How to reproduce a qPCR assay from a paper

Reproducing a published qPCR result means rebuilding the exact reaction, cycling program, and analysis the authors used. Most methods sections give primer names and a cycle count but skip efficiency, reference gene validation, and controls. This guide lists what to look for, how the key parameters depend on each other, and how to diagnose the usual failures.

What methods sections usually leave out

Amplification efficiency for each primer pair
The 2^-ΔΔCt method assumes efficiencies close to 100% and similar between target and reference. Without the authors' standard curve you cannot tell whether their fold changes hold for your primers.
Primer sequences and final primer concentration
Gene names alone do not identify an assay. Different primer pairs for the same gene can differ in efficiency, specificity, and isoform coverage.
How the reference gene was chosen and validated
If the reference gene shifts with your treatment, every normalized value shifts with it. Papers often name GAPDH or ACTB without showing it is stable under their conditions.
RNA quality and the reverse transcription setup
Input amount, RNA integrity, priming strategy (oligo-dT, random hexamers, or both), and the RT enzyme all change Cq values before any PCR happens.
Controls: no-template and no-RT
Without them you cannot rule out contamination or genomic DNA amplification, which is a common source of late, noisy Cq values.
What n means
Three technical replicate wells from one RNA sample are not three biological replicates. Many papers report n=3 without saying which.

Key parameters and what they change

Parameter	Typical	Changes together with
Reaction volume	10 to 20 µL per well	Master mix, primer, and template volumes per well; total master mix needed for the plate.
Final primer concentration	Often 200 to 500 nM each, optimized per assay	Primer stock dilution and volume per well; efficiency and primer dimer formation.
Template input	cDNA from a fixed RNA amount, often diluted before use	Expected Cq range; must stay inside the linear range of the standard curve.
Annealing / extension temperature	Often 60 °C in two-step cycling	Primer Tm and specificity; melt curve shape.
Number of reactions	Samples × replicates × genes, plus controls and pipetting overage	Every master mix component total. Change the sample count and all totals change.

Troubleshooting

Symptom	Likely causes	What to check first
Efficiency outside 90 to 110% (standard curve slope outside about -3.6 to -3.1)	Poor primer design, inhibitors carried over from RNA extraction, or a dilution series that leaves the linear range.	Re-run a 5-point dilution series, drop points at the extremes, check A260/230 for carryover, and redesign primers if the slope stays off.
Cq values drift between runs for the same sample	Template degradation after freeze-thaw, pipetting error at low volumes, or a different master mix lot.	Aliquot cDNA, use a calibrator sample on every plate, and pipette larger volumes of more dilute template.
Two peaks in the melt curve	Primer dimers, a second non-specific product, or occasionally a single amplicon with more than one melting domain; a gel distinguishes these.	Run the product on a gel, lower primer concentration, or raise the annealing temperature.
Signal in the no-template control	Contaminated reagents or primer dimers.	If the NTC melt peak matches the product, replace reagents; if it is a low-Tm peak, it is likely dimers.
Signal in the no-RT control	Genomic DNA contamination.	Add a DNase step and use primers that span an exon-exon junction.

Worked example: from a methods sentence to executable steps

Total RNA was reverse transcribed and target genes were quantified by SYBR Green qPCR using GAPDH as the internal control. Relative expression was calculated by the 2^-ΔΔCt method.

Each step is tagged by how clearly the text states it: explicit, partial, inferred, or missing.

1.
Reverse transcribe total RNA to cDNAExplicit
2.
RNA input amount and RT kitMissing
Not stated; needed to match Cq ranges.
3.
Run SYBR Green qPCR for each target and GAPDHExplicit
4.
Primer sequences and final concentrationMissing
Check the supplementary tables before guessing.
5.
Cycling programInferred
A standard two-step program is a reasonable start, but it is an assumption.
6.
Confirm efficiency of each primer pair is close to GAPDHMissing
Required for 2^-ΔΔCt to be valid.
7.
Calculate relative expression with 2^-ΔΔCtExplicit
8.
Number of biological replicatesMissing
Not stated in the methods; check figure legends, and confirm whether n is biological or technical.

How Vara helps

Paste the methods paragraph or upload the PDF, and Vara turns it into steps with parameters, each tagged explicit, partial, inferred, or missing so you can see what the paper never said.
Missing items such as efficiency, reference gene validation, and what n means are listed as reproduction risks instead of being silently filled in.
Reaction volume, number of reactions, and component amounts are linked by formulas. Change the sample count and the master mix totals recalculate.
Each run is logged against the protocol version, so when Cq values drift you can compare what changed.

Try Vara on your own protocol See how importing works

FAQ

What efficiency do I need for the 2^-ΔΔCt method?+

Both the target and reference assays should be close to 100% efficient and within a few percent of each other. A common acceptance range is 90 to 110%. If the efficiencies differ, use an efficiency-corrected model such as the Pfaffl method.

Why do my Cq values not match the paper?+

Absolute Cq values depend on RNA input, reverse transcription, instrument, and master mix, so they rarely match across labs. Compare relative expression and check that your efficiencies and reference gene stability are acceptable.

Is GAPDH a safe reference gene?+

Not automatically. GAPDH expression can change with treatment, metabolism, and cell type. Test several candidates under your conditions, rank them with a stability measure such as geNorm, and normalize to the geometric mean of the two or three most stable.

What should I do if the paper does not list primer sequences?+

Check the supplementary information and any cited earlier papers from the same lab. If they are still missing, contact the corresponding author. Using different primers is possible but means you are no longer reproducing the same assay.