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Droplet digital polymerase chain reaction-based quantification of circulating microRNAs using small RNA concentration normalization

Shalini Das Gupta, Xavier Ekolle Ndode‐Ekane, Noora Puhakka, Asla Pitkänen

2020Scientific Reports14 citationsDOIOpen Access PDF

Abstract

Quantification of plasma microRNAs (miRNAs) as non-invasive disease biomarkers is subject to multiple technical variabilities. This study aimed to develop an optimized protocol for miRNA quantification from rodent plasma. We hypothesized that a fixed small RNA concentration input for reverse transcription (RT) reaction will provide better miRNA quantification than a fixed RNA volume input. For this, tail-vein plasma was collected from 30 naïve, adult male Sprague-Dawley rats. Plasma hemolysis was measured with NanoDrop-1000 and Denovix DS-11 spectrophotometers. Plasma was then pooled, and RNA was extracted from 50-μl, 100-μl or 200-μl pool aliquots. Small RNA concentration was measured with Qubit miRNA assay. A fixed RNA volume (un-normalized) or a fixed small RNA concentration was used for RT (concentration-normalized). The method was setup with miR-23a-3p and validated with miR-103a-3p and miR-451a. Hemolysis measurements from Denovix and NanoDrop strongly correlated. Qubit revealed increased small RNA concentrations with increasing starting plasma volumes. With concentration-normalization, miRNA levels from 100-µl and 200-µl plasma volume groups mostly normalized to the level of the 50-µl in ddPCR. Our results indicate that miRNA quantification with ddPCR should be performed with small RNA concentration-normalization to minimize variations in eluted RNA concentrations occuring during RNA extraction.

Topics & Concepts

RNAmicroRNADigital polymerase chain reactionRNA extractionSmall RNANormalization (sociology)Molecular biologyChemistryReverse transcriptaseHemolysisMessenger RNAPolymerase chain reactionBiologyChromatographyGeneBiochemistryImmunologySociologyAnthropologyMicroRNA in disease regulationMolecular Biology Techniques and ApplicationsCancer-related molecular mechanisms research
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