Elsevier

Methods

Volume 50, Issue 4, April 2010, Pages 237-243
Methods

mRNA and microRNA quality control for RT-qPCR analysis

https://doi.org/10.1016/j.ymeth.2010.01.010Get rights and content

Abstract

The importance of high quality sample material, i.e. non-degraded or fragmented RNA, for classical gene expression profiling is well documented. Hence, the analysis of RNA quality is a valuable tool in the preparation of methods like RT-qPCR and microarray analysis. For verification of RNA integrity, today the use of automated capillary electrophoresis is state of the art. Following the recently published MIQE guidelines, these pre-PCR evaluations have to be clearly documented in scientific publication to increase experimental transparency.

RNA quality control may also be integrated in the routine analysis of new applications like the investigation of microRNA (miRNA) expression, as there is little known yet about factors compromising the miRNA analysis. Agilent Technologies is offering a new lab-on-chip application for the 2100 Bioanalyzer making it possible to quantify miRNA in absolute amounts [pg] and as a percentage of small RNA [%]. Recent results showed that this analysis method is strongly influenced by total RNA integrity. Ongoing RNA degradation is accompanied by the formation of small RNA fragments leading to an overestimation of miRNA amount on the chip. Total RNA integrity is known to affect the performance of RT-qPCR as well as the quantitative results in mRNA expression profiling. The actual study identified a comparable effect for miRNA gene expression profiling. Using a suitable normalization method could partly reduce the impairing effect of total RNA integrity.

Introduction

The expression level of RNAs serves as a good indicator of the physiological status of a cell or tissue. Various studies showed a distinct influence of total RNA integrity on the performance of gene expression profiling using RT-qPCR or microarrays [1], [2], [3]. RNAs are very sensitive molecules and the ubiquitous occurrence of nucleases poses a constant risk of RNA degradation. For this reason cautious handling in every single pre-PCR step of the gene expression analysis (e.g. sampling, storage and extraction) is important as only experiments conducted with high quality starting material provide reliable results. The recently published guidelines for “minimum information for publication of quantitative real-time PCR experiments” (MIQE guidelines) demand a higher transparency of the pre-PCR steps like the documentation of sample quality [4]. These guidelines are supposed to give recommendations for authors, which details are necessary to be declared in a publication. This should guarantee to get a standardized paperwork for gene expression experiments to help the reader to evaluate and reproduce published results, to promote consistency between laboratories, and to increase experimental transparency.

RNA quality control arose the interest in gene expression analysis as it was shown to strongly influence the performance and quantitative data of RT-qPCR, which is the method of choice to study gene regulation. The term RNA quality is defined as the composition of RNA purity and RNA integrity.

RNA purity can be measured photometrically using the NanoDrop (peqLab Biotechnologie GmbH, Erlangen, Germany), the NanoVue (GE Healthcare, Munich, Germany) or other sensitive spectrophotometers e.g. the NanoPhotometer (Implen, Munich, Germany), which is an optimal solution for application of very small volumes. The optical density (OD) is measured at different wave lengths: 230 nm (absorption of contaminants & background absorption), 260 nm (absorption maxima of nucleic acids), 280 nm (absorption maxima of proteins), and 320 nm (absorption of contaminants & background absorption). The OD260/280 ratio is used as indicator for RNA purity. A ratio higher than 1.8 is assumed as suitable for gene expression measurements [5], [6]. The OD260/230 and the OD260/320 should be maximized as these represent the degree of background absorption and contaminants.

Classical quality control of nucleic acids uses high resolution 4% agarose gel electrophoresis to separate the different fractions (5S, 18S, 28S) of ribosomal RNA (rRNA) subunits. For RNA of good quality a 28S/18S ratio of 2.0 is assumed. The subjective interpretation of these agarose gel images strongly depends on the experience and examination of the individual researcher and can hardly be compared between different users and laboratories.

Today, lab-on-chip technology for automated capillary electrophoresis is state of the art and is recommended for standardized RNA integrity control. Different lab-on-chip instruments are commercially available like the 2100 Bioanalyzer (Agilent Technologies, Waldbronn, Germany) and the Experion (Bio-Rad Laboratories, Munich, Germany). Both devices are sensitive, highly reproducible and suitable for a reliable quality control of RNAs [19]. For visualization and better interpretation, an electropherogram and a virtual gel image are generated. The 28S/18S ratio is calculated by assessing the peaks recorded in the electropherogram and the bands occurring on the gel-like image. Additionally, to simplify the assessment of RNA integrity the instrument software calculates a numerical value: RNA integrity number (RIN) on the 2100 Bioanalyzer and RNA quality index (RQI) on the Experion. A RQI/RIN of 1 represents almost fragmented and degraded RNA and a RQI/RIN of 10 represents intact and non-fragmented RNA [7].

MicroRNAs (miRNAs) are small RNAs with a length of approximately 22 nucleotides, those are thought to be involved in the regulation of many physiological processes like growth and development. These molecules were already described in 1993 [8], the name “miRNAs” was primary alluded in 2001, and the analytical interest in valid miRNAs quantification arose over the past years. Concerning functional studies, especially the investigation of miRNA expression profiles is of great interest, because miRNAs are implicated in the genesis of different cancer types and therefore could be used as clinical markers in diagnosis [9], [10], [11]. As miRNAs belong to the group of nucleic acids, they are examined with the same technologies as long RNAs like mRNAs. Problems start with the quantification and quality control of miRNAs, as classical photometrical methods for measuring the concentration of nucleic acids do not allow discriminating between different fractions of RNAs. For quantitative expression profiling of mRNAs, RT-qPCR has become the gold standard. Concerning mRNA, factors influencing RT-qPCR like inhibitors or RNA quality are well investigated and the immane influence of RNA integrity on the performance of RT-qPCR and quantitative results is stated [1], [2], [12]. The evaluation of RNA integrity should also be integrated as a routine step in pre-PCR for expression profiling of miRNAs, as little is known about the accessibility of miRNA to degradation and the influence of total RNA integrity as a factor possibly compromising the expression profiling of miRNAs [13]. Agilent Technologies offers a new small RNA tool on the 2100 Bioanalyzer making it possible to analyze small RNA (<200 nt) with the lab-on-chip technology. Within this small RNA fraction, fragments with a size of 15–40 nt are defined as miRNA (Fig. 1A). The concentration of miRNA is calculated as absolute amount [pg] and as a percentage of small RNA [%]. By now, this chip offers one of the few possibilities to quantify miRNA.

A study was conducted to investigate the influence of total RNA quality on mRNA and miRNA quantification with the small RNA Assay on the Bioanalyzer and the miRNA expression measured using RT-qPCR. Also, an adequate normalization method for miRNA expression data should be validated, as normalization is an essential step in RT-qPCR analysis to avoid technical variations and to prove that the evaluated miRNA expression differences are of biological kind.

Section snippets

RNA extraction

Total RNA has been extracted using miRNeasy Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s recommendation. Extractions were done from different bovine tissues [liver, muscle, white blood cells (WBC)] in six replicates per tissue (n = 6).

RNA degradation

For artificial RNA degradation, the six replicates of each tissue were pooled and the pool divided into two equal portions. One portion was degraded by exposure to UV light for 90 min to create a fragmented and degraded RNA fraction. The second

RNA degradation

RNA degradation via UV light was successful in all tissues and a quality gradient could be created (exemplary the results for WBC are shown in Table 2 and Fig. 1B). As RNA quality consists of RNA integrity and RNA purity, also the OD260/280 ratio and the OD260/230 ratio have been checked photometrically to ensure good RNA purity. This examination showed constant RNA purity for all degradation steps with a mean OD260/280 of 2.033 ± 0.027 and a mean OD260/230 of 1.925 ± 0.14 (n = 28) indicating that

Discussion

It is generally accepted that sustaining of high RNA quality is one of the keys to get reliable and reproducible results from mRNA expression analysis [2], [12]. This finding should be kept in mind for new applications also dealing with nucleic acids, e.g. expression profiling of miRNAs. Interestingly, samples with low total RNA quality showed the highest concentrations of miRNA. These data suggest an impairing influence of total RNA also for miRNA quantification and raised the question, if

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