scholarly journals Functional analysis of long intergenic non-coding RNAs in phosphate-starved rice using competing endogenous RNA network

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Xi-Wen Xu ◽  
Xiong-Hui Zhou ◽  
Rui-Ru Wang ◽  
Wen-Lei Peng ◽  
Yue An ◽  
...  
Keyword(s):  
Functional Analysis ◽  
Competing Endogenous Rna ◽  
Competing Endogenous Rna Network ◽  
Non Coding Rnas

scholarly journals Construction of asthma related competing endogenous RNA network revealed novel long non-coding RNAs and potential new drugs

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Yifang Liao ◽  
Ping Li ◽  
Yanxia Wang ◽  
Hong Chen ◽  
Shangwei Ning ◽  
...  
Keyword(s):  
Gene Expression ◽  
Drug Repositioning ◽  
New Drugs ◽  
Differentially Expressed ◽  
Interaction Data ◽  
Competing Endogenous Rna ◽  
Non Coding Rna ◽  
Competing Endogenous Rna Network ◽  
Non Coding Rnas ◽  
Long Non Coding Rna

Abstract Background Asthma is a heterogeneous disease characterized by chronic airway inflammation. Long non-coding RNA can act as competing endogenous RNA to mRNA, and play significant role in many diseases. However, there is little known about the profiles of long non-coding RNA and the long non-coding RNA related competing endogenous RNA network in asthma. In current study, we aimed to explore the long non-coding RNA-microRNA-mRNA competing endogenous RNA network in asthma and their potential implications for therapy and prognosis. Methods Asthma-related gene expression profiles were downloaded from the Gene Expression Omnibus database, re-annotated with these genes and identified for asthma-associated differentially expressed mRNAs and long non-coding RNAs. The long non-coding RNA-miRNA interaction data and mRNA-miRNA interaction data were downloaded using the starBase database to construct a long non-coding RNA-miRNA-mRNA global competing endogenous RNA network and extract asthma-related differentially expressed competing endogenous RNA network. Finally, functional enrichment analysis and drug repositioning of asthma-associated differentially expressed competing endogenous RNA networks were performed to further identify key long non-coding RNAs and potential therapeutics associated with asthma. Results This study constructed an asthma-associated competing endogenous RNA network, determined 5 key long non-coding RNAs (MALAT1, MIR17HG, CASC2, MAGI2-AS3, DAPK1-IT1) and identified 8 potential new drugs (Tamoxifen, Ruxolitinib, Tretinoin, Quercetin, Dasatinib, Levocarnitine, Niflumic Acid, Glyburide). Conclusions The results suggested that long non-coding RNA played an important role in asthma, and these novel long non-coding RNAs could be potential therapeutic target and prognostic biomarkers. At the same time, potential new drugs for asthma treatment have been discovered through drug repositioning techniques, providing a new direction for the treatment of asthma.

scholarly journals Genome-wide characterization of coding and non-coding RNAs in the ovary of honeybee workers and queens

Apidologie ◽  
2020 ◽  
Vol 51 (5) ◽  
pp. 777-792
Author(s):  
Xiao Chen ◽  
Wei Shi
Keyword(s):  
Egg Laying ◽  
Differentially Expressed ◽  
Sequencing Data ◽  
Competing Endogenous Rna ◽  
Genome Wide ◽  
Competing Endogenous Rna Network ◽  
Non Coding Rnas ◽  
Virgin Queens ◽  
Potential Interactions

Abstract Adult honeybee queens and workers drastically differ in ovary state and ovary size. However, this reproductive bias is only partially understood from the view of a single RNA type. In this study, we predicted 10,271 mRNAs, 7235 lncRNAs, 11,794 circRNAs, and 164 miRNAs in the ovary of honeybee workers through bioinformatics. Combining RNA sequencing data of honeybee virgin queens, 4385 mRNAs, 2390 lncRNAs, 5602 circRNAs, and 75 miRNAs were differentially expressed in workers compared with virgins. Compared with egg-laying queens, 6536 mRNAs, 3130 lncRNAs, 5751 circRNAs, and 81 miRNAs were differentially expressed in workers. Further, functional annotation revealed that neural regulation was closely related to ovary state. Moreover, the potential interactions among circRNAs, miRNAs, lncRNAs, and mRNAs revealed that vitellogenin, ecdysone-induced protein 74, ame_circ_0001176, and ame_circ_0001243 might play critical roles in the competing endogenous RNA network. These findings suggest that the integrative RNA networks have potential effects in ovarian phenotype differences in honeybees.

scholarly journals H19- and hsa-miR-338-3p-mediated NRP1 expression is an independent predictor of poor prognosis in glioblastoma

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260103
Author(s):  
Yong Liu ◽  
Yuelin Liu ◽  
Yong Gao ◽  
Lei Wang ◽  
Hengliang Shi ◽  
...  
Keyword(s):  
Operating Characteristic ◽  
Independent Predictor ◽  
Clinical Diagnostics ◽  
Competing Endogenous Rna ◽  
Kaplan Meier ◽  
Competing Endogenous Rna Network ◽  
Non Coding Rnas ◽  
Patient Prognosis ◽  
Cox Analysis ◽  
Improve Patient

Glioblastoma multiforme (GBM) is the most common and also the most invasive brain cancer. GBM progression is rapid and its prognosis is poor. Therefore, finding molecular targets in GBM is a critical goal that could also play important roles in clinical diagnostics and treatments to improve patient prognosis. We jointly analyzed the GSE103227, GSE103229, and TCGA databases for differentially expressed RNA species, obtaining 52 long non-coding RNAs (lncRNAs), 31 microRNAs (miRNAs), and 186 mRNAs, which were used to build a competing endogenous RNA network. Kaplan–Meier and receiver operating characteristic (ROC) analyses revealed five survival-related lncRNAs: H19, LINC01574, LINC01614, RNF144A-AS1, and OSMR-AS1. With multiple optimization mRNAs, we found the H19-hsa-miR-338-3P-NRP1 regulatory pathway. Additionally, we noted high NRP1 expression in GBM patients, and Kaplan–Meier and ROC analyses showed that NRP1 expression was associated with GBM prognosis. Cox analysis indicated that NRP1 is an independent prognostic factor in GBM patients. In conclusion, H19 and hsa-miR-338-3P regulate NRP1 expression, and this pathway plays an important role in GBM.

Identification of novel biomarkers for intracerebral hemorrhage via long noncoding RNA-associated competing endogenous RNA network

2021 ◽  
Author(s):  
Chunyu Yang ◽  
Jiao Wu ◽  
Xi Lu ◽  
Shuang Xiong ◽  
Xiaoxue Xu
Keyword(s):  
Intracerebral Hemorrhage ◽  
Cause Of Death ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Competing Endogenous Rna ◽  
Competing Endogenous Rna Network ◽  
Novel Biomarkers ◽  
Non Coding Rnas

Intracerebral hemorrhage (ICH) is a leading cause of death and disability worldwide. This study aimed to examine the involvement of long non-coding RNAs (lncRNAs), a group of non-coding transcripts, in...

scholarly journals AFCMEasyModel: An Easy Interface for Modeling Competing Endogenous RNA Networks using ODEs

2017 ◽  
Author(s):  
Mohammad M. Tarek
Keyword(s):  
Gene Expression ◽  
Public Access ◽  
Regulatory Function ◽  
Circular Rnas ◽  
Messenger Rnas ◽  
Competing Endogenous Rna ◽  
Shiny App ◽  
Competing Endogenous Rna Network ◽  
Non Coding Rnas ◽  
User Friendly

AbstractCompeting endogenous RNA networks have been considered to be important regulators of genetic data expression. Circular RNAs and microRNAs interact to form a circular sponge that have been shown to regulate messenger RNAs and hence regulating gene expression. The kinetics by which these non-coding RNAs interact together affecting gene expression are crucial to understand the mechanism of their regulatory function. Herein, we developed AFCMEasyModel as a user-friendly shiny app that enables users to modify regulation parameters of a competing endogenous RNA network based on interaction between circular RNAs and microRNAs in the simulation environment to form a sponge complex. The App provides the source-code for more customized models and allow users to download simulation plots for supplementation of their publications.The App was made available for public-access at: https://mohammadtarek.shinyapps.io/afcmeasymodel/

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