Structure-Guided Design of Exogenous Spike-in Controls Improves Analytical Precision in RT-qPCR-Based Small RNA Quantification

Abstract

Accurate reverse transcription quantitative PCR (RT-qPCR)-based quantification of circulating microRNAs (miRNAs) is limited by workflow-dependent bias arising from RNA extraction, enzymatic cDNA synthesis, amplification, matrix-derived inhibition, and sequence-dependent behavior of short RNA targets. Conventional exogenous spike-ins monitor technical process variation but are often selected without considering target-specific physicochemical properties such as GC content and predicted 3′-end structure. Here, we introduce a structure-guided framework for selecting and designing exogenous spike-in controls in small RNA quantification workflows. Native, sequence-modified, and newly engineered synthetic spike-ins were evaluated across no-extraction, pre-extraction, and post-extraction conditions, including an ethanol inhibition challenge. Secondary-structure prediction and calibration-curve-based quantification were combined with workflow-resolved coefficient of variation (CV) and ΔCq analyses. Control performance varied with the target miRNA, assay configuration, and workflow condition, with significant control, workflow, or interaction effects in selected target−assay combinations. Direct modification of predicted 3′-end structure revealed context-dependent effects on normalization precision, including a significant variant-dependent difference under the ethanol challenge, and circular dichroism (CD) spectroscopy of the hsa-miR-146a-5p variant set provided experimental support for the predicted stability differences. Finally, four engineered spike-ins spanning contrasting GC/ΔG profiles were evaluated as proof-of-concept controls for a target-informed selection framework. This study provides a measurement-focused strategy for technical internal-standard design and supports assay- and workflow-specific validation of exogenous spike-in controls in complex biofluid workflows.