transcriptional changes in the female brain. Modules involved in endocannabinoid signaling and inflammation were correlated with memory deficits in the female dorsal medial striatum and ventral tegmental area, respectively. Converging pathways related to dopamine signaling and addiction were altered in the female amygdala and male nucleus accumbens. Moreover, the connectivity map of THC-correlated modules uncovered intra- and inter-region molecular circuitries influenced by THC. Lastly, modules altered by THC were enriched in genes relevant for human cognition and neuropsychiatric disorders. Conclusions: These findings provide novel insights concerning the genes, pathways and brain regions underlying persistent behavioral deficits induced by adolescent exposure to THC in a sex-specific manner.

Validation of novel hub genes and molecular mechanisms in acute lung injury using an integrative bioinformatics approach

2021 ◽  
Author(s):  
Qingchun Liang ◽  
Qin Zhou ◽  
Jinhe Li ◽  
Zhugui Chen ◽  
Zhihao Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Lung Injury ◽  
Lung Injury ◽  
Molecular Mechanisms ◽  
Molecular Biomarkers ◽  
Functional Enrichment ◽  
Lung Injury Score ◽  
Control Group ◽  
High Morbidity ◽  
Hub Genes

Abstract Acute lung injury (ALI) is an inflammatory pulmonary disease that can easily develop into serious acute respiratory distress syndrome, which has high morbidity and mortality. However, the molecular mechanism of ALI remains unclear, and few molecular biomarkers for diagnosis and treatment have been identified. In this study, we aimed to identify novel molecular biomarkers using a bioinformatics approach. Gene expression data were obtained from the Gene Expression Omnibus database, co-expressed differentially expressed genes (CoDEGs) were identified using R software, and further functional enrichment analyses were conducted using the online tool Database for Annotation, Visualization, and Integrated Discovery. A protein–protein interaction network was established using the STRING database and Cytoscape software. Lipopolysaccharide (LPS)-induced ALI mouse model was constructed and verified. The hub genes were screened and validated in vivo. The transcription factors (TFs) and miRNAs associated with the hub genes were predicted using the NetworkAnalyst database. In total, 71 CoDEGs were screened and found to be mainly involved in the cytokine–cytokine receptor interactions, and the tumor necrosis factor and malaria signaling pathways. Animal experiments showed that the lung injury score, bronchoalveolar lavage fluid protein concentration, and wet-to-dry weight ratio were higher in the LPS group than those in the control group. Real-time polymerase chain reaction analysis indicated that most of the hub genes such as colony-stimulating factor 2 (Csf2) were overexpressed in the LPS group. A total of 20 TFs including nuclear respiratory factor 1 (NRF1) and two miRNAs were predicted to be regulators of the hub genes. In summary, Csf2 may serve as a novel diagnostic and therapeutic target for ALI. NRF1 and mmu-mir-122-5p may be key regulators in the development of ALI.

scholarly journals 17β-Estradiol regulates cyclin A1 and cyclin B1 gene expression in adult rat seminiferous tubules

2011 ◽  
Vol 48 (2) ◽  
pp. 89-97 ◽  
Author(s):  
Camille Bois ◽  
Christelle Delalande ◽  
Hélène Bouraïma-Lelong ◽  
Philippe Durand ◽  
Serge Carreau
Keyword(s):  
Gene Expression ◽  
Male Gamete ◽  
Cyclin B1 ◽  
Seminiferous Tubules ◽  
Cyclin A1 ◽  
Adult Rat ◽  
Germ Cell Differentiation ◽  
Estrogen Synthesis ◽  
B1 Gene ◽  
17Β Estradiol

Spermatogenesis, which is the fundamental mechanism allowing male gamete production, is controlled by several factors, and among them, estrogens are likely concerned. In order to enlighten the potential role of estrogen in rat spermatogenesis, seminiferous tubules (ST) from two groups of seminiferous epithelium stages (II–VIII and IX–I) were treated with either 17β-estradiol (E2) agonists or antagonists for estrogen receptors (ESRs). In this study, we show that cyclin A1 and cyclin B1 gene expression is controlled by E2at a concentration of 10−9 M only in stages IX–I. This effect is mimicked by a treatment with the G-protein coupled estrogen receptor (GPER) agonist G1 and is abolished by treatment with the ESR antagonist ICI 182 780. Moreover, using letrozole, a drug that blocks estrogen synthesis, we demonstrate that these genes are under the control of E2within rat ST. Thus, germ cell differentiation may be regulated by E2which acts through ESRs and GPER, expressed in adult rat ST.

scholarly journals Genome-wide methylation and expression analyses reveal the epigenetic landscape of immune-related diseases for tobacco smoking

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Ying Mao ◽  
Peng Huang ◽  
Yan Wang ◽  
Maiqiu Wang ◽  
Ming D. Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cigarette Smoke ◽  
Tobacco Smoking ◽  
Molecular Mechanisms ◽  
Functional Enrichment ◽  
Chronic Obstructive ◽  
Rna Seq ◽  
Immune System Diseases ◽  
Genome Wide ◽  
A Genome

Abstract Background Smoking is a major causal risk factor for lung cancer, chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), and is the main preventable cause of deaths in the world. The components of cigarette smoke are involved in immune and inflammatory processes, which may increase the prevalence of cigarette smoke-related diseases. However, the underlying molecular mechanisms linking smoking and diseases have not been well explored. This study was aimed to depict a global map of DNA methylation and gene expression changes induced by tobacco smoking and to explore the molecular mechanisms between smoking and human diseases through whole-genome bisulfite sequencing (WGBS) and RNA-sequencing (RNA-seq). Results We performed WGBS on 72 samples (36 smokers and 36 nonsmokers) and RNA-seq on 75 samples (38 smokers and 37 nonsmokers), and cytokine immunoassay on plasma from 22 males (9 smokers and 13 nonsmokers) who were recruited from the city of Jincheng in China. By comparing the data of the two groups, we discovered a genome-wide methylation landscape of differentially methylated regions (DMRs) associated with smoking. Functional enrichment analyses revealed that both smoking-related hyper-DMR genes (DMGs) and hypo-DMGs were related to synapse-related pathways, whereas the hypo-DMGs were specifically related to cancer and addiction. The differentially expressed genes (DEGs) revealed by RNA-seq analysis were significantly enriched in the “immunosuppression” pathway. Correlation analysis of DMRs with their corresponding gene expression showed that genes affected by tobacco smoking were mostly related to immune system diseases. Finally, by comparing cytokine concentrations between smokers and nonsmokers, we found that vascular endothelial growth factor (VEGF) was significantly upregulated in smokers. Conclusions In sum, we found that smoking-induced DMRs have different distribution patterns in hypermethylated and hypomethylated areas between smokers and nonsmokers. We further identified and verified smoking-related DMGs and DEGs through multi-omics integration analysis of DNA methylome and transcriptome data. These findings provide us a comprehensive genomic map of the molecular changes induced by smoking which would enhance our understanding of the harms of smoking and its relationship with diseases.

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