Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is a highly transmissible virus causing the ongoing global pandemic, COVID-19. Evidence suggests that viral and host microRNAs play pivotal roles in progression of such infections. The decisive impact of viral miRNAs and their putative targets in modulating the transcriptomic profile of its host, however remains unexplored. We hypothesized that the SARS-CoV-2 derived miRNAs can potentially play a contributory role in its pathogenicity and aid in its survival. A series of computational tools predicted 34 SARS-CoV-2 encoded miRNAs and their putative targets in the host. Immune and apoptotic pathways were identified as most enriched pathways. Further investigation using a dataset of SARS-CoV-2 infected cells (available from public repository- GSE150392) revealed that 46 genes related to immune and apoptosis-related functions were deregulated. Of these 46 genes, 42 genes were identified to be significantly up-regulated and 4 genes were down-regulated
. In silico
analysis revealed all of the these significantly down-regulated genes to be putative targets of 9 out of 34 of our predicted viral miRNAs. Overall, 123 out of 324 genes that are differentially regulated in SARS-CoV2 infected cells, and also identified as putative targets of viral miRNAs, were found to be significantly down-regulated. KEGG pathway analysis using these genes revealed p53 signaling as the most enriched pathway – a pathway that is known to influence immune responses. This study thus provides the theoretical foundation for the underlying molecular mechanisms involved in progression of viral pathogenesis.
Fetal hemoglobin (HbF) induction is considered to be a promising therapeutic strategy to ameliorate the clinical severity of β-hemoglobin disorders, and has gained a significant amount of attention in recent times. Despite the enormous efforts towards the pharmacological intervention of HbF reactivation, progress has been stymied due to limited understanding of γ-globin gene regulation. In this study, we intended to investigate the implications of lncRNA-associated competing endogenous RNA (ceRNA) interactions in HbF regulation. Probe repurposing strategies for extraction of lncRNA signatures and subsequent in silico analysis on publicly available datasets (GSE13284, GSE71935 and GSE7874) enabled us to identify 46 differentially expressed lncRNAs (DElncRNAs). Further, an optimum set of 11 lncRNAs that could distinguish between high HbF and normal conditions were predicted from these DElncRNAs using supervised machine learning and a stepwise selection model. The candidate lncRNAs were then linked with differentially expressed miRNAs and mRNAs to identify lncRNA-miRNA-mRNA ceRNA networks. The network revealed that 2 lncRNAs (UCA1 and ZEB1-AS1) and 4 miRNAs (hsa-miR-19b-3p,hsa-miR-3646,hsa-miR-937 and hsa-miR-548j) sequentially mediate cross-talk among different signaling pathways which provide novel insights into the lncRNA-mediated regulatory mechanisms, and thus lay the foundation of future studies to identify lncRNA-mediated therapeutic targets for HbF reactivation.
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