01Find the measurement behind the gene-expression label

The 2025 MIQE 2.0 guidelines address variability across sample preparation, reverse transcription, amplification and analysis. They emphasise that analysis choices and amplification efficiency can affect the reported quantity, so a Cq value is not a self-explanatory expression result.Bustin and colleagues — MIQE 2.0: Revision of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments Guidelines (opens in a new tab)

Cq is a cycle-related measurement from an amplification curve. The study should explain how that signal becomes the quantity compared between samples. Do not read a one-unit change in Cq as a one-unit change in transcript amount.

Record the target and whether the experiment begins with RNA. The reverse-transcription step matters for an RNA-expression claim; a qPCR method directed at DNA asks a different question.

Also inspect the names used in the results. A gene symbol may appear beside protein measurements elsewhere in the paper. Keep the RNA result attached to the RNA assay rather than allowing the shared symbol to blur the distinction.

02Read normalisation as a comparison of quantities

MIQE 2.0 calls for justification of reference-gene selection and evidence of expression stability under the relevant conditions. It also explains why assuming identical, perfect amplification efficiencies can bias expression calculations.Bustin and colleagues — MIQE 2.0: Revision of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments Guidelines (opens in a new tab)

The original fictional table below starts with already estimated target and reference quantities. It deliberately does not derive them from Cq or assume an amplification efficiency.

B has twice the target quantity, but its target-to-reference ratio is unchanged. The normalised finding and the unnormalised finding therefore answer different questions. Neither number should be substituted for the other in a summary.

03Check the information needed to assess the estimate

Look for the reported amplification behaviour, controls and analysis method. If a result depends on excluding reactions or assigning values to undetected targets, those decisions should be visible enough to understand the comparison.

Suppose a fictional figure contains three reaction wells for each of two independently prepared cultures. Six wells do not automatically represent six independent biological samples. Record the structure so that the apparent amount of evidence is not inflated.

For a low-signal result, distinguish absence of a reported estimate from evidence that no transcript exists. The method’s usable range and treatment of missing observations determine what can be concluded.

A large fold difference also deserves its starting context. A change from a very small estimated quantity can produce a large ratio; the ratio alone does not show how much material was present or how precisely either endpoint was estimated.

04Separate transcript evidence from a pathway claim

A peptide-associated increase in a normalised transcript estimate supports that particular expression comparison in the sampled model and interval. It does not directly measure the amount, location or activity of the corresponding protein.

When the discussion names a pathway, follow the evidence connecting the measured transcript to that conclusion. Several changed genes can motivate a hypothesis, but the qPCR endpoint itself is still a measurement of selected targets.

If a functional assay is included, describe its finding separately. This lets the reader see whether the broader conclusion rests on measured function, a correlated molecular pattern or an inference awaiting further testing.

A useful note contains the target, model, sampling time, normalisation and supported direction of change. Add the main uncertainty about measurement or interpretation, rather than compressing the result into an unexplained claim that a peptide activates or repairs a system.