Consequently, quality control of the RNA starting material is an essential checkpoint addressed by the guidelines. These require that RNA integrity be measured by manual gel electrophoresis at the very least, but preferably by microfluidics-based RNA analysis using a system such as the Experion (Bio-Rad Laboratories) or the Bioanalyzer 2100 (Agilent Technologies). This technique is fast, highly standardized, uses a small amount of total RNA, and is automated, including the data analysis.
Each system uses a quality index scale to represent the level of degradation in a sample. The Agilent RNA Integrity Number (RIN) is a number from 1 to 10 derived by an algorithm that takes into account eight portions of the electrophoretic trace. The Bio-Rad RNA Quality Indicator (RQI), also a number from 1 to 10, is generated by an algorithm that takes into account three portions of the electrophoretic trace and then compares the electropherogram of RNA samples to a series of standard degraded RNA samples.
The two quality indices are correlated and can generally be used interchangeably as reliable indicators of RNA quality7. The PCR-based 3´:5´ mRNA integrity assay8 constitutes an additional RNA quality-assessment tool, although its practical usefulness remains to be determined.
Ideally, a threshold that delineates the quality of RNA required to produce reliable results should be established for each study. For example, in a study of more than 700 biopsies from neuroblastoma patients, the average values for samples with acceptable quality were a difference in Cq of 2.36 for the 3´:5´ assay and an Experion-derived RQI of 7.4, while both of these indices show a wide distribution of values across the samples (Figure 4)9.
A general guideline has also been suggested that recommends an RIN of at least 5 to obtain reliable RT-qPCR results10. Finally, inhibition of reverse-transcription or PCR should be checked by dilution of the sample or use of a universal inhibition assay such as SPUD11.
qPCR and RT-qPCR are powerful enabling technologies that impel the advances made in our understanding of basic biological and disease processes as well as underpin the field of molecular diagnostics. However, the combination of ease of use and lack of rigorous standards of practice has resulted in widespread misinterpretation of data and consequent publication of erroneous conclusions.
The RNA quality issue highlighted in this article is just one example of the many crucial parameters that must be addressed by guidelines that shift the focus of concern from questions regarding the technological relevance underlying a publication’s conclusion to the actual biological or diagnostic issues being addressed. MIQE and RDML have initiated a dialogue in the research community that should result in guidelines that promote absolute transparency of experiments, high confidence in results, and valid conclusions that continue to advance our understanding.
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