Abstract
In the past several years, with the in-depth development of RNA-related research, exploring the application of transcriptome and corresponding RNA biomarkers has become one of the research hotspots in the field of forensic science. High-quality RNA is essential for successful downstream workflows, especially in the steps of screening biomarkers by microarray or RNA sequencing (RNA-seq). Thus, accurately evaluating the quality of RNA samples is a critical step in obtaining meaningful expression data. The RNA integrity number (RIN) generated from the Agilent Bioanalyzer system has been widely used for RNA quality control in the past two decades. Recently, Thermo Fisher Scientific launched a ratiometric fluorescence-based method to quickly check whether an RNA sample has degraded, and the results are presented as RNA integrity and quality number (RNA IQ). Both quality score systems determine RNA quality using a numerical system based on a scale of 1–10, with 1 denoting significantly degraded specimens and 10 representing high-quality, intact RNA samples. In this preliminary study, we evaluated the consistency, reproducibility and linearity of two quality scores in RNA quality determination by analyzing heat- and RNase- artificially degraded samples. Meanwhile, the expression levels of three microRNAs (hsa-let-7 g-5p, hsa-miR-93–5p and hsa-miR-191–5p) in intact and severely degraded RNA samples were estimated by TaqMan-qPCR and droplet digital PCR. Overall, both quality scores showed good repeatability and reproducibility in their respective tests. In the samples subjected to thermal degradation, RIN showed a trend corresponding to heating time, while RNA IQ value showed almost no change on the time gradient. However, in RNase A mediated degradation, RNA IQ value observed better linearity. Furthermore, the expression levels of three microRNAs in the severely degraded samples did not show significant changes compared to the intact RNA samples. RNA degradation is a very complex and highly variable process, which is difficult to comprehensively evaluate through any one index and cannot directly compare these two parameters. Nevertheless, combined with previous research results and the expression levels of three microRNAs in this study, analyzing RNA biomarkers with stable regions or small sizes in challenged samples may be a conservative and reliable approach.
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