Computational Lncrna – Mirna Interaction Analyses in Epilepsy Syndrome
Journal Title: The 1st Annual Meeting of Georgian Center for Neuroscience Research - Year 2020, Vol 2, Issue 20
Abstract
Epilepsy is a neurological disorder associated to Central Nervous System. The seizures of epilepsy anomaly accurse due to the electrical activity disruption in the brain. Almost 80% of epilepsy cases are the results of genetically anomalies and there are more than 900 genes linked to this disease. Over 100 gene mutations have defined in biological pathways result in epilepsy. Lots of growing number of studies are being focused on Long Non-coding RNAs (lncRNAs) taking part in dysregulating during epileptogenesis. Thus, several changes can affect the expression of lncRNA and microRNA (miR) which ultimately change the expression of genes in the correct order and cause disease such epilepsy. In this study, long non-coding RNAs and microRNAs were selected through DIANA TOOLS and MiRTarBase databases respectively. Their related genes were collected as the text mining in the GEO database. Cytoscape was the last software used for finding the network between genes and lncRNAs. Our resulting of lncRNA - miRNA - genes network, nominated 78 non-coding RNAs and 21 genes with strong possibility, which may have crucial roles in regulating this biological process. Possible targeting effects of different miRNAs on some genes showed that they can dysregulate the expression of important genes in the process of epilepsy disorder. Since noncoding RNAs are known as important regulators in cellular and molecular functions, disorderly changes, inforce the biological pathways to get disarranged. According to the bioinformatics findings, it can be predicted that 21 genes in above mentioned database probably can have critical role in epilepsy disease process. This investigation shows that lncRNAs could be vital biomarkers in different diseases such as epilepsy and they could be introduced as suitable candidate genes for in vitro model of epilepsy anomaly studies.
Authors and Affiliations
Pegah Javid, Masoud Baghi, Mansoureh Azadeh
Keywords
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- EP ID EP677958
- DOI 10.29088/GCNR-2020.49
- Views 168
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