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What RT-qPCR Is

RT-qPCR (reverse transcription quantitative PCR) has two coupled stages: (1) reverse transcription converts RNA (mRNA, viral RNA, microRNA) into complementary DNA (cDNA); (2) quantitative PCR amplifies the cDNA in real time, with fluorescence reporting product accumulation each cycle. The cycle at which fluorescence crosses threshold (Ct/Cq) is inversely proportional to starting template log-concentration, enabling sensitive quantification from minimal RNA input RT-PCR protocol chapter (Methods in Enzymology). Detecting RNA-derived signal specifically requires DNase treatment to prevent amplification of genomic DNA In situ RT-PCR in archaeal cells (AEM).

Quantification and Efficiency

Primer amplification efficiency should sit near 90–110% with regression coefficients near 1.0. Published validation data illustrate acceptable metrics across nine primer pairs:

Out of range, values such as amsB (104.9%) and hrpN (95%) were accepted but show how efficiency varies; poor efficiency biases relative-quantification fold changes Reference gene validation in E. amylovora (Sci Rep).

Normalization: The Critical Weak Point

Relative quantification divides target signal by a reference (housekeeping) gene—but housekeeping genes are condition-dependent. Multi-algorithm validation (geNorm, NormFinder, BestKeeper, delta-Ct, RefFinder) is now the standard: in E. amylovora, proC, recA, and ffh were most stable; in filamentous fungi, six genes (ubcB, sac7, fis1, sarA, TFC1, UBC6) were proposed but require revalidation per condition Fungal reference gene tracking (BMC Genomics); in developing mouse cortex, B2m, Gapdh, and Hprt were most stable while the classic Actb was among the least stable Mouse cortex reference gene evaluation (BMC Neurosci).

Applications and Diagnostic Sensitivity

RT-qPCR spans basic transcriptomics, viral variant surveillance (a Bolivian multiplex assay matched whole-genome sequencing at 97.5% concordance on 41 samples) Bolivian SARS-CoV-2 multiplex RT-qPCR (Epid Infect), liquid biopsy (extracellular vesicle microRNAs for disease biomarkers) EV microRNA RT-qPCR review (Biomarkers in Medicine), and cancer diagnostics. Sample preparation alone can change sensitivity: magnetic-bead extraction of cell-free EBV DNA raised positive detection from 40.8% to 75.84% (AUC 0.704 to 0.879) versus precipitation in 2,088 NPC patients MB vs CP cfEBV DNA RT-qPCR (Sci Rep).

Limitations and Confidence

Key blindspots: reference-gene stability does not generalize across strains, tissues, or conditions; mutation-panel assays can miss novel variants; retrospective clinical comparisons risk selection bias; and single-cell/in situ variants depend on permeabilization and cycle number. Confidence in the core quantitative framework is high (strong, replicated across studies); confidence in specific reference-gene recommendations is moderate and context-bound. The conclusion would change if independent multi-condition validations showed the recommended genes varying >2-fold, or if IVD-registered RT-qPCR assays failed to match WGS concordance at scale.