qPCR troubleshooting follows a few common patterns. Most failures fall into one of ten categories — and most can be solved without ordering new reagents.
1. No amplification at all
Symptoms: All wells flat, no Ct values.
Likely causes: Master mix issue, wrong primers, no template, wrong cycling protocol.
Fixes: Run a positive control (a known-working sample). Check primer concentrations and template integrity. Verify the cycling protocol — wrong annealing temperature or missing steps cause silent failures.
2. Late Ct values across all samples
Symptoms: Ct values 5–10 cycles later than expected.
Likely causes: Low input template, degraded template, inhibitors in sample.
Fixes: Re-quantify cDNA. For RT-qPCR, check RNA quality (Bioanalyzer RIN). Dilute samples 1:5 or 1:10 to dilute potential inhibitors and re-run.
3. Amplification in the no-template control (NTC)
Symptoms: NTC produces signal, often late.
Likely causes: Contamination, primer-dimers (SYBR Green), aerosol contamination.
Fixes: Always inspect the melt curve — primer-dimers melt at lower temperatures than your amplicon. Use filter tips, dedicate primer aliquots, set up reactions in a clean area, and decontaminate the bench with a bleach or 10% acid solution.
4. Primer-dimer peak in melt curve
Symptoms: Multiple peaks in melt curve; small peak at lower Tm.
Likely causes: Primer self-complementarity, low template, suboptimal primer concentration.
Fixes: Redesign primers using OligoAnalyzer to avoid self/cross-complementarity. Reduce primer concentration. Increase annealing temperature. Verify with gel — primer-dimers run as a smear <100 bp.
5. Multiple melt curve peaks (multi-product amplification)
Symptoms: Two or more distinct melt peaks (excluding primer-dimers).
Likely causes: Primers amplify multiple targets, contamination, genomic DNA contamination.
Fixes: Verify primer specificity by Primer-BLAST. Run on agarose gel to see all amplicons. If genomic DNA is amplifying, redesign primers across an exon-exon junction or treat samples with DNase before reverse transcription.
6. Poor standard curve efficiency
Symptoms: Slope outside -3.6 to -3.1 (efficiency <90% or >110%).
Likely causes: Suboptimal primers, pipetting errors, inhibitors in sample, suboptimal cycling.
Fixes: Use a fresh dilution series, check pipettes, optimize annealing temperature with a gradient PCR, and verify primer concentrations.
7. Inconsistent replicates
Symptoms: Technical replicates differ by >0.5 Ct.
Likely causes: Pipetting variability, plate sealing issues, edge effects, low template.
Fixes: Use accurate pipettes; consider electronic or repeating pipettes. Mix master mix thoroughly. Avoid plate edges or apply a thermal mat. For low-template samples, increase replicate count.
8. Bad reference gene
Symptoms: Reference gene Ct varies between conditions, making normalization unreliable.
Likely causes: Reference gene actually changes with treatment, varying input quantity not corrected.
Fixes: Validate reference gene stability across your conditions. Use 2–3 reference genes and average via geNorm or NormFinder. Quantify input cDNA before normalizing.
9. Plateau effect (curves saturate too early)
Symptoms: Amplification curves don’t reach typical fluorescence intensity.
Likely causes: Reagent depletion, dye quenching, reaction inhibition.
Fixes: Don’t focus on the plateau — quantification uses early exponential phase. If consistently low, check master mix and dye stability.
10. Discordant results between qPCR and other methods
Symptoms: qPCR data don’t match RNA-seq or western blot.
Likely causes: Primer specificity issues, isoform-specific expression, post-transcriptional regulation.
Fixes: Confirm primers detect all relevant isoforms. Check whether RNA and protein are concordant — they often aren’t, due to translation regulation. Validate primers by Sanger sequencing the amplicon.
Prevention checklist
- Always run a melt curve with SYBR Green
- Always include NTC for every primer pair
- Validate primer efficiency with a standard curve before relying on results
- Use 2+ reference genes and validate stability
- Pipette accurately and use master mixes when possible
- Document each run completely — date, lot numbers, conditions
Most qPCR problems are diagnostic, not catastrophic. Look at the Ct values, melt curves, and replicate spread together — the pattern usually points to the cause within a few minutes.
