scholarly journals High-throughput sequencing profile of laryngeal cancers: analysis of co-expression and competing endogenous RNA networks of circular RNAs, long non-coding RNAs, and messenger RNAs

2021 ◽  
Vol 9 (6) ◽  
pp. 483-483
Author(s):  
Zheng Wang ◽  
Jia Gu ◽  
Tao Han ◽  
Kai Li
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Circular Rnas ◽  
Messenger Rnas ◽  
Competing Endogenous Rna ◽  
Non Coding Rnas

scholarly journals The TWIST1-centered competing endogenous RNA network promotes proliferation, invasion, and migration of lung adenocarcinoma

Oncogenesis ◽  
2019 ◽  
Vol 8 (11) ◽  
Author(s):  
Wenjie Xia ◽  
Qixing Mao ◽  
Bing Chen ◽  
Lin Wang ◽  
Weidong Ma ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Migration And Invasion ◽  
Circular Rnas ◽  
Messenger Rnas ◽  
Competing Endogenous Rna ◽  
Invasion And Migration ◽  
Non Coding Rnas ◽  
And Migration

Abstract The proposed competing endogenous RNA (ceRNA) mechanism suggested that diverse RNA species, including protein-coding messenger RNAs and non-coding RNAs such as long non-coding RNAs, pseudogenes and circular RNAs could communicate with each other by competing for binding to shared microRNAs. The ceRNA network (ceRNET) is involved in tumor progression and has become a hot research topic in recent years. To date, more attention has been paid to the role of non-coding RNAs in ceRNA crosstalk. However, coding transcripts are more abundant and powerful than non-coding RNAs and make up the majority of miRNA targets. In this study, we constructed a mRNA-mRNA related ceRNET of lung adenocarcinoma (LUAD) and identified the highlighted TWIST1-centered ceRNET, which recruits SLC12A5 and ZFHX4 as its ceRNAs. We found that TWIST1/SLC12A5/ZFHX4 are all upregulated in LUAD and are associated with poorer prognosis. SLC12A5 and ZFHX4 facilitated proliferation, migration, and invasion in vivo and in vitro, and their effects were reversed by miR-194–3p and miR-514a-3p, respectively. We further verified that SLC12A5 and ZFHX4 affected the function of TWIST1 by acting as ceRNAs. In summary, we constructed a mRNA-mRNA related ceRNET for LUAD and highlighted the well-known oncogene TWIST1. Then we verified that SLC12A5 and ZFHX4 exert their oncogenic function by regulating TWIST1 expression through a ceRNA mechanism.

scholarly journals Identification of Non-coding RNA Biomarkers in Stress-induced Depression via Comprehensive Analysis of Competing Endogenous RNA Network

2020 ◽  
Author(s):  
xuanjun liu ◽  
Lan Yan ◽  
Chun Lin ◽  
Yiliang Zhang ◽  
Haofei Miao ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Comprehensive Analysis ◽  
Differentially Expressed ◽  
Psychiatric Disease ◽  
Circular Rnas ◽  
Messenger Rnas ◽  
Competing Endogenous Rna ◽  
Non Coding Rna ◽  
Non Coding Rnas ◽  
Promising Perspective

Abstract BackgroundDepression is one of the most common psychiatric disease worldwide. Although the research about the pathogenesis of depression have achieved progress, the detailed effect of non-coding RNAs (ncRNAs) in depression are still not clearly elucidated. This study was aimed to identify non-coding RNA biomarkers in stress-induced depression via comprehensive analysis of competing endogenous RNA networkMethodsIn this present study, we acquired RNA expression from RNA seq expression profile in three mice with depressive-like behaviors using chronic restraint stress paradigm and three C57BL/6J wild-type mice as control mice. ResultsA total of 41 differentially expressed circular RNAs (circRNAs) and 181 differentially expressed messenger RNAs (mRNAs) were up-regulated, and 65 differentially expressed circRNAs and 289 differentially expressed mRNAs were down-regulated, which were selected by a threshold of fold change ≥2 and a p-value < 0.05. Gene Ontology was performed to analyze the biological functions, and we predicted potential signaling pathways based on Kyoto Encyclopedia of Genes and Genomes pathway database. In addition, we constructed a circRNA-microRNA (miRNA)-mRNA regulatory network to further identify non-coding RNAs biomarkers. ConclusionsOur findings provide a promising perspective for further research into molecular mechanisms of depression, and targeting circRNA -mediated competing endogenous RNA (ceRNA) network is a useful strategy to early recognize the depression.

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/

scholarly journals Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson’s Disease

2020 ◽  
Vol 21 (18) ◽  
pp. 6513 ◽  
Author(s):  
Shubhra Acharya ◽  
Antonio Salgado-Somoza ◽  
Francesca Maria Stefanizzi ◽  
Andrew I. Lumley ◽  
Lu Zhang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
High Throughput ◽  
Regulatory Networks ◽  
Current Knowledge ◽  
Circular Rnas ◽  
Clinical Markers ◽  
Wide Range ◽  
Non Coding Rnas ◽  
The Brain

Parkinson’s disease (PD) is a complex and heterogeneous disorder involving multiple genetic and environmental influences. Although a wide range of PD risk factors and clinical markers for the symptomatic motor stage of the disease have been identified, there are still no reliable biomarkers available for the early pre-motor phase of PD and for predicting disease progression. High-throughput RNA-based biomarker profiling and modeling may provide a means to exploit the joint information content from a multitude of markers to derive diagnostic and prognostic signatures. In the field of PD biomarker research, currently, no clinically validated RNA-based biomarker models are available, but previous studies reported several significantly disease-associated changes in RNA abundances and activities in multiple human tissues and body fluids. Here, we review the current knowledge of the regulation and function of non-coding RNAs in PD, focusing on microRNAs, long non-coding RNAs, and circular RNAs. Since there is growing evidence for functional interactions between the heart and the brain, we discuss the benefits of studying the role of non-coding RNAs in organ interactions when deciphering the complex regulatory networks involved in PD progression. We finally review important concepts of harmonization and curation of high throughput datasets, and we discuss the potential of systems biomedicine to derive and evaluate RNA biomarker signatures from high-throughput expression data.

scholarly journals seekCRIT: Detecting and characterizing differentially expressed circular RNAs using high-throughput sequencing data

2020 ◽  
Vol 16 (10) ◽  
pp. e1008338
Author(s):  
Mohamed Chaabane ◽  
Kalina Andreeva ◽  
Jae Yeon Hwang ◽  
Tae Lim Kook ◽  
Juw Won Park ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Differentially Expressed ◽  
Circular Rnas ◽  
Sequencing Data ◽  
High Throughput Sequencing Data
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