Tissue Specific Reference Genes for MicroRNA Expression Analysis in a Mouse Model of Peripheral Nerve Injury.

Theodora Kalpachidou,Miodrag Mitrić,Michaela Kress,Kai K Kummer

doi:10.3389/fnmol.2019.00283

Theodora Kalpachidou, Miodrag Mitrić + Show 2 more

Open Access

https://doi.org/10.3389/fnmol.2019.00283

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Abstract

MicroRNAs (miRNAs) have emerged as master switch regulators in many biological processes in health and disease, including neuropathy. miRNAs are commonly quantified by reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR), usually estimated as relative expression through reference genes normalization. Different non-coding RNAs (ncRNAs) are used for miRNA normalization; however, there is no study identifying the optimal reference genes in animal models for peripheral nerve injury. We evaluated the stability of eleven ncRNAs, commonly used for miRNA normalization, in dorsal root ganglia (DRG), dorsal horn of the spinal cord (dhSC), and medial prefrontal cortex (mPFC) in the mouse spared nerve injury (SNI) model. After RT-qPCR, the stability of each ncRNA was determined by using four different methods: BestKeeper, the comparative delta-Cq method, geNorm, and NormFinder. The candidates were rated according to their performance in each method and an overall ranking list was compiled. The most stable ncRNAs were: sno420, sno429, and sno202 in DRG; sno429, sno202, and U6 in dhSC; sno202, sno420, and sno142 in mPFC. We provide the first reference genes’ evaluation for miRNA normalization in different neuronal tissues in an animal model of peripheral nerve injury. Our results underline the need for careful selection of reference genes for miRNA normalization in different tissues and experimental conditions. We further anticipate that our findings can be used in a broad range of nerve injury related studies, to ensure validity and promote reproducibility in miRNA quantification.

Highlights

MicroRNAs are small non-coding RNAs of approximately 22 nucleotides length, which can regulate gene expression by translational inhibition or promotion of degradation of their target mRNAs (Eulalio et al, 2008). miRNAs play fundamental roles in biological processes, such as cell proliferation, differentiation, and survival and are crucial for normal developmental processes, homeostasis, as well as a plethora of diseases and pathologies (Vidigal and Ventura, 2015)
Raw amplification data were imported to LinRegPCR program (Ramakers et al, 2003; Ruijter et al, 2009, 2015; Tuomi et al, 2010), which performs a baseline correction of the amplification data, determines a window of linearity, and through a linear regression analysis determines the qPCR efficiency and the Cq value per reaction, in order to estimate the mean PCR efficiency per primer set or assay [52]
The stability of all evaluated non-coding RNAs (ncRNAs) was estimated based on the Cq values obtained from single threshold settings and LinRegPCR program adjustments, by using four different statistical approaches that are commonly used for stability assessment of reference genes: BestKeeper (Pfaffl et al, 2004), the comparative delta-Cq method (Silver et al, 2006), geNorm (Vandesompele et al, 2002), and NormFinder (Andersen et al, 2004)

Summary

INTRODUCTION

MicroRNAs (miRNAs) are small non-coding RNAs (ncRNAs) of approximately 22 nucleotides length, which can regulate gene expression by translational inhibition or promotion of degradation of their target mRNAs (Eulalio et al, 2008). miRNAs play fundamental roles in biological processes, such as cell proliferation, differentiation, and survival and are crucial for normal developmental processes, homeostasis, as well as a plethora of diseases and pathologies (Vidigal and Ventura, 2015). Several studies have identified miRNAs that are upregulated upon peripheral nerve injury and can promote regeneration (Strickland et al, 2011; Zhou et al, 2012; Wu and Murashov, 2013; Motti et al, 2017), rendering miRNAs attractive potential targets for therapeutic interventions (Jiangpan et al, 2016; Ghibaudi et al, 2017; Zhang J. et al, 2018) To this end, in depth mechanistic understanding of the role of up- and downregulated miRNAs in human pathologies and mouse models of the respective disorders is increasing, which in turn necessitates the reliable and reproducible quantification of miRNA expression levels. Upon rating each ncRNA according to its performance in the different methods, we compiled an overall ranking list and propose the most appropriate reference genes for assessing miRNA expression in the SNI mouse model in three neuronal tissues

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