Challenges in microRNAs’ targetome prediction and validation

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MicroRNAs (miRNAs) are small RNA molecules with important roles in post-transcriptional regula-tion of gene expression. In recent years, the predicted number of miRNAs has skyrocketed, largely as a consequence of high-throughput sequencing technologies becoming ubiquitous. This dramatic increase in miRNA candidates poses multiple challenges in terms of data deposition, curation, and validation. Al-though multiple databases containing miRNA annotations and targets have been developed, ensuring data quality by validating miRNA-target interactions requires the efforts of the research community. In order to generate databases containing biologically active miRNAs, it is imperative to overcome a multitude of hurdles, including restricted miRNA expression patts, distinct miRNA biogenesis machineries, and divergent miRNA-mRNA interaction dynamics. In the present review, we discuss recent advances and limitations in miRNA prediction, identification, and validation. Lastly, we focus on the most enriched neu-ronal miRNA, miR-124, and its gene regulatory network in human neurons, which has been revealed using a combined computational and experimental approach.
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