Circular RNA (circRNA) expression profiles in lung tissues from mice with and without ventilator-induced lung injury (VILI) were analyzed using high-throughput sequencing and bioinformatics to clarify their potential role in… Click to show full abstract
Circular RNA (circRNA) expression profiles in lung tissues from mice with and without ventilator-induced lung injury (VILI) were analyzed using high-throughput sequencing and bioinformatics to clarify their potential role in VILI pathogenesis and provide valuable molecular markers for VILI diagnosis and treatment. A VILI mouse model was established using high-tidal volume ventilation, and lung tissue was stained with HE and TUNEL. The present study used high-throughput sequencing technology to analyze the expression profile of circRNAs in the lung tissue of mice with and without VILI. Bioinformatics was used to analyze the enrichment of differentially expressed circRNAs using Gene Ontology and KEGG to predict function. Among the top 10 circRNAs with significant differential expression, we used real-time quantitative polymerase chain reaction technology (qRT-PCR) to verify the accuracy of the high-throughput sequencing results and constructed the corresponding circRNA-miRNA-mRNA-specific binding network map using software prediction. The most upregulated circRNAs were novel_circ_0000899 and novel_circ_0014815, and the most downregulated circRNAs were novel_circ_0015069. A total of 14,347 circRNAs were detected using high-throughput sequencing. Compared to the control group, 285 circRNAs were abnormally and significantly expressed in the lung tissues of VILI mice (|log2(FC)| > 1, p < 0.05). A total of 171 circRNAs were significantly upregulated, and 114 circRNAs were significantly downregulated. Gene ontology analyses indicated that the differentially expressed circRNAs were involved in multiple biological functions, such as regulation of metabolic processes, protein phosphorylation, and chromatin organization. KEGG pathway analyses revealed that the Ras signaling pathway, rap1 signaling pathway, PI3K − Akt signaling pathway, and ECM receiver interaction were related to the differentially expressed circRNAs. The qRT-PCR verification results were generally consistent with the circRNA expression trends of the high-throughput sequencing data. The circRNA-miRNA-mRNA interaction network suggested that miRNAs and mRNAs related to circRNAs played a key role in VILI. Differentially expressed circRNAs were identified in the tissues of VILI mice using high-throughput sequencing combined with bioinformatics analysis, and the results lay a foundation for further study of the mechanism of circRNAs in the occurrence and development of VILI.
               
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