1.Identification of MicroRNAs Binding Site in the 3’Untranslated Region of Long Non-Coding RNA, MIR497HG: A Bioinformatic Prediction
Nursyamila Shamsuddin ; Fazleen Haslinda Mohd Hatta ; Mizaton Hazizul Hasan ; Mohd Shihabuddin Ahmad Noorden
Malaysian Journal of Medicine and Health Sciences 2024;20(No.1):161-167
Introduction: Prediction and identification of miRNAs target genes are crucial for understanding the biology of miRNAs. Amidst reported long-coding RNA (lncRNA), the microRNA 195-497 cluster host gene (MIR497HG) regulation
is mediated by multiple non-coding RNAs (ncRNAs) such as microRNAs (miRNAs). MIR497HG has been implicated
as a tumour suppressor in various cancers. However, the impact of MIR497HG and its derived miRNAs is largely
unknown and still needs to be further explored. Employing an experimental approach is often challenging since
some lncRNAs are difficult to identify and isolate by the current isolation technique. Thus, bioinformatic tools are
introduced to aid these problems. This study sought to search and identify the miRNAs targeting the 3’untranslated
region (3’UTR) of MIR497HG. Methods: Here, bioinformatic tools were adopted to identify a unique list of miRNAs
that potentially target the 3’UTR of MIR497HG. Results: A total of 57 candidate miRNAs that target the 3’UTR of
MIR497HG were extracted using the miRDB. Meanwhile, STarMir predicted 291 miRNAs that potentially target the
3’UTR of MIR497HG. A common list of 36 miRNAs was obtained using the Venny 2.1.0 and further narrowed down
using the LogitProb score of StarMir. Finally, a total 4 miRNAs (hsa-miR-3182, hsa-miR-7156-5p, hsa-miR-452-3p
and hsa-miR-2117) were identified. The mRNA target of identified miRNAs was identified by TargetScan. Finally,
Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of mRNA
target was done using Enrichr. Conclusion: This finding could be useful in understanding the complex interaction
between MIR497HG and its regulatory miRNA. In addition, a comparative analysis of computational miRNA-target
predictions is provided in this study would potentially lay the foundations for miRNAs to be used for biomarkers in
cancer research.