A comprehensive method for identification of suitable reference genes in extracellular vesicles

Abstract

Reverse transcription–quantitative polymerase chain reaction (RT-qPCR) is one of the most sensitive, economical and widely used methods for evaluating gene expression. However, the utility of this method continues to be undermined by a number of challenges including normalization using appropriate reference genes. The need to develop tailored and effective strategies is further underscored by the burgeoning field of extracellular vesicle (EV) biology. EVs contain unique signatures of small RNAs including microRNAs (miRs). In this study we develop and validate a comprehensive strategy for identifying highly stable reference genes in a therapeutically relevant cell type, cardiosphere-derived cells. Data were analysed using the four major approaches for reference gene evaluation: NormFinder, GeNorm, BestKeeper and the Delta Ct method. The weighted geometric mean of all of these methods was obtained for the final ranking. Analysis of RNA sequencing identified miR-101-3p, miR-23a-3p and a previously identified EV reference gene, miR-26a-5p. Analysis of a chip-based method (NanoString) identified miR-23a, miR-217 and miR-379 as stable candidates. RT-qPCR validation revealed that the mean of miR-23a-3p, miR-101-3p and miR-26a-5p was the most stable normalization strategy. Here, we demonstrate that a comprehensive approach of a diverse data set of conditions using multiple algorithms reliably identifies stable reference genes which will increase the utility of gene expression evaluation of therapeutically relevant EVs.

miRNA Reference Genes in Extracellular Vesicles Released from Amniotic Membrane-Derived Mesenchymal Stromal Cells

“…In this context, U6 snRNA was recommended for miRNA quantification in pure EVs or vesicle-enriched body fluids [70,71]. Nevertheless, its suitability as EV-RG was questioned in a recent publication that analyzed cardiosphere-derived cell EVs [53]. This may be due to the mechanistically separated biogenesis of U6 snRNA, which is not processed by the spliceosome but by the Drosha complex [72].…”

“…According to the literature, 12 miRNAs and one small RNA (U6 snRNA) were selected for stability analysis (Table 1) [8,[48][49][50][51][52][53][54][55]. 2.6.…”

Astrocyte-Derived Small Extracellular Vesicles Regulate Dendritic Complexity through miR-26a-5p Activity

“…We detected that overexpression of Aldo C induced a much larger and variable change of miR-26a-5p content in sEVs compared to homogenates. This could be partially explained by differences in the relative abundance of miR-26a-5p between sEVs and astrocyte homogenates, but also by the intrinsic complexity of sEVs in terms of loading control normalization [49][50][51]. For specific astrocyte-derived sEVs, there is not a clear consensus regarding normalization of miRNA levels.…”

NeuroEVs: Characterizing Extracellular Vesicles Generated in the Neural Domain

“…With regard to an appropriate singular reference RNA for qRT-PCR quantification, some in the field use U6, but there is evidence that U6 can have variable expression in biofluid samples (Xiang et al, 2014). This has led others to propose averaging multiple putative reference miRNAs together to ascertain an average background level of expression or estimating the total number of EVs in a sample (Akers et al, 2013;Gouin et al, 2017), but these approaches may still lead to biased findings depending on the miRNAs selected or EV quantification method used, respectively.…”