Vestergaard Anna Lindeløv, Blankestijn Maaike, Stahl Jonathan Lucien, Pallesen Emil Marek Heymans, Bang-Berthelsen Claus Heiner, Pociot Flemming, Novotny Guy Wayne, Lundh Morten, Mandrup-Poulsen Thomas
Laboratory for Immuno-Endocrinology, Department of Biomedical Sciences, University of Copenhagen, 2200 Copenhagen N, Denmark.
Center for Non-coding RNA in Technology and Health, Department of Pediatrics, Herlev and Gentofte Hospital, 2730 Herlev, Denmark.
Int J Mol Sci. 2016 Jun 7;17(6):896. doi: 10.3390/ijms17060896.
As microRNAs (miRs) are gaining increasing attention as key regulators of cellular processes, expressional quantification is widely applied. However, in the processing of relatively quantified data, the importance of testing the stability of several reference mRNAs and/or miRs and choosing among these for normalization is often overlooked, potentially leading to biased results. Here, we have optimized the purification of miR-enriched total RNA from pancreatic insulin-producing INS-1 cells. Additionally, we optimized and analyzed miR expression by a qPCR-based microarray and by specific qPCR and tested the stability of candidate reference mRNAs and miRs. Hence, this study gives a widely applicable example on how to easily and systematically test and decide how to normalize miR quantification. We suggest that caution in the interpretation of miR quantification studies that do not comprise stability analysis should be exerted.
由于微小RNA(miR)作为细胞过程的关键调节因子越来越受到关注,其表达定量得到了广泛应用。然而,在处理相对定量数据时,测试几种参考mRNA和/或miR的稳定性并在这些中选择用于标准化的重要性常常被忽视,这可能导致有偏差的结果。在这里,我们优化了从胰腺胰岛素分泌INS-1细胞中富集miR的总RNA的纯化。此外,我们通过基于qPCR的微阵列、特异性qPCR优化并分析了miR表达,并测试了候选参考mRNA和miR的稳定性。因此,本研究给出了一个广泛适用的示例,说明如何轻松、系统地测试并决定如何对miR定量进行标准化。我们建议,对于不包含稳定性分析的miR定量研究的解释应谨慎。