Imported from FridrichMethod/awesome-skills (skills/qpcr-primers/SKILL.md). Install upstream with npx skills add FridrichMethod/awesome-skills --skill qpcr-primers. Copyright stays with the author.

Version Compatibility

Reference examples tested with: primer3-py 2.3+.

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show primer3-py then help(primer3.design_primers) to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

qPCR Primer and Probe Design -- Building a Quantitative Measurement Device

"Design qPCR primers (and a probe) for this target" -> Co-design a short, single-product, Tm-matched amplicon with an optional internal probe whose constraints are coupled to the primers -- because the assay's job is not to amplify but to MEASURE, and every qPCR-specific rule protects the efficiency the quantification math assumes.

• Python: primer3.design_primers(seq_args, global_args) with PRIMER_PICK_INTERNAL_OLIGO=1 and PRIMER_INTERNAL_* for the probe.

Scope: co-designing qPCR/RT-qPCR primers and hydrolysis/beacon probes under coupled Tm/size/junction constraints. Genome-wide specificity / pseudogene checking -> primer-specificity. Intramolecular dimers/hairpins of the oligos and probe -> primer-validation. Standard (non-quantitative) PCR -> primer-basics.

The Single Most Important Modern Insight -- A qPCR Assay Is a Measurement Device, and Efficiency Is a Parameter in the Equation, Not a QC Afterthought

1. Validity rests on efficiency and specificity. A Cq difference maps to a true fold-change only through (1+E)^-dCq (at ideal E=1, 2^-ddCq). That requires amplification efficiency E ~ 90-110% (standard-curve slope -3.6 to -3.1, R^2 > 0.99) AND a single product. The short amplicon (70-150 bp), tight Tm, and zero-dimer requirement all exist to protect E and specificity. 2^-ddCq is valid ONLY when the target and reference-gene efficiencies are matched and near 100% -- so design for matched ~100% E, or fall back to Pfaffl's efficiency-corrected model.
2. The probe is coupled to the primers, not bolted on. A hydrolysis probe must be BOUND when the polymerase extends through it (so Taq's 5'->3' exonuclease cleaves it and frees the reporter), which is why its Tm must sit 8-10 C ABOVE the primer Tm. It must NOT start with G (a 5'-G quenches the reporter even after cleavage), and the C-rich strand is preferred because G-richness anywhere near the reporter also quenches it. primer3's internal-oligo Tm defaults EQUAL the primer defaults, so they must be raised, and there is no dedicated no-5'-G tag -- enforce it with PRIMER_INTERNAL_MUST_MATCH_FIVE_PRIME='HNNNN' (IUPAC H = not G) or a post-hoc filter. This is the hydrolysis (TaqMan) probe path; a molecular beacon needs engineered complementary stem arms (a deliberate hairpin) that primer3's internal-oligo picker does NOT design and would flag as a liability -- design the linear core here, add the stem afterward, and exclude that hairpin from validation.
3. Design-level gDNA exclusion is real but leaky. Exon-junction-spanning or intron-flanking primers reduce genomic-DNA amplification, but processed pseudogenes (intronless retro-copies that usually carry the junction) defeat junction-spanning, and tiny introns defeat flanking. So DNase + a no-RT control + a genome specificity check (-> primer-specificity) remain mandatory; single-exon genes have no design-level option at all.

The Quantification Math (Why the Constraints Exist)

Efficiency from a standard curve: E = 10^(-1/slope) - 1; perfect doubling is slope -3.32 (E = 100%). Relative quantification with matched ~100% efficiency uses 2^-ddCq (Livak & Schmittgen 2001 Methods 25:402); with UNEQUAL efficiencies use the efficiency-corrected ratio E_target^dCq / E_ref^dCq (Pfaffl 2001 Nucleic Acids Res 29:e45). Report per MIQE (Bustin 2009 Clin Chem 55:611): efficiency, slope, R^2, Cq method, NTC and no-RT controls, and validated reference genes. The design objective is therefore "single short amplicon with slope near -3.32," not "two oligos that amplify."

Tool Taxonomy

Decision Tree by Scenario

Default when uncertain: TaqMan primers+probe, amplicon 70-150 bp, primers Tm ~60 C (within 2 C), probe Tm ~68-70 C with HNNNN, exon-junction-spanning for expression, then route the pair to primer-specificity and run a standard curve.

Co-Design Primers and a TaqMan Probe

Goal: Produce a short, Tm-matched amplicon with an internal probe whose Tm is 8-10 C above the primers and whose 5' base is not G.

Approach: Turn on internal-oligo picking, set the primer Tm window and a short product range, RAISE the PRIMER_INTERNAL_* Tm window 8-10 C above the primers (the defaults equal the primer Tm), and forbid a 5'-G probe with PRIMER_INTERNAL_MUST_MATCH_FIVE_PRIME='HNNNN'. For an expression assay add SEQUENCE_OVERLAP_JUNCTION_LIST.

import primer3

template = 'ATGC...'  # cDNA (mark the junction position if expression-specific)

result = primer3.design_primers(
    seq_args={'SEQUENCE_ID': 'assay1', 'SEQUENCE_TEMPLATE': template},
    global_args={
        'PRIMER_PICK_LEFT_PRIMER': 1, 'PRIMER_PICK_RIGHT_PRIMER': 1,
        'PRIMER_PICK_INTERNAL_OLIGO': 1,                 # design the probe
        'PRIMER_PRODUCT_SIZE_RANGE': [[70, 150]],        # short amplicon for efficiency
        'PRIMER_NUM_RETURN': 3,
        'PRIMER_OPT_TM': 60.0, 'PRIMER_MIN_TM': 58.0, 'PRIMER_MAX_TM': 62.0,
        'PRIMER_PAIR_MAX_DIFF_TM': 2.0,
        'PRIMER_INTERNAL_OPT_TM': 70.0, 'PRIMER_INTERNAL_MIN_TM': 68.0, 'PRIMER_INTERNAL_MAX_TM': 72.0,
        'PRIMER_INTERNAL_MUST_MATCH_FIVE_PRIME': 'HNNNN',  # IUPAC H = A/C/T = not G at the probe 5' end
        # 'SEQUENCE_OVERLAP_JUNCTION_LIST': [junction_pos],  # add for cDNA-specific assays
    })

for i in range(result['PRIMER_PAIR_NUM_RETURNED']):
    probe = result[f'PRIMER_INTERNAL_{i}_SEQUENCE']
    print(result[f'PRIMER_LEFT_{i}_SEQUENCE'], result[f'PRIMER_RIGHT_{i}_SEQUENCE'], probe,
          'probe5=', probe[0], 'probeTm=', round(result[f'PRIMER_INTERNAL_{i}_TM'], 1),
          'size=', result[f'PRIMER_PAIR_{i}_PRODUCT_SIZE'])

Exon-Junction Spanning, and Its Limits

For a cDNA-specific assay, place a primer or the probe across a splice junction with SEQUENCE_OVERLAP_JUNCTION_LIST = [pos] plus PRIMER_MIN_3_PRIME_OVERLAP_OF_JUNCTION (default 4) and PRIMER_MIN_5_PRIME_OVERLAP_OF_JUNCTION (default 7); the 3' overlap is the specificity-determining knob because a primer that only overlaps at its 5' end can still prime off gDNA from its 3' anchor. The internal-oligo equivalents (PRIMER_INTERNAL_MIN_3_PRIME_OVERLAP_OF_JUNCTION / _5_PRIME_) constrain the probe. The hard caveat: this does NOT protect against processed pseudogenes, which typically carry the junction in DNA -- so the assay still needs a genome specificity check (-> primer-specificity), DNase treatment, and a no-RT control. Intron-flanking (primers in different exons across a large intron) is the alternative, but fails across tiny introns.

Assembling a Multiplex Panel

Multiplex is the most failure-prone mode; assemble it in order: (1) design each assay independently (short amplicon, matched Tm, probe offset); (2) check ALL primer+probe oligos pairwise for cross-dimers -- for k assays that is O((2k primers + k probes)^2) checks (a 5-plex = 10 primers + 5 probes = 105 pairwise calls), weighting 3'-end involvement (-> primer-validation); (3) run in-silico PCR over the POOLED primer set so cross-pair amplicons (one assay's forward meeting another's reverse) are caught (-> primer-specificity); (4) assign spectrally distinct fluorophores -- the instrument's optical channels and spectral overlap CAP the plex (most platforms resolve ~4-6 dyes, with color compensation), so the channel count, not the chemistry, usually limits a high-plex; (5) match efficiencies on a multiplex standard curve and primer-limit the abundant targets so they do not starve the rare ones.

Per-Method Failure Modes

Fold-changes reported without measuring efficiency

Trigger: Applying 2^-ddCq without a standard curve. Mechanism: the method assumes target and reference efficiencies are matched and ~100%; if not, fold-changes are systematically biased. Symptom: numbers that are not measurements; results that do not replicate across instruments. Fix: run a standard curve, report E/slope/R^2 (MIQE), and use Pfaffl if efficiencies differ.

Probe Tm not 8-10 C above primers

Trigger: Leaving PRIMER_INTERNAL_* Tm at the default (equal to the primers). Mechanism: the probe is not bound when the polymerase extends through it, so the exonuclease never cleaves it. Symptom: weak or no TaqMan signal. Fix: raise the internal Tm window 8-10 C above the primer window.

5'-G on the probe

Trigger: Not forbidding a 5' guanine. Mechanism: a 5'-G quenches the reporter even after cleavage. Symptom: low signal despite good amplification. Fix: PRIMER_INTERNAL_MUST_MATCH_FIVE_PRIME='HNNNN' or filter returned probes; prefer the C-rich strand.

Assuming exon-junction primers are gDNA-proof

Trigger: Trusting junction-spanning alone. Mechanism: processed pseudogenes carry the spliced junction in genomic DNA. Symptom: a positive no-RT control; a genomic amplicon at the cDNA size. Fix: genome specificity check (primer-specificity), DNase, and a no-RT control.

Primer-dimers in a SYBR assay

Trigger: Any extendable cross-dimer with SYBR detection. Mechanism: the dye reports the dimer, which competes with and can swamp a low-copy target. Symptom: a low-Tm shoulder in the melt curve; inflated NTC/low-copy signal. Fix: inspect the melt curve for a single sharp peak; validate dimers at reaction conditions (primer-validation).

Single, unvalidated reference gene

Trigger: Normalizing to GAPDH/ACTB by habit. Mechanism: the reference may itself be regulated by the treatment. Symptom: apparent target changes that track a moving normalizer. Fix: rank a candidate panel with geNorm/NormFinder and validate stability in the actual experimental conditions.

Quantitative Thresholds

Common Errors

References

• Bustin SA, Benes V, Garson JA, et al. 2009. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55:611-622.
• Untergasser A, Cutcutache I, Koressaar T, et al. 2012. Primer3 - new capabilities and interfaces. Nucleic Acids Res 40:e115.
• Livak KJ, Schmittgen TD. 2001. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods 25:402-408.
• Pfaffl MW. 2001. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res 29:e45.
• Vandesompele J, De Preter K, Pattyn F, et al. 2002. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3:RESEARCH0034.
• Andersen CL, Jensen JL, Orntoft TF. 2004. Normalization of real-time quantitative RT-PCR data: a model-based variance estimation approach to identify genes suited for normalization. Cancer Res 64:5245-5250.
• Koressaar T, Remm M. 2007. Enhancements and modifications of primer design program Primer3. Bioinformatics 23:1289-1291.

Related Skills

• primer-basics - Design fundamentals, Tm matching, and the constraint model
• primer-validation - Dimers/hairpins of primers and probe at reaction conditions
• primer-specificity - Genome/pseudogene specificity and gDNA exclusion checking
• sequence-manipulation/transcription-translation - Work with cDNA and reading frames
• differential-expression/deseq2-basics - Downstream analysis qPCR validates against