Circular RNA Expression Profiles and Bioinformatic Analysis in Mouse Models of Obstructive Sleep Apnea-Induced Cardiac Injury: Novel Insights Into Pathogenesis
Circular RNAs (circRNAs) participate in the development of various kinds of diseases. However, the function and roles of circRNAs in obstructive sleep apnea (OSA)-induced cardiovascular disease remain poorly understood. Therefore, we sought to explore the circRNA expression profiles and predict thei...
Guardado en:
| Autores principales: | , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Frontiers Media S.A.
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/352ddd01fdf74ecdb0a7dead9a643265 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | Circular RNAs (circRNAs) participate in the development of various kinds of diseases. However, the function and roles of circRNAs in obstructive sleep apnea (OSA)-induced cardiovascular disease remain poorly understood. Therefore, we sought to explore the circRNA expression profiles and predict their functions in OSA-induced cardiac injury with the use of bioinformatics analysis. The model of OSA was established in mouse treated by chronic intermittent hypoxia (CIH) exposure. Then, we screened the circRNA profile using circRNA microarray. By comparing circRNA expression in three matched pairs of CIH-treated cardiac tissues and controls, differentially expressed circRNAs were identified in the CIH groups. Comparison of the selected circRNAs expression levels was performed between qRT-PCR and microarray. Meanwhile, we employed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses to predict the functions of these selected circRNAs. Finally, we constructed a circRNA-miRNA-mRNA network based on the target prediction. It was found that a total of 124 circRNAs were differentially expressed in CIH-treated cardiac tissues (p ≤ 0.05, fold-change ≥ 1.5). Among them, 23 circRNAs were significantly down-regulated, and the other 101 were up-regulated. Then, ten circRNAs were randomly selected to validate the reliability of the microarray results by using qRT-PCR. Next, we conducted the GO and KEGG pathway analysis to explore the parental genes functions of differentially expressed circRNA. Finally, two significantly differentially expressed circRNAs (mmu_circRNA_014309 and mmu_circRNA_21856) were further selected to create a circRNA-miRNA-mRNA regulation network. Our study did first reveal that the differentially expressed circRNAs played a vital role in the pathogenesis of OSA-induced cardiac damage. Thus, our findings bring us closer to unraveling the pathophysiologic mechanisms and eliciting novel therapeutic targets for the treatment of OSA-associated cardiovascular diseases. |
|---|