MicroRNAs (miRNAs) are promising tools as biomarkers and therapeutic agents in various chronic diseases such as osteoporosis, cancers, type I and II diabetes, and cardiovascular diseases. Considering the rising interest in the regulatory role of miRNAs in bone metabolism, aging, and cellular senescence, accurate normalization of qPCR-based miRNA expression data using an optimal endogenous control becomes crucial. We used a systematic approach to select candidate endogenous control miRNAs that exhibit high stability with aging from our miRNA sequence data and literature search. Validation of miRNA expression was performed using qPCR and their comprehensive stability was assessed using the RefFinder tool which is based on four statistical algorithms: GeNorm, NormFinder, BestKeeper, and comparative delta CT. The selected endogenous control was then validated for its stability in mice and human bone tissues, and in bone marrow stromal cells (BMSCs) following induction of senescence and senolytic treatment. Finally, the utility of selected endogenous control versus U6 was tested by using each as a normalizer to measure the expression of miR-34a, a miRNA known to increase with age and senescence. Our results show that Let-7f did not change across the groups with aging, senescence or senolytic treatment, and was the most stable miRNA, whereas U6 was the least stable. Moreover, using Let-7f as a normalizer resulted in significantly increased expression of miR-34a with aging and senescence and decreased expression following senolytic treatment. However, the expression pattern for miR-34a reversed for each of these conditions when U6 was used as a normalizer. We show that optimal endogenous control miRNAs, such as Let-7f, are essential for accurate normalization of miRNA expression data to increase the reliability of results and prevent misinterpretation. Moreover, we present a systematic strategy that is transferrable and can easily be used to identify endogenous control miRNAs in other biological systems and conditions.
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