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1
Slattery, Martha L., Jennifer S. Herrick, John R. Stevens, Roger K. Wolff, and Lila E. Mullany. "An Assessment of Database-Validated microRNA Target Genes in Normal Colonic Mucosa: Implications for Pathway Analysis." Cancer Informatics 16 (January 1, 2017): 117693511771640. http://dx.doi.org/10.1177/1176935117716405.
Повний текст джерелаАнотація:
Background: Determination of functional pathways regulated by microRNAs (miRNAs), while an essential step in developing therapeutics, is challenging. Some miRNAs have been studied extensively; others have limited information. In this study, we focus on 254 miRNAs previously identified as being associated with colorectal cancer and their database-identified validated target genes. Methods: We use RNA-Seq data to evaluate messenger RNA (mRNA) expression for 157 subjects who also had miRNA expression data. In the replication phase of the study, we replicated associations between 254 miRNAs associated with colorectal cancer and mRNA expression of database-identified target genes in normal colonic mucosa. In the discovery phase of the study, we evaluated expression of 18 miRNAs (those with 20 or fewer database-identified target genes along with miR-21-5p, miR-215-5p, and miR-124-3p which have more than 500 database-identified target genes) with expression of 17 434 mRNAs to identify new targets in colon tissue. Seed region matches between miRNA and newly identified targeted mRNA were used to help determine direct miRNA-mRNA associations. Results: From the replication of the 121 miRNAs that had at least 1 database-identified target gene using mRNA expression methods, 97.9% were expressed in normal colonic mucosa. Of the 8622 target miRNA-mRNA associations identified in the database, 2658 (30.2%) were associated with gene expression in normal colonic mucosa after adjusting for multiple comparisons. Of the 133 miRNAs with database-identified target genes by non-mRNA expression methods, 97.2% were expressed in normal colonic mucosa. After adjustment for multiple comparisons, 2416 miRNA-mRNA associations remained significant (19.8%). Results from the discovery phase based on detailed examination of 18 miRNAs identified more than 80 000 miRNA-mRNA associations that had not previously linked to the miRNA. Of these miRNA-mRNA associations, 15.6% and 14.8% had seed matches for CRCh38 and CRCh37, respectively. Conclusions: Our data suggest that miRNA target gene databases are incomplete; pathways derived from these databases have similar deficiencies. Although we know a lot about several miRNAs, little is known about other miRNAs in terms of their targeted genes. We encourage others to use their data to continue to further identify and validate miRNA-targeted genes.
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Hou, Yawei, Yameng Li, Yichuan Wang, Wenpu Li, and Zhenwei Xiao. "Screening and Analysis of Key Genes in miRNA-mRNA Regulatory Network of Membranous Nephropathy." Journal of Healthcare Engineering 2021 (November 16, 2021): 1–13. http://dx.doi.org/10.1155/2021/5331948.
Повний текст джерелаАнотація:
Background. MicroRNAs (miRNAs) are confirmed to participate in occurrence, development, and prevention of membranous nephropathy (MN), but their mechanism of action is unclear. Objective. With the GEO database and the use of bioinformatics, miRNA-mRNA regulatory network genes relevant to MN were explored and their potential mechanism of action was explained. Methods. The MN-related miRNA chip data set (GSE51674) and mRNA chip data set (GSE108109) were downloaded from the GEO database. Differential analysis was performed using the GEO2R online tool. TargetScan, miRTarBase, and StarBase databases were used to predict potential downstream target genes regulated by differentially expressed miRNAs, and the intersection with differential genes were taken to obtain candidate target genes. According to the regulatory relationship between miRNA and mRNA, the miRNA-mRNA relationship pair was clarified and Cytoscape was used to construct a miRNA-mRNA regulatory network. WebGestalt was used to conduct enrichment analysis of the biological process of differential mRNAs in the regulatory network; FunRich analyzes the differential mRNA pathways in the miRNA-mRNA regulatory network. And the STRING database was used to construct a PPI network for candidate target genes, and Cytoscape visually analyzes the PPI network. Results. Experiments were conducted to screen differentially expressed miRNAs and mRNAs. There were 30 differentially expressed miRNAs, including 22 upregulated and 8 downregulated; and 1267 differentially expressed mRNAs, including 536 upregulated and 731 downregulated. Using TargetScan, miRTarBase, and StarBase databases to predict the downstream targets of differentially expressed miRNAs, 2957 downstream target genes coexisting in the 3 databases were predicted to intersect with differentially expressed mRNAs to obtain 175 candidate target genes. Finally, 36 miRNA-mRNA relationship pairs comprising 10 differentially expressed miRNAs and 27 differentially expressed mRNAs were screened out, and the regulatory network was constructed. Further analysis revealed that the miRNA regulatory network genes may be involved in the development of membranous nephropathy by mTOR, PDGFR-β, LKB1, and VEGF/VEGFR signaling pathways. Conclusion. The miRNA regulatory network genes may participate in the regulation of podocyte autophagy, lipid metabolism, and renal fibrosis through mTOR, PDGFR-β, LKB1, and VEGF/VEGFR signaling pathways, thereby affecting the occurrence and development of membranous nephropathy.
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Li, Yameng, Yukun Xu, Yawei Hou, and Rui Li. "Construction and Bioinformatics Analysis of the miRNA-mRNA Regulatory Network in Diabetic Nephropathy." Journal of Healthcare Engineering 2021 (November 18, 2021): 1–11. http://dx.doi.org/10.1155/2021/8161701.
Повний текст джерелаАнотація:
Background. MicroRNA (miRNA) has been confirmed to be involved in the occurrence, development, and prevention of diabetic nephropathy (DN), but its mechanism of action is still unclear. Objective. With the help of the GEO database, bioinformatics methods are used to explore the miRNA-mRNA regulatory relationship pairs related to diabetic nephropathy and explain their potential mechanisms of action. Methods. The DN-related miRNA microarray dataset (GSE51674) and mRNA expression dataset (GSE30122) are downloaded through the GEO database, online analysis tool GEO2R is used for data differential expression analysis, TargetScan, miRTarBase, and miRDB databases are used to predict potential downstream target genes regulated by differentially expressed miRNAs, and intersection with differential genes is used to obtain candidate target genes. According to the regulatory relationship between miRNA and mRNA, the miRNA-mRNA relationship pair is clarified, and the miRNA-mRNA regulatory network is constructed using Cytoscape. DAVID is used to perform GO function enrichment analysis and KEGG pathway analysis of candidate target genes. By GeneMANIA prediction of miRNA target genes and coexpressed genes, the protein interaction network is constructed. Results and Conclusions. A total of 67 differentially expressed miRNAs were screened in the experiment, of which 42 were upregulated and 25 were downregulated; a total of 448 differentially expressed mRNAs were screened, of which 93 were upregulated and 355 were downregulated. Using TargetScan, miRTarBase, and miRDB databases to predict downstream targets of differentially expressed miRNAs, 2283 downstream target genes coexisting in 3 databases were predicted to intersect with differentially expressed mRNAs to obtain 96 candidate target genes. Finally, 44 miRNA-mRNA relationship pairs consisting of 12 differentially expressed miRNAs and 27 differentially expressed mRNAs were screened out; further analysis showed that miRNA regulatory network genes may participate in the occurrence and development of diabetic nephropathy through PI3K/Akt, ECM-receptor interaction pathway, and RAS signaling pathway.
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Chen, Yuhao, and Xiaowei Wang. "miRDB: an online database for prediction of functional microRNA targets." Nucleic Acids Research 48, no. D1 (August 31, 2019): D127—D131. http://dx.doi.org/10.1093/nar/gkz757.
Повний текст джерелаАнотація:
Abstract MicroRNAs (miRNAs) are small noncoding RNAs that act as master regulators in many biological processes. miRNAs function mainly by downregulating the expression of their gene targets. Thus, accurate prediction of miRNA targets is critical for characterization of miRNA functions. To this end, we have developed an online database, miRDB, for miRNA target prediction and functional annotations. Recently, we have performed major updates for miRDB. Specifically, by employing an improved algorithm for miRNA target prediction, we now present updated transcriptome-wide target prediction data in miRDB, including 3.5 million predicted targets regulated by 7000 miRNAs in five species. Further, we have implemented the new prediction algorithm into a web server, allowing custom target prediction with user-provided sequences. Another new database feature is the prediction of cell-specific miRNA targets. miRDB now hosts the expression profiles of over 1000 cell lines and presents target prediction data that are tailored for specific cell models. At last, a new web query interface has been added to miRDB for prediction of miRNA functions by integrative analysis of target prediction and Gene Ontology data. All data in miRDB are freely accessible at http://mirdb.org.
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Liu, Chun-Jie, Xin Fu, Mengxuan Xia, Qiong Zhang, Zhifeng Gu, and An-Yuan Guo. "miRNASNP-v3: a comprehensive database for SNPs and disease-related variations in miRNAs and miRNA targets." Nucleic Acids Research 49, no. D1 (September 29, 2020): D1276—D1281. http://dx.doi.org/10.1093/nar/gkaa783.
Повний текст джерелаАнотація:
Abstract MicroRNAs (miRNAs) related single-nucleotide variations (SNVs), including single-nucleotide polymorphisms (SNPs) and disease-related variations (DRVs) in miRNAs and miRNA-target binding sites, can affect miRNA functions and/or biogenesis, thus to impact on phenotypes. miRNASNP is a widely used database for miRNA-related SNPs and their effects. Here, we updated it to miRNASNP-v3 (http://bioinfo.life.hust.edu.cn/miRNASNP/) with tremendous number of SNVs and new features, especially the DRVs data. We analyzed the effects of 7 161 741 SNPs and 505 417 DRVs on 1897 pre-miRNAs (2630 mature miRNAs) and 3′UTRs of 18 152 genes. miRNASNP-v3 provides a one-stop resource for miRNA-related SNVs research with the following functions: (i) explore associations between miRNA-related SNPs/DRVs and diseases; (ii) browse the effects of SNPs/DRVs on miRNA-target binding; (iii) functional enrichment analysis of miRNA target gain/loss caused by SNPs/DRVs; (iv) investigate correlations between drug sensitivity and miRNA expression; (v) inquire expression profiles of miRNAs and their targets in cancers; (vi) browse the effects of SNPs/DRVs on pre-miRNA secondary structure changes; and (vii) predict the effects of user-defined variations on miRNA-target binding or pre-miRNA secondary structure. miRNASNP-v3 is a valuable and long-term supported resource in functional variation screening and miRNA function studies.
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Pian, Cong, Guangle Zhang, Libin Gao, Xiaodan Fan, and Fei Li. "miR+Pathway: the integration and visualization of miRNA and KEGG pathways." Briefings in Bioinformatics 21, no. 2 (January 16, 2019): 699–708. http://dx.doi.org/10.1093/bib/bby128.
Повний текст джерелаАнотація:
Abstract miRNAs represent a type of noncoding small molecule RNA. Many studies have shown that miRNAs are widely involved in the regulation of various pathways. The key to fully understanding the regulatory function of miRNAs is the determination of the pathways in which the miRNAs participate. However, the major pathway databases such as KEGG only include information regarding protein-coding genes. Here, we redesigned a pathway database (called miR+Pathway) by integrating and visualizing the 8882 human experimentally validated miRNA-target interactions (MTIs) and 150 KEGG pathways. This database is freely accessible at http://www.insect-genome.com/miR-pathway. Researchers can intuitively determine the pathways and the genes in the pathways that are regulated by miRNAs as well as the miRNAs that target the pathways. To determine the pathways in which targets of a certain miRNA or multiple miRNAs are enriched, we performed a KEGG analysis miRNAs by using the hypergeometric test. In addition, miR+Pathway provides information regarding MTIs, PubMed IDs and the experimental verification method. Users can retrieve pathways regulated by an miRNA or a gene by inputting its names.
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Park, Sungjin, SeongRyeol Moon, Kiyoung Lee, Ie Byung Park, Dae Ho Lee, and Seungyoon Nam. "miR2Diabetes: A Literature-Curated Database of microRNA Expression Patterns, in Diabetic Microvascular Complications." Genes 10, no. 10 (October 9, 2019): 784. http://dx.doi.org/10.3390/genes10100784.
Повний текст джерелаАнотація:
microRNAs (miRNAs) have been established as critical regulators of the pathogenesis of diabetes mellitus (DM), and diabetes microvascular complications (DMCs). However, manually curated databases for miRNAs, and DM (including DMCs) association studies, have yet to be established. Here, we constructed a user-friendly database, “miR2Diabetes,” equipped with a graphical web interface for simple browsing or searching manually curated annotations. The annotations in our database cover 14 DM and DMC phenotypes, involving 156 miRNAs, by browsing diverse sample origins (e.g., blood, kidney, liver, and other tissues). Additionally, we provide miRNA annotations for disease-model organisms (including rats and mice), of DM and DMCs, for the purpose of improving knowledge of the biological complexity of these pathologies. We assert that our database will be a comprehensive resource for miRNA biomarker studies, as well as for prioritizing miRNAs for functional validation, in DM and DMCs, with likely extension to other diseases.
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Huang, Hsi-Yuan, Yang-Chi-Dung Lin, Shidong Cui, Yixian Huang, Yun Tang, Jiatong Xu, Jiayang Bao, et al. "miRTarBase update 2022: an informative resource for experimentally validated miRNA–target interactions." Nucleic Acids Research 50, no. D1 (November 30, 2021): D222—D230. http://dx.doi.org/10.1093/nar/gkab1079.
Повний текст джерелаАнотація:
Abstract MicroRNAs (miRNAs) are noncoding RNAs with 18–26 nucleotides; they pair with target mRNAs to regulate gene expression and produce significant changes in various physiological and pathological processes. In recent years, the interaction between miRNAs and their target genes has become one of the mainstream directions for drug development. As a large-scale biological database that mainly provides miRNA–target interactions (MTIs) verified by biological experiments, miRTarBase has undergone five revisions and enhancements. The database has accumulated >2 200 449 verified MTIs from 13 389 manually curated articles and CLIP-seq data. An optimized scoring system is adopted to enhance this update’s critical recognition of MTI-related articles and corresponding disease information. In addition, single-nucleotide polymorphisms and disease-related variants related to the binding efficiency of miRNA and target were characterized in miRNAs and gene 3′ untranslated regions. miRNA expression profiles across extracellular vesicles, blood and different tissues, including exosomal miRNAs and tissue-specific miRNAs, were integrated to explore miRNA functions and biomarkers. For the user interface, we have classified attributes, including RNA expression, specific interaction, protein expression and biological function, for various validation experiments related to the role of miRNA. We also used seed sequence information to evaluate the binding sites of miRNA. In summary, these enhancements render miRTarBase as one of the most research-amicable MTI databases that contain comprehensive and experimentally verified annotations. The newly updated version of miRTarBase is now available at https://miRTarBase.cuhk.edu.cn/.
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Kehl, Tim, Fabian Kern, Christina Backes, Tobias Fehlmann, Daniel Stöckel, Eckart Meese, Hans-Peter Lenhof, and Andreas Keller. "miRPathDB 2.0: a novel release of the miRNA Pathway Dictionary Database." Nucleic Acids Research 48, no. D1 (November 6, 2019): D142—D147. http://dx.doi.org/10.1093/nar/gkz1022.
Повний текст джерелаАнотація:
Abstract Since the initial release of miRPathDB, tremendous progress has been made in the field of microRNA (miRNA) research. New miRNA reference databases have emerged, a vast amount of new miRNA candidates has been discovered and the number of experimentally validated target genes has increased considerably. Hence, the demand for a major upgrade of miRPathDB, including extended analysis functionality and intuitive visualizations of query results has emerged. Here, we present the novel release 2.0 of the miRNA Pathway Dictionary Database (miRPathDB) that is freely accessible at https://mpd.bioinf.uni-sb.de/. miRPathDB 2.0 comes with a ten-fold increase of pre-processed data. In total, the updated database provides putative associations between 27 452 (candidate) miRNAs, 28 352 targets and 16 833 pathways for Homo sapiens, as well as interactions of 1978 miRNAs, 24 898 targets and 6511 functional categories for Mus musculus. Additionally, we analyzed publications citing miRPathDB to identify common use-cases and further extensions. Based on this evaluation, we added new functionality for interactive visualizations and down-stream analyses of bulk queries. In summary, the updated version of miRPathDB, with its new custom-tailored features, is one of the most comprehensive and advanced resources for miRNAs and their target pathways.
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Liu, Xinhong, Feng Chen, Fang Tan, Fang Li, Ruokun Yi, Dingyi Yang, and Xin Zhao. "Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network." BioMed Research International 2020 (November 4, 2020): 1–18. http://dx.doi.org/10.1155/2020/6149174.
Повний текст джерелаАнотація:
Background. Breast cancer is a malignant tumor that occurs in the epithelial tissue of the breast gland and has become the most common malignancy in women. The regulation of the expression of related genes by microRNA (miRNA) plays an important role in breast cancer. We constructed a comprehensive breast cancer-miRNA-gene interaction map. Methods. Three miRNA microarray datasets (GSE26659, GSE45666, and GSE58210) were obtained from the GEO database. Then, the R software “LIMMA” package was used to identify differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The BRCA GE-mRNA datasets (GSE109169 and GSE139038) were downloaded from the GEO database for identifying differentially expressed genes (DE-genes). Next, GO annotation and KEGG pathway enrichment analysis were conducted. A PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes were further evaluated. Results. We found 6 upregulated differentially expressed- (DE-) miRNAs and 18 downregulated DE-miRNAs by analyzing 3 Gene Expression Omnibus databases, and we predicted the upstream transcription factors and downstream target genes for these DE-miRNAs. Then, we used the GEO database to perform differential analysis on breast cancer mRNA and obtained differentially expressed mRNA. We found 10 hub genes of upregulated DE-miRNAs and 10 hub genes of downregulated DE-miRNAs through interaction analysis. Conclusions. In this study, we have performed an integrated bioinformatics analysis to construct a more comprehensive BRCA-miRNA-gene network and provide new targets and research directions for the treatment and prognosis of BRCA.
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Moss, Tiffanie Y., and Christopher A. Cullis. "Computational prediction of candidate miRNAs and their targets from the completed Linum ussitatissimum genome and EST database." Journal of Nucleic Acids Investigation 3, no. 1 (June 5, 2012): 2. http://dx.doi.org/10.4081/jnai.2012.4150.
Повний текст джерелаАнотація:
Flax is an important agronomic crop grown for its fiber (linen) and oil (linseed oil). In spite of many thousands of years of breeding some fiber varieties have been shown to rapidly respond to environmental stress with heritable changes to its genome. Many miRNAs appear to be induced by abiotic or biotic conditions experienced through the plant life cycle. Computational miRNA analysis of the flax genome provides a foundation for subsequent research on miRNA function in <em>Linum usitatissimum </em>and may also provide novel insight into any regulatory role the RNAi pathway may play in generating adaptive structural variation in response to environmental stress. Here a bioinformatics approach is used to screen for miRNAs previously identified in other plant species, as well as to predict putative miRNAs unique to a particular species which may not have been identified as they are less abundant or dependent upon a specific set of environmental conditions. Twelve miRNA genes were identified in flax on the basis of unique pre-miRNA positions with structural homology to plant pre-miRNAs and complete sequence homology to published plant miRNAs. These miRNAs were found to belong to 7 miRNA families, with an additional 2 matches corresponding to as yet unnamed poplar miRNAs and a parologous miRNA with partial sequence homology to mtr-miR4414b. An additional 649 novel and distinct flax miRNA genes were identified to form from canonical hairpin structures and to have putative targets among the ~30,000 flax Unigenes.
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Yu, Dong-Ling, Zu-Guo Yu, Guo-Sheng Han, Jinyan Li, and Vo Anh. "Heterogeneous Types of miRNA-Disease Associations Stratified by Multi-Layer Network Embedding and Prediction." Biomedicines 9, no. 9 (September 3, 2021): 1152. http://dx.doi.org/10.3390/biomedicines9091152.
Повний текст джерелаАнотація:
Abnormal miRNA functions are widely involved in many diseases recorded in the database of experimentally supported human miRNA-disease associations (HMDD). Some of the associations are complicated: There can be up to five heterogeneous association types of miRNA with the same disease, including genetics type, epigenetics type, circulating miRNAs type, miRNA tissue expression type and miRNA-target interaction type. When one type of association is known for an miRNA-disease pair, it is important to predict any other types of the association for a better understanding of the disease mechanism. It is even more important to reveal associations for currently unassociated miRNAs and diseases. Methods have been recently proposed to make predictions on the association types of miRNA-disease pairs through restricted Boltzman machines, label propagation theories and tensor completion algorithms. None of them has exploited the non-linear characteristics in the miRNA-disease association network to improve the performance. We propose to use attributed multi-layer heterogeneous network embedding to learn the latent representations of miRNAs and diseases from each association type and then to predict the existence of the association type for all the miRNA-disease pairs. The performance of our method is compared with two newest methods via 10-fold cross-validation on the database HMDD v3.2 to demonstrate the superior prediction achieved by our method under different settings. Moreover, our real predictions made beyond the HMDD database can be all validated by NCBI literatures, confirming that our method is capable of accurately predicting new associations of miRNAs with diseases and their association types as well.
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Li, Jian-Rong, Chun-Yip Tong, Tsai-Jung Sung, Ting-Yu Kang, Xianghong Jasmine Zhou, and Chun-Chi Liu. "CMEP: a database for circulating microRNA expression profiling." Bioinformatics 35, no. 17 (January 22, 2019): 3127–32. http://dx.doi.org/10.1093/bioinformatics/btz042.
Повний текст джерелаАнотація:
Abstract Motivation In recent years, several experimental studies have revealed that the microRNAs (miRNAs) in serum, plasma, exosome and whole blood are dysregulated in various types of diseases, indicating that the circulating miRNAs may serve as potential noninvasive biomarkers for disease diagnosis and prognosis. However, no database has been constructed to integrate the large-scale circulating miRNA profiles, explore the functional pathways involved and predict the potential biomarkers using feature selection between the disease conditions. Although there have been several studies attempting to generate a circulating miRNA database, they have not yet integrated the large-scale circulating miRNA profiles or provided the biomarker-selection function using machine learning methods. Results To fill this gap, we constructed the Circulating MicroRNA Expression Profiling (CMEP) database for integrating, analyzing and visualizing the large-scale expression profiles of phenotype-specific circulating miRNAs. The CMEP database contains massive datasets that were manually curated from NCBI GEO and the exRNA Atlas, including 66 datasets, 228 subsets and 10 419 samples. The CMEP provides the differential expression circulating miRNAs analysis and the KEGG functional pathway enrichment analysis. Furthermore, to provide the function of noninvasive biomarker discovery, we implemented several feature-selection methods, including ridge regression, lasso regression, support vector machine and random forests. Finally, we implemented a user-friendly web interface to improve the user experience and to visualize the data and results of CMEP. Availability and implementation CMEP is accessible at http://syslab5.nchu.edu.tw/CMEP.
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Lagana, A., S. Forte, A. Giudice, M. R. Arena, P. L. Puglisi, R. Giugno, A. Pulvirenti, D. Shasha, and A. Ferro. "miRo: a miRNA knowledge base." Database 2009 (August 7, 2009): bap008. http://dx.doi.org/10.1093/database/bap008.
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Li, Yingyuan, Wulin Tan, Fang Ye, Faling Xue, Shaowei Gao, Wenqi Huang, and Zhongxing Wang. "Identification of microRNAs and genes as biomarkers of atrial fibrillation using a bioinformatics approach." Journal of International Medical Research 47, no. 8 (June 20, 2019): 3580–89. http://dx.doi.org/10.1177/0300060519852235.
Повний текст джерелаАнотація:
Objective We aimed to explore potential microRNAs (miRNAs) and target genes related to atrial fibrillation (AF). Methods Data for microarrays GSE70887 and GSE68475, both of which include AF and control groups, were downloaded from the Gene Expression Omnibus database. Differentially expressed miRNAs between AF and control groups were identified within each microarray, and the intersection of these two sets was obtained. These miRNAs were mapped to target genes in the miRNet database. Functional annotation and enrichment analysis of these target genes was performed in the DAVID database. The protein-protein interaction (PPI) network from the STRING database and the miRNA-target-gene network were merged into a PPI-miRNA network using Cytoscape software. Modules of this network containing miRNAs were detected and further analyzed. Results Ten differentially expressed miRNAs and 1520 target genes were identified. Three PPI-miRNA modules were constructed, which contained miR-424, miR-15a, miR-542-3p, and miR-421 as well as their target genes, CDK1, CDK6, and CCND3. Conclusion The identified miRNAs and genes may be related to the pathogenesis of AF. Thus, they may be potential biomarkers for diagnosis and targets for treatment of AF.
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Kang, Ran, Zhengtang Tan, Mei Lang, Linqi Jin, Yin Zhang, Yiming Zhang, Tailin Guo, and Zhiyun Guo. "EnhFFL: A database of enhancer mediated feed-forward loops for human and mouse." Precision Clinical Medicine 4, no. 2 (April 14, 2021): 129–35. http://dx.doi.org/10.1093/pcmedi/pbab006.
Повний текст джерелаАнотація:
Abstract Feed-forward loops (FFLs) are thought to be one of the most common and important classes of transcriptional network motifs involved in various diseases. Enhancers are cis-regulatory elements that positively regulate protein-coding genes or microRNAs (miRNAs) by recruiting DNA-binding transcription factors (TFs). However, a comprehensive resource to identify, store, and analyze the FFLs of typical enhancer and super-enhancer FFLs is not currently available. Here, we present EnhFFL, an online database to provide a data resource for users to browse and search typical enhancer and super-enhancer FFLs. The current database covers 46 280/7000 TF-enhancer-miRNA FFLs, 9997/236 enhancer-miRNA-gene FFLs, 3 561 164/3 193 182 TF-enhancer-gene FFLs, and 1259/235 TF-enhancer feed-back loops (FBLs) across 91 tissues/cell lines of human and mouse, respectively. Users can browse loops by selecting species, types of tissue/cell line, and types of FFLs. EnhFFL supports searching elements including name/ID, genomic location, and the conservation of miRNA target genes. We also developed tools for users to screen customized FFLs using the threshold of q value as well as the confidence score of miRNA target genes. Disease and functional enrichment analysis showed that master miRNAs that are widely engaged in FFLs including TF-enhancer-miRNAs and enhancer-miRNA-genes are significantly involved in tumorigenesis. Database URL:http://lcbb.swjtu.edu.cn/EnhFFL/.
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Li, Chang, Brian Wu, Han Han, Jeff Zhao, Yongsheng Bai, and Xiaoming Liu. "Identification of MicroRNA-Related Tumorigenesis Variants and Genes in the Cancer Genome Atlas (TCGA) Data." Genes 11, no. 9 (August 19, 2020): 953. http://dx.doi.org/10.3390/genes11090953.
Повний текст джерелаАнотація:
MicroRNAs (miRNAs) are a class of small non-coding RNA that can down-regulate their targets by selectively binding to the 3′ untranslated region (3′UTR) of most messenger RNAs (mRNAs) in the human genome. Single nucleotide variants (SNVs) located in miRNA target sites (MTS) can disrupt the binding of targeting miRNAs. Anti-correlated miRNA–mRNA pairs between normal and tumor tissues obtained from The Cancer Genome Atlas (TCGA) can reveal important information behind these SNVs on MTS and their associated oncogenesis. In this study, using previously identified anti-correlated miRNA–mRNA pairs in 15 TCGA cancer types and publicly available variant annotation databases, namely dbNSFP (database for nonsynonymous SNPs’ functional predictions) and dbMTS (database of miRNA target site SNVs), we identified multiple functional variants and their gene products that could be associated with various types of cancers. We found two genes from dbMTS and 33 from dbNSFP that passed our stringent filtering criteria (e.g., pathogenicity). Specifically, from dbMTS, we identified 23 candidate genes, two of which (BMPR1A and XIAP) were associated with diseases that increased the risk of cancer in patients. From dbNSFP, we identified 65 variants located in 33 genes that were likely pathogenic and had a potential causative relationship with cancer. This study provides a novel way of utilizing TCGA data and integrating multiple publicly available databases to explore cancer genomics.
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Shinde, Santosh, and Utpal Bhadra. "MicroRNA Gene Interaction in Amyotrophic Lateral Sclerosis Dataset." Dataset Papers in Science 2014 (June 30, 2014): 1–24. http://dx.doi.org/10.1155/2014/780726.
Повний текст джерелаАнотація:
All microRNAs (miRNAs) in amyotrophic lateral sclerosis (ALS) study were collected from public databases such as miRBase, mir2Disease, and Human miRNA and Disease Database (HMDD). These miRNA datasets were used for target identification; these sets of miRNAs were expressed in brain specific parts of brain such as midbrain, cerebellum, frontal cortex, and hippocampus. Gene’s information and sequences were collected from NCBI and KEGG databases. All miRNAs were used for target prediction against 35 ALS associated genes. Three programs were used for target identification, namely, miRanda, TargetScan, and PicTar. The dataset contained information about miRNA targets sites identified by each program. Intersection studies of three programs such as miRanda versus TargetScan, miRanda versus PicTar, and TargetScan versus PicTar were carried out with all datasets. Target sites identified by each program were further explored for distribution of target sites across 35 genes in 5′ UTR, CDS, and 3′ UTR for miRNAs expressed in midbrain, cerebellum, frontal cortex, and hippocampus as predicted. Dataset was also used for calculation of multiplicity and coopretivity; this information was then used for construction of complex gene-microRNA interaction map.
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Zhang, Huizhe, Xue Wang, Yanchen Shi, Mengying Liu, Qingqing Xia, Weilong Jiang, and Yufeng Zhang. "Danggui Buxue Decoction Ameliorates Idiopathic Pulmonary Fibrosis through MicroRNA and Messenger RNA Regulatory Network." Evidence-Based Complementary and Alternative Medicine 2022 (April 26, 2022): 1–19. http://dx.doi.org/10.1155/2022/3439656.
Повний текст джерелаАнотація:
Objective. To develop a putative microRNA (miRNA) and messenger RNA (mRNA) regulatory network of Danggui Buxue decoction’s (DGBXD) amelioration of idiopathic pulmonary fibrosis (IPF). Methods. The Gene Expression Omnibus (GEO) database was used to identify differentially expressed miRNAs (DE-miRNAs) and differentially expressed mRNAs (DE-mRNAs). Using miRNet, the predicted target genes of identified DE-miRNAs were estimated, and then the target genes of DE-miRNAs in IPF were comprehensively examined. The Enrichr database was used to conduct functional enrichment and pathway enrichment. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was employed to obtain the target genes of DGBXD as well as active compounds. A putative miRNA-mRNA regulatory network of DGBXD acting on IPF was developed by intersecting the target genes of DGBXD with the DE-miRNA target genes in IPF. A bleomycin-induced mouse model was established and used to perform histopathology as well as real-time quantitative polymerase chain reaction (qRT-PCR) analyses of some miRNA-mRNA pairs. Results. Fourteen upmodulated DE-miRNAs and six downmodulated DE-miRNAs were screened. The downstream target genes of upmodulated and downmodulated DE-miRNAs were predicted. Subsequently, 1160 upmodulated DE-mRNAs and 1427 downmodulated DE-mRNAs were identified. Then, target genes of DE-miRNAs comprising 49 downmodulated and 53 upmodulated target genes were further screened to perform functional enrichment and pathway enrichment analyses. Subsequently, 196 target genes of DGBXD were obtained from TCMSP, with six downregulated target genes and six upregulated target genes of DGBXD acting on IPF being identified. A promising miRNA-mRNA regulatory network of DGBXD acting on IPF was developed in this study. Moreover, mir-493 together with its target gene Olr1 and mir-338 together with Hif1a were further validated by qRT-PCR. Conclusion. This study proposed detailed possible processes of miRNA-mRNA modulatory axis in IPF and constructed a prospective IPF-related miRNA-mRNA modulatory network with the aim of alleviating IPF with DGBXD.
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Zhang, Huizhe, Xue Wang, Yanchen Shi, Mengying Liu, Qingqing Xia, Weilong Jiang, and Yufeng Zhang. "Danggui Buxue Decoction Ameliorates Idiopathic Pulmonary Fibrosis through MicroRNA and Messenger RNA Regulatory Network." Evidence-Based Complementary and Alternative Medicine 2022 (April 26, 2022): 1–19. http://dx.doi.org/10.1155/2022/3439656.
Повний текст джерелаАнотація:
Objective. To develop a putative microRNA (miRNA) and messenger RNA (mRNA) regulatory network of Danggui Buxue decoction’s (DGBXD) amelioration of idiopathic pulmonary fibrosis (IPF). Methods. The Gene Expression Omnibus (GEO) database was used to identify differentially expressed miRNAs (DE-miRNAs) and differentially expressed mRNAs (DE-mRNAs). Using miRNet, the predicted target genes of identified DE-miRNAs were estimated, and then the target genes of DE-miRNAs in IPF were comprehensively examined. The Enrichr database was used to conduct functional enrichment and pathway enrichment. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was employed to obtain the target genes of DGBXD as well as active compounds. A putative miRNA-mRNA regulatory network of DGBXD acting on IPF was developed by intersecting the target genes of DGBXD with the DE-miRNA target genes in IPF. A bleomycin-induced mouse model was established and used to perform histopathology as well as real-time quantitative polymerase chain reaction (qRT-PCR) analyses of some miRNA-mRNA pairs. Results. Fourteen upmodulated DE-miRNAs and six downmodulated DE-miRNAs were screened. The downstream target genes of upmodulated and downmodulated DE-miRNAs were predicted. Subsequently, 1160 upmodulated DE-mRNAs and 1427 downmodulated DE-mRNAs were identified. Then, target genes of DE-miRNAs comprising 49 downmodulated and 53 upmodulated target genes were further screened to perform functional enrichment and pathway enrichment analyses. Subsequently, 196 target genes of DGBXD were obtained from TCMSP, with six downregulated target genes and six upregulated target genes of DGBXD acting on IPF being identified. A promising miRNA-mRNA regulatory network of DGBXD acting on IPF was developed in this study. Moreover, mir-493 together with its target gene Olr1 and mir-338 together with Hif1a were further validated by qRT-PCR. Conclusion. This study proposed detailed possible processes of miRNA-mRNA modulatory axis in IPF and constructed a prospective IPF-related miRNA-mRNA modulatory network with the aim of alleviating IPF with DGBXD.
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Guo, Zhonglong, Zheng Kuang, Ying Wang, Yongxin Zhao, Yihan Tao, Chen Cheng, Jing Yang, et al. "PmiREN: a comprehensive encyclopedia of plant miRNAs." Nucleic Acids Research 48, no. D1 (October 11, 2019): D1114—D1121. http://dx.doi.org/10.1093/nar/gkz894.
Повний текст джерелаАнотація:
Abstract MicroRNAs (miRNAs) are small non-coding RNA molecules that function as diverse endogenous gene regulators at the post-transcriptional level. In the past two decades, as research effort on miRNA identification, function and evolution has soared, so has the demand for miRNA databases. However, the current plant miRNA databases suffer from several typical drawbacks, including a lack of entries for many important species, uneven annotation standards across different species, abundant questionable entries, and limited annotation. To address these issues, we developed a knowledge-based database called Plant miRNA Encyclopedia (PmiREN, http://www.pmiren.com/), which was based on uniform processing of sequenced small RNA libraries using miRDeep-P2, followed by manual curation using newly updated plant miRNA identification criteria, and comprehensive annotation. PmiREN currently contains 16,422 high confidence novel miRNA loci in 88 plant species and 3,966 retrieved from miRBase. For every miRNA entry, information on precursor sequence, precursor secondary structure, expression pattern, clusters and synteny in the genome, potential targets supported by Parallel Analysis of RNA Ends (PARE) sequencing, and references is attached whenever possible. PmiREN is hierarchically accessible and has eight built-in search engines. We believe PmiREN is useful for plant miRNA cataloguing and data mining, therefore a resource for data-driven miRNA research in plants.
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Chen, Hailin, and Zuping Zhang. "Prediction of Associations between OMIM Diseases and MicroRNAs by Random Walk on OMIM Disease Similarity Network." Scientific World Journal 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/204658.
Повний текст джерелаАнотація:
Increasing evidence has revealed that microRNAs (miRNAs) play important roles in the development and progression of human diseases. However, efforts made to uncover OMIM disease-miRNA associations are lacking and the majority of diseases in the OMIM database are not associated with any miRNA. Therefore, there is a strong incentive to develop computational methods to detect potential OMIM disease-miRNA associations. In this paper, random walk on OMIM disease similarity network is applied to predict potential OMIM disease-miRNA associations under the assumption that functionally related miRNAs are often associated with phenotypically similar diseases. Our method makes full use of global disease similarity values. We tested our method on 1226 known OMIM disease-miRNA associations in the framework of leave-one-out cross-validation and achieved an area under the ROC curve of 71.42%. Excellent performance enables us to predict a number of new potential OMIM disease-miRNA associations and the newly predicted associations are publicly released to facilitate future studies. Some predicted associations with high ranks were manually checked and were confirmed from the publicly available databases, which was a strong evidence for the practical relevance of our method.
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Li, Junzui, Bin Zhao, Cui Yang, and Qionghua Chen. "Construction of a MicroRNA-mRNA Network Underlying Decidualized Endometriotic Cyst Stromal Cells Using Bioinformatics Analysis." BioMed Research International 2020 (August 19, 2020): 1–12. http://dx.doi.org/10.1155/2020/9246868.
Повний текст джерелаАнотація:
Background. Decidualization of ectopic endometrium often leads to the extensive proliferation of local tissue and is easily misdiagnosed as malignant tumors. The study is aimed at constructing a microRNA- (miRNA-) mRNA network underlying decidualized endometriotic cyst stromal cells (ECSCs). Methods. All data were collected from the Gene Expression Omnibus (GEO) database. Firstly, the differentially expressed genes (DEGs, adj. P‐Val<0.05, | log FC | ≥1) and miRNAs (DEMs, P‐Val<0.05, ∣log FC∣≥1) were analyzed by the limma package. Secondly, we predicted the target genes (TGs) of these DEMs through the TargetScan, miRDB, and miRTarBase databases. The overlapping genes between DEGs and TGs were screened out. Thirdly, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses of the overlapping genes were performed for integrated discovery, visualization, and annotation. Then, the protein-protein interaction (PPI) network of the overlapping genes was conducted by the STRING database. Finally, we combined the PPI network and the miRNA-mRNA pairs to build a miRNA-mRNA network. Results. There are 29 DEMs and 523 DEGs. Fourteen overlapping genes were screened out, and these genes were significantly enriched in metabolism and immunity. What is more, a miRNA-mRNA network, including 14 mRNAs and 9 miRNAs, was successfully constructed. Conclusions. Taken together, the miRNA-mRNA regulatory networks described in this study may provide new insights in the decidualization of ECSCs, suggesting further investigations in novel pathogenic mechanisms.
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Jia, Kaining, Xiaocang Ren, Yuee Liu, and Jiawei Wang. "Screening and Biological Function Analysis of miRNA and mRNA Related to Lung Adenocarcinoma Based on Bioinformatics Technology." Journal of Oncology 2022 (August 31, 2022): 1–13. http://dx.doi.org/10.1155/2022/4339391.
Повний текст джерелаАнотація:
Objective. To screen the differentially expressed miRNAs (DEMs) and the differentially expressed gene mRNAs (DEGs) in lung adenocarcinoma (LUAD) from the TCGA database and to explore the relationship between miRNAs and the prognosis of lung adenocarcinoma and their biological functions. Methods. The RNA-seq and miRNA-seq data of lung adenocarcinoma samples were downloaded from the TCGA database for analysis, and the R program was used to screen for differentially expressed miRNAs and mRNAs. Then, the molecular functions, biological processes, cellular components, and signaling pathways involved in the occurrence and development of LUAD were analyzed using the functional accumulation analysis software of GSEA. The relationship between the integrated differentially expressed RNAs was analyzed by miRcode, TargetScan, and miRTarbase databases, and the miRNA-mRNA network was constructed. Result. A total of 516 differentially expressed miRNAs and 5464 differentially expressed mRNAs were identified in LUAD. The GSEA enrichment analysis showed that miRNAs and mRNAs were mainly enriched in extracellular structure organization, external encapsulating structure organization, extracellular matrix organization, and gated channel activity. They were mainly involved in neuroactive ligand-receptor interaction signaling pathway. Some miRNAs and mRNAs in clustering modules were found to be associated with the prognosis of LUAD. Four targeting networks consisting of 22 miRNAs and 531 mRNAs were constructed. Conclusion. The miRNA and mRNA related to the prognosis of LUAD were screened out, which provided a valuable preliminary basis for the follow-upin-depth clinical research and basic experimental research of LUAD.
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Bovolenta, Luiz Augusto, Danillo Pinhal, Marcio Luis Acencio, Arthur Casulli de Oliveira, Simon Moxon, Cesar Martins, and Ney Lemke. "miRTil: An Extensive Repository for Nile Tilapia microRNA Next Generation Sequencing Data." Cells 9, no. 8 (July 22, 2020): 1752. http://dx.doi.org/10.3390/cells9081752.
Повний текст джерелаАнотація:
Nile tilapia is the third most cultivated fish worldwide and a novel model species for evolutionary studies. Aiming to improve productivity and contribute to the selection of traits of economic impact, biotechnological approaches have been intensively applied to species enhancement. In this sense, recent studies have focused on the multiple roles played by microRNAs (miRNAs) in the post-transcriptional regulation of protein-coding genes involved in the emergence of phenotypes with relevance for aquaculture. However, there is still a growing demand for a reference resource dedicated to integrating Nile Tilapia miRNA information, obtained from both experimental and in silico approaches, and facilitating the analysis and interpretation of RNA sequencing data. Here, we present an open repository dedicated to Nile Tilapia miRNAs: the “miRTil database”. The database stores data on 734 mature miRNAs identified in 11 distinct tissues and five key developmental stages. The database provides detailed information about miRNA structure, genomic context, predicted targets, expression profiles, and relative 5p/3p arm usage. Additionally, miRTil also includes a comprehensive pre-computed miRNA-target interaction network containing 4936 targets and 19,580 interactions.
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Yin, Xi, Miao Wang, Wei Wang, Tong Chen, Ge Song, Yixuan Niu, Ziying Jiang, Zhongbao Gao, and Zhenfu Wang. "Identification of Potential miRNA-mRNA Regulatory Network Contributing to Parkinson’s Disease." Parkinson's Disease 2022 (September 5, 2022): 1–12. http://dx.doi.org/10.1155/2022/2877728.
Повний текст джерелаАнотація:
Parkinson’s disease (PD) is a common neurodegenerative disease, and the mechanism underlying PD pathogenesis is not completely understood. Increasing evidence indicates that microRNAs (miRNAs) play a critical regulatory role in the pathogenesis of PD. This study aimed to explore the miRNA-mRNA regulatory network for PD. The differentially expressed miRNAs (DEmis) and genes (DEGs) between PD patients and healthy donors were screened from the miRNA dataset GSE16658 and mRNA dataset GSE100054 downloaded from the Gene Expression Omnibus (GEO) database. Target genes of the DEmis were selected when they were predicted by three or four online databases and overlapped with DEGs from GSE100054. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were then conducted by Database for Annotation, Visualization and Integrated Discovery (DAVID) and Metascape analytic tools. The correlation between the screened genes and PD was evaluated with the online tool Comparative Toxicogenomics Database (CTD), and protein-protein interaction (PPI) networks were built by the STRING platform. We further investigated the expression of genes in the miRNA-mRNA regulatory network in blood samples collected from PD patients and healthy donors via qRT-PCR. We identified 1505 upregulated and 1302 downregulated DEGs, and 77 upregulated and 112 downregulated DEmis were preliminarily screened from the GEO database. Further functional enrichment analysis identified 10 PD-related hub genes, including RAC1, IRS2, LEPR, PPARGC1A, CAMKK2, RAB10, RAB13, RAB27B, RAB11A, and JAK2, which were mainly involved in Rab protein signaling transduction, AMPK signaling pathway, and signaling by Leptin. A miRNA-mRNA regulatory network was then constructed with 10 hub genes, and their interacting miRNAs overlapped with DEmis, including miR-30e-5p, miR-142-3p, miR-101-3p, miR-32-3p, miR-508-5p, miR-642a-5p, miR-19a-3p, and miR-21-5p. Analysis of clinical samples verified significant upregulation of LEPR and downregulation of miR-101-3p and miR-30e-5p in PD patients as compared with healthy donors. Thus, the miRNA-mRNA regulatory network was initially constructed and has the potential to provide novel insights into the pathogenesis and treatment of PD.
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Xiao, Kui, Shenggang Liu, Yijia Xiao, Yang Wang, Zhiruo Zhu, Yaohui Wang, De Tong, and Jiehan Jiang. "Bioinformatics prediction of differential miRNAs in non-small cell lung cancer." PLOS ONE 16, no. 7 (July 21, 2021): e0254854. http://dx.doi.org/10.1371/journal.pone.0254854.
Повний текст джерелаАнотація:
Background Non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancers. The drug resistance of NSCLC has clinically increased. This study aimed to screen miRNAs associated with NSCLC using bioinformatics analysis. We hope that the screened miRNA can provide a research direction for the subsequent treatment of NSCLC. Methods We screened out the common miRNAs after compared the NSCLC-related genes in the TCGA database and GEO database. Selected miRNA was performed ROC analysis, survival analysis, and enrichment analysis (GO term and KEGG pathway). Results A total of 21 miRNAs were screened in the two databases. And they were all highly expressed in normal and low in cancerous tissues. Hsa-mir-30a was selected by ROC analysis and survival analysis. Enrichment analysis showed that the function of hsa-mir-30a is mainly related to cell cycle regulation and drug metabolism. Conclusion Our study found that hsa-mir-30a was differentially expressed in NSCLC, and it mainly affected NSCLC by regulating the cell cycle and drug metabolism.
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Matos de Oliveira, Gabriela Correia, Raymundo Paraná, and Luís Jesuino De Oliveira Andrade. "IN SILICO MODELING OF THE MOLECULAR STRUCTURE OF microRNAs MARKERS FOR LIVER FIBROSIS IN HEPATITIS C." Revista de Patologia Tropical / Journal of Tropical Pathology 48, no. 3 (November 4, 2019): 135–47. http://dx.doi.org/10.5216/rpt.v48i3.58660.
Повний текст джерелаАнотація:
Molecular biology looks for evidence that microRNA (miRNAs) plays a relevant function both in the beginning and advanced stages of hepatic fibrosis (HF), and has been proposed as an additional biomarker for HF forecasting in carriers of hepatitis C virus (HCV) infection. The purpose of this study was to develop an in silico modeling of the two-dimensional (2D) molecular structure of miRNA markers for HF in carriers of HCV. A search was initially performed for the nucleotide sequence of 6 miRNAs defined as biomarkers for HF, performinga computational simulation of the molecular structure of the following miRNAs: miRNA-182, miRNA-183, miRNA-1260b, miRNA-122-3p, miRNA-378i, and miRNA-214-5p. The nucleotide sequences were chosen in the GenBank of the American National Institutes of Health genetic sequence database. The nucleotide sequence alignment was carried out with a text-based format (FASTA) tool. In the molecular modeling, the structures were built with the RNAstructure, a completely automated miRNAs structure modelling server, available through Web Servers for RNA Secondary Structure Prediction. This study presented the nucleotide sequence and the computational simulation of molecular structures for the following miRNA: miRNA-182, miRNA-183, miRNA-1260b, miRNA-122-3p, miRNA-378i, and miRNA-214-5p. The molecular structure of miRNAs markers for HF in HCV carriers, through computational biology, is essential for designing more efficient optional tools for accurate treatment.
KEY WORDS: micro-RNA; Hepatitis C; Hepatic Fibrosis; Computational Biology.
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Yu, Liwei, Tengfei Yao, Zhoulei Jiang, and Tong Xu. "Integrated Analysis of miRNA-mRNA Regulatory Networks Associated with Osteonecrosis of the Femoral Head." Evidence-Based Complementary and Alternative Medicine 2021 (August 12, 2021): 1–11. http://dx.doi.org/10.1155/2021/8076598.
Повний текст джерелаАнотація:
Osteonecrosis of the femoral head (ONFH) accounts for as many as 18% of total hip arthroplasties. Knowledge of genetic changes and molecular abnormalities could help identify individuals considered to be at a higher risk of developing ONFH. In this study, we sought to identify differentially expressed miRNAs (DEmiRs) and genes (DEGs) associated with ONFH by integrated bioinformatics analyses as well as to construct the miRNA-mRNA regulatory network involving in the pathogenesis of ONFH. We performed differential expression analysis using a gene expression profile GSE123568 and a miRNA expression profile GSE89587 deposited in the Gene Expression Omnibus and identified 47 DEmiRs (24 upregulated miRNAs and 23 downregulated miRNAs) and 529 DEGs (218 upregulated genes and 311 downregulated genes). Gene Ontology enrichment analyses of DEGs suggested that DEGs were significantly enriched in neutrophil activation, cytosol, and ubiquitin-protein transferase activity. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of DEGs revealed that DEGs were significantly enriched in transcriptional misregulation in cancer. DEGs-based miRNA-mRNA regulatory networks were obtained by searching miRNA-mRNA prediction databases, TargetScan, miTarBase, miRMap, miRDB, and miRanda databases. Then, overlapped miRNAs were selected between these putative miRNAs and DEmiRs between ONFH and non-ONFH, and pairs of the DEmiR-DEG regulatory network were finally depicted. There were 12 nodes and 64 interactions for upDEmiR-downDEG regulatory networks and 6 nodes and 16 interactions for downDEmiR-upDEG regulatory networks. Using the STRING database, we established a protein-protein interaction network based on the overlapped DEGs between ONFH and non-ONFH. C5AR1, CDC27, CDC34, KAT2B, CPPED1, TFDP1, and MX2 were identified as the hub genes. The present study characterizes the miRNA profile, gene profile, and miRNA-mRNA regulatory network in ONFH, which may contribute to the interpretation of the pathogenesis of ONFH and the identification of novel biomarkers and therapeutic targets for ONFH.
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Zheng, Ming-Jun, Rui Gou, Wen-Chao Zhang, Xin Nie, Jing Wang, Ling-Ling Gao, Juan-Juan Liu, Xiao Li, and Bei Lin. "Screening of prognostic biomarkers for endometrial carcinoma based on a ceRNA network." PeerJ 6 (December 10, 2018): e6091. http://dx.doi.org/10.7717/peerj.6091.
Повний текст джерелаАнотація:
Objective This study aims to reveal the regulation network of lncRNAs-miRNAs-mRNA in endometrial carcinoma (EC), to investigate the underlying mechanisms of EC occurrence and progression, to screen prognostic biomarkers. Methods RNA-seq and miRNA-seq data of endometrial carcinoma were downloaded from the TCGA database. Edge.R package was used to screen differentially expressed genes. A database was searched to determine differentially expressed lncRNA-miRNA and miRNA-mRNA pairs, to construct the topological network of ceRNA, and to elucidate the key RNAs that are for a prognosis of survival. Results We screened out 2632 mRNAs, 1178 lncRNAs and 189 miRNAs that were differentially expressed. The constructed ceRNA network included 97 lncRNAs, 20 miRNAs and 73 mRNAs. Analyzing network genes for associations with prognosies revealed 169 prognosis-associated RNAs, including 92 lncRNAs, 16miRNAs and 61 mRNAs. Conclusion Our results reveal new potential mechanisms underlying the carcinogenesis and progression of endometrial carcinoma.
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Shu, Xin, Xinyuan Zang, Xiaoshuang Liu, Jie Yang, and Jin Wang. "Predicting MicroRNA Mediated Gene Regulation between Human and Viruses." Cells 7, no. 8 (August 8, 2018): 100. http://dx.doi.org/10.3390/cells7080100.
Повний текст джерелаАнотація:
MicroRNAs (miRNAs) mediate various biological processes by actively fine-tuning gene expression at the post-transcriptional level. With the identification of numerous human and viral miRNAs, growing evidence has indicated a common role of miRNAs in mediating the interactions between humans and viruses. However, there is only limited information about Cross-Kingdom miRNA target sites from studies. To facilitate an extensive investigation on the interplay among the gene regulatory networks of humans and viruses, we designed a prediction pipeline, mirTarP, that is suitable for miRNA target screening on the genome scale. By applying mirTarP, we constructed the database mirTar, which is a comprehensive miRNA target repository of bidirectional interspecies regulation between viruses and humans. To provide convenient downloading for users from both the molecular biology field and medical field, mirTar classifies viruses according to “ICTV viral category” and the “medical microbiology classification” on the web page. The mirTar database and mirTarP tool are freely available online.
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Chien, Chia-Hung, Yi-Fan Chiang-Hsieh, Ann-Ping Tsou, Shun-Long Weng, Wen-Chi Chang, and Hsien-Da Huang. "Large-Scale Investigation of Human TF-miRNA Relations Based on Coexpression Profiles." BioMed Research International 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/623078.
Повний текст джерелаАнотація:
Noncoding, endogenous microRNAs (miRNAs) are fairly well known for regulating gene expression rather than protein coding. Dysregulation of miRNA gene, either upregulated or downregulated, may lead to severe diseases or oncogenesis, especially when the miRNA disorder involves significant bioreactions or pathways. Thus, how miRNA genes are transcriptionally regulated has been highlighted as well as target recognition in recent years. In this study, a large-scale investigation of novelcis- andtrans-elements was undertaken to further determine TF-miRNA regulatory relations, which are necessary to unravel the transcriptional regulation of miRNA genes. Based on miRNA and annotated gene expression profiles, the term “coTFBS” was introduced to detect common transcription factors and the corresponding binding sites within the promoter regions of each miRNA and its coexpressed annotated genes. The computational pipeline was successfully established to filter redundancy due to short sequence motifs for TFBS pattern search. Eventually, we identified more convinced TF-miRNA regulatory relations for 225 human miRNAs. This valuable information is helpful in understanding miRNA functions and provides knowledge to evaluate the therapeutic potential in clinical research. Once most expression profiles of miRNAs in the latest database are completed, TF candidates of more miRNAs can be explored by this filtering approach in the future.
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Wang, Xianyue, Hong Jiang, Wei Wu, Rongxin Zhang, Lingxiang Wu, Huan Chen, Pengping Li, et al. "An Integrating Approach for Genome-Wide Screening of MicroRNA Polymorphisms Mediated Drug Response Alterations." International Journal of Genomics 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/1674827.
Повний текст джерелаАнотація:
MicroRNAs (miRNAs) are a class of evolutionarily conserved small noncoding RNAs, ~22 nt in length, and found in diverse organisms and play important roles in the regulation of mRNA translation and degradation. It was shown that miRNAs were involved in many key biological processes through regulating the expression of targets. Genetic polymorphisms in miRNA target sites may alter miRNA regulation and therefore result in the alterations of the drug targets. Recent studies have demonstrated that SNPs in miRNA target sites can affect drug efficiency. However, there are still a large number of specific genetic variants related to drug efficiency that are yet to be discovered. We integrated large scale of genetic variations, drug targets, gene interaction networks, biological pathways, and seeds region of miRNA to identify miRNA polymorphisms affecting drug response. In addition, harnessing the abundant high quality biological network/pathways, we evaluated the cascade distribution of tarSNP impacts. We showed that the predictions can uncover most of the known experimentally supported cases as well as provide informative candidates complementary to existing methods/tools. Although there are several existing databases predicting the gain or loss of targeting function of miRNA mediated by SNPs, such as PolymiRTS, miRNASNP, MicroSNiPer, and MirSNP, none of them evaluated the influences of tarSNPs on drug response alterations. We developed a user-friendly online database of this approach named Mir2Drug.
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Kamenova, Saltanat, Aksholpan Sharapkhanova, Aigul Akimniyazova, Karlygash Kuzhybayeva, Aida Kondybayeva, Aizhan Rakhmetullina, Anna Pyrkova, and Anatoliy Ivashchenko. "piRNA and miRNA can Suppress the Expression of Multiple Sclerosis Candidate Genes." Nanomaterials 13, no. 1 (December 21, 2022): 22. http://dx.doi.org/10.3390/nano13010022.
Повний текст джерелаАнотація:
Multiple sclerosis (MS) is a common inflammatory demyelinating disease with a high mortality rate. MS is caused by many candidate genes whose specific involvement has yet to be established. The aim of our study was to identify endogenous miRNAs and piRNAs involved in the regulation of MS candidate gene expression using bioinformatic methods. A program was used to quantify the interaction of miRNA and piRNA nucleotides with mRNA of the target genes. We used 7310 miRNAs from three databases and 40,000 piRNAs. The mRNAs of the candidate genes revealed miRNA binding sites (BSs), which were located separately or formed clusters of BSs with overlapping nucleotide sequences. The miRNAs from the studied databases were generally bound to mRNAs in different combinations, but miRNAs from only one database were bound to the mRNAs of some genes. For the first time, a direct interaction between the complete sequence of piRNA nucleotides and the nucleotides of their mRNA BSs of target genes was shown. One to several clusters of BSs of miRNA and piRNA were identified in the mRNA of ADAM17, AHI1, CD226, EOMES, EVI5, IL12B, IL2RA, KIF21B, MGAT5, MLANA, SOX8, TNFRSF1A, and ZBTB46 MS candidate genes. These piRNAs form the expression regulation system of the MS candidate genes to coordinate the synthesis of their proteins. Based on these findings, associations of miRNAs, piRNAs, and candidate genes for MS diagnosis are recommended.
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Nie, Jin, Ling Gong, Zhu Li, Dong Ou, Ling Zhang, Yi Liu, Jianyong Zhang, and Daishun Liu. "Bioinformatics Analysis of mRNAs and miRNAs for Identifying Potential Biomarkers in Lung Adenosquamous Carcinoma." Computational and Mathematical Methods in Medicine 2022 (March 2, 2022): 1–12. http://dx.doi.org/10.1155/2022/5851269.
Повний текст джерелаАнотація:
Background. Lung adenosquamous carcinoma (LASC) is a special type of lung cancer. LASC is a malignant tumor with strong aggressiveness and a poor prognosis. Previous studies have revealed that microRNAs (miRNAs) are widely involved in the development of tumors by targeting mRNA. This study is aimed at identifying the key mRNAs and miRNAs of LASC and constructing miRNA-mRNA networks for deeply comprehending the latent molecular mechanisms. Methods. mRNA dataset (GSE51852) and miRNA dataset (GSE51853) were extracted and downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were picked out by the GEO2R web tool. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted in the DAVID database. The protein-protein interaction (PPI) network was performed and analyzed by using the STRING database and Cytoscape software, respectively. TransmiR v2.0 was applied to predict potential transcription factors of miRNAs. The target genes of DEMs were predicted in the miRWalk database. Results. In comparison to normal tissues, a total of 1458 DEGs (511 upregulated and 947 downregulated) and 13 DEMs (5 upregulated and 8 downregulated) were screened out in LASC tissues. The PPI network of the DEGs displayed five key modules and seventeen hub genes. Six target genes of the DEMs were predicted, and five essential miRNA-mRNA regulatory pairs were established. Ensuingly, CENPF, one of the target genes, was also the hub genes of GSE51852, which was obtained from MCODE and cytoHubba and regulated by hsa-miR-205. Conclusions. We constructed the miRNA-mRNA regulatory pairs, which are helpful to study the potential regulatory mechanisms and find out promising diagnosis biomarkers and therapeutic targets for LASC.
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Son, Ju Cheol, Hyoung Oh Jeong, Deaui Park, Sang Gyoon No, Eun Kyeong Lee, Jaewon Lee, and Hae Young Chung. "miR-10a and miR-204 as a Potential Prognostic Indicator in Low-Grade Gliomas." Cancer Informatics 16 (January 1, 2017): 117693511770287. http://dx.doi.org/10.1177/1176935117702878.
Повний текст джерелаАнотація:
This study aimed to identify and characterize microRNAs (miRNAs) that are related to radiosensitivity in low-grade gliomas (LGGs). The miRNA expression levels in radiosensitive and radioresistant LGGs were compared using The Cancer Genome Atlas database, and differentially expressed miRNAs were identified using the EBSeq package. The miRNA target genes were predicted using Web databases. Fifteen miRNAs were differentially expressed between the groups, with miR-10a and miR-204 being related to overall survival (OS) of patients with LGG. Patients with upregulated miR-10a expression had a higher mortality rate and shorter OS time, whereas patients with downregulated miR-204 expression had a lower mortality rate and longer OS time. Two genes, HSP90AA1 and CREB5, were targets for both miRNAs. Thus, this study suggests that expression of miR-10a and miR-204 is significantly related to both radiosensitivity and the survival of patients with LGG. These miRNAs could therefore act as clinical biomarkers for LGG prognosis and diagnosis.
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Biswas, Manosh Kumar, Dhiman Biswas, Mita Bagchi, Ganjun Yi, and Guiming Deng. "A Comprehensive Plant microRNA Simple Sequence Repeat Marker Database to Accelerate Genetic Improvements in Crops." Agronomy 11, no. 11 (November 13, 2021): 2298. http://dx.doi.org/10.3390/agronomy11112298.
Повний текст джерелаАнотація:
Microsatellites, or simple sequences repeat (SSRs), are distributed in genes, intergenic regions and transposable elements in the genome. SSRs were identified for developing markers from draft genome assemblies, transcriptome sequences and genome survey sequences in plant and animals. The identification, distribution, and density of microsatellites in pre-microRNAs (miRNAs) are not well documented in plants. In this study, SSRs were identified in 16,892 pre-miRNA sequences from 292 plant species in six taxonomic groups (algae to dicots). Fifty-one percent of pre-miRNA sequences contained SSRs. Mononucleotide repeats were the most abundant, followed by di- and trinucleotide repeats. Tetra-, penta-, and hexarepeats were rare. A total of 9,498 (57.46%) microsatellite loci had potential as pre-miRNA SSR markers. Of the markers, 3,573 (37.62%) were non-redundant, and 2,341 (65.51%) primer pairs could be transferred to at least one of the plant taxonomic groups. All data and primer pairs were deposited in a user-friendly, freely accessible plant miRNA SSR marker database. The data presented in this study, accelerate the understanding of pre-miRNA evolution and serve as valuable genomic treasure for genetic improvements in a wide range of crops, including legumes, cereals, and cruciferous crops.
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Major, Jennifer L., Rushita A. Bagchi, and Julie Pires da Silva. "Application of microRNA Database Mining in Biomarker Discovery and Identification of Therapeutic Targets for Complex Disease." Methods and Protocols 4, no. 1 (December 30, 2020): 5. http://dx.doi.org/10.3390/mps4010005.
Повний текст джерелаАнотація:
Over the past two decades, it has become increasingly evident that microRNAs (miRNA) play a major role in human diseases such as cancer and cardiovascular diseases. Moreover, their easy detection in circulation has made them a tantalizing target for biomarkers of disease. This surge in interest has led to the accumulation of a vast amount of miRNA expression data, prediction tools, and repositories. We used the Human microRNA Disease Database (HMDD) to discover miRNAs which shared expression patterns in the related diseases of ischemia/reperfusion injury, coronary artery disease, stroke, and obesity as a model to identify miRNA candidates for biomarker and/or therapeutic intervention in complex human diseases. Our analysis identified a single miRNA, hsa-miR-21, which was casually linked to all four pathologies, and numerous others which have been detected in the circulation in more than one of the diseases. Target analysis revealed that hsa-miR-21 can regulate a number of genes related to inflammation and cell growth/death which are major underlying mechanisms of these related diseases. Our study demonstrates a model for researchers to use HMDD in combination with gene analysis tools to identify miRNAs which could serve as biomarkers and/or therapeutic targets of complex human diseases.
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Wilson, Michael, Nan Leng, Sachin Sah, Edward Sekinger, Frederick Fletcher, and Charles Johnson. "A High-Density MicroRNA Array for Analyzing the Expression of 15,090 Verified and Predicted Small, Non-Coding RNAs." Blood 108, no. 11 (November 16, 2006): 4210. http://dx.doi.org/10.1182/blood.v108.11.4210.4210.
Повний текст джерелаАнотація:
Abstract We have designed and evaluated the performance of a custom Affymetrix microRNA (miRNA) microarray that enables the analysis of 15,090 unique mature miRNAs that are predicted or biologically verified. The comprehensive probe content of the array was selected from multiple sources including the Sanger miRBase sequence database (version 8.0), published reports, and a proprietary database of predicted miRNAs. Most of the ~31,000 25-mer probes on the array were designed by selecting two overlapping oligonucleotide sequences that span the mature miRNA sequences and a portion of the flanking precursors (pre-miRs). We also included antisense control probes as well as probes that target the predicted hairpin loop region of the pre-miR for a subset of well-characterized human miRNAs. We evaluated the array performance using a model system of two total RNA reference standards isolated from different tissues that were mixed in calibrated ratios. The custom array performance was compared to an enhanced mirVana™ miRNA Bioarray, using the same calibrated mixtures of reference RNAs. We assessed the reproducibility, relative sensitivity, dynamic range and concordance between the results from the two platforms. The performance of the two platforms was similar, with both platforms reliably detecting differential miRNA expression. For those miRNAs that are represented on both platforms, there was a strong correlation of the log2 ratios of differential expression levels between the RNA reference standards. Many of the miRNAs with detectable expression signals were novel predicted miRNAs derived from bioinformatic exploration of human genomic sequence data. This provides initial evidence that some of the predicted miRNAs are expressed in tissues and, therefore, may function as regulators by mechanisms consistent with other well-characterized miRNAs. In summary, our data illustrate the technological and biological feasibility of the custom high-density miRNA microarray for the comprehensive identification and global expression profiling of novel miRNAs.
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Wang, Ying, Jidong Ru, Xianglian Meng, Jianhua Song, Qingfeng Jiang, Shengqing Li, Jiulei Jiang, and Yi Li. "Role of SNPs in the Biogenesis of Mature miRNAs." BioMed Research International 2021 (June 17, 2021): 1–13. http://dx.doi.org/10.1155/2021/2403418.
Повний текст джерелаАнотація:
Single nucleotide polymorphisms (SNPs) play a significant role in microRNA (miRNA) generation, processing, and function and contribute to multiple phenotypes and diseases. Therefore, whole-genome analysis of how SNPs affect miRNA maturation mechanisms is important for precision medicine. The present study established an SNP-associated pre-miRNA (SNP-pre-miRNA) database, named miRSNPBase, and constructed SNP-pre-miRNA sequences. We also identified phenotypes and disease biomarker-associated isoform miRNA (isomiR) based on miRFind, which was developed in our previous study. We identified functional SNPs and isomiRs. We analyzed the biological characteristics of functional SNPs and isomiRs and studied their distribution in different ethnic groups using whole-genome analysis. Notably, we used individuals from Great Britain (GBR) as examples and identified isomiRs and isomiR-associated SNPs (iso-SNPs). We performed sequence alignments of isomiRs and miRNA sequencing data to verify the identified isomiRs and further revealed GBR ethnographic epigenetic dominant biomarkers. The SNP-pre-miRNA database consisted of 886 pre-miRNAs and 2640 SNPs. We analyzed the effects of SNP type, SNP location, and SNP-mediated free energy change during mature miRNA biogenesis and found that these factors were closely associated to mature miRNA biogenesis. Remarkably, 158 isomiRs were verified in the miRNA sequencing data for the 18 GBR samples. Our results indicated that SNPs affected the mature miRNA processing mechanism and contributed to the production of isomiRs. This mechanism may have important significance for epigenetic changes and diseases.
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Zhao, Haochen, Linai Kuang, Xiang Fen, Quan Zou, and Lei Wang. "A Novel Approach Based on a Weighted Interactive Network to Predict Associations of MiRNAs and Diseases." International Journal of Molecular Sciences 20, no. 1 (December 28, 2018): 110. http://dx.doi.org/10.3390/ijms20010110.
Повний текст джерелаАнотація:
Accumulating evidence progressively indicated that microRNAs (miRNAs) play a significant role in the pathogenesis of diseases through many experimental studies; therefore, developing powerful computational models to identify potential human miRNA–disease associations is vital for an understanding of the disease etiology and pathogenesis. In this paper, a weighted interactive network was firstly constructed by combining known miRNA–disease associations, as well as the integrated similarity between diseases and the integrated similarity between miRNAs. Then, a new computational method implementing the newly weighted interactive network was developed for discovering potential miRNA–disease associations (WINMDA) by integrating the T most similar neighbors and the shortest path algorithm. Simulation results show that WINMDA can achieve reliable area under the receiver operating characteristics (ROC) curve (AUC) results of 0.9183 ± 0.0007 in 5-fold cross-validation, 0.9200 ± 0.0004 in 10-fold cross-validation, 0.9243 in global leave-one-out cross-validation (LOOCV), and 0.8856 in local LOOCV. Furthermore, case studies of colon neoplasms, gastric neoplasms, and prostate neoplasms based on the Human microRNA Disease Database (HMDD) database were implemented, for which 94% (colon neoplasms), 96% (gastric neoplasms), and 96% (prostate neoplasms) of the top 50 predicting miRNAs were confirmed by recent experimental reports, which also demonstrates that WINMDA can effectively uncover potential miRNA–disease associations.
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Thomas, John P., Marton Ölbei, Johanne Brooks-Warburton, Tamas Korcsmaros, and Dezso Modos. "Analysing miRNA-Target Gene Networks in Inflammatory Bowel Disease and Other Complex Diseases Using Transcriptomic Data." Genes 13, no. 2 (February 18, 2022): 370. http://dx.doi.org/10.3390/genes13020370.
Повний текст джерелаАнотація:
Patients with inflammatory bowel disease (IBD) are known to have perturbations in microRNA (miRNA) levels as well as altered miRNA regulation. Although experimental methods have provided initial insights into the functional consequences that may arise due to these changes, researchers are increasingly utilising novel bioinformatics approaches to further dissect the role of miRNAs in IBD. The recent exponential increase in transcriptomics datasets provides an excellent opportunity to further explore the role of miRNAs in IBD pathogenesis. To effectively understand miRNA-target gene interactions from gene expression data, multiple database resources are required, which have become available in recent years. In this technical note, we provide a step-by-step protocol for utilising these state-of-the-art resources, as well as systems biology approaches to understand the role of miRNAs in complex disease pathogenesis. We demonstrate through a case study example how to combine the resulting miRNA-target gene networks with transcriptomics data to find potential disease-specific miRNA regulators and miRNA-target genes in Crohn’s disease. This approach could help to identify miRNAs that may have important disease-modifying effects in IBD and other complex disorders, and facilitate the discovery of novel therapeutic targets.
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Gurjar, Anoop Kishor Singh, Abhijeet Singh Panwar, Rajinder Gupta, and Shrikant S. Mantri. "PmiRExAt: plant miRNA expression atlas database and web applications." Database 2016 (2016): baw060. http://dx.doi.org/10.1093/database/baw060.
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Yang, Yun, Xin Xin, and Ting Xu. "Identification of Potential miRNA-mRNA Regulatory Network in the Development of Oral Cancer." Disease Markers 2022 (August 18, 2022): 1–8. http://dx.doi.org/10.1155/2022/9376608.
Повний текст джерелаАнотація:
Background. Oral cancer is a difficult question in modern medical system, and there are few effective strategies to completely heal these diseases. This research investigated the miRNA-mRNA network in oral cancer development via bioinformatics excavation. Methods. GSE28100 and GSE23558 in the GEO database were selected for bioinformatics analysis. The datasets were analyzed with GEO2R to obtain the related matrix files. The hot plot and heatmap of the matrix files were drawn with R language. The MiRDIP database was applied to predict and screen the targets of miRNAs. The DEGs in the matrix files were analyzed with the DAVID database and visualized with R language for enrichment analysis. The PPI-network of the DEGs was established with the STRING database and Cytoscape. Besides, the miRNA-mRNA was visualized by Cytoscape. Results. 35 genes were identified as the DEGs in GES28100. 1651 genes were identified as the DEGs in GSE23558. 143 common genes in the targets of miRNAs in GSE28100 and the DEGs in GSE the targets of DEGs in GES28100 and common genes were enriched in the PI3K/AKT pathway, MAPK pathway, etc. The DEGs in GSE28100 and GSE23558 were involved in the regulations of transcription from RNA polymerase II promoter and DNA transcription. The DEGs in GSE28100 and GSE23558 were established with the miRNA-mRNA network. Conclusion. This research identified miR-15b-5p, miR-199a-3p, miR-21-5p, miR-424-5p, and miR-454-3p as the biomarker of oral cancer and established the miRNA-mRNA network in oral progression.
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Nie, Renqing, Wenling Niu, Tang Tang, Jin Zhang, and Xiaoyi Zhang. "Integrating microRNA expression, miRNA-mRNA regulation network and signal pathway: a novel strategy for lung cancer biomarker discovery." PeerJ 9 (October 25, 2021): e12369. http://dx.doi.org/10.7717/peerj.12369.
Повний текст джерелаАнотація:
Background Since there are inextricably connections among molecules in the biological networks, it would be a more efficient and accurate research strategy to screen microRNA (miRNA) markers combining with miRNA-mRNA regulatory networks. The independent regulation mode is more “fragile” and “influential” than the co-regulation mode. miRNAs can be used as biomarkers if they can independently regulate hub genes with important roles in the PPI network, simultaneously the expression products of the regulated hub genes play important roles in the signaling pathways of related tissue diseases. Methods We collected miRNA expression of non-small cell lung cancer (NSCLC) from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Volcano plot and signal-to-noise ratio (SNR) methods were used to obtain significant differentially expressed (SDE) miRNAs from the TCGA database and GEO database, respectively. A human miRNA-mRNA regulatory network was constructed and the number of genes uniquely targeted (NOG) by a certain miRNA was calculated. The area under the curve (AUC) values were used to screen for clinical sensitivity and specificity. The candidate markers were obtained using the criteria of the top five maximum AUC values and NOG ≥ 3. The protein–protein interaction (PPI) network was constructed and independently regulated hub genes were obtained. Gene Ontology (GO) analysis and KEGG pathway analysis were used to identify genes involved in cancer-related pathways. Finally, the miRNA which can independently regulate a hub gene and the hub gene can participate in an important cancer-related pathway was considered as a biomarker. The AUC values and gene expression profile analysis from two external GEO datasets as well as literature validation were used to verify the screening capability and reliability of this marker. Results Fifteen SDE miRNAs in lung cancer were obtained from the intersection of volcano plot and SNR based on the GEO database and the TCGA database. Five miRNAs with the top five maximum AUC values and NOG ≥ 3 were screened out. A total of 61 hub genes were obtained from the PPI network. It was found that the hub gene GTF2F2 was independently regulated by miR-708-5p. Further pathway analysis indicated that GTF2F2 participates in protein expression by binding with polymerase II, and it can regulate transcription and accelerate tumor growth. Hence, miR-708-5p could be used as a biomarker. The good screening capability and reliability of miR-708-5p as a lung cancer marker were confirmed by AUC values and gene expression profiling of external datasets, and experimental literature. The potential mechanism of miR-708-5p was proposed. Conclusions This study proposes a new idea for lung cancer marker screening by integrating microRNA expression, regulation network and signal pathway. miR-708-5p was identified as a biomarker using this novel strategy. This study may provide some help for cancer marker screening.
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Wu, KunZhe, ChunDong Zhang, Cheng Zhang, and DongQiu Dai. "A Novel Three-miRNA Signature Identified Using Bioinformatics Predicts Survival in Esophageal Carcinoma." BioMed Research International 2020 (February 10, 2020): 1–11. http://dx.doi.org/10.1155/2020/5973082.
Повний текст джерелаАнотація:
Objective. We identified differentially expressed microRNAs (DEMs) between esophageal carcinoma (ESCA) tissues and normal esophageal tissues. We then constructed a novel three-miRNA signature to predict the prognosis of ESCA patients using bioinformatics analysis. Materials and Methods. We combined two microarray profiling datasets from the Gene Expression Omnibus (GEO) database and RNA-seq datasets from the Cancer Genome Atlas (TCGA) database to analyze DEMs in ESCA. The clinical data from 168 ESCA patients were selected from the TCGA database to assess the prognostic role of the DEMs. The TargetScan, miRDB, miRWalk, and DIANA websites were used to predict the miRNA target genes. Functional enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery (David), and protein-protein interaction (PPI) networks were obtained using the Search Tool for the Retrieval of Interacting Genes database (STRING). Results. With cut-off criteria of P<0.05 and |log2FC| > 1.0, 33 overlapping DEMs, including 27 upregulated and 6 downregulated miRNAs, were identified from GEO microarray datasets and TCGA RNA-seq count datasets. The Kaplan–Meier survival analysis indicated that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) was significantly associated with the overall survival of ESCA patients. The results of univariate and multivariate Cox regression analysis showed that the three-miRNA signature was a potential prognostic factor in ESCA. Furthermore, the gene functional enrichment analysis revealed that the target genes of the three miRNAs participate in various cancer-related pathways, including viral carcinogenesis, forkhead box O (FoxO), vascular endothelial growth factor (VEGF), human epidermal growth factor receptor 2 (ErbB2), and mammalian target of rapamycin (mTOR) signaling pathways. In the PPI network, three target genes (MAPK1, RB1, and CLTC) with a high degree of connectivity were selected as hub genes. Conclusions. Our results revealed that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) is a potential novel prognostic biomarker for ESCA.
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Wang, Huiyuan, Huihui Wang, Hangxiao Zhang, Sheng Liu, Yongsheng Wang, Yubang Gao, Feihu Xi, et al. "The interplay between microRNA and alternative splicing of linear and circular RNAs in eleven plant species." Bioinformatics 35, no. 17 (January 24, 2019): 3119–26. http://dx.doi.org/10.1093/bioinformatics/btz038.
Повний текст джерелаАнотація:
Abstract Motivation MicroRNA (miRNA) and alternative splicing (AS)-mediated post-transcriptional regulation has been extensively studied in most eukaryotes. However, the interplay between AS and miRNAs has not been explored in plants. To our knowledge, the overall profile of miRNA target sites in circular RNAs (circRNA) generated by alternative back splicing has never been reported previously. To address the challenge, we identified miRNA target sites located in alternatively spliced regions of the linear and circular splice isoforms using the up-to-date single-molecule real-time (SMRT) isoform sequencing (Iso-Seq) and Illumina sequencing data in eleven plant species. Results In total, we identified 399 401 and 114 574 AS events from linear and circular RNAs, respectively. Among them, there were 64 781 and 41 146 miRNA target sites located in linear and circular AS region, respectively. In addition, we found 38 913 circRNAs to be overlapping with 45 648 AS events of its own parent isoforms, suggesting circRNA regulation of AS of linear RNAs by forming R-loop with the genomic locus. Here, we present a comprehensive database of miRNA targets in alternatively spliced linear and circRNAs (ASmiR) and a web server for deposition and identification of miRNA target sites located in the alternatively spliced region of linear and circular RNAs. This database is accompanied by an easy-to-use web query interface for meaningful downstream analysis. Plant research community can submit user-defined datasets to the web service to search AS regions harboring small RNA target sites. In conclusion, this study provides an unprecedented resource to understand regulatory relationships between miRNAs and AS in both gymnosperms and angiosperms. Availability and implementation The readily accessible database and web-based tools are available at http://forestry.fafu.edu.cn/bioinfor/db/ASmiR. Supplementary information Supplementary data are available at Bioinformatics online.
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Ma, Jinhua, Xiaodong Hu, Baoqiang Dai, Qiang Wang, and Hongqin Wang. "Prediction of the mechanism of miRNAs in laryngeal squamous cell carcinoma based on the miRNA-mRNA regulatory network." PeerJ 9 (August 24, 2021): e12075. http://dx.doi.org/10.7717/peerj.12075.
Повний текст джерелаАнотація:
In this study, a bioinformatics analysis is conducted to screen differentially expressed miRNAs and mRNAs in laryngeal squamous cell carcinoma (LSCC). Based on this information, we explored the possible roles of miRNAs in the pathogenesis of LSCC. The RNA-Seq data from 79 laryngeal cancer samples in the Gene Expression Omnibus (GEO) database were sorted. Differentially expressed miRNAs and mRNAs in LSCC are screened using the PERL programming language, and it was analysed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The miRNA-mRNA regulatory network of LSCC is constructed using Cytoscape software. Then, quantitative real-time PCR (QRT- PCR), Cell Counting Kit-8 (CCK8) and flow cytometry analysis we are used to further validate key miRNAs. We identified 99 differentially expressed miRNAs and 2,758 differentially expressed mRNAs in LSCC tissues from the GEO database. Four more important miRNAs displaying a high degree of connectivity are selected, these results suggest that they play an important role in the pathogenesis of LSCC. As shown in the present study, we identified specific miRNA-mRNA networks associated with the occurrence and development of LSCC through bioinformatics analysis. We found a miRNA molecule closely related to LSCC based on miRNA-mRNA network: miR-140-3p was down-regulated in LSCC. In addition, the potential antitumor effect of miR-140-3p in LSCC was verified in the experiment, and it was proved that overexpression of miR-140-3p could inhibit the proliferation of LSCC cells and promote cell apoptosis, suggesting that miR-140-3p may be a potential tumor marker in LSCC.
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Li, Mingxin, Yu Fan, Yiting Zhang, and Zhibin Lv. "Using Sequence Similarity Based on CKSNP Features and a Graph Neural Network Model to Identify miRNA–Disease Associations." Genes 13, no. 10 (September 28, 2022): 1759. http://dx.doi.org/10.3390/genes13101759.
Повний текст джерелаАнотація:
Among many machine learning models for analyzing the relationship between miRNAs and diseases, the prediction results are optimized by establishing different machine learning models, and less attention is paid to the feature information contained in the miRNA sequence itself. This study focused on the impact of the different feature information of miRNA sequences on the relationship between miRNA and disease. It was found that when the graph neural network used was the same and the miRNA features based on the K-spacer nucleic acid pair composition (CKSNAP) feature were adopted, a better graph neural network prediction model of miRNA–disease relationship could be built (AUC = 93.71%), which was 0.15% greater than the best model in the literature based on the same benchmark dataset. The optimized model was also used to predict miRNAs related to lung tumors, esophageal tumors, and kidney tumors, and 47, 47, and 37 of the top 50 miRNAs related to three diseases predicted separately by the model were consistent with descriptions in the wet experiment validation database (dbDEMC).
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Langi, Gladys, Lukasz Szczerbinski, and Adam Kretowski. "Meta-Analysis of Differential miRNA Expression after Bariatric Surgery." Journal of Clinical Medicine 8, no. 8 (August 15, 2019): 1220. http://dx.doi.org/10.3390/jcm8081220.
Повний текст джерелаАнотація:
Bariatric surgery is an efficient treatment for weight loss in obese patients and for resolving obesity comorbidities. However, the mechanisms behind these outcomes are unclear. Recent studies have indicated significant alterations in the transcriptome after surgery, specifically in the differential expression of microRNAs. In order to summarize the recent findings, we conducted a systematic summary of studies comparing microRNA expression levels before and after surgery. We identified 17 animal model and human studies from four databases (Ovid, Scopus, Web of Science, and PubMed) to be enrolled in this meta-analysis. From these studies, we identified 14 miRNAs which had the same direction of modulation of their expression after surgery in at least two studies (downregulated: hsa-miR-93-5p, hsa-miR-106b-5p, hsa-let-7b-5p, hsa-let-7i-5p, hsa-miR-16-5p, hsa-miR-19b-3p, hsa-miR-92a-3p, hsa-miR-222-3p, hsa-miR-142-3p, hsa-miR-140-5p, hsa-miR-155-5p, rno-miR-320-3p; upregulated: hsa-miR-7-5p, hsa-miR-320c). Pathway analysis for these miRNAs was done using database resources (DIANA-TarBase and KEGG pathway database) and their predicted target genes were discussed in relation with obesity and its comorbidities. Discrepancies in study design, such as miRNA source, bariatric surgery type, time of observation after surgery, and miRNA profiling methods, were also discussed.