Comparing MicroRNA Target Gene Predictions Related to Alzheimer\'s Disease Using Online Bioinformatics Tools

Abstract

Introduction: The prediction of microRNAs related to target genes using bioinformatics tools saves time and costs of the experimental analyses. In the present study, the prediction of microRNA target genes relevant to Alzheimer’s Diseases (AD) were compared with the experimentally reported data using different bioinformatics tools. Method: A total of 41 microRNAs associated with 21 essential genes involved in AD were selected based on experimental results reported in previously published literature. Then, the prediction of the target gene for each microRNA was done using three bioinformatics tools, including MirTarget, TargentScan, and Diana-microT. The results of the predictions for all three tools considering the reported target genes were compared with each other. Results: The results showed that MirTarget, TargetScan, and Diana-microT correctly predicted 66%, 61%, and 27% of microRNAs’ attachment to the previously reported target genes involved in AD, respectively. However, none of the tools could predict the attachment of 22% of the microRNAs to the target genes reported in the literature. Conclusion: It can be concluded that MirTarget and TargetScan can better predict the target gene for microRNAs involved in AD compared with Diana-microT. Considering the algorithm used in MirTarget, this bioinformatics tool provides more functional and accurate results in predicting the target genes for microRNAs and it is recommended for predicting the target genes of microRNAs. It can also be concluded that the reported target genes for microRNAs involved in AD need further investigations in some cases.

Keywords

• microrna
• bioinformatics
• target gene prediction
• alzheimer disease