UbiNet 2.0: a verified, classified, annotated and updated database of E3 ubiquitin ligase–substrate interactions

Abstract Ubiquitination is an important post-translational modification, which controls protein turnover by labeling malfunctional and redundant proteins for proteasomal degradation, and also serves intriguing non-proteolytic regulatory functions. E3 ubiquitin ligases, whose substrate specificity determines the recognition of target proteins of ubiquitination, play crucial roles in ubiquitin–proteasome system. UbiNet 2.0 is an updated version of the database UbiNet. It contains 3332 experimentally verified E3–substrate interactions (ESIs) in 54 organisms and rich annotations useful for investigating the regulation of ubiquitination and the substrate specificity of E3 ligases. Based on the accumulated ESIs data, the recognition motifs in substrates for each E3 were also identified and a functional enrichment analysis was conducted on the collected substrates. To facilitate the research on ESIs with different categories of E3 ligases, UbiNet 2.0 performed strictly evidence-based classification of the E3 ligases in the database based on their mechanisms of ubiquitin transfer and substrate specificity. The platform also provides users with an interactive tool that can visualize the ubiquitination network of a group of self-defined proteins, displaying ESIs and protein–protein interactions in a graphical manner. The tool can facilitate the exploration of inner regulatory relationships mediated by ubiquitination among proteins of interest. In summary, UbiNet 2.0 is a user-friendly web-based platform that provides comprehensive as well as updated information about experimentally validated ESIs and a visualized tool for the construction of ubiquitination regulatory networks available at http://awi.cuhk.edu.cn/~ubinet/index.php.

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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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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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Integrated analysis of the expression, involved functions, and regulatory network of RUNX3 in melanoma

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207324666210816121833 ◽

2021 ◽

Vol 24 ◽

Author(s):

Yanxin Liu ◽

Zhang Feng ◽

Huaxia Chen

Keyword(s):

Protein Interactions ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Differentially Expressed ◽

Integrated Analysis ◽

Protein Protein Interactions ◽

Nf Kappab ◽

Microarray Datasets

Background: As a tumor suppressor or oncogenic gene, abnormal expression of RUNX family transcription factor 3 (RUNX3) has been reported in various cancers. Introduction: This study aimed to investigate the role of RUNX3 in melanoma. Methods: The expression level of RUNX3 in melanoma tissues was analyzed by immunohistochemistry and the Oncomine database. Based on microarray datasets GSE3189 and GSE7553, differentially expressed genes (DEGs) in melanoma samples were screened, followed by functional enrichment analysis. Gene Set Enrichment Analysis (GSEA) was performed for RUNX3. DEGs that co-expressed with RUNX3 were analyzed, and the transcription factors (TFs) of RUNX3 and its co-expressed genes were predicted. The protein-protein interactions (PPIs) for RUNX3 were analyzed utilizing the GeneMANIA database. MicroRNAs (miRNAs) that could target RUNX3 expression, were predicted. Results : RUNX3 expression was significantly up-regulated in melanoma tissues. GSEA showed that RUNX3 expression was positively correlated with melanogenesis and melanoma pathways. Eleven DEGs showed significant co-expression with RUNX3 in melanoma, for example, TLE4 was negatively co-expressed with RUNX3. RUNX3 was identified as a TF that regulated the expression of both itself and its co-expressed genes. PPI analysis showed that 20 protein-encoding genes interacted with RUNX3, among which 9 genes were differentially expressed in melanoma, such as CBFB and SMAD3. These genes were significantly enriched in transcriptional regulation by RUNX3, RUNX3 regulates BCL2L11 (BIM) transcription, regulation of I-kappaB kinase/NF-kappaB signaling, and signaling by NOTCH. A total of 31 miRNAs could target RUNX3, such as miR-326, miR-330-5p, and miR-373-3p. Conclusion: RUNX3 expression was up-regulated in melanoma and was implicated in the development of melanoma.

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Construction of ceRNA Coexpression Network and Screening of Molecular Targets in Colorectal Cancer

Disease Markers ◽

10.1155/2020/2860582 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9

Author(s):

Zhao Hui ◽

Wang Zhanwei ◽

Yang Xi ◽

Liu Jin ◽

Zhuang Jing ◽

...

Keyword(s):

Colorectal Cancer ◽

Protein Interactions ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Differentially Expressed ◽

Normal Tissues ◽

Cerna Network ◽

Cancer Tissues

Objective. To screen some RNAs that correlated with colorectal cancer (CRC). Methods. Differentially expressed miRNAs, lncRNAs, and mRNAs between cancer tissues and normal tissues in CRC were identified using data from the Gene Expression Omnibus (GEO) database. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interactions (PPIs) were performed to do the functional enrichment analysis. And a lncRNA-miRNA-mRNA network was constructed which correlated with CRC. RNAs in this network were subjected to analyze the relationship with the patient prognosis. Results. A total of 688, 241, and 103 differentially expressed genes (diff-mRNA), diff-lncRNA, and diff-miRNA were obtained between cancer tissues and normal tissues. A total of 315 edges were obtained in the ceRNA network. lncRNA RP11-108K3.2 and mRNA ONECUT2 correlated with prognosis. Conclusion. The identified RNAs and constructed ceRNA network could provide great sources for the researches of therapy of the CRC. And the lncRNA RP11-108K3.2 and mRNA ONECUT2 may serve as a novel prognostic predictor of CRC.

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

Lipids in Health and Disease ◽

10.1186/s12944-019-1142-0 ◽

2019 ◽

Vol 18 (1) ◽

Cited By ~ 1

Author(s):

Liu-An Zhuo ◽

Yi-Tao Wen ◽

Yong Wang ◽

Zhi-Fang Liang ◽

Gang Wu ◽

...

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Roc Curve ◽

Regulatory Networks ◽

Pairwise Comparison ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Diagnostic Value ◽

Functional Enrichment ◽

Rna Seq

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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Identifying Complex lncRNA/Pseudogene-miRNA-mRNA Crosstalk in Hormone-Dependent Cancers

10.20944/preprints202109.0337.v1 ◽

2021 ◽

Author(s):

Dulari Jayarathna ◽

Miguel E. Rentería ◽

Emilie Sauret ◽

Jyotsna Batra ◽

Neha S. Gandhi

Keyword(s):

Regulatory Networks ◽

Cancer Survival ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Messenger Rnas ◽

Protein Activity ◽

Cerna Network ◽

Non Coding Rnas

The discovery of microRNAs (miRNAs) has fundamentally transformed our understanding of gene regulation. The competing endogenous RNA (ceRNA) hypothesis postulates that not only messenger RNAs but also other RNA transcripts, such as long non-coding RNAs and pseudogenes, can act as natural miRNA sponges. These RNAs influence each other’s expression levels by competing for the same pool of miRNAs through miRNA response elements on their target transcripts, thereby modulating gene expression and protein activity. In recent years, these ceRNA regulatory networks have gained considerable attention in cancer research. Several studies have identified cancer-specific ceRNA networks. Nevertheless, prior bioinformatic analyses have focused on long non-coding RNAs-associated ceRNA networks. Here, we identify an extended-ceRNA network (including both long non-coding RNAs and pseudogenes) shared across a group of four hormone-dependent (HD) cancers, i.e., prostate, breast, colorectal, and endometrial cancers, using data from The Cancer Genome Atlas (TCGA). We performed a functional enrichment analysis for differentially expressed genes in the shared ceRNA network of HD cancers, followed by a survival analysis to determine their prognostic ability. We identified two long non-coding RNAs, nine genes, and seventy-four miRNAs in the shared ceRNA network across four HD cancers. Among them, two genes and forty-one miRNAs were associated with at least one HD cancer survival. This study is the first to investigate pseudogene associated ceRNAs across a group of related cancers and highlights the value of this approach to understanding shared molecular pathogenesis in a group of related diseases.

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The Integrative Analysis of Competitive Endogenous RNA Regulatory Networks in Coronary Artery Disease

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.647953 ◽

2021 ◽

Vol 8 ◽

Author(s):

Yuyao Ji ◽

Tao Yan ◽

Shijie Zhu ◽

Runda Wu ◽

Miao Zhu ◽

...

Keyword(s):

Coronary Artery Disease ◽

Coronary Artery ◽

Correlation Coefficient ◽

Regulatory Networks ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Cardiovascular Death ◽

Functional Enrichment ◽

Hub Genes ◽

Artery Disease

Background: Coronary artery disease (CAD) is the leading cause of cardiovascular death. The competitive endogenous RNAs (ceRNAs) hypothesis is a new theory that explains the relationship between lncRNAs and miRNAs. The mechanism of ceRNAs in the pathological process of CAD has not been fully elucidated. The objective of this study was to explore the ceRNA mechanism in CAD using the integrative bioinformatics analysis and provide new research ideas for the occurrence and development of CAD.Methods: The GSE113079 dataset was downloaded, and differentially expressed lncRNAs (DElncRNAs) and genes (DEGs) were identified using the limma package in the R language. Weighted gene correlation network analysis (WGCNA) was performed on DElncRNAs and DEGs to explore lncRNAs and genes associated with CAD. Functional enrichment analysis was performed on hub genes in the significant module identified via WGCNA. Four online databases, including TargetScan, miRDB, miRTarBase, and Starbase, combined with an online tool, miRWalk, were used to construct ceRNA regulatory networks.Results: DEGs were clustered into ten co-expression modules with different colors using WGCNA. The brown module was identified as the key module with the highest correlation coefficient. 188 hub genes were identified in the brown module for functional enrichment analysis. DElncRNAs were clustered into sixteen modules, including seven modules related to CAD with the correlation coefficient more than 0.5. Three ceRNA networks were identified, including OIP5-AS1-miR-204-5p/miR-211-5p-SMOC1, OIP5-AS1-miR-92b-3p-DKK3, and OIP5-AS1-miR-25-3p-TMEM184B.Conclusion: Three ceRNA regulatory networks identified in this study may play crucial roles in the occurrence and development of CAD, which provide novel insights into the ceRNA mechanism in CAD.

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An advanced strategy for comprehensive profiling of ADP-ribosylation sites using mass spectrometry-based proteomics

10.1101/501353 ◽

2018 ◽

Cited By ~ 1

Author(s):

Ivo A. Hendriks ◽

Sara C. Larsen ◽

Michael L. Nielsen

Keyword(s):

Electron Transfer ◽

Electron Transfer Dissociation ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Post Translational Modification ◽

Tyrosine Residues ◽

Adp Ribosylation ◽

Cellular Processes ◽

Nuclear Proteome

ABSTRACTADP-ribosylation is a widespread post-translational modification (PTM) with crucial functions in many cellular processes. Here, we describe an in-depth ADP-ribosylome using our Af1521-based proteomics methodology for comprehensive profiling of ADP-ribosylation sites, by systematically assessing complementary proteolytic digestions and precursor fragmentation through application of electron-transfer higher-energy collisional dissociation (EThcD) and electron transfer dissociation (ETD), respectively. While ETD spectra yielded higher identification scores, EThcD generally proved superior to ETD in identification and localization of ADP-ribosylation sites regardless of protease employed. Notwithstanding, the propensities of complementary proteases and fragmentation methods expanded the detectable repertoire of ADP-ribosylation to an unprecedented depth. This system-wide profiling of the ADP-ribosylome in HeLa cells subjected to DNA damage uncovered >11,000 unique ADP-ribosylated peptides mapping to >7,000 ADP-ribosylation sites, in total modifying over one-third of the human nuclear proteome and highlighting the vast scope of this PTM. High-resolution MS/MS spectra enabled identification of dozens of proteins concomitantly modified by ADP-ribosylation and phosphorylation, revealing a considerable degree of crosstalk on histones. ADP-ribosylation was confidently localized to various amino acid residue types, including less abundantly modified residues, with hundreds of ADP-ribosylation sites pinpointed on histidine, arginine, and tyrosine residues. Functional enrichment analysis suggested modification of these specific residue types is directed in a spatial manner, with tyrosine ADP-ribosylation linked to the ribosome, arginine ADP-ribosylation linked to the endoplasmic reticulum, and histidine ADP-ribosylation linked to the mitochondrion.

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Regulatory role of non-coding RNA in ginseng rusty root symptom tissue

Scientific Reports ◽

10.1038/s41598-021-88709-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Xingbo Bian ◽

Pengcheng Yu ◽

Ling Dong ◽

Yan Zhao ◽

He Yang ◽

...

Keyword(s):

Fatty Acid ◽

Regulatory Networks ◽

Target Genes ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Differentially Expressed ◽

Circular Rnas ◽

Primary Metabolism ◽

Non Coding Rna

AbstractGinseng rusty root symptom (GRS) is one of the primary diseases of ginseng. It leads to a severe decline in the quality of ginseng and significantly affects the ginseng industry. The regulatory mechanism of non-coding RNA (ncRNA) remains unclear in the course of disease. This study explored the long ncRNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs) in GRS tissues and healthy ginseng (HG) tissues and performed functional enrichment analysis of the screened differentially expressed ncRNAs. Considering the predictive and regulatory effects of ncRNAs on mRNAs, we integrated ncRNA and mRNA data to analyze and construct relevant regulatory networks. A total of 17,645 lncRNAs, 245 circRNAs, and 299 miRNAs were obtained from HG and GRS samples, and the obtained ncRNAs were characterized, including the classification of lncRNAs, length and distribution of circRNA, and the length and family affiliations of miRNAs. In the analysis of differentially expressed ncRNA target genes, we found that lncRNAs may be involved in the homeostatic process of ginseng tissues and that lncRNAs, circRNAs, and miRNAs are involved in fatty acid-related regulation, suggesting that alterations in fatty acid-related pathways may play a key role in GRS. Besides, differentially expressed ncRNAs play an essential role in regulating transcriptional translation processes, primary metabolism such as starch and sucrose, and secondary metabolism such as alkaloids in ginseng tissues. Finally, we integrated the correlations between ncRNAs and mRNAs, constructed corresponding interaction networks, and identified ncRNAs that may play critical roles in GRS. These results provide a basis for revealing GRS's molecular mechanism and enrich our understanding of ncRNAs in ginseng.

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