Bioinformatic Prediction of Novel microRNAs Encoded in Krüppel-like Factor 4 Gene

MicroRNAs are small non-coding RNAs that can regulate gene expression that affects various cellular processes. Krüppel-like factor 4 (KLF4) is a transcription factor that has different regulatory functions, and it plays a role in various cellular processes. This study aims to identify novel microRNAs in KLF4 gene using bioinformatics tools. This study significantly contributes to our understanding of the complex function of KLF4 and reveals additional layers of regulatory complexity that affect gene function and cellular dynamics. Advanced bioinformatics methods, including SSCprofiler website, were used to predict stem-loop structures in KLF4 gene, and MatureBayes website was used to predict the mature sequence of microRNAs, which indicate potential miRNA candidates. Using the RNAfold website, the stem-loop structure of microRNAs was determined. The UCSC database assessed the conservation status of these miRNAs and their precursors. From the results of bioinformatics analysis of KLF4 gene, three microRNAs were predicted. Websites and bioinformatics tools were able to predict the sequence of possible microRNAs along with their mature sequence and then depict their stem-loop structure. The analysis of the obtained sequences showed that they are highly conserved, which indicates their importance in the genome. The results obtained in this study show the power and functionality of bioinformatics tools. While the bioinformatic results increase our understanding of the function of the KLF4 gene, experimental studies are needed to confirm these results, which can give us more information about the function of this gene in the future.